optimal management of water resources in selected...

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OPTIMAL MANAGEMENT OF WATER RESOURCES IN

SELECTED HILL TORRENT COMMAND AREA OF

PAKISTAN

BY

ENGR. MATLOB AHMAD

96-ag-1065

M.Sc. (HONS.) AGRICULTURAL ENGINEERING

A THESIS SUBMITTED IN PARTIAL FULFILLMENT OF THE

REQUIREMENT OF THE DEGREE OF

DOCTOR OF PHILOSOPHY

IN

AGRICULTURAL ENGINEERING

DEPARTMENT OF IRRIGATION AND DRAINAGE

FACULTY OF AGRICULTURAL ENGINEERING & TECHNOLOGY

UNIVERSITY OF AGRICULTURE, FAISALABAD

2016

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DECLARATION

I hereby declare that the contents of the thesis “Optimal Management of Water

Resources in Selected Hill Torrent Command Area of Pakistan” are product of my

own research and no part has been copied from any published source (except the

references, standard mathematical models/ equations/ formulate/ protocols, etc.). I further

declare that this work has not been submitted for the award of any other diploma/degree.

The university may take action if the information provided by me is found inaccurate at

any stage.

ENGR. MATLOB AHMAD

Regd. No. 96-ag-1065

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The Controller of Examinations,

University of Agriculture,

Faisalabad

We, the Supervisory Committee, certify that the contents and form of thesis

submitted by Mr. Matlob Ahmad, Regd. No. 96-ag-1065 have been found satisfactory

and recommend that it be processed for evaluation by the External Examiner(s) for the

award of degree of “Doctor of Philosophy”.

SUPERVISORY COMMITTEE

1. Chairman

Prof. Dr. Muhammad Arshad

2. Member

Dr. M. Jehanzeb Masud Cheema

3. Member

Prof. Dr. Riaz Ahmad

Chairman, Dean,

Department of Irrigation and Drainage Faculty of Agri. Engineering & Technology

University of Agriculture, Faisalabad University of Agriculture, Faisalabad

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ACKNOWLEDGEMENT

All praises to the Almighty Allah, the most merciful and beneficent, who is entire source

of all knowledge and wisdom, and who despite numerous difficulties enabled me to

complete my PhD studies.

I express sincere thanks and gratitude to my worthy supervisor Prof. Dr.

Muhammad Arshad for his dynamic supervision, valuable suggestions and inspiring

attitude throughout the period of my PhD studies. His continuous care and unlimited

enthusiasm have been major driving forces throughout my studies at University of

Agriculture, Faisalabad (UAF). I also express my sincere gratitude to Dr. M. Jehanzeb

Masud Cheema and Prof. Dr. Riaz Ahmad for their valuable guidelines and serving as

member on the supervisory committee. I am thankful to Prof. Dr. Rai Niaz Ahmad who

was member of my supervisory committee at UAF. Later he accepted the position as Vice

Chancellor, PMAS Arid Agriculture University, Rawalpindi and left the UAF and could

no longer participate on the committee. Words can’t explain my sincere recognition of

Prof. Dr. Muhammad Rafiq Choudhray for his immeasurable contribution in research and

dissertation of my postgraduate studies at UAF. It gives me great satisfaction to thanks

Prof. Dr. Muhammad Iqbal. He has been my boss and supported me in gaining admission

and study leave for PhD studies. I also give my thanks to Prof. Dr Shafqat Nawaz for his

help and guidance in soil related work of my PhD studies. I am very thankful to my

linkedIn.com friend Ms. Karen Murday, Senior Project Officer, Queensland Government,

Australia for review and grammatical corrections of the Chapter No. 1& 2.

Words are insufficient for my feelings towards my beloved parents, brothers,

sisters and family members for their prayers and encouragement for higher education. It

would be unjust to overlook the sacrifices of my wife, Naila Farid Malik, daughters,

Almiray Aimen and Misha Mahnoor, and son, Muhammad Sarim Matlob throughout the

period of my PhD studies.

Special thanks to Spate Irrigation Network Pakistan for providing me an

opportunity during my PhD studies to visit and learn about spate irrigation system at

Yemen. I am also thankful to the staff of the Soil and Water Testing Laboratory,

Research Wing, DG Khan and Faculty of Agricultural Sciences, Ghazi University, DG

Khan for facilitation in soil and water samples analysis.

Last, but certainly not least, sincere thanks to my friends near and far. I am whole-

heartedly thankful to all, especially Mr. Muhammad Sulaiman Bughlani, Engr.

Muhammad Mohsin Waqas, Engr. Amir Shakoor, Engr. Muhammad Awais and Dr. Jaffar

Hussain Khosa for their cooperation and support in collecting data and analyzing it.

(ENGR. MATLOB AHMAD)

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DEDICATED TO MY BELOVED FATHER

On the last day of life (September 01, 2013), my father, Haji Atta Muhammad Changwani

(Late) was seriously unwell but insisted me to continue the scheduled data collection for

my PhD research instead of going to hospital with him. He prioritized my studies over his

health, so I went to the field visit to collect data. My elder and younger brothers

accompanied him to the hospital but on the way he passed away (Ina lillahe wa ina elaihe

rajeon). I can never forget this immeasurable loss in my life. My father provided me with

all kinds of values and resources throughout his life to make me a successful person but

sadly he did not live long enough to see this successful moment in my life.

May Allah rest his soul in peace (Aamin)

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TABLE OF CONTENTS

CHAPTER TITLE PAGE NO.

ACKNOWLEDGEMENTS iii

TABLE OF CONTENTS v

LIST OF TABLES ix

LIST OF FIGURES xii

LIST OF APPENDICES xiv

LIST OF ABBREVIATIONS xvi

1 INTROCUCTION 1

1.1 Water resources of Pakistan 2

1.1.1 Rainfall 2

1.1.2 Surface water 2

1.1.3 Groundwater 4

1.2 Hill torrent areas of Pakistan 5

1.2.1 North & North Western mountains hill torrents 5

1.2.2 Sulaiman, Kachhi & Khirthar basin hill torrents 6

1.2.3 Low mountains hill torrents 7

1.3 Potential in hill torrents of Pakistan 7

1.4 Statement of the problems 9

1.5 Objectives of the study 11

2 REVIEW OF LITERATURE 12

2.1 Hill torrent irrigation system management 12

2.2 Crop water requirement 23

2.3 Groundwater simulation using MODFLOW model 26

2.4 Summary of review 28

3 MATERIALS AND METHODS 30

3.1 Features of the research area 30

3.1.1 Geological characteristics 30

3.1.2 Climate and rainfall 31

3.1.3 Agriculture 31

3.1.4 Livestock 33

3.1.5 Soil type and sedimentation 33

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3.2 Socio-economic condition of the farmers 33

3.3 Irrigation practices and water rights 34

3.4 Water conservation 36

3.5 Groundwater 36

3.6 Drainage 37

3.7 Field layout and water allocation 37

3.8 Mithawan hill torrent command area irrigation system 37

3.9 Data collection 41

3.9.1 Primary data 41

3.9.2 Secondary data 42

3.10 Contribution of available water resources to crop water requirement

42

3.10.1 Discharge measurement of the pumps 42

3.10.2 Volume of water available to the crops 44

3.11 Estimation of crop water requirement using CROPWAT model 45

3.11.1 Data required for CROPWAT model 45

3.11.2 Climate/ETo data input and output 45

3.11.3 Rainfall data input and output 47

3.11.4 Crop and cropping pattern data 49

3.12 Irrigation efficiency of canal water and/or groundwater irrigated

fields 51

3.13 Hill torrent irrigation 52

3.13.1 Socio-economic and environmental condition of the

farmers 53

3.13.2 Benefit cost ratio of the crop 53

3.13.3 Irrigation water and soil salinity 53

3.14 Groundwater pumping 56

3.15 Groundwater model 58

3.16 Description of “MODFLOW” model 58

3.16.1 Evapotranspiration module (EVT) 58

3.16.2 Recharge module (RCH) 59

3.16.3 River module (RIV) 60

3.17 Preparation of “MODFLOW” input data file 61

3.17.1 Development of input directory 61

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3.17.2 Creation of grid 61

3.17.3 Defining of layer type 62

3.17.4 Transmissivity 62

3.17.5 Boundary conditions 62

3.17.6 Elevation of top and bottom of layer 63

3.17.7 Simulation time 64

3.17.8 Initial conditions 64

3.17.9 Initial hydraulic head 64

3.17.10 Horizontal and vertical hydraulic conductivity 65

3.17.11 Effective porosity 65

3.17.12 Time constant parameters 65

3.17.13 Time variant parameters 66

3.18 Model calibration 66

3.19 Statistical calibration performance of the MODFLOW model 70

3.20 Water balance 71

3.21 Strategies for the efficient use of water resources 72

4 RESULTS AND DISCUSSION 73

4.1 Farmers’ interviews 73

4.1.1 Educational level of the farmers 73

4.1.2 Land use and cropping pattern 74

4.1.3 Cropping intensities 77

4.1.4 Sources of irrigation water 77

4.1.5 Pumping units and sources of powers 80

4.1.6 Yield of crops 84

4.2 Sediment load in hill torrent flow 85

4.3 Benefit cost ratio of the crops 85

4.4 Contribution of irrigation water sources to crop water requirement 88

4.5 Irrigation application efficiency 89

4.6 Water productivity of crops 91

4.7 Impact of irrigation applications on soil physical properties 92

4.8 Groundwater fluctuation 104

4.8.1 Simulation of existing pattern (Scenario-I) 104

4.8.2 Increased groundwater pumping following the historic

trend under current conditions (Scenario-II) 110

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4.8.3 Current rate of groundwater pumping and hill torrent water

resources management (Scenario-III) 115

4.9 Management strategies for the efficient use of water resources 120

5 CONCLUSIONS AND RECOMMENDATIONS 121

5.1 Conclusions 121

5.2 Recommendations 122

6 SUMMARY 124

REFERENCES 127

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LIST OF TABLES

TABLE TITLE PAGE NO.

1.1 Prospective sites for hill torrents development in Pakistan 8

2.1 Major hill torrents’ catchment areas and average discharge 13

2.2 Estimated land and water resources of hill torrents 14

2.3 Maximum discharge at the outlet of hill torrents 20

3.1 Peak discharge of DG Khan hill torrents 31

3.2 Average discharge of pumps installed in the study area 44

3.3 ETo data obtained through CROPWAT using climatic data of the study area 47

3.4 Monthly effective rainfall of study area during the year 2012-2014 49

3.5 Planting and harvesting dates of the crop sown in study area 50

3.6 Length of crops growth stages for planting period 50

3.7 Kc values of crops cultivated in the study area 51

3.8 Maximum root depth, soil water depletion fraction and seasonal yield

response functions (Ky) of the crops cultivated in the study area 51

3.9 Maximum evapotranspiration rate of the study area 59

3.10 Recharge flux for the stress period of study area 60

3.11 Range of the values of head in the canal during each stress period 61

3.12 Geographic boundaries for the model of study area 63

3.13 Thickness of aquifer layers 64

3.14 Initial hydraulic heads of observation wells 64

3.15 Values of effective porosity of the soil layers 65

3.16 Soil layer, horizontal & vertical hydraulic conductivity, specific storage

and specific yield for the study area 65

3.17 Location of observation wells in the model grid 66

4.1 Educational level of the farmers 73

4.2 Land use of selected hill torrent command area 74

4.3 Cropping pattern of Kharif season, 2012 (wet year) 74

4.4 Cropping pattern of Kharif season, 2013 (dry year) 75

4.5 Cropping pattern of Rabi season, 2012-13 (wet year) 75

4.6 Cropping pattern of Rabi season, 2013-14 (dry year) 76

4.7 Land use patterns during wet and dry years 77

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4.8 Cropping intensity during a wet and dry year (2012-14) 77

4.9 Sources of irrigation water available to the farmers 78

4.10 Availability of hill torrent flow for spate irrigation on yearly basis 79

4.11 Cost of construction of diversion structures and repairing of bunds 79

4.12 Use of hill torrent and depth of water applied in the bund 80

4.13 Groundwater pumping units and partnership among farmers 80

4.14 Types of pump installed for groundwater pumping 80

4.15 Design parameters and cost of pumping wells 81

4.16 Farmers’ views on the quality of groundwater 81

4.17 Laboratory results of the groundwater quality 81

4.18 Sources of power used for groundwater pumping units 82

4.19 Farmers preference regarding the source of power for future use 82

4.20 Installation trend of groundwater pumps in the study area 83

4.21 Yield of various crops cultivated in the study area 84

4.22 Sediment load in the flow of hill torrent at different reaches of channel 85

4.23 Investment of the farmers for cultivation of crops 86

4.24 Income from the crops cultivated in the study area 87

4.25 Benefit Cost Ratio of the crops in Mithawan hill torrent command area 88

4.26 Volume of water applied to the crops 88

4.27 Total volume of water available to the crops 89

4.28 Water applied to the crops through different sources 89

4.29 Water requirement of crops cultivated in the study area 90

4.30 Irrigation efficiency (distribution and application) in the study area 91

4.31 Water productivity of crops cultivated in the study area 91

4.32 Water quality analysis of Mithawan hill torrent flow 93

4.33 Quality analysis of groundwater 93

4.34 EC of fields irrigated by the hill torrent and groundwater 94

4.35 pH of fields irrigated by the hill torrent and groundwater 95

4.36 Na analysis of fields irrigated by the hill torrent and groundwater 97

4.37 Ca+Mg analysis of fields irrigated by the hill torrent and groundwater 99

4.38 Cl analysis of fields irrigated by the hill torrent and groundwater 100

4.39 CO3 analysis of fields irrigated by the hill torrent and groundwater 100

4.40 HCO3 analysis of fields irrigated by the hill torrent and groundwater 101

4.41 SAR analysis of fields irrigated by the hill torrent and groundwater 102

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4.42 RSC of fields irrigated by the hill torrent and groundwater 103

4.43 Predicted groundwater heads at OW No. 1-9 under the Scenario-I 110

4.44 Predicted groundwater heads at OW No. 1-9 under the Scenario-II 114

4.45 Predicted groundwater heads at OW No. 1-9 under the Scenario-III 119

4.46 Comparison of decline in groundwater heads under different scenarios 119

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LIST OF FIGURES

FIGURE TITLE PAGE NO.

3.1 Location of the Mithawan hill torrent command area, DG Khan 30

3.2 Grazing of animals in the gram crop 32

3.3 Sowing and germination of gram crop in sediment crusted bund 33

3.4 Fields layout of Mithawan hill torrent irrigation system 37

3.5 Water channel layout of the Mithawan hill torrent command area 38

3.6 Wah at Mithawan hill torrent command area 39

3.7 Wakrha at Mithawan hill torrent after the cutoff of flow 39

3.8 Bund at Mithawan hill torrent command area 40

3.9 Location of observation wells in the study area 57

3.10 Generated model grid of study area 62

3.11 Geographical boundaries of the model domain 63

3.12 Simulated and observed groundwater head at an OW-1 67









3.21 Water balance of the study area from June, 2012 to June, 2014 72

4.1 Yearly basis installation of groundwater pumps in the study area 83

4.2 Comparison of crop yields cultivated in the study area 85

4.3 Comparison of the cost of production with total income from the crop 87

4.4 EC comparison of hill torrent and groundwater irrigated field 94

4.5 EC map of hill torrent (a) and groundwater (b) irrigated fields 95

4.6 pH comparison of hill torrent and groundwater irrigated fields 96

4.7 pH map of hill torrent (a) and groundwater (g) irrigated fields 96

4.8 Concentration of Na in hill torrent and groundwater irrigated fields 98

4.9 Na map of hill torrent (a) and groundwater (b) irrigated fields 98

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4.10 Concentration of Ca+Mg in hill torrent and groundwater irrigated fields 99

4.11 Concentration of Cl in hill torrent and groundwater irrigated fields 100

4.12 Concentration of HCO3 in hill torrent and groundwater irrigated fields 101

4.13 Comparison of SAR of hill torrent and groundwater irrigated fields 102

4.14 SAR of hill torrent (a) and groundwater (b) irrigated fields 103

4.15 Predicted groundwater head for an OW No. 1 under the Scenario-I 105









4.24 Predicted groundwater heads for OW No. 1-9 under the Scenario-I 110

4.25 Predicted groundwater head for an OW No. 1 under the Scenario-II 111









4.34 Predicted groundwater heads for OW No. 1-9 under the Scenario-II 114

4.35 Predicted groundwater head for an OW No. 1 under the Scenario-III 115









4.44 Predicted groundwater heads for OW No. 1-9 under the Scenario-III 118

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LIST OF APPENDICES

AP. NO. TITLE PAGE NO.

A1 Questionnaire; agricultural practices of the farmers under Mithawan hill torrent

command area, DG Khan-Pakistan 134

A2 Educational status and landholding of the farmers of study area 138

A3 Area cultivated with different crops during Kharif season, 2012 139

A4 Area cultivated with different crops during Rabi season, 2012-13 140

A5 Area cultivated with different crops during Kharif season, 2013 142

A6 Area cultivated with different crops during Rabi season, 2013-14 143

A7 Sources of irrigation and pumping units of the farmers 144

A8 Year and specification of the pumping units installed in the area 146

A9 Well drilling and depth of watertable in the study area 147

A10 Method of irrigation and frequency of hill torrents occurrence in the study area

149

B1 Discharge measurement of 6ʺx7ʺ centrifugal pumps installed at DG canal

for irrigation of the study area using cut-throat flume of 10x90cm size 151

B2 Discharge measurement of the pumps installed in the study area using

cut-throat flume of 10x90cm size 151

B3 Discharge measurement of 2-submersible pumps of 2ʺ delivery pipe dia. of

each installed in the study area using volumetric method 151

C1 Economic value of wheat crop cultivated in the study area 152

C2 Economic value of gram crop cultivated in the study area 152

C3 Economic value of brassica crop cultivated in the study area 153

C4 Economic value of arugula crop cultivated in the study area 153

C5 Economic value of sorghum crop cultivated in the study area 153

C6 Economic value of millet crop cultivated in the study area 154

C7 Economic value of guar crop cultivated in the study area 155

C8 Economic value of cotton crop cultivated in the study area 155

C9 Economic value of onion crop cultivated in the study area 155

D1 Electrical conductivity and pH of hill torrent water samples 156

D2 Water samples analysis of hill torrent flow 156

D3 Electrical conductivity and pH of groundwater samples of the study area 156

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D4 Groundwater samples analysis of the study area 157

D5 Electrical conductivity of soil samples of the fields of study area 157

D6 pH of soil samples of the fields of study area 158

D7 Na concentration in soil samples of the fields of study area 158

D8 Ca+Mg concentration in soil samples of the fields of study area 159

D9 Cl concentration in soil samples of the fields of study area 159

D10 CO3 concentration in soil samples of the fields of study area 160

D11 HCO3 concentration in soil samples of the fields of study area 160

D12 SAR of soil samples of the fields of study area 161

D13 RSC concentration in soil samples of the fields of study area 161

E1 Observed watertable data of selected observation wells at selected hill torrent

command area 162

F1 Elevation of the top of soil surface of study area w.r.t. mean sea level 167

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LIST OF ABBREVIATIONS

ABBREVIATION MEANINGS

CROPWAT A decision support tool developed by the Land and Water

Development Division of FAO

DG Khan Dear Ghazi Khan (a district of the Punjab province of Pakistan)

ESCAP Economic and Social Commission for Asia and the Pacific

FAO Food and Agriculture Organization

FATA Federally Administrated Tribal Areas (Pakistan)

FFC Federal Flood Commission

GWG Groundwater Governance

I&PD Irrigation and Power Department

IWASRI International Water logging and Salinity Research Institute

IWMI International Water Management Institute

JFIT Judicial Flood Inquiry Tribunal

KPK Khyber Pakhtunkhwa (a province of Pakistan)

MODFLOW Modular Three-Dimensional Finite Difference Groundwater Flow

Model

NESPAK National Engineering Services Pakistan

NSL Natural Surface Level

OW Observation Well

PIPD Punjab Irrigation and Power Department

PMD Pakistan Meteorological Department

RD Reduced Distance

UN United Nations

WAPDA Water and Power Development Authority (Pakistan)

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CHAPTER 1

INTRODUCTION

Pakistan is the second largest country in South Asia by size with a total area of

79.61mha and population 184.35 million (Wasti, 2013). The potential area for agriculture

and forestry is estimated as 46% (36.62mha) of the total area of country (Hasan, 2008).

The average annual cultivated area of the country was 25.72mha, out of which, about

19.27mha was under full control of irrigation (i.e. 6.91mha canal irrigated, 4.13mha

groundwater irrigated, 7.96mha combined with canal water and groundwater, and

0.27mha irrigated with wastewater), 2mha by the spate irrigation, 3.2mha rainfed (Barani)

and 1.25mha was sailaba riverine (Ahmad, 2007; Baig et al., 2013; Frenken, 2012). So

far, there are enough land resources to meet the grain demand of increasing population

but there is shortage of water. Pakistan is facing the shortage of water for many years,

mainly due to increase in population and mismanagement of available water resources.

The increase in population of country has decreased the surface water supplies from

5260m3/capita in 1951 to 1032m3/capita in 2013 (WAPDA, 2013). In addition to the

increase in population, other factors, such as lack of storage facilities, inefficient canal

system, water losses through distributaries, wastage of water at the farm level and

mismanagement of hill torrents are also responsible for water scarcity in the country.

Since creation, Pakistan has experienced severe problems of droughts and floods.

Droughts generally brought huge damages to the provinces of Balochistan, Sindh and

Southern Punjab. Drought periods of 2000 to 2003 spread across 68 districts of the four

provinces of Pakistan, which severely affected economy through crop and property

damages, death of humans & animals, and the migration of thousands of farming

communities. Similarly, floods of various magnitudes in 1950, 1956, 1957, 1973, 1976,

1978, 1988, 1992 and 2010 were very destructive (Hashmi et al., 2012). During 2010, a

flood flow of about 6790m3/s from Dera Ghazi Khan (DG Khan) and Rajanpur hill

torrents was added into the Indus river system, which hit vast areas of Southern Punjab,

Sindh, hilly areas of Khyber Pakhtunkhwa (KPK), Balochistan and Federally

Administrated Tribal Areas (FATA). Requisite consideration to efficiently utilize the hill

torrent water resources has not been given. In September 2012, heavy rains occurred in

KPK, Southern Punjab, Northern Balochistan and Upper Sindh of Pakistan and caused the

flash floods, which raised the water level in nullas and hill torrents. As a result of heavy

torrential floods, DG Khan and Rajanpur districts of Southern Punjab, Kashmore, Sukkur,

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Jacobabad, Shikarpur, Larkana, Qambar-Shahdadkot, Dadu and Badin districts of Sindh,

Loralai, Jaffarabad, Naseerabad, Jhal Magsi, and Qila Saifullah districts of Balochistan,

were harshly damaged. These floods affected 4.85 million population of Punjab, Sindh

and Balochistan including loss of 571 lives, 14159 villages, 636438 houses and 0.474mha

of cropped area (FFC, 2012). Consequently, Pakistan has been facing severe flood

damages and resultantly, billions of rupees have been lost in these floods. Thus, based on

the previous experience, the country may face severe water challenges in the future.

1.1 Water resources of Pakistan

Major water resources of Pakistan include Rainfall, Surface water and Groundwater,

which are briefly described below:

1.1.1 Rainfall

In Pakistan, there is a huge spatial and temporal variability in the occurrence and

magnitude of rainfall. Its distribution varies with two major seasons i.e. monsoon season

and winter precipitations. Monsoon season starts from July to September as a result of

monsoon winds entering the country from East to North-East. The winter rains are mainly

the result of western disturbances entering from Iran and Afghanistan and continue from

December to March every year. Khyber Pakhtunkhwa and Balochistan provinces receive

maximum rainfall during winter rains whereas the Punjab and Sindh provinces receive

about 50-75% of annual rainfall during monsoon season. The rainfall magnitude varies

from about 100mm in the Southern to 1500mm in the Western parts of the country.

Eighty nine percent area of Pakistan (70mha) has arid and semi-arid climate. In arid and

semi-arid climate of the country, the natural precipitation is very little. Over 50% of the

country receives less than 200mm average annual rainfall and on 20% of the Northern

areas, rainfall occurs in excess of 400mm (Gopalakrishnan, 2005). About 70% of annual

rainfall occurs during monsoon season that produces rainfall runoff, which mostly goes

unused to the Arabian Sea. In Pakistan, rainfall contribution has been estimated as 9.24

billion cubic meters (BCM) to the irrigated agriculture and 7.34BCM to Barani irrigated

areas in the Indus Basin (ESCAP, 2005).

1.1.2 Surface water

The surface water resources have been further divided into (i) River system flows

(ii) Hill torrent flows

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(i) River system flows

The river system flows consist of river and spring flows that continue to flow

throughout the year. The rivers including Indus, Jhelum, Chenab, Ravi and Sutlej

originate from the high mountains of snowmelt and heavy rainfall in their catchment

areas and flow through the plains of Pakistan and collect water from large number of

small river lets and streams at various reaches. Out of all these rivers, Indus is the major

one and others are its tributaries. Some of the minor tributaries include Soan, Harow and

Siran rivers. There are other minor tributaries, which join the river Indus from its western

side include Kabul, Kunar, Punj, Kora. Likewise, Kurram, Gomal, Tai, Kohat and Tank

are other small streams. In addition, a large number of hill torrents join the river Indus

from its western side after originating from the mountainous areas of Sulaiman

Mountains. The catchment area of Indus river system exists at seven highest peaks of the

world after Mount Everest, which includes K-2 (6813.72m), Nanga Parbat (8128m),

Rakaposhi (7790.25m) etc. Similarly, the seven largest glaciers of the world are also

situated in the catchment area of the Indus, namely, Siachin, Hispar, Biafo, Batura,

Baltoro, Barpu and Hopper.

On average, the Indus Basin Irrigation System of Pakistan receives about

190BCM of water every year. Out of this, 178.87BCM is contributed from the rivers

Indus, Jhelum and Chenab, and 11.13BCM from the rivers Ravi, Beas and Sutlej. Out of

the total input to the rivers system, 129.3BCM is used for irrigation, 48.64BCM goes to

the Arabian Sea as unused and 12.06BCM is lost during conveyances through the

irrigation channels (Ahmed et al., 2007). The water, which flows to the Arabian Sea as

unused varied from 11.11BCM to 113.57BCM and is available in the river for 70 to 100

days during summer season (WAPDA, 2013).

Pakistan’s major water reservoirs include Tarbela, Mangla and Chashma. No

reservoir has been added to the system after commissioning of Tarbela reservoir. Thus,

the country is badly lacking in storage facilities to regulate the river flows and input to the

irrigation system. Currently, it is estimated that the designed live storage capacity of 3

surface water reservoirs is 144m3/capita as compared to 6000m3/capita in USA, which

shows that the per capita water availability in the country is too low. Furthermore, the

existing reservoirs can store the flow for 30 days while the storage system associated with

Colorado River in USA, is capable of storing the flow for 900 days (Ahmad, 2007). Lack

of storage facilities in the country result in floods and wastage of water resources.

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(ii) Hill torrent flows

Hill torrent is the high speed huge discharge of rainfall runoff from hills to plain.

It can also be defined as the rainwater collected from different mountainous or hilly areas

through a large number of smaller gorges into a bigger one that eventually flows in the

form of flood to the plains. In many regions of the world, different typical terms are used

for hill torrents. In the province of Punjab Pakistan, it is locally known as Nai and Rod

Kohi, in Khyber Pakhtunkhwa province it is known as Rod-Kohi, Sailaba (flood water) and

Khushkaba (rainfall and localized runoff) in Balochistan, and Nai as well as Gabarband in

Sindh province. Rod Kohi is the combination of two Persian words Rod and Kohi, “Rod”

means stream and “Kohi” means hill. Thus, Rod Kohi is a stream, which originates from

the hills as a result of incident intense rains.

In Afghanistan this system is called Pago, while in some parts of Iran, it is called

Sahraa and in Eritrea this system is locally known as Jerif. Recently, for this system a

unique term Spate Irrigation is being used on large scale at local as well as international

level. Initially, Iranian farmers diverted the hill torrent flows into their newly developed

fields, which made the fields ready for cultivation that was previously not feasible.

Consequently, the water diverted into the fields was left to infiltrate deeply into the soil

and recharged to the groundwater that could be utilized further for a number of purposes

(Nawaz and Qazi, 2002).

Occurrence of the hill torrent depends on rainfall and may occur at any time.

Generally, the hill torrents in Pakistan occur in monsoon season i.e. from July to

September. The estimated catchment area of hill torrents in Pakistan is 40.12mha, which

drain about 55% of the total area of country. The average annual hill torrent potential in

Pakistan is about 23BCM against the command area of about 2.34mha (Sufi et al., 2011).

A major part (more than 50%) of this water is lost due to mismanagement (PILDAT,

2003). The water of hill torrents may further move towards the canal irrigated areas or fall

in the river system in unmanaged manner.

1.1.3 Groundwater

Groundwater is an important source of irrigation, which is available for crop

production through pumping systems. It meets about 50% of the global drinking water

and 43% irrigation requirements (GWG, 2010). The groundwater contribution is

diminishing because of over-exploitation, which may also cause severe salt water

intrusion and land degradation (Gleeson et al., 2012). In Pakistan, it contributes more than

23

50BCM of pumped water annually, which is about 40% of the surface water available at

farm gates or canal outlets. Groundwater provides supplemental irrigation for potential

crop production and so far, 1050 thousands tubewells have been installed in the country

to pump groundwater (GoP, 2015a). However, the current situation of uncontrolled

installation of tubewells has created problems of over pumping, leading to undermining

of groundwater, lowering of watertable and saltwater intrusion leading to the deterioration

of adjoining soils of the Indus Basin. The lowering of watertable, in turn, increases the

cost of pumping and lowers wells yield. In Punjab, about 4.5mha of land is suffering from

salinity due to the application of saline groundwater. Similarly, in Sindh about 56% of the

land has deteriorated with poor quality of groundwater. In Balochistan, the watertable has

dropped at about 2-3m per year and thus 15% of its cultivation area had been restricted

(Qureshi et al., 2010).

1.2 Hill torrent areas of Pakistan

The hill torrent areas of Pakistan have been grouped into the following three

major regions:

North and North Western mountains hill torrents

Sulaiman, Kachhi and Khirthar basin hill torrents

Low mountains hill torrents

1.2.1 North & North Western mountains hill torrents

Theses hill torrents originate from the high mountains of North and North-

Western parts of Pakistan and their flows can be conserved by constructing low head

dams at potential sites. The major hill torrents under this region are discussed below:

(i) Azad Jammu and Kashmir (AJK) hill torrents

These hill torrents originate from Himalayas and flow toward the foot of hills at

North of Azad Jammu and Kashmir. Under these hill torrents, the area suitable for

agriculture is located along the sides of torrents.

(ii) Northern areas hill torrents (Gilgit – Baltistan)

The Northern Areas Hill Torrents hill torrents originate from the high altitude of

Hindu Kush and surrounding mountains. Generally, these hill torrents are the result of

snow melt and have low sediment loads and hence can be stored in the reservoirs. There

is less area for cultivation but some patches of land can be developed for the cultivation

24

of vegetables and orchards under various hill torrents. However, a large number of

suitable sites are available for the construction of low head storage facilities.

(iii)Federally administrated tribal areas (FATA) hill torrents

The federally administrated tribal areas hill torrents originate from the snow

covered mountains of tribal agencies and frontier regions. Currently, about 6% of the area

is cultivated and 7% more can be brought under cultivation, if water resources of these

hill torrents are managed properly. However, a large number of suitable sites are available

for the construction of mini dams to control and beneficially utilize the flow of these hill

torrents.

(iv) Hazara, Kabul & Bannu area (HKB) hill torrents

HKB hill torrents occupied about 64% of the total area of KPK that consisted of

the mountainous and plain areas bounded by the hills. Some of the tributaries of river

Indus such as Kabul, Swat, Kurram, Panjkora etc. pass through this area. However,

various sites for the construction of mini dams are available under these hill torrents to

develop land and water resources of the area.

1.2.2 Sulaiman, Kachhi & Khirthar basin hill torrents

The following six major hill torrent areas have been included in this region:

(i) Dera Ismail Khan (DI Khan) hill torrents

(ii) DG Khan and Rajanpur hill torrents

(iii)Kachhi basin hill torrents

(iv) Khirthar range hill torrents

(v) Sehwan & Petaro area hill torrents

(vi) Karachi area hill torrents

The hill torrents of DI Khan, DG Khan and Rajanpur originate from the Sulaiman

Mountains and after passing through the Pachadh area (a 360 km long and 30-40km wide

belt of land from Ramak to Kashmore between Sulaiman Mountains and CRBC, DG &

Dajal Canals) these hill torrents strike with the right banks of Chashma Right Bank Canal,

DG Khan Canal and Dajal Branch Canal, respectively. The Kachhi Basin hill torrents

originate from the Marri and Bughti hills and strike with the Pat Feeder Canal. However,

the remaining hill torrents of this region originate from the Kirther range. Malir Nadi hill

torrent of Karachi area crosses the super highway and railway line of Karachi Hyderabad,

while Kalu and Choherh Nalas hill torrents, after crossing railway line of Karachi

Hyderabad, outfall into the Kinjhar Lake.

25

1.2.3 Low mountains hill torrents

(i) Pothohar area hill torrents

(ii) Rechna & Chaj Doabs hill torrents

(iii)Kharan closed desert basin hill torrents

(iv) Makran coastal basin hill torrents

Out of the above four hill torrent areas, Pothohar Area or Pothohar Plateau exists

in the districts of Jhelum, Chakwal, Rawalpindi, Attock and some area in the northern

part of district Gujarat. These hill torrents have harsh impact on the soil degradation in the

form of gully erosion. The Rachna and Chaj Doabs hill torrents originate from the low

height mountains of Indian occupied Jammu & Kashmir. The command area of these hill

torrents exists in the north eastern side of the Punjab, Pakistan. A large number of small

dams at various sites on the way of these hill torrents can be constructed to conserve their

flows.

Kharan Closed Basin Hill Torrent Areas exist in the North Western part of

Balochistan and covered by the dry mountains. The area receives less rainfall with closed

drainage whereby the flow of torrents drains toward the swamps of Hamun.e.Lora and

Hamun.e.Mashkel, which are mostly dry after low rainfall. The intensive rainfall

produces heavy floods, which are wasted due to lack of storage facilities in the area.

Makran Coastal Basin Hill Torrents Area exists along the coastal strip of Arabian

Sea in eastern part of Balochistan. Physiographical features of the area consist of series of

mountains and alluvial plains and there is more influence of monsoon rainfall, which

causes different intensities of hill torrents. The area has no proper conservation and

drainage system for handling the hill torrent flows, and hence, after damage to the roads,

villages and crops, the major part of flow outfalls into the sea as unused.

1.3 Potential in hill torrents of Pakistan

Hill torrent irrigation system covers an area of about 3.3mha in 14 countries such

as, Pakistan, Kazakhstan, Somalia, Eritrea, Mongolia, Tunisia, Sudan, Yemen, Algeria,

and Morocco. It covers about 11% of the total irrigated areas of these countries. Among

these countries, Pakistan has largest area under hill torrent irrigation system. Mostly, this

system of irrigation is practiced at lowland command areas at the west of River Indus

(Mirjat et al., 2011).

Spate irrigation, which is accomplished by the supply of water from hill torrent, is

the second largest source of irrigation after canal water irrigation in Pakistan. This system

26

of irrigation prevails in the country since centuries. Spate irrigation system is

participatory in nature and environment friendly as it does not require energy due to

gravity flow and has organic farming produce. Presence of heavy sediments in hill torrent

flow also plays an important role in agricultural production. There is the average annual

potential of around 23 billion m3 of water from 14 major hill torrents (Sufi et al., 2011).

Out of these, 13 hill torrents (excluding Kharan Closed Basin Hill Torrent Areas) have

great potential for land and water resources development at about 1204 conservation sites.

The highest potential for hill torrent management exists in Balochistan, whereas, the other

potential hill torrents include DG Khan, DI Khan, Bannu, Hazara, Kachhi Basin, Kirther

Range, Karachi area, Sehwan, Petaro (Ahmad, 2012). A major part of 13.25mha of

potential land, out of which 6.35mha lying in the hilly areas and 6.9mha in the

foothills/plains, can be brought under cultivation through efficient utilization of hill

torrents water. Depending upon the occurrence of hill torrents and their management,

however, only 0.72 to 2.0mha of land is annually cultivated with spate irrigation, which

makes about 9% of the total annually irrigated area of Pakistan (Mirjat et al., 2011). The

scarce water resources of the country including canal water and groundwater alone cannot

meet the future water requirements without managing the hill torrent water resources to

its productive potential. The detail of possible sites for hill torrent development in

Pakistan is as given in Table 1.1(NESPAK, 1998b).

Table 1.1: Prospective sites for hill torrents development in Pakistan

Province/area No. of potential hill torrent sites

Balochistan 423

Khyber Pakhtunkhwa 417

Punjab 211

AJK and Northern Areas 120

Sindh 33

Total 1204

In Balochistan province, annual hill torrents water availability is about

12.46BCM, out of which, only 1.56BCM is beneficially utilized (Nature, 2000). Potential

spate irrigated area in Balochistan is around 1.07mha, out of which, about 0.20mha are

commanded annually. Whereas, in KPK potential spate irrigated area is around 0.52mha,

out of which, about 0.26mha are commanded on annual basis in DI Khan, Tank and

Kulachi (Ahmad, 2001).

In Punjab, the spate irrigation systems mainly exist in the districts of DG Khan

and Rajanpur, where conventionally, it is called as Rod Kohi irrigation. These districts

27

cover an area of 2.39mha, out of which, 17 percent is Canal Command, 35 percent

Pachadh area (Rod Kohi/spate Irrigated), and 48 percent mountainous and sub-

mountainous area. Pachadh area lies within arid climatic zone of the country having

thirteen major and about 192 minor hill torrents, which originate from the Sulaiman

range. Out of thirteen major hill torrents, seven exist in DG Khan (from north to south

namely; Kaura, Vehowa, Sanghar, Sori Lund, Vidore, Sakhi Sarwar and Mithawan) and

six in Rajanpur. These hill torrents receive an average annual rainfall of 250mm at

catchment area of 10180 square kilometer. The average runoff from the Sakhi Sarwar and

Sanghar hill torrents varies from 0.017 to 0.784BCM. In addition to the non-perennial hill

torrent system, there are some perennial torrent flows in DG Khan, which are termed as

“Kalapani or Aab.e.Siah”. In District DG Khan alone, average irrigated area under seven

major hill torrents is about 0.2mha covering a potential command area of about 0.41mha

(NESPAK, 1990).

1.4 Statement of the problems

Water is one of the major sources for economic development and poverty

reduction in Pakistan. In the country, water resources are consistently losing due to poor

management and climate change. In contrast, the land use has increased to promise the

grain requirement of increasing population. Thus, the gap between supply and demand of

water has adversely affected to rank Pakistan in the category of acute water deficit

country. The harshness of water deficit cannot be ignored while attempting to achieve the

economic development of the country. The issue of water crisis has become a serious

challenge for water managers. Appropriate management of river flows is indispensable to

cope with future needs of increasing population and to safeguard the country from water

short category. Droughts and severe shortage of water are causing food scarcity in the

country; therefore, the management of hill torrent water resources is very important to

promote agriculture in spate irrigated areas.

In spate irrigated areas, water scarcity is major threat to agriculture. The farmers

of these areas are facing a number of problems, such as high cost of diversion structures,

poor financial resources, damages through floods, heavy sediment load, low yield of crop,

less attention by the researchers and government etc. Crop yield of spate irrigated areas is

less than its potential, mainly due to poor irrigation management. Spate irrigation is

applied once before the sowing of crops and subsequently, the crops are dependent on

direct rainfall that satisfy less than 15% of the requirement (Qureshi et al., 2004b). If,

28

subsequent irrigation is applied by the spate water then already germinated crop is buried

due to heavy sediment load. Furthermore, the spate irrigation system needs to repair the

bunds and construct heavy duty structures across the flow of water to divert it into the

field, which require high cost.

As a result of gradual development in agriculture, the crop yields have increased

significantly in canal commanded areas. On the other hand, at hill torrent commanded

areas, the requisite production level has not been achieved, mainly because the requisite

development has not been carried out yet. Hill torrent flow path and regime are not

managed properly causing huge losses to the land, crops and property. At the command

area of hill torrents, a little part of water is utilized and remaining part of the peak

discharge flows to the canal irrigation system where it causes the variety of flood

damages. The management strategies for hill torrents must be developed to facilitate its

safe flow and efficient utilization for agricultural development. Therefore, it becomes

necessary to give attention to the problems of farmers and conduct the studies relevant to

the management of hill torrent flows. In order to carry out the present study and achieve

the planned objectives for meaningful results within available study period, the command

of Mithawan hill torrent of DG Khan is selected to implement the study.

Mithawan hill torrent is one of the thirteen major hill torrents that originate from

Koh-e-Sulaiman. Its command area lies in the Pachadh area of DG Khan, which is major

hill torrent area of the Punjab province of Pakistan. Usually, the area consists of sandy

soil, loam, sandy loam and silt loam soil types (Ahmad, 2003), which are good for

agriculture with the exception of sandy soils. Because of uncertainty or temporal and

spatial variability in the occurrence of rainfall, the hill torrent/spate water may or may not

be available at the time of sowing (Javed et al., 2007). To ensure water availability at the

time of sowing, therefore farmers in Mithawan hill torrent command area, DG Khan have

installed pumping units for lifting groundwater and canal water for irrigation (where

feasible). They have a choice to use either canal water, groundwater or hill torrent water

separately or conjunctively. Irrigation with the groundwater permits the farmers to timely

sow the crops and provides subsequent irrigations. Such farmers don’t invest money and

can save the cost that may be incurred on the construction of hill torrent control and

diversion structures but have to bear the additional cost of installing turbines and

pumping groundwater.

In Mithawan hill torrent command area, groundwater exists at a greater. The

quality of groundwater in top layer is not fit for irrigation while the second layer is usable

29

for irrigation purposes. The continuous application of groundwater deteriorates the upper

surface of soil due to its poor quality. To overcome this problem, farmers need flood

irrigation through spate water at least after every three years. If, spate water is not

applied, the yield of crop is decreases. Moreover, the continuous and excessive pumping

of groundwater may cause the decline of watertable in the area.

The dependence on groundwater in the selected hill torrent command area has

been significantly increased and therefore, the management of water resources and its

utilization need to be improved through efficient harvesting of hill torrents and adopting

groundwater recharge techniques to mitigate the effects of extensive pumping. It is

estimated that if turbine installation and pumping trends continue with current rate then in

future, water may not be available at this depth and all installed pumps may fail. The

studies conducted so far, on hill torrents, reported different options for management of

hill torrents but none of those addressed the groundwater pumping and its management.

Hence, there is a dire need to focus on groundwater in addition to the surface water,

manage all the existing water resources conjunctively. The study would not only identify

the problems faced by the farmers but also develop strategies to manage the available

surface and groundwater resources at the selected command. The results of study may be

considered for future planning of water resources in similar hill torrent commands.

1.5 Objectives of the study

The objectives of the study are given below:

1. To assess the relative contribution of surface water, groundwater and rainfall to meet

the crop water requirement at a selected hill torrent command area.

2. To investigate the impact of hill torrent and groundwater irrigation application on land

fertility, crop productivity, environmental conditions of the area, and socio-economic

conditions of the farmers.

3. To develop the management strategies for efficient use of water resources in selected

hill torrent commanded area.

30

CHAPTER 2

REVIEW OF LITERATURE

Hill torrent irrigation system is a centuries old irrigation system in areas of the world and

a number of management schemes have been introduced to manage and utilize this

precious source of water beneficially. This chapter summarizes the relevant research

studies carried out in the past to update the existing knowledge on the subject. The review

helped the understanding of the importance of water resources management at global and

national level to improve the agricultural production. However, a number of reports have

been written by different organizations, planning agencies and departments but less

scientific studies have been conducted so far on this resource of water. Furthermore, this

chapter also contains the appraisal of CROPWAT and MODFLOW models used for this

study.

2.1 Hill torrent irrigation system management

In Pakistan, first serious attempts for the control of hill torrents was made after the

worst flood of 1929, which seriously destroyed the Pachadh area of Dera Ghazi Khan.

Heavy hill torrents floods in DG Khan occurred during the monsoon seasons of 1906,

1917, 1929, 1955, 1967, 1973, 1975, 1976, and 1988. To date, a number of management

proposals have been submitted by different government officials and institutions but none

could be implemented due to one or more reasons.

WAPDA (1976) organized the major hill torrents of Pakistan into regional clusters

indicating the preliminary potential of some of the largest ones. Those hill torrents were

classified into Hazara, Bannu, DI Khan, DG Khan, Kachhi Basin, Kirther Range, Karachi

area, Sehwan and Petaro areas. Utilization of the flow of these hill torrents was very

important in view of the limitations of water resources to meet the increasing demands of

growing population.

Ahmad and Mazhar (1980) reported the major hill torrents catchment areas,

average discharge, farm landholdings and estimated farm income from the project area.

Small, medium and large size village population, number of animals, tubewells and canal

irrigated areas of the project were also reported as given in Table 2.1.

31

Table 2.1: Major hill torrents’ catchment areas and average discharge

Major hill torrents Catchment area

(sq. km)

Average discharge in 1978

(m3/s)

Sanghar 4806.75 3499.25

Vehova 2892.86 906.83

Kaura 510.20 513.35

NESPAK (1984) conducted “Master Planning Studies for Flood Management of

Hill Torrents of Dera Ghazi Khan Division”. These hydrometeorologic studies indicated

the water potential of each of the 13 major hill torrents of the area. Based on water rights,

soil classification, existing land use, agro-irrigation practices, available land potential, the

possibilities of watershed management and the optimal development plans were

presented. The plans were formulated on cost effective and multipurpose basis so as to

achieve the targets of agro-economic development as well as proper flood protection of

the cities, villages, agricultural land and infrastructure. The plan included the Mithawan

hill torrent area, which was one of the 13 major hill torrents of the region. Under that

plan, the construction of flood dispersion structures and allied works were recommended.

Afterward, JICA updated the study, recommending the construction of flood dispersions

structures in Pachadh while Vidore hill torrent was recommended as a pilot project. A

dispersion structure was constructed to divide the flow equally into three branches.

PIPD (1984) conducted the hydraulic model study of Mithawan Hill Torrent to

conclude the width and elevation of outlets of distribution structure to assure the required

shares of flow prior to the designing of the distributor. The model test showed the

development of sandbars upstream of structure, which intended the possibility of unequal

shares of flood distribution. Hereafter, the hydraulic model test was reviewed and it was

pointed out that proposed narrow outlets of distributor would increase the flow velocity

that would cause severe scouring, resulting in collapse of the distributor.

Heiler and Brown (1989) summarized the major villages of DI Khan, which were

irrigated by Rod Kohi system. The major finding of study was a mismatch in time

between the availability and demand for irrigation water. Similarly, it was concluded in

the study that problems associated with water control during the periods of availability

were of short duration and high discharge. Irrigation practices of the area were suffered

because of high discharge, inadequate management control and sedimentation.

Bhatti (1990) reported that in DG Khan and Rajanpur districts, there were about

200 small and large hill torrents emerging from Suleiman Mountains, of which 13 were

major ones. Total area of both districts was about 2.4mha, of which about 1.17mha was

32

hill torrents catchment area, 0.81mha Pachadh area and about 0.40mha was irrigated area

commanded by the DG Khan canal.

NESPAK (1995) estimated that total agricultural land under hill torrents was

2.34mha against gross water potential of over 1.50mha-m. Based on the hydrologic

analysis, soil survey maps and local agro-economic data, the prospective land and water

resources of various hill torrent areas of provinces are given in the Table 2.2.

Table 2.2: Estimated land and water resources of hill torrents

Province Catchment area

(mha)

Average annual run-off

mha-m (MAF)

Agri. land

(mha)

Balochistan 25.4737 0.5 (4.05) 0.69

KPK (NWFP) 4.3597 0.4 (3.24) 0.53

Sindh 3.2314 0.12 (0.98) 0.18

Punjab 4.3332 0.24 (1.94) 0.52

FATA 2.722 0.24 (1.94) 0.42

Total 40.12 1.5 (12.15) 2.34

NESPAK (1996) reported that the problems were faced in the canal network,

when flow rate of the torrents exceeded the capacity of cross drainage structures. Water

accumulated along the right bank of canal, caused serious breaching and inundated in the

canal command area. The heavy torrential flow not only destroyed human life, property

and infrastructure in the area but also caused closure of the canal for extended periods.

Steenbergen (1997) reported that the spate irrigation in Balochistan was

essentially important to provide livelihood for a large number of financially poor people

of arid areas. It included the activities of farming communities of spate irrigated areas to

cope with uncertainties in seven interlinked social themes; originality, internal division,

risk coping plans, labor peaks and mechanization, restricted land possession, active land

development and reactive water rights. It was suggested to look at flood management

approaches, with focus on institutional possessions, use of land formation processes and a

river-basin wide perception.

NESPAK (1998a) conducted the hill torrents frequency analysis of flow rates,

flow volumes during different months, use of torrents water and command area of canals

inundated by torrents flood, for return period of 2.33, 5, 10 and 20 years. The study

showed that most of the flow was during the months of June to September and maximum

flow was observed during the month of August. These flows were short time and

sustained only for a few days during the season.

33

NESPAK (1998b) reported that the potential area of about 6.94mha could be brought

under cultivation by the hill torrents in the country. About 24 billion cubic meters (BCM) of

water was obtained by the hill torrents, which was available at the rate of about 3478m3/ha

potential area of hill torrents. In Punjab province of Pakistan, potentially 0.57mha was

benefited by 3.345BCM of water from hill torrents. The available amount of water per

hectare was insufficient as compared to canal irrigated area. However, this inadequate

amount of water could be beneficially utilized for valuable crops using high efficiency

irrigation systems or by cultivating crops that require low amount of water such as oilseeds,

pulses, sorghum and millet. Similarly, the other options to beneficially utilize the available

water resources were to create the storage facilities, minimize the conveyance losses,

apply adequate amount of water.

Sadiq et al. (2002) conducted a series of studies in Barkhan area of Balochistan

and evaluated the efficiency of various low cost engineering structures, such as

distribution, diversion and check dams under hill torrent system. The cost of per structure

varied from Rs. 1500 to Rs. 4000 and provided livelihood to a large number of the

farmers of area. The engineering structures constructed for study improved the overall

efficiency of run-off farming system and encouraged conflict free environment among

farmers by efficient water distribution and diversion. Through this study, a decrease in

earthen channel gradient from 7 to 2% caused 25% increase in the yield of wheat crop.

Tesfai and Sterk (2002) conducted a study in Sheeb area of Eastern Eritrea and

reported that spate irrigation enabled the farmers to grow crops without the application of

fertilizers. Besides the continuous deposition of sediment in the fields, it created cultural

and management problems. The bed levels of fields were raised, which required the

raising of bunds embankments. Similarly, the cultivation practices had become hard due

to crust formation and sediment layer development. The study reported the sediment

deposition of 8.3 to 31.6, 6.0 to 18.0, and 5.2 to 8.6mm/annum in upstream, middle, and

downstream fields, respectively. This matched with an average sedimentation of

143tons/ha in a year that improved the physical and chemical properties of soil but in

future the soil may require the addition of nutrients.

Ahmad and Choudhry (2005) conducted a study at Mithawan hill torrent

command area of DG Khan and reported that unfair use, insufficient availability of water,

high cost of diversion structures, lack of labor & machinery, and poor financial condition

of the farmers were the major problems and constraints in the development of hill torrents

irrigation system. About 63% of the farmers responded that the hill torrents flow were

34

sufficient to the crops requirement but could not be beneficially utilized due to the

problems and constraints. It was assessed that an average irrigation application efficiency

of bunds were 27.7% and an average yield of wheat, gram, sorghum, millet, and brassica

was 1229.9, 575.6, 564.4, 519.5, and 561.6kg/ha; and water productivity was 0.161,

0.070, 0.067, 0.063, and 0.075kg/m3, respectively.

El-Askari (2005) developed the Spate Management Model (SMM) for the

simulation of spate irrigation practices in Wadi Tuban and Wadi Zabid of Yemen. The

model was used for decision support process of operation and management of spate

irrigation system for the Wadis. SMM could be used to simulate the channel and

distributions of flood water from head to tail. The flow distribution at the channel takeoff

points and water diversion structures were dependent on user defined water rights,

channel capacities and crop water requirements of spate irrigated area. Losses from

riverbed and channel network were considered in the simulation process. The output of

the model included volume of water diverted, volume of water at rest, volume of water

consumed to fulfill the crop water need, volume of water lost, the volume of water that

was not diverted to the each command area and the amount of water drained in the form

of runoff as well as volume of water replenished groundwater aquifer of the command

area. The model output could be presented in tabulated format or exported to GIS for

geographical presentation.

Lawrence and Steenbergen (2005) reported that about 20% inhabitants in central

region of the Governorate of Shabwah, Yemen had installed wells to minimize the risk of

droughts and get good yield of crops. The farmers installed wells, obtained double profits

than those had not installed the wells (KIT 2002). Since 1970s and 1980s, a large number

of wells were installed to extract shallow groundwater from coastal area of Yemen.

Funding for these wells was provided by their family members employed abroad or by the

agriculture credit banks. The government ban on the import of fruits and vegetables that

resulted an increase in the use of groundwater for irrigation. Consequently, it caused the

depletion of watertable and increases the risk of saline intrusion. Similarly, in different

command areas of Wadis a number of wells have been installed, such as about 1900 in

the command area of Wadi Tuban and 2000 to 2400 electrical pumping units installed in

Wadi Zabid. Generally, the farmers of area cultivated banana, other fruits and vegetables.

Some farmers also cultivated sorghum as a cash crop by selling it as green fodder

markets. Financial and hydrological constraints were major limits of groundwater

irrigation. The practice of installation of pumping units in spate irrigated areas of Pakistan

35

were far less than Yemen but the trend was started in DG Khan and Balochistan areas of

Pakistan.

Mehari et al. (2006) conducted a study of salinity hazard involved in spate

irrigation system in Wadi Laba, Eritrea. The spate irrigation system was only the source

of irrigation to cultivate sorghum and maize on about 2600ha in the Wadi. The farmers

had constructed earthen/brushwood diversion structures, which were frequently damaged

by the large floods (>100m3/s). However, in 2000, with the aim to irrigate the entire Wadi

using large floods (up to 265m3/s) and to double the crop yields, the Government of

Eritrea worked on the construction of permanent diversion structures. This construction

was done lacking in view the effect of potential salinity hazard. In 2002 and 2003, it was

determined that the salinity of floodwater increases with the discharge. For flood flows

great than 100m3/s, the leaching fractions for average root zone salinities ranged from 0.1

to 0.3, which would reduce the yield especially for maize crop from about 30 to 100%. It

was concluded that water management practices alone could not double the crop yields

until the floodwater allowance was considered for the need to control salinity.

Javed et al. (2007) compiled the previous reports prepared for hill torrent flood

management of DG Khan Division. It was stated that first time the Government of Punjab

appointed Mr. P. Claxton to study and prepare the hill torrents flood control proposal.

One dam for each location at Gulki and Haran Bore on Sanghar, Pishi on Vidore and

Harrand on Kaha hill torrent was proposed in the report. The proposal could not get

approval by the government due to lack of economic feasibility and insufficient geo-

hydrological data. In 1944-45, Irrigation Department worked on the flood control options

of hill torrents of DG Khan and proposed the construction of distributor at Darrah on

Sanghar hill torrent. Later the execution of the proposal could not be made due to lack of

financial justification and uncertainty at the time of independence. In 1951, a study on

sediment load of Sanghar hill torrent was conducted and it was conclude the hill torrent

brought heavy sediment load and could not be stored in reservoir. In 1952, a study

reported the spreading of various torrents into two to three different directions toward the

fields. In 1958, it was proposed to construct the storage reservoirs, check dams and delay

action dams but these plans could not get execution work because of uneconomical and

unfavorable geological conditions. Soon after the flood of 1976, a panel of Irrigation

Engineers proposed the establishment of Hill Torrent and Pachadh Development

Authority for hill torrents flood management and upgrading the irrigation system of

Pachadh area. While, three suggestions were given to the panel by the SE, Derajat Circle;

36

1) construction of distributors at Darrah with under sluice cum weir and main torrent

training work for the uniform distribution of water into the channels 2) retention of

unnecessary flood, if any, at right bank of DG Khan Canal by changing the right bank of

canal into heavy flood embankment and 3) construction of ogee shape speed breaker and

check dams to break the peak of flood. In 1976, it was proposed to distribute the hill

torrent floods into the command area through distributor and channel system. It was also

proposed to allow the entering of water accumulated at right bank of DG Khan Canal into

the canal command area through the construction of cross drainage structures over the

canal. The removal of hill torrent floods into the River Indus through the construction of

cross drainage structures over the existing infrastructure was also proposed by the

construction of hundreds of miles main and submain drains. During 1980s, NESPAK

carried a study on the management of hill torrents of Pachadh area. NESPAK worked on

thirteen major hill torrents of DG Khan Division and proposed the arrangement of

diversion structure and flood safety services for each hill torrent at the expanse of

government investment. The report was technically sound and economically viable and

hence largely accepted. Later, in 1990s the proposal was updated as part of the “Master

Feasibility Studies for Flood Management of Hill Torrents of Pakistan” and a

comprehensive study was conducted for “Core-Project” of the area by means of economic

analysis. As a result, a pilot project was planned and executed on Kaha and Mithawan

Hill Torrents under Flood Protection Sector Phase-1 (FPSP-1). After the construction of

Chashma Right Bank Canal (CRBC) a problem of flooding at right bank of CRBC has

created across the flood plains of Kaura, Sanghar, Vehowa and Sori Lund hill torrents. A

major part of the command area of these hill torrents had fallen in the command area of

CRBC and thus affected the situations of project. For which twenty one (21) flood

carrying channels had been constructed to remove the flows of these hill torrents.

Mehari et al. (2008) reported that in spate irrigated area of Wadi Laba, sorghum

and maize completed the growth period from September to April through the moisture

available due to spate irrigation from June 15 to August 15. Farmers of the area were

diverting harsh floods into their fields for about three to four times up to a depth of 0.5m

and obtained sorghum and maize production of 4.5tons/ha/year. The farmers of area

implemented two rules to ensure the equitability distribution of spate water among the

shareholders. (1) A field was irrigated twice, thrice and four times, if all other fields had

been irrigated once, twice and thrice, respectively. (2) Upstream, middle and downstream

fields were entitled to be irrigated on priority at medium (50m3/s), somewhat large to

37

large (50-200m3/s) and very large floods (200-265m3/s), respectively. These rules were

seriously followed when the farmers were dependent to each other for the maintenance

and construction of diversion structures. Although in 2000, these rules failed due to the

construction of concert diversion structures for spate irrigation system. For this, Soil

Water Accounting Model (SWAM) was developed, which computed the soil moisture at

the start of sowing when a field was irrigated twice, thrice or four times. The moisture

contents were 67.5, 72.0 and 77.5cm, if the field had its last irrigation on July 15, July 30

and August 15, respectively. The results were validated with Soil Water Atmosphere

Plant (SWAP) model and found that 67.5cm depth of water was enough for the said yield

of sorghum and maize. The concrete structures made it possible to irrigate the field up to

four times with spate irrigation system. Therefore, it was suggested that the water right

should be revised from size of flood to the time of floods.

Shahid and Ahmad (2008) reported that locally generated floodwater in

Balochistan province of Pakistan was the largest source of water i.e. about 2/3rd of the

total water resources of the province. In spite of huge amount of water, in the past less

importance was given to this source of spate irrigation. For sustainable agriculture,

necessary actions were required to utilize this source of irrigation water, which coupled

with high risk of uncertainty. The management of this floodwater would offer an

opportunity to spread it over large areas and contribute to the groundwater recharge in

potential zones. Similarly, the construction of storage reservoirs would minimize the risk

of uncertainties and assure supply of irrigation water during droughts. Therefore, it was

recommended that the development of spate irrigation along with the construction of

storage reservoirs would increase the reliability of water during dry year.

Steenbergen and Mehari (2009) stated that spate irrigation system management

needed the construction of field embankments, channels and diversion structures that

could gently handle, the large volume of water for a large scale. This needed strong

cooperation between the local communities on how to use the things, which were

uncertain and uneven. Generally, spate irrigation system was ignored in agricultural

investment programs, which had great potential to poverty alleviation and food security.

Globally, about 2.5mha of land was under spate irrigation system, which was the major

source of livelihoods of about 2.1 million households. Spate irrigation system existed in

Pakistan, Afghanistan, Iran, Yemen, Saudi Arabia, Ethiopia, Eritrea, Sudan, Somalia,

Morocco, Algeria, Tunesia and intermittently in some parts of Africa, South America and

Central Asia. However, the major part of this system exists in Pakistan and Iran. It

38

supported highly productive low cost farming systems. In lowlands of Eritrea the yield of

sorghum under this system ranged from 3750kg/ha to rarely 6000kg/ha. It was possible

because of two, three times spate irrigation application and sufficient storage of moisture

in the soil, which remained through entire crop season.

FFC (2010) investigated that in DG Khan and Rajanpur districts, hill torrents

experienced high flash floods during July and August and the maximum discharge at the

outlets of hill torrents were given in the Table 2.3. During 2010 the hill torrents raised the

flood flow of river Indus and caused huge losses. In the same year, vedore hill torrent

inundated the huge land area of urban DG Khan, Choti Zareen and Khanpur Munjwala.

Table 2.3: Maximum discharge at the outlet of hill torrents

Sr. No. Date Hill torrents Discharge (m3/s)

1 22-7-2010 Kaha 2267.09

2 22-7-2010 Chachar 991.85

3 05-8-2012 Sanghar 2167.90

4 05-8-2012 Vidore 2748.84

5 05-8-2012 Suri Lund 1463.41

6 08-8-2012 Vehowa 3131.42

7 08-8-2012 Kaura 1904.35

8 08-8-2012 Mithawan 1754.16

Cumulative Potential 6789.93

Source: Federal Flood Commission, Report on Floods 2010

JFIT (2010) reported that unmanaged flow of hill torrents contributed to the flood

peaks in the river Indus. It caused a variety of damage to the infrastructure, buildings, and

crops that were in the path. By the channelization and construction of storage facilities,

this valuable resource of water could be used for irrigation and livestock in the districts of

DG Khan and Rajanpur.

Muhammad et al. (2010) recommended that in piedmont plains, the farmers

practicing hill torrent irrigation since 300BC and with existing water rights made by the

British government have a number of issues. The upstream farmers had right on water

and excess water might be allowed to move down. Similarly, at some place even left or

right side farmers had no right on water to divert it into their fields. It was suggested that

a separate set up of directorate or autonomous authority consisting of engineers and other

trained staff from the relevant departments should be made for the development of area.

There should be a strong coordination among the administrative, politicians, lawmakers,

and law enforcing agencies for the projects and development of the area. In the area there

was a need for the efficient use of energy and need to introduce solar energy system and

39

wind mills, which were efficient for the area because of no long and dense vegetation.

Installation of tubewells and deep well turbines might cause the depletion of groundwater

because of low or no recharge and more discharge.

Oosterbaan (2010) submitted that in hill torrent areas, bund method of irrigation a

centuries old method of irrigation was still was in practice. These bunds might have the

capacity to store one meter depth of water. About three decades ago the hill torrents water

was being effectively used on an area of about 0.28mha but due to the change in socio-

economic conditions of the farmers, it decreased to 0.04mha. The practice of hill torrents

irrigation was seven times less than that of the past and caused flood damage. Hill torrents

irrigation was not only a source of water for crops but it offered protection from floods.

As per estimates of the farmers of DI Khan and Tank districts about 20 to 25 percent of

water was utilized for cultivation and the remaining flowed to Indus River. It was

recommended that socio-economic studies must be conducted to find the reasons of

deterioration of hill torrents irrigation system.

Nejabat et al. (2011) presented that over 90% of the area of Iran was arid and semi

arid due to very little and uneven distribution of rainfall. While, about 55% of the

irrigation water requirement was satisfied by the groundwater pumping this was depleting

the precious groundwater resources of Iran because of over pumping. If this trend of

groundwater pumping continues then Iran would face more arid conditions in future.

However, the flood water dispersion to recharge groundwater and spate irrigation of

rangeland and crops could be an appropriate means of the management of the problem. In

Gareh Bygone Plain at south east of Iran, spate irrigation practices by the floodwater

distribution were carried out by the dwellers of desert for drinking and irrigation

purposes. It was estimated that 48 socio-economic and environmental factors in the form

of 8 groups namely: soil, land, climate, flood, groundwater, vegetation, social and flood

losses could affect the spate irrigation system.

Steenbergen et al. (2011) worked on groundwater security in Yemen and reported

the decline in the watertable in different areas. The groundwater abstraction assessed by

different agencies quoted by Steenbergen was 270, 34 and 235MCM against the recharge

of 51, 18 and 115MCM in Sana’a Basin, Wadi Ahwar and Hadramawt, respectively. It

had become very difficult to drill the wells that hit the water level for their national rural

water supply program and hence 40% of the well drillings failed. There were 35

groundwater pumping units in Al-sinah basin, of which most were installed in 1970s at an

average depth of 260m and watertable 96m. The continuous abstraction of groundwater

40

had declined the watertable to 6m to the year 2010. Similarly, it was reported that short

term hill torrent floods were diverted into Wadi al Qarada in Sana’a Basin to irrigate

fields and recharge the shallow groundwater aquifers. There were over 100 wells in the

Wadi at a distance of about 300m apart. In 2008, the watertable reached to a depth of

320m with decline of 15m per annum. The increase in watertable reduced the well yield

by 50% and increased the level of sulphur and fluoride in pumped groundwater.

However, the construction of 47 stone check dams across the river bed improved the

groundwater recharge of the area. These structures slowed the speed of water, increased

infiltration rate and decreased sediment load in the flood water. The performance of these

structures were compared to recharge dams and found to be predominantly more effective

in groundwater recharging predominantly in contrast with large dams.

Oya et al. (2012) conducted a study in semi-arid area of Zway, Oromia Region of

Ethiopia to evaluate the effect of supplemental irrigation on cabbage and tomato yield.

Supplementary irrigation was decided on the basis of effective rainfall (5mm/day) and

soil moisture contents (at 25% by volume of 20cm depth) with treatment of 5.6mm/day

and 11.2mm/day using furrow and watering can irrigation. By furrow irrigation,

significant increase in the yield of cabbage was observed and with no affect on tomato

yield. Whereas, watering can has no effect on yield. However, the decision of water

application based on the soil moisture content was more effective than effective rainfall.

Similarly, the irrigation efficiency or water productivity of furrow irrigation was higher

than that of watering can technique. It was also concluded that the spate irrigation jointly

with farm ponds for supplemental irrigation would be effective for farming in semi arid

areas.

Shafiq (2013) investigated the initiatives taken regarding hill torrents management

and found that more recently during 2008, 2010, 2012 and 2013 DG Khan and Rajanpur

districts of Southern Punjab were severely damaged by the hill torrents. About 0.2mha

piedmont area locally known as Pachadh area was failed to receive hill torrent irrigation.

Pachadh area covered about 360km length from Ramak to Kashmore with 30 to 40km

width between Sulaiman Mountains and river Indus from Ramak to Taunsa Barrage,

between Sulaiman Mountains and DG Khan Canal from Taunsa Barrage to Zero

headwork at DG Canal and between Sulaiman Mountains and Dajal Branch from Zero

headwork to Kashmore. There about 200 small and large hill torrents occurred from the

catchment area of about 2.45mha. Initiatives on the hill torrents flood management started

from 1929 and Government started comprehensive work on Kaura, Vehova and Sanghar

41

hill torrents in 2009, improved Kaha hill torrents in 2011, and Vidore hill torrents in

2012, which were different stages of completion. With these projects about 50-60% of

water was being beneficially utilized. The irrigation intensity of the area was increased

from 8-50%.

Asif and Haque (2014) reported that there was potential of 23.05BCM water in

water short regions of the Pakistan, which were known as Rod Kohi/spate irrigated areas.

Agricultural practices in these areas were highly dependent on hill torrent and rainfall.

Unluckily, the major part of this water was not only wasted but also caused the loss of

human lives and property due to the lack of scientific work on water management and

modern farming activities. The destructive conditions were due to the absence of check-

dams as well as storage facilities at the foot of hills, which might be helpful in reducing

sediment load, groundwater recharge, diverted successfully into the fields etc. This

unattended source of water, if managed scientifically might improve the living standard

of the millions of people residing in these areas.

Saher et al. (2014) reported that in semi-arid regions of Pakistan, agricultural

practices were very difficult regarding economic feasibility of irrigation water

management and its guaranteed supply. Hill torrent waters had considerable potential for

agriculture development in these regions. Optimal management of hill torrent water was

the basic problem of this source of water. To overcome this issue a study on Vehowa hill

torrent of DG Khan District of the Punjab province of Pakistan was conducted for

reservoir site selection using GIS and Remote Sensing techniques. A water reservoir of

1.73MCM at an elevation of 1270m was proposed in this study and it was assumed that

the reservoir would be capable to mitigate the issues of droughts and irrigation in the

spate irrigated areas. In this study, a methodology was developed for the assessment of

water holding capacity of reservoir and potential sites of hill torrent catchments and

storage were separated using geo-informatics tools. As an output, the geo database was

generated with the aim to use it for future research projects. This database were included

layers of satellite imagery, GPS coordinates of ground control points, channel layout,

catchments and administrative boundaries, location of proposed reservoir and polygon

characteristics.

2.2 Crop water requirement

The application of required amount of water to crop is the only way to improve

irrigation efficiency, water productivity and cultivation area. Thus, the estimation of crop

42

water requirement is an important parameter of irrigation water research, planning and

designing of irrigation projects. Numerous methods are used to compute the reference

evapotranspiration but the American Society of Civil Engineers (ASCE) found that the

Penman-Monteith is most accurate method of reference evapotranspiration determination.

Therefore, the Penman-Monteith method was recommended as a standard method for

computing reference evapotranspiration (Jensen et al., 1990). This method overcame the

shortcomings of all other previous methods and provided more consistent values of ETo

in all regions and climates (Smith et al., 1991). The method is globally valid for reference

crop evapotranspiration and crop water requirement calculations.

Abdelhadi et al. (2000) computed the crop water requirement of Acala Cotton

using Penman-Monteith reference crop evapotranspiration with crop coefficients in

Gezira, Sudan. The crop water requirement of Acala Cotton was also determined by the

current practice of Penman evaporation from surface water using crop factors (Farbrother,

1970). Both methods were compared with actual crop water requirement of Acala Cotton

crop determined by Fadl in 1987 and found the Penman-Monteith method better than

Farbrother method.

Droogers and Allen (2002) estimated the worldwide reference evapotranspiration

using high-resolution dataset of monthly climate. The results of reference crop

evapotranspiration obtained using Penman-Monteith method was compared with

Hargreaves method and both showed very close agreement with each other. The original

Hargreaves method was modified including rainfall, which improved the estimate

extensively for arid climate. Further, the estimates of reference evapotranspiration for

accurate and inaccurate weather data also were compared. The reference

evapotranspiration of inaccurate climatic data using Penman-Monteith and Modified

Hargreaves method were compared with the result of accurate climatic data using

Penman-Monteith method. It was found that the Modified Hargreaves method performed

better than Penman-Monteith method when inaccurate climatic data was used. It was also

found that the Penman-Monteith method performed better if accurate climatic data was

available otherwise Modified Hargreaves method performed better.

Yin et al. (2008) investigated the manual calculation of reference crop

evapotranspiration was a risky and error making method because of long and tedious

procedure. Computerized method made easy the estimation of crop water requirements

from weather data and permits the development of reliable criteria for planning and

management of irrigation water resources for agriculture. Currently, a large number of

43

computer software are available to speed up the computation procedure but FAO

CROPWAT computer model uses the Penman-Monteith equation and has proved

relatively accurate in both humid and arid climate due to the incorporation of

thermodynamic and aerodynamic aspects.

Mehari et al. (2010) explored the studies conducted during last five years to

summarize the modern spate irrigated agriculture, especially in Yemen, Pakistan and

Eritrea. The modernization of spate irrigated agriculture could improve the crop

production. The recommended measures of the modernization of spate irrigated

agriculture were to include; avoiding the expansion of the command area, applying a

maximum of two irrigations or 1000mm of irrigation in a season, limiting the bund height

to 1.0m, applying water from bund-to-bund instead of constructing an individual water

diversion structure for each bund, constituting the rule to entitle downstream farmers to

use the flow of small and medium type hill torrent floods, optimizing the soil water

holding capacity and soil intake rate through tillage as well as a combination of tillage

and mulch.

Stancalie et al. (2010) estimated the daily actual evapotranspiration of maize crop

using CROPWAT model and Earth Observation data of agro-meteorological locations of

Romania. For this purpose, the CROPWAT model was run using climatic data of year

2000 of two main agro-meteorological zone of Romania; Alexandria and Craiova. The

NOAA-AVHRR cloud free satellite images of the study regions were collected for maize

crop vegetation period i.e. April to September 2000. The daily evapotranspiration of

maize crop was obtained by the surface energy balance method using two simplified

versions and results were compared with CROPWAT model. The comparison showed

that the crop water requirement measured through surface energy balance method, which

used NOAA-AVHRR images were greater than CROPWAT model. The difference varied

from +0.45 to 1.9mm/day. The result obtained through simplified versions of the surface

energy balance methods were almost similar and had good correlation with estimates of

the CROPWAT model with relative errors of 10 to 15%.

Khan et al. (2011) determined the crop water requirement of wheat and cotton for

Kachhi Plains using Penman-Monteith Equation through spread sheet and CROPWAT

model. The total water requirement of wheat and cotton were computed as 380mm and

928mm, respectively. The results were compared with four other well known methods.

The results of spread sheet and CROPWAT model matched well with each other, while

44

they varied about 3% from the results of other methods estimated for the feasibility report

of Kachhi Canal.

2.3 Groundwater simulation using MODFLOW model

Usually a large number of groundwater models were available to simulate

groundwater fluctuation, which might be influenced by the pumping and recharge source.

A MODFLOW (a 3-D finite difference groundwater model), which could run more

accurately with least available dataset was the preference for this study. Therefore, the

influence of rainfall, hill torrent floods, pumping activities, and irrigation water

penetration to groundwater aquifer was simulated using MODFLOW model.

Punthakey et al. (1996) studied the impact of irrigation on groundwater rise in

Lower Murrumbidgee, Australia using groundwater model “MODFLOW”. The effect of

rivers and streams to groundwater recharge contribution were determined by the river

package of MODFLOW model. The model was calibrated using observed water level

heads from 1980-85 and a close relationship between the contours of observed and

modeled heads of the study area was built. It was concluded that the watertable of half of

the study area was raised from 1-3m and other half study area raised about 1m over the 5

years.

IWASRI (1998) applied the MODFLOW model to check the effectiveness of

inceptor drain to collect seepage water from Chashma Right Bank Canal. For that study,

soil profile, boundary conditions, hydraulic conductivity and depth of watertable were

used as input parameters of the model. Groundwater fluctuation was observed for

sufficient time period by opening and closing the drain. Groundwater head was simulated

by running the model during canal closure and running days. The running time of canal

and model simulation for water level was 20 days. A good agreement was found between

the canal bed and the watertable head due to seepage of unit hydraulic gradient. This

showed that drain was working as a field drain not as interceptor. The seepage from the

canal bed was joining the groundwater instead of entering into the drain.

Abdulla and Assa’d (2006) used the MODFLOW model to study groundwater

flow behavior of Mujib aquifer, Jordan under different stress periods. The model was

calibrated under steady state and transient condition matching observed and computed

contour lines of water level heads. Initial head was used for steady state calibration and

head data from 1985 to 1995 were used for transient calibration process. Similarly the

head data from 1996 to 2002 were used to validate the model. The horizontal hydraulic

45

conductivity and specific yield of the calibrated model ranged from 0.001 to 40m/day and

0.0001 to 0.15, respectively. The water balance of aquifer system under steady state

condition responded the total annual recharge 20.4MCM, inflow 13MCM, spring

discharge 15.3MCM and outflow 18.7MCM. Different scenarios were developed under

different conditions to predict the behavior of aquifer system. The sensitivity analysis of

results indicated that the model was highly sensitive to specific yield, horizontal hydraulic

conductivity, anisotropy and low level of recharge rate.

Saatsaz and Sulaiman (2008) used the groundwater MODFLOW model as a

management tool for aquifer system development, drainage installation, integrated use of

surface water and groundwater to overcome the issues of soil and water at agricultural

centers of Ramhormooz plain, Iran. The required data were collected, analyzed and input

to different packages of Visual MODFLOW2.6 model. The model was calibrated using

trail and error’s assessment of hydrodynamic coefficients and results were optimized

through PEST code. The auto calibrated results of the model showed that the regression

coefficient and variance between observed and computed heads were 0.9994 and 0.78m,

respectively. After the assured validation, the model was used for assessing four

management options including prediction of groundwater heads from 2002 to 2005

considering average historical discharge and recharge rates, aquifer development, and

prediction of aquifer system behavior in response to installation of the drainage system in

high watertable areas.

Arshad et al. (2009) conducted a study to simulate time variant seepage from

branch canal system in Punjab province of Pakistan under the crop, land and water

scenarios using MODFLOW model. The model was calibrated to closely match the

observed and simulated groundwater heads for one year of study period. The average

monthly seepage rate of 12.1 m3/s/million-m2 was estimated from the canal flowing at

monthly average discharge of 106m3/s. It was concluded that the contribution of seepage

to groundwater recharge was dependent of recharge flow, irrigation applied, rainfall,

lateral flow and evapotranspiration from existing cropping pattern.

Akram et al. (2012) compared the results of groundwater flow simulation

produced by the MIKE SHE and MODFLOW models. Both models were calibrated using

available hydro-geological and weather data for high Barind area of Bangladesh. The

differences in simulated hydrographs of the both models including expected seasons were

discussed and found that the MODFLOW model has huge advantage than MIKE SHE

because of easy to learn, facility of auto calibration, require minimum data and time of

46

operation, allow rectangular/finer grid for the study area etc. It was concluded that the

MODFLOW model is most suitable for groundwater issues where irrigation was not

present. It was recommended that MODFLOW can be used for irrigated areas, if recharge

is calculated by another source.

Youssef et al. (2012) applied the MODFLOW (a quasi-three dimensional

groundwater flow model) for predicting changes in the aquifer system of El-Moghra

Aquifer in Wadi El-Farigh (MAIWF), Egypt. The model simulated results were menaced

to continue the development in the aquifer system of Wadi. The model simulated a

decline of 30m/7years at current situation of groundwater exploitation while the decline

will appear 35m/7year in case of 15% increase in groundwater pumping. It was concluded

that the construction of proposed irrigation canal of MAIWF would increase the

groundwater recharge and decrease the decline up to 16m/7years. It was recommended to

decrease the number of pumping units, minimize the running time, apply high efficiency

irrigation system, and the implementation of groundwater recharge policy from the

proposed new canal to protect the groundwater aquifer system of the MAIWF for the term

future.

Lamsoge et al. (2014) conducted a study in the WR-2 watershed in Warud Taluk,

Amaravti district, Maharashtra. The aim of study was to propose a framework for

groundwater management using modeling approach and it must be economical, realistic

and systematic. For this purpose, MODFLOW model was used to evaluate the

groundwater system at present scenario and for future prediction of groundwater

behavior. The model simulated results by the year 2020 showed 15m decline in water

level and drying off an area of 243km2.

2.4 Summary of review

Hill torrent irrigation system known by various nomenclatures has immeasurable

world history. Out of all countries with hill torrent irrigation system, Pakistan has greatest

area under this system. Pakistan is blessed with hill torrent irrigation system along with

other major sources of irrigation i.e. surface water and groundwater. The review of

literature showed that in hill torrent areas of Pakistan, the first time the Government of

Punjab started work on hill torrent flood management was after the harsh flood of 1929.

Studies conducted so far on hill torrent irrigation system in Pakistan by the national and

international organizations have only submitted observant proposals and reports. Only a

few studies conducted on this system addressed the research issues. Most of the studies

47

conducted by NESPAK, WAPDA, FFC and others reported the potential in hill torrent

areas, losses estimation due to harsh floods, major crops, problems and constraints of the

management etc. However, so far no research has been conducted on groundwater in hill

torrent areas of Pakistan, groundwater quality effects on crop yields and soil salinity, hill

torrent water resources management options, hill torrent irrigation impacts on

environment and socio-economic conditions of the farmers of area. The study area exists

in Pachadh area where there is no availability of the required research data; therefore, this

research would create a database regarding the use of surface water (hill torrents) and

groundwater using CROPWAT and MODFLOW models, which are suited to the

conditions of the study area.

48

CHAPTER 3

MATERIALS AND METHODS

This chapter explains the detailed methodologies and tools used for the present research

work conducted at Mithawan hill torrent command area of Dera Ghazi Khan (DG Khan),

a district of the Punjab province of Pakistan.

3.1 Features of the research area

3.1.1 Geological characteristics

The study area is located in Pachadh area that lies between Suleiman Mountains

and Kachhi Canal at 316.43 RD on west of a town Choti Zareen, and falls under the

administrative control of DG Khan District, Punjab, Pakistan. The study area exists

between latitude 29.731o N to 29.862o N and longitude 70.314o E to 70.487o E with an

average altitude of about 158m (min 122m & max 194m) as shown in Fig. 3.1. Mithawan

hill torrent is one of the thirteen major hill torrents originate from Koh-e-Sulaiman with

watershed area of about 741km2. The total area under this torrent is about 16000ha, out of

which 11010ha is entitled to be irrigated through water rights. The area has arid climate

and erratic rainfall pattern, which received 25 years return period discharge of 2210m3/s

(I&PD, 2002a). The maximum discharge of selected hill torrent along with other major

hill torrents of the area occurred during the study period was as given in the Table 3.1.

Fig.3.1: Location of the Mithawan hill torrent command area, DG Khan

49

Table 3.1: Peak discharge of DG Khan hill torrents, (m3/s)

Name of hill torrent/ year 2010 2011 2012 2013 2014

Kaura 3642 1236 1236 1903 1115

Vehova 3131 1575 1924 1575 1575

Sanghar 6490 2812 2812 1726 1164

Sori Lund 1458 829 2346 2769 1822

Vidore 2752 1353 4112 1594 1594

Sakhi Sarwar 925 309 244 266 309

Mithawan 1754 238 1403 543 970

Source: GoP (2015b)

3.1.2 Climate and rainfall

The climate of the area is characterized as arid and distribution of rainfall differs

according to the altitude and gradually decreases from North to South. It varies from

310mm in North-Western hilly region to 200mm at the foot hills. However, the average

annual rainfall of the area was 144.2 mm (I&PD, 2002b). The winter season extends from

December to March and summer season lasts from June to September. The area has hot

summers and mildly cold winters. The hotest month is June with an average maximum

temperature of 41.7 oC and January is the coldest month with an average minimum

temperature of about 6.5 oC. A maximum temperature of 48 oC was recorded in 1995.

3.1.3 Agriculture

Owing to absence of business and industrial opportunities, the economy of study

area is totally based on agriculture and livestock. Agriculture is mainly dependent on hill

torrent/rainfall. In the absence of hill torrent at the time of cultivation, crops are grown

with groundwater and/or lifting canal water. The crop yield of area is less than its

potential due to various factors such as inefficient irrigation practices, non-availability of

recommended seed, poor disease control and farming activities. There is huge potential to

increase the crop yield by addressing the problems and constraints associated with soil,

crop inputs, and machinery.

The cropping pattern of study area varies with the occurrence of hill torrent and its

management for irrigation application. During the year 2012, a large number of hill

torrents occurred, which were utilized by the majority of famers for spate irrigation. So,

the year 2012 was considered a wet year. Whereas, in 2013, about 4 to 5 times hill torrent

occurred for a short duration with low discharge, which could not be utilized by the large

number of farmers and thus, it was considered a dry year. Cotton, maize, sorghum, millet

and guar were sown during Kharif season while wheat, tobacco, sunflower, gram,

brassica and arugula during the Rabi season. However, onion and fodder were cultivated

50

in both the seasons. Out of aforementioned crops, cotton, wheat, onion, maize and fodders

were irrigated by the canal water and groundwater separately or conjunctively. Whereas

sorghum, millet and guar/cluster bean were sown through the spate irrigation that was

applied once before the sowing of crop, while the successive crop water requirement was

satisfied by the rainfall. The cultivation of wheat crop through spate irrigation was done

rarely on limited area.

Sowing and harvesting of crops in the field (Bund) is not done at a time. It is done

according to field capacity and maturity of crops. If one part of the bund reaches early at

field capacity then farmers sow it first and then continue this process until the entire bund

is cultivated. Similarly, the crop is usually harvested at its maturity stage. Farmers grow

only one crop in a year with spate irrigation; if in a specific year, hill torrents and rainfalls

occur for a number of times then some of the farmers cultivate two crops in a year. First,

farmers cultivate sorghum and then gram, if enough moisture in the soil is left at the time

of gram sowing. For this, the farmers cut sorghum, feed it to the animals and sow gram. If

rainfall occurs at the critical stages of crop, then sufficient yield is produces. Sometimes,

to increase the number of tillers, farmers let their animals in gram fields for grazing as

shown in the Fig.3.2. In addition to these crops naturally grown tree plants e.g. Acacia

nilotica (kiker), Prosopis cineraria (jand or kanda), Prosopis Juliflora (mesquite), Tamarix

articulata (farash) and Ziziphus mauritiana (ber) are commonly present in the study area.

Fig. 3.2: Grazing of animals in the gram crop

51

3.1.4 Livestock

Owing to lack of developed agriculture in the study area, livestock and rearing of

animal is an important source of farmers’ livelihoods. It is the major source of income for

the farmers and significantly contributes to agriculture development. It includes rearing of

sheep, goat, cow, buffalo, camel etc. and also provides security against crop failures

during extremely high floods or droughts.

3.1.5 Soil type and sedimentation

There is huge spatial variation in the selected hill torrent command area.

Generally, two distinct soil types are present namely, the alluvial/piedmont plain and

sandy soil. Both are fairly different in nature and can be assessed due to their general

physical properties and mode of deposition. The area consists of sandy soil, loam, sandy

loam and silt loam soil types (Ahmad, 2003), which are good for agriculture except sandy

soil. During the wet year 2012, sedimentation of about 7 to 30cm was observed in

different fields of the study area. Such a heavy sedimentation and crust formation creates

problems in the farming activities. Therefore, it becomes difficult for the farmers to break

crust formation and prepare seedbed. To overcome this problem, farmers broadcast seed

over crusted field and then sweep over the field to drop seed into the cracks. The

successful germination of gram crop over the crust formation is shown in Fig. 3.3.

Fig. 3.3: Sowing and germination of gram crop in sediment crusted bund

3.2 Socio-economic condition of the farmers

The socio-economic condition of the farmers of study area is very poor and totally

depends on agriculture and livestock. The economic condition of the farmers is affected

52

by the cropping pattern, which varies with the availability of water from hill torrent. In a

wet year, hill torrent occurred for a number of times and hence the cropping pattern of

area is improved. The people from nearby hilly or mountainous area come to the selected

hill torrent command area to earn their livelihood as a farm labor. They earn grain and

rear livestock during harvesting and threshing activities. Transportation in the area is very

difficult due to embankments and lack of roads. Thus, farmers cannot easily shift their

produces from field to market and hence in the field, farmers are offered low price of

produces by the middleman.

The entire command area of selected hill torrent has a tiny market located at

313.336 RD of DG Canal. The farmers cannot frequently visit market and buy necessary

commodities. They have developed their taste to eat the local food stuff. Normally, they

use milk, butter, curd and meat of their own domestic animals and poultry. They cook

their own grown vegetables and had less availability of fresh fruits for their nutritional

requirements. Most of the people of area are nutrient deficit. They have the availability of

locally grown “ber” as fruit. Similarly, the lack of school, hospital, roads, security and

other infrastructure are main constraints in the development of area and hence it is the

cause of low living standard of the population.

3.3 Irrigation practices and water rights

Spate irrigation system is a unique and centuries old irrigation system in Pakistan,

which is still being traditionally practiced in the whole country. The farmers construct

earthen embankments around the fields to store the spate water into it, which is locally

called as bund. The height and width of embankments varies from about 0.91m to 2.29m

and 1.0m (top width) to 3.0m (bottom width), respectively. The size of bunds varies with

landholding of the farmers. During the field visit a largest bund of about 41ha was

observed in the study area.

Under this system, mostly during the low flow of hill torrent, lower riparian fields

remain un-irrigated. To divert water into the bunds, the farmers of area construct an

earthen diversion structure across the flow of torrent. These earthen diversion structures

may be constructed by the individual or group of farmers to make the hill torrent flow

available for irrigation of bund(s). The irrigation turn system starts from upper to lower

riparian, without consideration of duration and magnitude of flow. After the successful

application of water, the upstream farmer cuts the diversion structure and let the water

move down. Then downstream farmers divert the water into their bunds with the help of

53

already constructed diversion structures in the torrent channel. Upon drying up water in

bund, crops are sown, which flourish on the moisture stored in soil. There is no further

irrigation application except rains. However, the farmers whose landholding is adjacent to

right bank of DG Canal have installed pumps for lifting canal water for the cultivation of

crops. Similarly, some farmers at the middle and tail of command area have installed tube

wells for cultivation of crops with groundwater in the absence or shortage of spate water.

For a bund there may be a number of owners/landholders. Mostly, the

shareholders do not contribute the required amount for the construction of diversion

structure, leveling, repairing and maintenance of bunds. Consequently, the flaws are left

in efficient utilization of water and its storage in the bund. Mostly, due to the construction

of embankments, depressions are produced within the bund. At the time of irrigation, the

bulk of water moves toward depression and causes the breaching of embankments. If an

influential shareholder of a bund can afford the installation and running cost of deep well

turbine then he doesn’t allow the other shareholders to divert the spate water into the

bund when he has already cultivated his share of land by groundwater. Such farmers even

not separate their share of land from the bund. Thus the poor farmers’ shares of land

remain without irrigation and they cannot cultivate the crops.

In spate irrigated areas, both upstream and downstream farmers face the problem

of irrigation. Sometime upstream farmers could not control and divert the flow of hill

torrent into their fields due to high velocity of water. Conversely, the famers at tail

receive no or uncontrolled flash flood, which was not handled by the upstream farmers

and hence it remains accumulated in their fields for a long time. The accumulation of

water at right bank of Kachhi as well as DG Khan Canal damages the standing crops.

Similarly, heavy erosion of bunds embankments is another big issue that needs more

investment for repairing. The poor farmers don’t have enough money to repair the

damaged bund and ultimately leave the field as uncultivated.

Some farmers of study area live in nearby cities, whenever, hill torrent occurs,

they are informed through cell phone call by the people residing at catchment area or foot

of hills. Consequently, they reach at bunds to make necessary arrangement for diverting

water into the bunds and control the back flow of water after cut off the irrigation supply.

If diversion structure is not well-built then it washes away because of high velocity and

pressure of upstream headed up water. Therefore, the farmers construct heavy duty

diversion structure for holding and diverting the water into their fields, which requires too

much investment every year. If, structure is washed away because of poor management,

54

the water cannot be diverted into the field. For this, multiple attempts to construct and

repair the diversion structures are required, which need heavy investment. It shows the

lack of technical motivation for the construction of structures.

The influential upstream farmers deprive the downstream poor farmers from

irrigation. They irrigate their fields again and again and don’t let the water to flow down.

After satisfying the demand of water they divert water to nearby bunds, which are not

entitled to be irrigated through that channel/structure. In this way, hill torrent is finished

without cutting diversion structure. By already constructed diversion structure, influential

farmers divert the flow of water many times and the downstream farmers’ bunds remain

un-irrigated even after several time occurrences of the hill torrents.

3.4 Water conservation

Water is the major limiting factor for agriculture. Its return can be increased by the

efficient utilization and soil moisture conservation practices. Generally, the farmers of study

area cultivate crop soon after the field capacity. If, hill torrent occurs earlier than the time of

sowing, the farmers conserve moisture in the soil. Moisture in the soil is conserved by

applying cultivator following the planker soon after bearing the load of machinery. By this,

moisture remains conserve within the soil till the time of sowing of crop.

3.5 Groundwater

In the selected hill torrent command area, groundwater exists at a greater depth

and has poor quality of water. A few of the study area adjacent the canal has two

groundwater layers; one is the top and other is lower layer. Top layer of groundwater is

present in the area adjacent to canal, while the lower layer of groundwater is present in

the whole study area. The groundwater potential for agriculture in the study area is

limited and currently utilized on small scale.

There is huge spatial variation of groundwater quality and quantity. Often, the

boreholes not satisfy the water requirement due to little or no availability of water.

Consequently, the farmers need to make borehole at another nearby area and number of

attempts are made for successful well bore, which need huge investment. During the year

2012, the distribution of pumps (deep well turbines and submersible pumps) in study area

was at the rate of about 3 pumps per km2. Farmers have installed deep well turbines and

submersible pumps to a depth of 75-100m and extract groundwater with low discharge

55

pumps. Water extracted through these pumps is quite costly and requires high cost of

pumping.

3.6 Drainage

Mithawan hill torrent flow finds its natural drainage to South-East and

accumulates along the Right Bank of Kachhi Canal. However, cross drainage structures

have been constructed at Kachhi and DG Canal to divert the excessive flow of hill torrent

into the left side of DG Canal. The crossed drainage flow breaches the canals and

damages crops, villages, and public property in canal commanded area. Sometime these

drains outfall in the Manka drain at its different reaches.

3.7 Field layout and water allocation

Generally, there is no symmetrical layout of the fields and turn system of

irrigation like canal irrigation in hill torrent command areas of Pakistan. Farmers

understand traditional method of irrigation, their water rights and local management of

water allocation, and water distribution among the shareholders. The farmers also

understand the terminology applied to the system. A line diagram of existing field layout

of Mithawan hill torrent irrigation system is shown in Fig. 3.4.

Fig. 3.4: Fields layout of Mithawan hill torrent irrigation system

3.8 Mithawan hill torrent command area irrigation system

In Mithawan hill torrent irrigated area different local terms are used by the

farmers. In order to understand the operational irrigation practices and conduct field

surveys, the understanding of terminology locally applied to the system is necessary,

which are summarized below:

56

1. Darrah

It is a point on the main torrent through which water passes after the contribution

of different small gorges originating from catchment area. After passing of water from

Darrah, it disperses into the command area through the network of channels. Each hill

torrent system has one Darrah and estimates of flow are recorded at this point. The flow

record of torrent is available at its Darrah in the form of stages rather than direct

discharge measurement.

2. Wah

A channel leading to one or more than one fields is called “Wah”. A Wah can

further be divided into Sub-Wah named as Wahi. Wah takes the water from the main

torrent stream and divert it directly into the field or Sub-Wah. Each hill torrent system has

a network of Wah to irrigate the farmers’ fields. The water channel (Wah) layout of

Mithawan hill torrent command area is shown in Fig. 3.5. There are 27 Wah in the study

area to irrigate the farmer’s field. A field existing Wah is shown in Fig. 3.6.

Fig. 3.5: Water channel layout of the Mithawan hill torrent command area

57

Fig. 3.6: Wah at Mithawan hill torrent command area

3. Gundh

It is a structure made up of heavy earthen dike with stones pitching/spur after the

Darrah to divert hill torrent water into different directions. Mostly, it is used to divert the

hill torrent water into two “Wah”.

4. Wakrha

It is an earthen structure constructed across the flow of Wah to raise and divert the

water into the field or sub-wah. The same structure constructed across the sub-wah to

divert water into the field is called Wakrhi. An existing Wakrha on the Mithawan hill

torrent system is shown in Fig. 3.7.

Fig. 3.7: Wakrha at Mithawan hill torrent after the cutoff of flow

58

5. Bund

It is structure by which a field is surrounded by the embankments to store

water into it. The bunds existing in Mithawan hill torrent command area are of different

sizes, depending upon the size of land holding of the farmers. These bunds are not

straight and each bund has its own name. A bund may be irrigated directly from Wah or

Wahi. A field existing bund is shown in Fig. 3.8.

Fig. 3.8: Bund at Mithawan hill torrent command area

6. Khaat

The eradication of weeds before the sowing of crop with the help of hand tools is

locally termed as “KHAAT”.

7. Kumbail

It is depression produced in the bund due to earth moving for the construction and

maintenance of embankments.

8. Bhargarh

It is the serious/deep erosion taken place as a result of the breaching of bunds’

embankments, which leads the affected portion of field as uncultivated.

9. Kundi

It is the embankment constructed inside the field around deeply eroded section of

bund’s embankment, which cannot be easily repaired and maintained with simple

agricultural tool.

59

3.9 Data collection

Data on various input parameters to populate hydrological models were collected

from both in-situ as well as government organizations. The following requisite

information/data were collected in order to achieve the objectives of study:

1) The desired hill torrent command area was selected where the identified management

problems exist and the command was approached for collecting the requisite data.

2) A questionnaire was developed to conduct the farmers’ interviews regarding the

objectives of study.

3) The field visits of selected hill torrent command area were conducted to carry out the

survey.

4) Randomly selected farmers were interviewed regarding their socio-economic

conditions and problems faced by them in using and managing water of hill torrent.

5) Collection of watertable data from selected observation wells along with the sources

of recharge.

6) Discharge of pumping units installed in the study area was measured with the help of

cutthroat flume of 10x90cm size.

7) Collection of soil and water samples from selected hill torrent command area.

8) Secondary data required for the objectives were collected from the relevant

departments/organizations.

3.9.1 Primary data

A reconnaissance survey of study area was conducted in order to examine the

prospect of research in the area. The data regarding number of installed turbines, their

status in term of functional or nonfunctional and coordinates were collected during the

survey. Nine vacant/inoperative boreholes were identified and used as observation wells.

The watertable data of selected observation wells were collected on weekly basis for

entire study period i.e. June 2012 to June 2014.

To carry out the farmers’ interviews, a questionnaire was developed as given in

Appendix-A1. The developed questionnaire was tested on about 10 respondents and

necessary amendments were made in the questionnaire. A total of 50 farmers were

interviewed, which were representing the landholdings of about 10% of total landholding

of the study area. The data collected through farmers’ interviews were included land

holding, culturable area, bund size, crops sown, sources of irrigation, hill torrent water

application, type of pumps, power source, number and duration of irrigation application,

60

crop inputs, cultural practices, yield of crop, price of yield etc. as given in Appendix-A2

to A10. For the cropping year 2012-13, the data were collected through direct meeting

with the farmers, whereas the information for cropping year 2013-14 and missing

information were obtained through telephonic conversation with the farmers. The data

gathered through questionnaire survey were analyzed using the computer software SPSS.

To evaluate the impact of hill torrent and groundwater irrigation application, soil

and water samples were collected. Soil samples were collected from twelve (12) different

locations namely A, B, C, D, E, F, G, H, I, J, K and L. From each location two fields, one

spate irrigated and other groundwater irrigated were selected to collect the soil samples.

Then from each field, three soil samples at a depth of 0-15cm, 15-30cm and 30-45cm

were taken. Thus a total of 72 soil samples were collected to evaluate the impact of

groundwater and spate irrigation application on soil properties. Similarly, 12 groundwater

samples representing the whole study area of about 500ml from the pumping units and 6

water samples of hill torrent at different reaches were collected. The soil samples were

collected in polythene bags and water samples were collected in plastic bottles that were

rinsed with the same water being sampled before taking sample. The floating debris or

any other contaminants were avoided while collecting the water samples.

3.9.2 Secondary data

The climatic data were taken from Pakistan Meteorological Department (PMD),

DG Khan. The hill torrent flow data were collected from Punjab Irrigation Department,

DG Khan.

3.10 Contribution of available water resources to crop water

requirement

The relative contribution of surface water, groundwater and rainfall to meet the

crop water requirement of canal water and/or groundwater irrigated crops was assessed

using the collected data regarding farmers’ irrigation practices, discharge of irrigation

pumps and rainfall in selected hill torrent command area.

3.10.1 Discharge measurement of the pumps

The discharge measurement of irrigation pumps was carried out as explained by

Skogerboe et al. (1973). The flow pattern of cut-throat flume may be a free flow or

submerge flow depending upon the extent of actual percentage submergence (S) and

61

transition submergence (St). Actual percentage submergence was calculated by the Eq.

3.1:

S = Hb

Ha × 100 (3.1)

where;

Ha = upstream head, (m)

Hb = downstream head, (m)

Transition submergence depends upon the flume length (L) and its value for 0.9m flume

length was taken 65% (Siddiqui, 2003). If, S ≤ St the flow pattern is called free flow,

otherwise it is submerged flow. The discharge measurement under free flow condition

was calculated using Eq. 3.2:

Q = C1Han1 (3.2)

where;

Q = discharge, (m3/s)

C1 = co-efficient of discharge for free flow and it was calculated by the Eq. 3.3:

C1 = K1W1.025 (3.3)

K1 = free flow co-efficient depends upon flume length

W = throat width, (m)

n1 = free flow exponent depends upon flume length

The Eq. 3.4 given below was used to measure the discharge under submerged flow

condition:

Q = C2(Ha − Hb)n1

(− log S)n2⁄ (3.4)

where;

C2 = submerged flow coefficient and calculated by the Eq. 3.8:

C2 = K2W1.025 (3.5)

n2 = submerged flow exponent

The values of K1, K2, n1 and n2 were taken 3.89, 2.15, 1.843 and 1.483, respectively as

given in the Irrigation and Drainage Engineering-Book (Siddiqui, 2003). The discharge of

pumps measured through cutthroat flume is given in Appendix-B1 to B3 was analyzed for

the average discharge of pumps using SPSS (statistical package for social sciences)

windows operated software. The results of average discharge of pumps are given in the

Table 3.2.

62

Table 3.2: Average discharge of pumps installed in the study area

Type of pump Delivery pipe dia.

(cm) No. of pumps

Min.

(m3/s)

Max.

(m3/s)

Mean

(m3/s)

Centrifugal 15.24 10 0.0280 0.0690 0.04130

Deep well turbine 15.24 2 0.0223 0.0312 0.02675



Submersible 12.70 2 0.0295 0.0299 0.02970

Submersible 10.16 2 0.0239 0.0249 0.02440

Submersible 5.08x5.08 2 0.0070 0.0090 0.00800

3.10.2 Volume of water available to the crops

The volume of water delivered to the crop was the sum of water applied through

canal water and/or groundwater supplies. The volume of canal water (VCW) applied

through centrifugal pump installed at right bank of DG Canal was calculated through Eq.

3.6 given by Kay and Hatcho (1992):

VCW = Qcp × T × N × 3600 (3.6)

where;

Qcp = discharge of centrifugal pump installed at the canal, (m3/s)

T = time of irrigation application, (hr/ha)

N = total number of irrigation applied to the crop in a season

The data regarding time of irrigation and total number of irrigation applied were collected

through farmers’ interview. Similarly, the volume of groundwater (VGW) applied to the

crop through deep well turbine/submersible pump was calculated by the Eq. 3.7:

VGW = QGW × T × N × 3600 (3.7)

where;

QGW = discharge of deep well turbine/submersible pump, (m3/s)

The volume of water delivered (VD) to the crops through canal water and/or groundwater

irrigation was calculated using the Eq. 3.8:

𝑉𝐷 = 𝑉𝐶𝑊 + 𝑉𝐺𝑊 (3.8)

The volume of water available to the crop through different sources was calculated using

Eq. 3.9:

VA = VD + PEff (3.9)

where;

VA = volume of water available to the crop through different sources, (m3/ha)

PEff = effective precipitation during the cropping season, (m3/ha)

63

The contribution of each source of water to crop water requirement was assessed by

calculating the percentage of each source in total water available to the crop.

3.11 Estimation of crop water requirement using CROPWAT model

Application of only required amount of water to the crop improves irrigation

efficiency and optimizes the crop production. Currently, a large number of computer

software are available to speed up the computation procedure but FAO CROPWAT

computer model uses the Penman-Monteith equation and has proved relatively accurate in

both humid and arid climate due to the incorporation of thermodynamic and aerodynamic

aspects (Yin et al., 2008). Therefore, in this study, CROPWAT 8.0 model was used for

the estimation of crop water requirement.

The model requires information on meteorological station (country, station name,

altitude, latitude and longitude) together with climatic data on rainfall, temperatures

(minimum & maximum), relative humidity, wind speed and sunshine hours for daily,

decade or monthly basis calculations. CROPWAT 8.0 includes standard crop and soil

data. When local data are available, these data files can be easily modified or new ones

can be created. Likewise, if local climatic data are not available, it can be obtained for

over 5,000 stations worldwide from CLIMWAT, the associated climatic database of

CROPWAT.

3.11.1 Data required for CROPWAT model

Generally, some conversions are required to adjust the data into the format

accepted by CROPWAT 8.0. So, the attention should be given to units in which climatic

data are given. The data format of different climatic parameter accepted by the

CROPWAT 8.0 is given below:

1. Minimum and maximum temperature in oC

2. Average daily relative humidity in percentage or vapor pressure in kPa

3. Sunshine in hours or sunshine percentage

4. Average daily wind speed in km/day or m/s

5. Rainfall in mm

3.11.2 Climate/ETo data input and output

The Climate module was selected by clicking on the “Climate/ETo” icon in the

module bar located on the left of main CROPWAT window. The data window opens with

the default data type (daily/ decade/ monthly values); it is possible to quickly change to

64

another data type using drop down menu from the “New” button on the toolbar. The

module is primary for data input, requiring information on the meteorological station

(country, station name, altitude, latitude and longitude) together with climatic data.

The software package can determine ETo using only temperature but humidity,

wind speed and sunshine should be entered, if available. There was no meteorological

station in the Mithawan hill torrent command area and it was very difficult to collect in

site climatic data. Therefore, the required data on climate were obtained from Pakistan

Meteorological Department (PMD), Meteorological Observatory at DG Khan. The

meteorology station was at an aerial distance of about 30 km northeast from the study

area. The study area existed near DG Khan Airport where only real time climatic data

were required for the air traffic control. There was no availability of proper climatic data

at DG Khan Airport and hence could not be obtained. Through the verbal communication

with climate data observer at PMD, DG Khan and DG Khan Airport, it was found that on

average the temperature of study area is about 0.5 oC greater than observatory at DG

Khan. Thus a factor of 0.5 was added in all the values of temperature. The data on other

climatic parameters were assumed same as observed at PMD, DG Khan.

Similarly, the data obtained from PMD contained relative humidity measured at

5:00 AM, 8:00 AM and 5:00 PM. In this study the mean relative humidity was used for

the calculation. The mean relative humidity was obtained by taking the mean of minimum

and maximum relative humidity taken at 5:00 AM and 5:00 PM. Similarly, the Penman-

Monteith Equation requires the wind speed measured at 2 m height above the surface. It

was important to verify the height at which wind speed measured. The wind speed data at

PMD, DG Khan were measured at 13.72m height. The Eq. 3.10 as given by Allen et al.

(1998) was used to adjust the wind speed data at 13.72m height to 2m height:

U2 = Uz ×4.87

ln(67.8z−5.42) (3.10)

where;

U2 = wind speed at 2m above ground surface, (m/s)

Uz = measured wind speed at z m above ground surface, (m/s)

z = height of measurement above ground surface, (m)

The Climate/ETo module includes calculations, producing radiation and ETo data using

the FAO Penman-Monteith approach. The ETo data obtained by the CROPWAT 8.0

model using climatic data input of the study area is given in Table 3.3.

65

Table 3.3: ETo data obtained through CROPWAT using climatic data of the study

area

Month Min temp

°C

Max temp

°C

Humidity

%

Wind

m/s

Sun

hours

Rad.

MJ/m²/day

ETo

mm/day

For the year 2012 (June to December)

Jun 27.3 42.8 43 1.3 8.6 22.9 6.61

Jul 29.2 40.9 57 1.4 8.7 23 6.44

Aug 28 38.4 66 1.5 7.8 20.8 5.56

Sep 25.9 35.3 76 1.5 8.4 19.8 4.62

Oct 19.8 33.4 64 0.9 9.2 18.1 3.69

Nov 15.3 28.4 65 0.8 7.8 13.9 2.39

Dec 10.1 23.6 67 0.6 7 12 1.59

Av. 19.2 32.5 58 1.1 8.3 18.7 4.23

For the year 2013

Jan 7.1 21.1 66 2.1 6.8 12.5 2.37

Feb 11.3 23 70 1 6.3 13.9 2.24

Mar 16.3 29.8 62 0.9 9.1 20.1 3.82

Apr 20.9 36 46 1.2 8.4 21.3 5.14

May 26.9 42.9 40 1.5 10.6 25.7 7.28

Jun 29.7 43 49 1.5 9.9 24.9 7.06

Jul 30.1 41 60 1.3 9.3 23.8 6.49

Aug 27.8 37.7 71 1.2 8.8 22.2 5.52

Sep 26.5 37.9 66 1 10.1 22.2 5.26

Oct 23.2 35.5 63 0.8 9 17.9 3.83

Nov 14.2 28.2 65 0.7 7.7 13.8 2.22

Dec 10 22.5 73 0.9 6.6 11.6 1.71

Av. 20.3 33.2 61 1.2 8.6 19.2 4.41

For the year 2014 (January to May)

Jan 7 21.7 64 0.7 6.8 12.4 1.68

Feb 9.7 22.9 66 0.8 7.3 15.1 2.3

Mar 14.8 27.4 65 0.9 7.4 17.8 3.31

Apr 20.5 35.2 54 1.2 9.5 23 5.22

May 25.5 39.7 47 1.4 9.4 24 6.51

Av. 15.5 29.4 59 1 8.1 18.5 3.8

3.11.3 Rainfall data input and output

The rainfall varies greatly from season to season and it becomes difficult to

predict how much water comes from rainfall and how much should be covered by

irrigation. In addition to rainfall variability, not all rainfall is used by the crop. Therefore,

the part of rainfall, which effectively contributes to CWR was important to calculate and

incorporate in the CWR calculations. The rain data required for CROPWAT 8.0 can be

66

daily, decade or monthly rainfall, commonly available from nearest climatic station(s).

The Rain module can be selected by clicking on the “Rain” icon in the module bar located

on left of the main CROPWAT window. The data window opens with the default data

type (daily/ decade/ monthly values); it is possible to quickly change to another data type

using the drop down menu from the “New” button on the toolbar. Once the window is

open with suitable data type, enter the rainfall data and check the input. The Rain module

include calculation of effective rainfall by using one of the approaches available, which

can be selected by clicking on “Options” on the toolbar while Rain module is the active

window.

There are four common empirical methods for the calculation of effective rainfall

(1) fixed percentage of rainfall (2) dependable rainfall (3) empirical formula, and (4)

USDA Soil Conservation Service Method (Smith, 1991). Out of these methods, the

USDA Soil Conservation Service method was used for this study. This method avoids

high degree of complexity, neither the soil intake rate nor rainfall intensities are

considered in it. The Eq. 3.11 and Eq. 3.12 as given below were used for this purpose:

For Ptot< 250 mm Peff = Ptot ×125−0.2Ptot

125 (3.11)

For Ptot> 250 mm Peff = 125 + 0.1 × Ptot (3.12)

where;

Peff = effective rainfall, (mm)

Ptot = total rainfall, (mm)

The monthly effective rainfall data of study area during research period were as given in

Table 3.4. The relative contribution of surface water, groundwater and rainfall to meet

crop water requirement of canal water and/or groundwater irrigated crops was assessed

using information obtained by the above process. The contribution of each source was

calculated as the percentage of total volume of water available to the crop during its

growing period. The monthly effective rainfall data of study area were as given in the

Table 3.4.

67

Table 3.4: Monthly effective rainfall of study area during the year 2012-2014

Month/year

2012 2013 2014

Rain

(mm)

Eff. rain

(mm)

Rain

(mm)

Eff. rain

(mm)

Rain

(mm)

Eff. rain

(mm)

January - - 0.0 0.0 0.0 0.0

February - - 58.1 52.7 13.0 12.7

March - - 7.0 6.9 12.6 12.3

April - - 16.0 15.6 40.3 37.7

May - - 1.5 1.5 43.2 40.2

June 20.4 19.7 3.2 3.2 - -

July 33.6 31.8 23.8 22.9 - -

August 7.1 7.0 151.2 114.6 - -

September 149.5 113.7 0.0 0.0 - -

October 9.0 8.9 0.0 0.0 - -

November 0.0 0.0 0.0 0.0 - -

December 1.0 1.0 0.0 0.0 - -

Total 241.6 202.8 260.8 217.4 109.1 103.0

3.11.4 Crop and cropping pattern data

The Crop module can be selected by clicking on the “Crop” icon in the module

bar located on the left of main CROPWAT window. The data window opens with the

default crop type; it is possible to quickly change to another crop type using the drop

down menu from the “New” button on the toolbar. In alternative, use the “New” button in

the “File” menu. CROPWAT 8.0 contains data for several common crops taken from the

FAO publications. The crop data file given in the model can be obtained by clicking on

“Open” button on the toolbar while “Crop” module is open. Whereas the most reliable

crop data remain the data obtained from local agricultural research stations. Most of the

crops planting and harvesting dates extended over a couple of weeks due to number of

reasons such as climate, cropping patterns, harvesting of previous crop, land preparation,

crop variety, availability of water etc. Therefore, it was assumed that all the farmers

cultivated the specific crop at same date and time. The most common planting and

harvesting dates of crops sown in the study area were assessed through field visit and

farmers’ interviews are given in the Table 3.5.

68

Table 3.5: Planting and harvesting dates of the crop sown in study area

Crop Planting date Harvesting date

Wheat 1-Dec 30-Mar

Cotton 1-May 11-Nov

Onion 15-Jul 17-Oct

Sunflower 21-Jan 30-May

Tobacco 11-Jan 30-Apr

Barley, Oat (Rabi fodder) 1-Dec 30-Mar

Berseem, Lucerne (Rabi fodder) 17-Dec 30-April

Maize (Kharif fodder) 15-Jul 12-Oct

Sorghum (Kharif fodder) 21-Jun 23-Oct

In addition to reference evapotranspiration, the calculation of actual crop

evapotranspiration requires the values of crop coefficient (Kc). The value of Kc for a

given crop varies over the growing period due to difference in evapotranspiration during

various growth stages. The growing period can be divided into four distinct growth

stages: initial, development, mid-season and late season. Due to shortage of data for study

area, the length of crop development stages were assumed from the FAO Irrigation and

Drainage Paper 56 (Allen et al., 2006) and FAO Water Development and Management

Unit (FAO, 2013). The assumed values of length of crops development stages for study

area are given in Table 3.6.

Table 3.6: Length of crops growth stages (days) for planting period

Crop Initial

stage

Development

stage

Mid

season

Late

season Total

Wheat 15 25 50 30 120

Cotton 30 50 60 55 195

Onion 20 45 20 10 95

Sunflower 25 35 45 25 130

Tobacco 20 30 30 30 110

Barley, Oat (Rabi fodder) 15 25 50 30 120

Berseem/Lucerne (Rabi

fodder) 10 30 Var. (50) Var. (45) 135

Maize (Kharif Fodder) 20 30 30 10 90

Sorghum (Kharif Fodder) 20 35 40 30 125

The data on Kc, rooting depth, depletion fraction and yield response function for

the study area were taken from the IWMI Working Paper 24 (Ullah et al., 2001), FAO

Irrigation and Drainage Paper 56 (Allen et al., 2006) & FAO Irrigation and Drainage

Paper 33 (Doorenbos and Kassam, 1979) as given in the Table 3.7 & 3.8.

69

Table 3.7: Kc values of crops cultivated in the study area

Crop Crop coefficient (Kc)

Initial Mid End

Wheat 0.28 1.15 0.30

Cotton 0.32 1.12 0.37

Onion 0.70 1.00 1.00

Sunflower 0.35 1.15 0.35

Tobacco 0.50 1.15 0.80

Barley, Oat (Rabi fodder) 0.28 1.15 0.30

Berseem/Lucerne (Rabi fodder) 0.40 0.90 0.85

Maize (Kharif Fodder) 0.09 0.83 0.18

Sorghum (Kharif Fodder) 0.18 0.98 0.23

Table 3.8: Maximum root depth, soil water depletion fraction and seasonal yield

response functions (Ky) of the crops cultivated in the study area

Crop Max root depth (m) Depletion fraction Ky

Wheat 1.5 0.55 1.15

Cotton 1.7 0.65 0.85

Onion 0.6 0.30 1.10

Sunflower 1.5 0.45 0.95

Tobacco 0.8 0.50 0.90

Barley, Oat (Rabi fodder) 1.5 0.55 1.15

Berseem/Lucerne (Rabi fodder) 0.9 0.50 1.00

Maize (Kharif Fodder) 1.2 0.50 1.25

Sorghum (Kharif Fodder) 2.0 0.50 0.90

The calculation of CWR was carried out by calling up successively the

appropriate climate and rainfall data sets, together with the crop files and the

corresponding planting dates. Once all the data were entered, CROPWAT Windows

automatically calculated the results. The conveyance/distribution efficiency of 75% (field

channel length of 200-2000 m) and application efficiency 60% for surface method of

irrigation i.e. basin, border and furrow as indicated by Brouwer et al. (1989) were

utilized by the FAO CROPWAT 8.0 in the assessment of irrigation water adequacy.

3.12 Irrigation efficiency of canal water and/or groundwater irrigated

fields

There are huge conveyance losses in the hill torrent/spate irrigation system. The

application efficiency of the Mithawan hill torrent irrigation system determined by

Ahmad (2003) varied from about 19 to 36% with an average application efficiency of

about 28%. The leveling of field is disturbed due to repairing and maintenance of the

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embankments, and also due to the application of high velocity huge discharge of hill

torrent flow. Therefore, the bunds exist in Mithawan hill torrent command area were

uneven and required high cost of leveling, if necessary to irrigate with canal water and/or

groundwater. Accordingly, the assessment of irrigation efficiency of canal water and/or

groundwater irrigated fields was important to plan an efficient irrigation system. The farm

irrigation efficiency of canal water and/or groundwater irrigated fields was calculated by

the Eq. 3.13:

EI = VR

VD × 100 (3.13)

where;

EI = farm irrigation efficiency of canal water and/or groundwater irrigated field, (%)

VR = volume of water required by the crop, (m3/ha)

VD = volume of water delivered from the source to crop, (m3/ha)

3.13 Hill torrent irrigation

In the study area, water scarcity is a major threat to agriculture, livestock and

human beings. Spate irrigated fields of study area are irrigated only once by the spate

water/hill torrent or rainfall runoff. The direct rainfall satisfy only less than 15% of

irrigation requirement (Qureshi et al., 2004a). Thus, there was huge difference between

water supplied and required by the crops. Due to this difference, the irrigation trend in the

study area has been changed from spate irrigation to groundwater irrigation using

submersible and deep well turbine pumps.

The reliance on groundwater in the study area has significantly increased and

extensive pumping was observed during the last two decades. Due to over- exploitation of

groundwater, the watertable has been lowered than screen level and a large number of

installed pumps have failed to pump water. Conversely, the application of poor quality of

groundwater irrigation was deteriorating the upper fertile surface of soil. Therefore, it was

necessary to determine the impact of hill torrent and groundwater irrigation application

on the study area. The impact of irrigation sources were assessed by the following

factors:

1. Impact assessment of hill torrent and groundwater irrigation on socio-economic

and environmental conditions of the farmers of study area

2. Comparison of benefit cost ratio of hill torrent irrigated crops with groundwater

irrigated

71

3. Assessment of the quality of hill torrent and groundwater

4. Impact of hill torrent and groundwater irrigation application on soil salinity

3.13.1 Socio-economic and environmental condition of the farmers

Hill torrent irrigation possesses significant impact on the socio-economic and

environmental condition of the farmers. The assessment of various factors was made

through field visits, survey and farmers’ interview regarding socio-economic and

environmental condition of the area. The results of such factors are summarized in

Chapter No.4.

3.13.2 Benefit cost ratio of the crop

The benefit cost ratio was used to evaluate the investment of farmers for

agriculture. The benefits cost ratios of the crops sown in study area were calculated using

the Eq. 3.14:

BCR = ∑ Bc

∑ Ci (3.14)

where;

BCR = benefit cost ratio of crop

∑Bc = sum of all benefits/income obtained from the crop, (Rs./ha)

∑Ci = sum of total investment on the crop, (Rs./ha)

The total investment on crop was included of costs of inputs, labor and machinery (seed,

irrigation, fertilizer, pesticides, seed bed preparation, labor of harvesting, threshing,

material handling, transportation etc.). Similarly the benefits/income from crop was

consisting of price of yield and by-products. The data on investment and income from

crops cultivated in the study are given in Appendix-C1 to C9

3.13.3 Irrigation water and soil salinity

The groundwater of study area was poor in quality and caused accumulation of

salts in the root zone. Whereas, the quality of hill torrent water was considered good by

the farmers and if available they applied it to their fields to meet the crop water

requirement as well as to leach down the salts from the root zone. The impact of hill

torrent and groundwater irrigation application was evaluated by comparing the soil and

water quality of the study area. The analyses of soil and water samples for desired

parameters were carried out at the Soil & Water Testing Laboratory, Research Wing, DG

72

Khan and in the analytical laboratories of the Faculty of Agricultural Sciences, Ghazi

University, DG Khan.

The suitability of water for a specific purpose depends upon the types and

amounts of dissolved salts. Water, which is not good for drinking and industrial purpose

may be quite suitable for irrigation. Irrigation water, irrespective of its source, always

contains some soluble salts. The following criteria given by Basu (2011) was used for the

assessment of irrigation water quality and soil salinity:

1. pH

2. Total concentration of soluble salts judged through electrical conductivity (EC)

3. Relative proportion of sodium to other cations such as Ca and Mg referred as

Sodium Adsorption Ratio (SAR)

4. Concentration of carbonates and bi-carbonate as related to the concentration of

calcium plus magnesium referred as Residual Sodium Carbonate (RSC)

5. Content of anions or nutritional benefit resulting from nutrients such as chloride,

nitrate, phosphate, and sulfate, which may be present in the irrigation water in

significant amounts

6. Concentration of boron or other elements that may be toxic to plants and may

inhibit plant growth or be an environmental hazard

Out of these indictors, salinity and/or sodicity is the most common problem associated

with irrigation water. Consequently, the following parameters were analyzed for quality

of irrigation waters and its impact on soil salinity.

1) Acidity-alkalinity (pH)

The pH of soil and water samples was measured using pH meter (pH-212,

microprocessor pH meter by Hanna) following the procedure as given in Agriculture

Handbook No. 60 (Richards, 1954). The pH data of soil and water samples are given in

Appendix-D1, D3 and D6.

2) Electrical conductivity (EC)

Salinity of irrigated soil is usually dependent and determined by the salinity of

irrigation water. Generally, all irrigation waters having EC less than 2.25dS/m were

considered suitable except in some unusual situations like very sensitive crops and highly

clay soils having poor permeability. However, the ideal value is less than 0.75dS/m and

the water widely used has the value between 0.75 and 2.25dS/m. The electrically

73

conductivity of soil samples was determined by EC meter (3173 conductivity meter by

Jenco) by following the procedure as given in Agriculture Handbook No. 60 (Richards,

1954). The values of EC of soil and water samples are given in Appendix-D1, D3 and

D5.

3) Sodium (Na)

Sodium competes with other nutrients for uptake by the plants and may also

become directly toxic. The determination of Na was carried out with the help of flame

photometer (PFP-7 by Jenway) following the procedure as given in Agriculture

Handbook No. 60 (Richards, 1954). The results of Na concentration in soil and water

samples are given in Appendix-D2, D4 and D7.

4) Calcium and magnesium (Ca & Mg)

Usually high level of Mg promoted the high development of exchangeable Na in

irrigated soil. Based on ratio of Mg to Ca, waters were categorized as given below (Cheng

and Bray, 1951):

Safe <1.5

Moderate 1.5–3.0

Unsafe >3.0

The estimations of Ca and Mg for this study were carried out following the procedure as

given in Agriculture Handbook No. 60 (Richards, 1954). The concentration of Ca plus

Mg presented in the soil and water samples are given in Appendix-D2, D4 and D8.

5) Sodium adsorption ratio (SAR)

The sodium hazard in water as well as soil extract was calculated by the sodium

adsorption ratio (SAR) using the Eq. 3.15:

SAR = Na+

√(Ca2++Mg2+)2

⁄

(3.15)

where; the concentrations of cations are recorded as me/L

The values of SAR of soil and water samples are given in Appendix-D2, D4 and D12.

Based on the value of SAR, waters were rated into different categories of sodicity as

given below (Richards, 1954):

Safe < 10

Moderately Safe 10-18

Moderately unsafe 19-26

74

Unsafe > 26

Waters with low SAR and low EC are widely suitable but when value of any one of these

parameters or both increases in its content, the water becomes less suitable for irrigation.

6) Carbonates and bi-carbonates

The estimation of carbonates and bicarbonates were carried out based on simple

acidimetric titration using different indicators following the procedure as given in

Agriculture Handbook No. 60 (Richards, 1954). The results of carbonates and bi-

carbonates of soil and water samples are given in the Appdendix-D2, D4, D10 and D11.

7) Residual sodium carbonate (RSC)

The RSC is important for carbonate and bicarbonate rich irrigation waters and

indicates their tendency to precipitate calcium as CaCO3. It was calculated from the data

for carbonates, bicarbonates and calcium plus magnesium using the Eq. 3.16:

RSC = (CO32− + HCO3

−) − (Ca2+ + Mg2+) (3.16)

where;

RSC and concentrations of cations and anions are in me/L

The results of RSC of the soil and water samples are given in Appendix-D2, D4 and D13.

Whereas, the sodicity hazard in term of RSC were categorized as under (Richards, 1954):

Safe <1.25

Moderate 1.25 – 2.5

Unsafe >2.5

The limits can vary depending upon types of soil, rainfall and climatic conditions.

Higher value of RSC can be considered safe for sandy soils in high rainfall area (> 600

mm/annum).

3.14 Groundwater pumping

The amount of water pumped for a particular period of time requires the total

number of tubewells, their discharge and time of operation. It is possible when tubewells

are installed and operated by the government or any institution but at regional level it

becomes difficult to obtain accurate information from the farmers’ tubewells. The change

in groundwater storage between the beginning and end of the dry season indicates the

total quantity of water withdrawn from groundwater storage, while the change between

the beginning and end of rainy (monsoon) season indicates the recharge or volume of

water gone into the aquifer/groundwater reservoir. If during monsoon season, the

75

recharge is more than extraction the groundwater storage increases, which can be utilized

in the subsequent dry season. The water levels may be high after occurrence and low just

before the occurrence of hill torrent.

The watertable of selected hill torrent command existed at a greater depth and it

required huge investment to make boreholes for the collection of watertable data. It is

reported that there should be at least 3 spatially well-distributed observation wells in the

unit, or one observation well per 100 square kilometer (Kumar, 2009). Therefore, during

survey it was aimed to find more observation wells from already installed tubewells than

minimum criteria. For this purpose, 9 boreholes available in the study area were selected

for data collection. There was no or low cultivation through canal water and/or

groundwater irrigation at western part of the study area. The observation wells were

available only at eastern part of the study area. The location of selected boreholes

(observation wells) is shown in the Fig. 3.9. The watertable data of selected observation

wells were collected on weekly basis from June 03, 2012 to June 01, 2014 as given in the

Appendix-E1. The collected data of observation wells were utilized for the assessment of

watertable fluctuation due to increasing trend of groundwater pumping and its impact on

the environment of study area.

Fig. 3.9: Location of observation wells in the study area

76

3.15 Groundwater model

A groundwater flow model is mostly used to predict watertable fluctuation and

water balance as influenced by the pumping activities against recharge sources i.e.

rainfall, hill torrent flooding and irrigation return flow. A large number of groundwater

numerical models are available but a model, which could simulate and run comparatively

more accurately with minimum available set of data, was preferred. As, “MODFLOW”

can simulate and run more accurately with the minimum available data thus it was used

for this study. It utilizes the observed data on watertable records, climate, crop and soil in

addition to hydraulic conductivity, evapotranspiration, and aquifer characteristics data.

The calibrated and validated model was used to predict watertable fluctuations for this

research study. A summary of description regarding the “MODFLOW” model is given

below:

3.16 Description of “MODFLOW” model

The partial differential equation describing the three-dimensional movement of

groundwater through porous material can be written as Eq. 3.17 (McDonald and

Harbaugh, 1984):

∂

∂x[Kxx

∂h

∂x] +

∂

∂y[Kyy

∂h

∂y] +

∂

∂z[Kzz

∂h

∂z] − W = Ss

∂h

∂t (3.17)

where;

x, y and z = three dimensional coordinates along the major axes of

hydraulic conductivity i.e. Kxx, Kyy and Kzz, (LT-1)

h = potentiometric head, (L)

W = volumetric flux per unit volume and represents sources

and/or sinks of water, (T-1)

Ss = the specific storage of the porous material, (L-1)

T = time, (T)

3.16.1 Evapotranspiration module (EVT)

For this study the evapotranspiration (ET) surface was selected as 0.5m below the

ground surface and extinction depth was 1.5m. The maximum evapotranspiration rate

(ETm) assessed by the CROPWAT model using climatic data (Table 3.3) is shown in the

Table 3.9. During stress period 1 (Kharif season) the maximum evapotranspiration rate

was 0.0068m/day and for stress period 2 (Rabi season) the maximum evapotranspiration

77

rate was 0.0042m/day. The high rate of ET during stress period 1 than stress period 2 was

due to high temperature and wind velocity in the study area during Kharif season.

Table 3.9: Maximum evapotranspiration rate of the study area

Stress period 1 2

ETm (m/day) 0.0068 0.0042

3.16.2 Recharge module (RCH)

The estimation of recharge is a complicated phenomenon and involves a number

of unknown factors, such precipitation, water channels and irrigation (groundwater, canal

water and hill torrent/spate irrigation). The recharge values were computed using series of

spreadsheet calculations based on rainfall and irrigation during the stress period.

1. Recharge from rainfall

According to Maaslands’s method, the estimated recharge varied from 17 to 22%

of the total annual rainfall (Ahmad and Chaudhary, 1988). Based on this assumption the

recharge to the groundwater from rainfall in the study was considered 17% of the total

rainfall. The precipitation data given in Table 3.4 were used for the estimation of recharge

from rainfall.

2. Recharge from irrigation sources

The estimates for the recharge as cited by Ahmad and Chaudhary (1988) from

previous studies are as follow:

Maasland (1966) assumed 15% of water delivered as recharge

Hunting Technical Services (1966) assumed these losses as 25%, all of which was

assumed to recharge to groundwater

Tipton and Kalmbach (1967) estimated the losses from watercourse and fields as

22%, of which 85% were assumed to recharge to groundwater

For this study Maasland assumption was used for the estimation of recharge from

irrigation sources. Spate irrigated fields are inundated to a greater depth and hence

Hunting Technical Service assumption was used for the estimation of recharge from spate

irrigation system. At upstream more recharge was assumed than downstream due to more

occurrences of hill torrents, but it was assumed low by the other sources of irrigation at

upstream. Similarly, at downstream more recharge was assumed than upstream through

canal water and/or groundwater irrigation. The recharge through rainfall was considered

78

to be uniform for all cells during a stress period. The recharge fluxes estimated using

spread sheet for the study area are shown in Table 3.10.

Table 3.10: Recharge flux for the stress period of study area

Stress period 1 2

Recharge flux (m/day) 0.00045 (0.00021 – 0.00062) 0.00035 (0.00016 – 0.00049)

Recharge to groundwater aquifer of the study area varied with the space

depending on water application. The recharge flux of stress period 1 ranged from 0.00021

to 0.00062m/day and for stress period 2 it ranged from 0.00016 to 0.00049m/day. The

average values of recharge flux during stress period 1 and 2 were found 0.00045 and

0.00049m/day, respectively. The more recharge of stress period 1 than stress period 2 was

due to more hill torrents and rainfall during the monsoon season. Different values of

recharge flux for cells were used. The high rate of recharge flux was assumed for

downstream of the study area due to more cultivation as well as irrigation application.

However the recharge flux was considered low for the upstream but that was only due to

rainfall and spate irrigation.

3.16.3 River module (RIV)

If the groundwater hydraulic head (h) in a canal cell is greater than RBOT, the rate

of leakage (QRIV) from the canal to the aquifer is calculated as:

QRIV = CRIV . (HRIV − h) h>RBOT (3.18)

The value of QRIV is negative if the hydraulic head h is greater than HRIV. It means

that water flows from the aquifer into the river and is removed from the groundwater

system.

When h falls below the bottom of the canal/riverbed, the leakage rate through the riverbed

is given by:

QRIV = CRIV . (HRIV − RBOT) h≤RBOT (3.19)

The value of canal/riverbed hydraulic conductance is often given by the Eq. 3.20 (Chiang

and Kinzelbach, 1998).

CRIV = K.L.W

M (3.20)

where;

CRIV = hydraulic conductance of the canal, (L2/T)

K = hydraulic conductivity of the canal material, (LT-1)

79

L = length of reach in canal, (L)

W = width of canal, (L)

M = thickness of canal bed (bank to bed height), (L)

The width of canal “W” was 52m, length of reach in canal “L” 500m and bank to

bed height “M” was approximately 5m. The Hydraulic conductivity of the canal/riverbed

material was taken 1-1.5m/day, as reported by Knipe et al. (1993). The hydraulic

conductance of the canal was computed as 7800m2/day. The recharge flux through canal

system was computed by the model. The elevation of riverbed bottom varied from 126 to

125m and values of head in the canal for different stress period are given in Table 3.11.

Table 3.11: Range of the values of head in the canal during each stress period

Stress period 1 2

Head in the canal (m) 128- 127 126.5 – 125.5

3.17 Preparation of “MODFLOW” input data file

MODFLOW model needs a properly prepared data file for simulation. The

preparation of input data and the presentation of modeling output were facilitated by

ArcGIS 9.3 software, and complimented by Microsoft Excel and MS WordPad. The

model was calibrated and validated under transient conditions covering 2 years from June

01, 2012 to May 31, 2014. The length of the stress period was taken 183 and 182 days,

for Kharif season (summer) and Rabi season (winter), respectively. The various steps

involved in the preparation of data file were as follows.

3.17.1 Development of input directory

First step in the preparation of model was to develop input directory using file

menu and was saved for further input of data.

3.17.2 Creation of grid

The model was able to handle whole aquifer system as a single unit. Therefore, in

the model an aquifer system was replaced by a discretized domain consisting of an array

of nodes and associated finite difference cells. Fig. 3.10 shows a spatial discretization of

an aquifer system with a mesh of cells and nodes at which concentration and hydraulic

heads can be calculated. The number of rows (i), columns (j) and layers (k) were given to

the model. Consequently, the location of cell was described in term of the notion i, j and

k.

80

Fig. 3.10: Generated model grid of study area

3.17.3 Defining of layer type

There was a large number of sand, silt, clay and combination of the layers in the

study area, which were grouped into four major types namely; clay silty with sand, sand

with silt, clay and sand. The model was set up as four layers representing the constituent

aquifer horizons namely, unconfined, confined/unconfined (transmissivity varies),

confined and confined/unconfined (transmissivity constant), corresponding to model layer

1, 3, 0 and 2, respectively. The thickness of each model layer is given in the Table 3.13.

3.17.4 Transmissivity

As the model needed the transmissivity value, it was set to be calculated by

defining the layer type, using a specified horizontal hydraulic conductivity.

3.17.5 Boundary conditions

The flows across the northern and southern boundaries of the aquifer geometry

were restricted by defining no flow boundaries of model (cell value = 0). The western

boundary of area is covered by the hills and eastern side is occupied by the canal.

81

Fig. 3.11: Geographical boundaries of the model domain

The model grid consisted of 17500m in length from west to east, 32 rows, 35

columns and 4 layers. The model grid contained 1120 cell, with cell dimensions of 500 x

500m, out of which 670 were active and 450 were inactive as shown in Fig. 3.11. The

geographic boundaries of the model domain are given in Universal Transverse Mercator

(UTM) co-ordinates in Table 3.12.

Table 3.12: Geographic boundaries for the model of study area

Easting Coordinate Northing Coordinates

X1 (bottom left x

coordinate, m) 624952.974

Y1 (bottom left y


X2 (top right x


Y2 (top right y


3.17.6 Elevation of top and bottom of layer

The elevation of top and bottom of the layer was specified to calculate

transmissivity. The values of elevation of ground surface as shown in Table 3.10 were

primarily the results of interpolation of known elevation of ground surface at all corner of

the domain.

Generally the study area has a slope from North West to South East. Soil surface

elevation difference factors (west east at north, west east at south, north south at west and

north south at east) were used to calculate the elevation of each cell of the study area.

Difference Factor of NSLW-E at North = (NSL at NW – NSL at NE)/No. of cells

= (228 – 165)/32 = 1.97 m

Difference Factor of NSLW-E at South = (NSL at SW – NSL at SE)/No. of cells

= (126 - 117)/32 = 0.28 m

82

Surface elevation at center of each cell of first row and last row was determined

by subtracting difference factor of NSL as determined by the given above process.

Afterward, the difference factor of NSL for each column from top to bottom was

calculated by the similar procedure. Similarly, the surface elevation at the center of each

cell of columns was calculated by subtracting the elevation difference factor from first to

last cell. The NSL values of each cell of study area rectangle are given in Appendix-F1.

The model required to specify the depth of each layer showing the homogenous

strata having a specific horizontal and vertical hydraulic conductivity. Accordingly, the

total depth was divided into 4 layers each of 6, 30, 19 m and remaining depth to the

bottom of aquifer as given in the Table 3.13.

Table 3.13: Thickness of aquifer layers

Layer 1 2 3 4

Thickness (m) 6 30 19 From the bottom of 3rd layer to bottom of aquifer

(bottom of 4th layer)

3.17.7 Simulation time

It comprises stress periods, which were 183 and 182 days for Kharif and Rabi

season, respectively.

3.17.8 Initial conditions

The values of variables taken at t = 0 at all points within the domain are known as

initial values. Therefore, the hydraulic head at t = 0 were given to the model as required

to start simulation. The initial groundwater heads, aquifer properties and abstraction rates

were obtained from the measured spatial and temporal field data.

3.17.9 Initial hydraulic head

The values of initial hydraulic heads of selected observation wells are given in the

Table 3.14.

Table 3.14: Initial hydraulic heads of observation wells

Observation well No. Initial hydraulic head (m)

1 116.03

2 114.41

3 113.06

4 113.83

5 111.67

6 110.40

7 111.50

8 111.20

9 116.45

83

3.17.10 Horizontal and vertical hydraulic conductivity

Horizontal and vertical hydraulic conductivity values were assigned to all the

layer of model domain. Transmissivity of the layer was calculated using hydraulic

conductivity and layer thickness by model itself. The values of horizontal and vertical

hydraulic conductivities of the model layers are given in Table 3.16.

3.17.11 Effective porosity

Effective porosity given to all the layers was used to calculate average velocity of

the flow through porous medium. The range of effective porosity of soil layers shown in

Table 3.15 as given by Rawls et al. (1982) was used in this study.

Table 3.15: Values of effective porosity of the soil layers

Soil layer Effective porosity range (average)

Clay silty with sand 0.28-0.50 (0.39)

Sand with silt 0.28-0.54 (0.41)

Clay 0.27-0.50 (0.38)

Sand 0.35-0.48 (0.42)

3.17.12 Time constant parameters

These parameters include:

1. Well logs

In order to determine the soil texture at various horizons of profile, the well logs

data were collected from well drilling contractors. There was a large number of soil layers

in the study area, which were grouped into four major ones namely; clay silty with sand,

sand with silt, clay and sand.

2. Hydraulic conductivity and specific yield

The hydraulic conductivity is an important characteristic of soil to estimate the

groundwater recharge from irrigation and canal. The basic parameters used in the model

are summarized in Table 3.16.

Table 3.16: Soil layer, horizontal & vertical hydraulic conductivity, specific storage

and specific yield for the study area

Soil layer

Horizontal

hydraulic

conductivity

(m/day)

Vertical

hydraulic

conductivity

(m/day)

Specific

storage

(m-1)

Specific yield

Clay silty with sand 1 0.1 0.001 0.10

Sand with silt 30 3 0.00001 0.20

Clay 0.05 0.005 0.001 0.05

Sand 100 10 0.000001 0.25

Source: CSIRO (2003)

84

3.17.13 Time variant parameters

These parameters include hydro-meteorological and water level records as

summarized below:

1. Hydro-meteorological data

The hydro-meteorological data regarding rainfall for the period from June 01,

2012 to May 31, 2014 were collected from PMD, DG Khan Observatory.

2. Water level monitoring data

To observe the changes in groundwater level and to assess the recharge

contribution, the watertable depth from June 03, 2012 to June 01, 2014 were collected

from selected observation wells in the study area. The location of selected observation

wells in the model domain is shown in Table 3.17. The data regarding depth to watertable

were collected with an Electric Watertable Depth Detector.

Table 3.17: Location of observation wells in the model grid

Well

name X (easting), m Y (northing), m

Location/cell No. (column,

row)

OW1 639610.513 3301574.972 30, 8

OW2 639825.021 3295660.676 30, 20

OW3 637986.379 3292872.07 27, 25

OW4 638047.667 3303321.681 27, 5

OW5 635780.01 3300625.007 22, 10

OW6 636454.178 3298510.57 23, 14

OW7 634584.893 3292259.189 20, 20

OW8 636576.754 3295109.083 24, 21

OW9 632072.083 3302463.649 15, 6

3.18 Model calibration

Generally, there are two ways of finding model parameters to achieve calibration:

(1) manual trial-and-error adjustment of parameters and (2) automated parameter

estimation. It is not common to make tens to hundreds of trial-and-error simulations

before an acceptable match is achieved. An alternative procedure for model calibration

includes use of inverse modeling techniques such as PEST and UCODE. During the

calibration it is desirable to make comparison between the calculated and observed head

on original water level data rather than interpolated water level data because of the

uncertainty involved in the interpolation process. However, interpolated water head data

has the advantage of being available in every model cell making it easier to judge the

success or failure of every model cell to replicate observation.

85

Calibrated water levels were compared with the observed water levels for 9

observation bores. The water level data for these wells available from June, 2012 to May,

2014 were used for the calibration and validation purposes. Hydraulic conductivity and

recharge values were adjusted until reasonable matches were obtained between the

observed and simulated water levels for all observation wells. Figs. 3.12-3.20 show the

simulated and observed temporal variation of water level at the selected observation wells

for this study. The model was successfully calibrated and validated with the observed

water levels. Since a close agreement was obtained between the observed and simulated

heads and the overall trend of the observed groundwater is also followed well by the

modeled data.

Fig. 3.12: Simulated and observed groundwater head at an OW-1


115

115.2

115.4

115.6

115.8

116

116.2

Dec, 2012 Jun, 2013 Dec, 2013 Jun, 2014

Hea

d,

m

Time

Observed headSimulated head

112

112.5

113

113.5

114

114.5

Dec, 2012 Jun, 2013 Dec, 2013 Jun, 2014

Hea

d,

m

Time


86




111.6

111.8

112

112.2

112.4

112.6

112.8

Dec, 2012 Jun, 2013 Dec, 2013 Jun, 2014

Hea

d,

m

Time


111

111.5

112

112.5

113

113.5

114

Dec, 2012 Jun, 2013 Dec, 2013 Jun, 2014

Hea

d,

m

Time

Observed head

Simulated head

108

108.5

109

109.5

110

110.5

111

111.5

Dec, 2012 Jun, 2013 Dec, 2013 Jun, 2014

Hea

d,

m

Time


87




107.5

108

108.5

109

109.5

110

110.5

111

Dec, 2012 Jun, 2013 Dec, 2013 Jun, 2014

Hea

d,

m

Time

Observed headSiumlated head

107.5

108

108.5

109

109.5

110

110.5

111

111.5

Dec, 2012 Jun, 2013 Dec, 2013 Jun, 2014

Hea

d,

m

Time


108.5

109

109.5

110

110.5

111

111.5

Dec, 2012 Jun, 2013 Dec, 2013 Jun, 2014

Hea

d,

m

Time


88


3.19 Statistical calibration performance of the MODFLOW model

The degree of fit between model simulated and observed water level heads was

checked through statistical analysis. The statistical analysis included the Mean Error

(ME), Mean Absolute Error (MEA), Root Mean Squared Error (RMSE) and Model

Efficiency (MEF). The error indices are usually used for the model evaluation (Saatsaz et

al., 2011). RMSE is one of the commonly used error index statistics (Singh et al., 2005).

The error criteria were defined as the error between simulated and observed heads. Mean

Error is the mean difference between the observed (ho) and simulated (hs) heads, which

was calculated using the Eq. 3.21.

ME = 1

n ∑ (ho − hs)n

i=1 (3.21)

Mean Absolute Error is the mean of the absolute value of the difference in observed and

simulated head, which was calculated using the Eq. 3.22

MAE = 1

n ∑ |ho − hs|n

i=1 (3.22)

Root Mean Squared Error is the average of the squared differences in observed and

simulated head, which were calculated using the Eq. 3.23.

RMSE = √1

n∑ (ho − hs)2n

i=1 (3.23)

The model efficiency was calculated using the Eq. 3.24 (Asghar et al., 2002)

MEF = 1 − ∑ (ho−hs)2n

i=1

∑ (ho−h̅)2n

i=1

(3.24)

where;

ho and hs = observed and simulated head

116.1

116.2

116.3

116.4

116.5

116.6

116.7

Dec, 2012 Jun, 2013 Dec, 2013 Jun, 2014

Hea

d,

m

Time


89

n = number of values used in the comparison

h̅ = observed average (h̅ = ∑ho

n)n

i=1

The model efficiency may be zero, which shows high variability between

observed and simulated heads. The zero value of efficiency shows very poor simulation

of the model. If the model simulated and observed values exactly math with each other

then ME = 0 and MEF = 1. The results of ME, MAE and RMSE were calculated as -

0.027, 0.14 and 0.16, respectively. Similarly, the model efficiency was computed as 0.99.

The MEF clearly indicates that there is no systematic error involved between observed

and modeled heads. Thus, the model simulation for future scenarios would result the

accurate heads of selected observation wells.

3.20 Water balance

Water balance is used to check the model change in aquifer storage due to external

stresses such as wells, recharge, evaporation and canal. It is also important to identify the

error, if any, in the iterative solution and check the model results of the study area. Fig.

3.21 shows the water balance results of the calibration period and describes the volume of

water entering, subtraction and net storage in the aquifer system. Water is entered into the

aquifer system through recharge and river leakage while, subtracted from the aquifer by

the pumping and evapotranspiration (ET). The plus sign of storage refers to the water

released from the aquifer and minus refers to the water added up in the aquifer system.

The storage in the aquifer during stress period 1, 2, 3 and 4 was -2.638, 2.827, -1.868 and

3.839MCM, respectively. Similarly, the volume of water abstracted from aquifer during

the stress period 1, 2, 3 and 4 was 8.865, 11.855, 8.356 and 12.231MCM, respectively. It

clearly indicates that during stress period 1 and 3 (i.e. from June, 2012 to December, 2012

and June 2013, to December, 2013) water was added to the aquifer system, while water

was released from the aquifer during the stress period 2 and 4 (i.e. from December, 2012

to June, 2013 and December, 2013 to June, 2014) to meet the crop water requirement.

The entering of water into aquifer during the stress period 1 and 3 was due to more

water/recharge from the rainfall, hill torrent and canal water due to flow at its full supply

level in the summer season. Whereas, during the stress period 2 and 4 water abstraction

was more due to more cultivation, less occurrence of rainfall and hill torrent in the study

area.

90

Fig. 3.21: Water balance of the study area from June, 2012 to June, 2014

3.21 Strategies for the efficient use of water resources

The management strategies were developed following the results of first and

second objectives of the study. The impact of all interrelated parameters were also

considered in the development of management options for Mithawan hill torrent

command area, DG Khan such as irrigation efficiency, benefit cost ratio of the crops,

cropping intensity, soil salinity, watertable fluctuation trend and its impact on the

environment etc.

-15

-10

-5

0

5

10

15

1 2 3 4MC

M

Stress Period

StorageWellsRechargeETRiver Leakage

91

CHAPTER 4

RESULTS AND DISCUSSION

This chapter contains the collected data results, their analysis and achieved pertaining to

the study. In addition, the chapter presents relevant discussion of study conducted at

Mithawan hill torrent command area of DG Khan.

4.1 Farmers’ interviews

4.1.1 Educational level of the farmers

Table 4.1 shows that 50% of the farmers of study area were uneducated and 50%

were educated. Out of 50% educated farmers, 24% were primary, 18% matriculation, 6%

intermediate and only 2% were graduated. While, educational level of the farmers of

same study area assessed by Ahmad (2003) was 73% uneducated, 22.5% had

completed primary and only 4.5% had secondary education. A very little

improvement was found in the educational level of the farmers from 2003 to 2014.

Usually, the illiterate farmers (who never attended the school/below the level of primary

education) were permanently residing in the study area. They were totally dependent on

the hill torrent based cultivation/spate agriculture and livestock. Some farmers of the area

with primary or middle education were also permanent residents of the area but all others

with matriculation or above level of education were involved in different business

activities and had some other sources of livelihood. Generally, the farmers who were

involved in other businesses come to the area only at the time of occurrence of hill torrent

to irrigate their fields and perform cultivation practices. Hence, such farmers had the

opportunity to get education from high schools or colleges.

Table 4.1: Educational level of the farmers

Educational level No. of respondents Percent of total farmers

Uneducated 25 50

Primary 12 24

Matriculation 09 18

Intermediate 03 06

Graduation (B.A, B.Sc.) 01 02

Total 50 100

92

4.1.2 Land use and cropping pattern

Table 4.2 shows the landholding of farmers, their culturable area and uncultivable

area. The total landholding of the farmers ranged from 1.42ha to 121.41ha with mean

value of 22.66ha. Similarly, the culturable and uncultivable areas ranged from 1.42ha to

121.41ha and 0.00ha to 20.23ha with mean value of 22.26ha and 0.4ha, respectively.

Based on survey data, about 98% of the study area was culturable and about 2%

uncultivable.

Table 4.2: Land use of selected hill torrent command area

Land use No. of

respondents Min. Max. Mean Sum

Percent of

total area

Total landholding (ha) 50 1.42 121.41 22.66 1133.25 100.00

Culturable area (ha) 50 1.42 121.41 22.26 1113.02 98.22

Uncultivable area (ha) 50 0.00 20.23 0.40 20.23 1.78

Table 4.3 shows the cropping pattern of Kharif season, 2012 (wet year). Cotton

was the major crop of season and it was cultivated on about 13 of the total selected

command area. Mostly, cotton crop was cultivated on area near the right bank of DG

Canal and irrigated by canal water lift irrigation system. While the other crops namely;

onion, maize, sorghum, millet, guar, fodders were cultivated on 4.61, 0.16, 6.18, 5.73,

0.76, 0.14% of the total area, respectively. About 18% of the total study area was

cultivated by the canal water and/or groundwater while about 13% by the spate irrigation.

Table 4.3: Cropping pattern of Kharif season, 2012 (wet year)

Crop type N Respondents (%) Cultivated area (ha) Percent of total area

Cotton 18 36 146.70 13.07

Onion 12 24 51.70 4.61

Maize 02 04 1.82 0.16

Sorghum 24 48 69.30 6.18

Millet 17 34 64.35 5.73

Guar 05 10 8.50 0.76

Fodders 04 08 1.62 0.14

Total 343.99 30.65 N = No. of Respondents

Table 4.4 shows the cropping pattern of Kharif season, 2013 (dry year). Cotton

was the major crop of season and cultivated on about 14% of the total study area. While

the other crops namely; onion, maize, sorghum, millet, guar, fodders were cultivated on

7.50, 0.23, 1.73, 1.19, 0.61, 0.41% of the total area, respectively. Mostly, maize crop

cultivated in the study area was used as a fodder. Sorghum, millet and guar were

cultivated by the upstream farmers of selected hill torrent command area either by direct

93

rainfall or low discharge of hill torrent. Therefore, about 22% of the study area of selected

hill torrent command was under canal water and/or groundwater irrigation and about

3.5% area was under spate irrigation. The comparison indicates that the area under

cultivation of cotton, guar, maize and fodder was almost same during the Kharif season of

wet and dry years while onion cultivation was less during the wet year and high during

the dry year. The less cultivation of onion during the wet year was due to the diversion of

farmers from onion to spate irrigated crops. Accordingly, the area under the cultivation of

sorghum and millet was higher during the wet year and low during the dry year. It

indicates that the farmers preferred the cultivation of spate irrigated crops during the wet

year.

Table 4.4: Cropping pattern of Kharif season, 2013 (dry year)

Crop N Respondents (%) Cultivated area (ha) Percent of total area

Cotton 17 34 157.5 13.90

Onion 20 40 84.99 7.50

Maize 02 04 2.63 0.23

Sorghum 10 20 19.63 1.73

Millet 03 06 13.46 1.19

Guar 04 08 6.88 0.61

Fodders 05 10 4.65 0.41


The cropping pattern of Rabi season, 2012-13 (wet year) is given in Table 4.5.

Wheat and gram were grown on about 23 and 29% of the total study area during the

season, respectively. Brassica was cultivated on about 3.62% of the total command area.

The all other crops namely; tobacco, sunflower, arugula and fodders were cultivated on

less than 1% of the total command area. Collectively, about 33% of the study area was

under spate irrigation and about 25% by the canal water and/or groundwater irrigation.

Table 4.5: Cropping pattern of Rabi season, 2012-13 (wet year)

Crop type N Respondents

(%) Cultivated area (ha)

Percent of total

area

Wheat 30 60 260.93 23.02

Gram 31 62 325.37 28.71

Tobacco 02 04 7.28 0.64

Sunflower 01 02 8.09 0.71

Brassica 19 38 41.08 3.62

Arugula 07 14 8.30 0.73

Fodders 13 26 9.71 0.86


94

Table 4.6 illustrates the cropping pattern of Rabi season 2013-14 (dry year).

Wheat, gram and fodders were grown on about 37, 1.59 and 1.38% of the total study area

during the season, respectively. The all other crops namely; onion, tobacco, sunflower,

brassica and arugula were cultivated on less than 1% of the total command area.

Collectively, about 40% of the total study area was under canal water and/or groundwater

irrigation while about 2.5% under spate irrigation. The comparison indicates that the area

under wheat cultivation was quite less during the wet year and more during the dry year.

While the area under cultivation of gram, brassica and arugula was relatively high during

the wet year than dry year. The less cultivation of wheat during the wet year was due to

more cultivation of gram, brassica and arugula through the spate irrigation. Out of spate

irrigated crops, gram was cultivated on major part of cultivated area during the Rabi

season of wet year 2012-13.

Table 4.6: Cropping pattern of Rabi season, 2013-14 (dry year)

Crop type N Respondents (%) Cultivated area (ha) Percent of total area

Wheat 41 82 423.80 37.40

Onion 03 06 5.36 0.47

Tobacco 02 04 4.05 0.36

Sunflower 02 04 6.27 0.55

Gram 04 08 18.01 1.59

Brassica 05 10 9.51 0.84

Arugula 01 02 0.81 0.07

Fodders 18 36 15.65 1.38


Table 4.7 shows that during the Kharif season, 2012 of a wet cropping year 2012-

13, about 30% of the total area were cultivated, 68% culturable waste and 2% was

uncultivable. Similarly, during the Rabi season, 2012-13 of same wet year, about 58% of

total area was cultivated, 40% culturable waste and 2% was uncultivable. Whereas,

during the Kharif season, 2013 of a dry year 2013-14, about 25.5% of total area was

cultivated, 72.5% uncultivated and 2% uncultivable. Similarly, during the Rabi season,

2013-14 of same dry year, about 42.5% of total area was cultivated, 55.5% culturable

waste and 2% was uncultivable.

95

Table 4.7: Land use patterns during wet and dry years

Land use (% of

the total area)

Wet year Dry year

Kharif, 2012 Rabi, 2012-13 Kharif, 2013 Rabi, 2013-14

Cultivated area 30.35 58.30 25.57 42.66

Culturable waste 67.86 39.91 72.64 55.55

Uncultivable area 1.79 1.79 1.79 1.79

Total 100 100 100 100

4.1.3 Cropping intensities

Table 4.8 shows that the seasonal cropping intensities for Kharif and Rabi seasons

were 30.91 and 59.37% during the cropping year, 2012-13, and 26.04 and 43.44% during

the cropping year, 2013-14, respectively. There was a less difference of area under

cultivation (<5%) during Kharif season of wet and dry year but a significant difference of

area under cultivation (<16%) was found during Rabi season of wet and dry year. The

significant difference in cropping intensities during Rabi seasons was due to more

cultivation of spate irrigated crops during the wet year than that of a dry year. The annual

cropping intensity of wet year was about 90% as compared to 70% of dry year. However,

the average cropping intensity of the selected hill torrent command area was found 80%,

which was far less than that of the average cropping intensity (173%) of irrigated areas of

Punjab, Pakistan (Raza et al., 2009).

Table 4.8: Cropping intensity during a wet and dry year (2012-14)

Cropping season/ year Cropping intensity (%)

Kharif 2012 30.91

Rabi 2012-13 59.37

Annual 2012-13 90.28

Kharif 2013 26.04

Rabi 2013-14 43.44

Annual 2013-14 69.48

Average annual 79.88

4.1.4 Sources of irrigation water

The access of different available sources of irrigation to the farmers of study area

is given in Table 4.9, which shows that 14% of the farmers had opportunity of using hill

torrent water for spate irrigation and 4% each for groundwater and canal water. Forty four

percent of the farmers had the facility to use hill torrent plus groundwater, 2% hill torrent

plus canal water, and 32% had access to all water sources. It indicates that overall 92% of

the farmers had the availability of hill torrent flow and remaining 8% had no access to the

hill torrent flow due to either non-existence of channel system or sand dunes. Similarly,

80% of the famers of study area had the opportunity of groundwater extraction and 38%

96

of farmers had access to the canal water lift irrigation. Canal water lift irrigation could be

availed only by the farmers located adjacent to the right bank of DG Canal. Generally, all

the farmers prefer to use hill torrent flow for spate irrigation when available. However,

farmers are forced to use canal water and/or groundwater to cultivate crops in case of

non-occurrence of hill torrents. The farmers who had access to both the canal water and

groundwater, they preferred to use canal water because of good quality and low energy

cost. Consequently, the priority of irrigation water application was found to be hill

torrent, canal water and groundwater. Therefore, the efficient utilization of hill torrent for

irrigation would attract farmers to bring more area under cultivation.

Table 4.9: Sources of irrigation water available to the farmers

Sources of irrigation No. of respondents Percent of total farmers

Hill torrents (HT) 07 14

Groundwater (GW) 02 04

Canal water (CW) 02 04

Hill torrents +

groundwater 22 44

Hill torrents + canal water 01 02

All sources

(HT+CW+GW) 16 32

Total 50 100

Table 4.10 shows the availability of hill torrent flow for spate irrigation on yearly

basis. About 32% of the farmers responded that the hill torrent flow was available every

year, 26% stated that flow was available after every two years, 6% had after every three

years, 2% replied the availability after every four years and 6% of the farmers replied that

the flow was available after every five years. However, 28% of the farmers were unable

to respond to the question. The hill torrent occurred every year but its availability for

spate irrigation varied with location of fields in the command area. The farmers who had

landholding at the upstream of command area, found the opportunity of spate irrigation

every year, while the farmers of downstream area found less chance of spate irrigation

every year. Most of the time hill torrent occurred for a short time and not available to the

farmers of middle and downstream of command area. Thus, the farmers of upstream

command area were more beneficial from the hill torrents than middle and downstream

farmers.

97

Table 4.10: Availability of hill torrent flow for spate irrigation on yearly basis

Interval of occurrence No. of respondents Percent of total farmers

Every year 16 32

After two years 13 26

After three years 03 06

After four years 01 02

After five or more years 03 06

No response 14 28

Total 50 100

Majority of the farmers of selected hill torrent command area could not divert the

flow of hill torrent into their fields because of the poor condition of diversion structures

and embankments. It required huge investment to construct heavy duty diversion

structures and embankments. Expanses paid by the farmers for spate irrigation regarding

the construction of diversion structures and repairing of embankments are given in Table

4.11. Cost of the construction of diversion structures and repairing of the embankments

varied from Rs. 9000 to Rs. 857100/culturable area of the farmer, which showed an

average amount of Rs. 194360/culturable area of the farmer. The investment per unit area

varied from Rs. 2718 to Rs. 30888/ha with an average value of Rs. 8527/ha.

Table 4.11: Cost of construction of diversion structures and repairing of bunds

Cost of work N Minimum Maximum Mean

Based on total culturable area (Rs.) 39 9000 857100 194360

Cost per unit culturable area

(Rs./ha) 39 2718 30888 8527

N = No. of Respondents

As shown in Table 4.12, about 88% of farmers could control and divert the hill torrents

for spate irrigation, while 12% of the farmers could not use the hill torrent flow for spate

irrigation. The reasons for the farmers not using spate water were one or more such as

failure of diversion structures due to high discharge, non-existence of channel network,

deprivation by the influential and lack of financial resources for making diversion

structures. Mostly, the land area of farmers who faced aforementioned constraints

remained uncultivated in the study area. The farmers who were recipient of hill torrent

flow diverted 0.61 to 1.68m depth of water into their fields. On an average, 1.05m depth

of water was applied into the bunds while the successive crop water requirement was

satisfied by the rainfall, if any. Thus, apart from direct rainfall, the spate irrigated crops

were applied 10500m3/ha of water in a season. Under the existing scenario, the overall

application efficiency of spate irrigation was determined as 28% (Ahmad and Choudhry,

2005).

98

Table 4.12: Use of hill torrent and depth of water applied in the bund

Use of hill torrent N Percent

of N

Min. depth

(m)

Max. depth

(m)

Mean depth

(m)

Used for irrigation 44 88 0.61 1.68 1.05

Unable to use 06 12 - - - N = No. of Respondents

4.1.5 Pumping units and sources of powers

At Mithawan hill torrent command area about 80% of the farmers have installed

groundwater pumping units. Table 4.13 shows the number of pumping unit installed by

the farmer, partnership in pumping units and borehole(s) of the farmer failed so far. The

number of pumping units installed by the farmer varied from 1 to 5 and partnership in the

pumping units ranged from 1 to 10 farmers per pumping unit. Normally, the borehole

failed due to lowering of watertable, low quality of pipe/filters, mixing of two different

quality layers of groundwater etc. The number of failed bore holes ranged from 0 to 5

with an average value of about 1 for each farmer. Furthermore, there was also partnership

between the farmers of study area in canal water lift irrigation systems.

Table 4.13: Groundwater pumping units and partnership among farmers

Pumping units N Minimum Maximum Sum Mean

Groundwater pumping units 40 1 05 54 1.35

Ownership in a pumping unit 40 1 10 138 3.45

Borehole failed 40 1 05 34 0.85 N = No. of Respondents

Table 4.14 represents the types of pumps installed by the farmers for pumping

groundwater in the study area. Out of the installed pumps, about 9% were submersible

and 91% were deep well turbine pumps. The less number of submersible pumps was due

to unavailability of electricity in most parts of the study area.

Table 4.14: Types of pump installed for groundwater pumping

Type of pump No. of pumps Percent of total pumps

Submersible pumps 05 09

Deep well turbine pumps 49 91

Total 54 100

Table 4.15 shows the detail of various parameters of pumping units installed in the

study area. The depth of watertable ranged from 11.59 to 60.98m with an average depth

of 27m and depth of borehole made by the farmers ranged from 76.22 to 152.44m with

average depth of 94.40m. Similarly, the depth of lowering of deep well turbines and

submersible pumps in the borehole/casing ranged from 21 to 84m with an average depth

99

of 43m and the number of stages of deep well turbine pumps installed in the study area

varied from 5 to 14 with an average value of 9. The diameter of delivery pipes ranged

from 5 to 15cm with mean value of 11.62m. The farmers reported that the watertable

depth had lowered from 0 to 9.15m because of the continuous pumping of groundwater

with an average decline in the watertable depth of 1.65m by the year 2014. However, the

cost of groundwater pumping ranged from Rs. 200 to Rs. 700/hr with an average cost of

Rs. 479/hr. The cost was minimum adjacent to canal due to less power requirement and it

was maximum at upstream of command area due to more power requirement for the

running of deeply installed pumps.

Table 4.15: Design parameters and cost of pumping wells

Specification of the pumping units N Min. Max. Mean

Depth of watertable (m) 54 11.59 60.98 27.04

Depth of well bore (m) 54 76.22 152.44 94.40

Depth of lowering of turbine/ submersible (m) 54 21.34 83.84 42.94

Stages of the deep well turbine pumps 49 5.00 14.00 9.55

Dia. of delivery pipe (cm) 54 5.08 15.24 11.62

Watertable decline (m) 54 0.00 9.15 1.65

Groundwater pumping cost (Rs./hr) 54 200 700 478.70 N = No. of Installed Pumps

Table 4.16 shows the views of farmers regarding the quality of groundwater.

About 78% of farmers stated that the groundwater extracted was fit for irrigation and 7%

replied that the groundwater quality of their pumping units was unfit. While 15% of the

farmers responded that the water quality of pumping unit was marginally fit for irrigation.

In contrast, it was found from the analysis of groundwater samples that 50% of the

groundwater in study area was fit for irrigation and 50% unfit as given in Table 4.17.

Table 4.16: Farmers’ views on the quality of groundwater

Groundwater quality No. of pumps Percent of total pumps

Fit for irrigation 42 77.8

Unfit for irrigation 04 7.4

Marginally fit for irrigation 08 14.8

Total 54 100

Table 4.17: Laboratory results of the groundwater quality

Groundwater quality N Percent

Unfit for irrigation 06 50.0

Fit for irrigation 06 50.0

Total 12 100

100

Table 4.18 shows the sources of power used to run the pumping units installed in

the study area. About 72% of the farmers were using diesel engine to run the pumps. Out

of which, tractor was the major source of power and second one was stationary

peter/diesel engine. Similarly, about 20% of the farmers were using electricity to run their

irrigation pumps. About 4% of the farmers had the facility of electricity and standby

diesel engine to run the irrigation pumps at the time of electricity load shading. Only 4%

of the farmers had installed solar energy system to run their groundwater pumps.

Whereas, the Table 4.19 shows that 97.5% of the farmers were interested to shift their

groundwater pumping units on solar energy system, if government provides them subsidy

for this system. Similarly, 2.5% of the famers were interested in both the solar energy

system and biogas power plant. It was concluded that the solar energy systems, if

successful and available in open market or on subsidized rate by the government, was the

preference of all farmers. Under the circumstances, the farmers would prefer to shift their

groundwater pumping units to solar energy system.

Table 4.18: Sources of power used for groundwater pumping units

Source of power No. of pumps Percent of total pumps

Diesel engine (tractor/peter) 39 72.2

Electricity 11 20.4

Electricity + diesel engine 02 3.7

Solar energy system 02 3.7

Total 54 100

Table 4.19: Farmers preference regarding the source of power for future use

Preferable source of power No. of respondents Percent of total farmers

Solar energy system 39 97.5

Solar energy system/ biogas plant 01 2.5

Total 40 100

The watertable is influenced by the groundwater recharge and withdrawal through

pumps. However, the main source of groundwater recharge in study area was only hill

torrent irrigation application in the fields (Bunds). Table 4.20 shows the increasing trend

of groundwater pumps installation in the study area. There was no groundwater pumping

unit in the study area till 1990. While, 7.41% of the current pumps were installed during

1991-1995 and 30% during 1996-2000, which was comparatively high rate due to

increase in farmers’ awareness regarding development in tubewells technology and low

price of diesel. During 2001-2005, the installation rate decreased to 9.26% that was

probably because of uncertainty in the country and inflating prices of diesel. The

101

installation rate of pumping units during 2006-2010 was 39% of the current pumping

units and this high rate was due to supply of electricity at some villages of the study area.

During the period from 2011-2013, the installation of pumps were about 15% and it was

again at low rate due to sudden increase in the diesel and electricity prices. Fig. 4.1 shows

the yearly basis installation of groundwater pumping units in the study area. It concluded

that about 5% of previous year pumps were added to the system each year. The prices of

diesel and electricity influenced on the installation and running of groundwater pumps. It

is assumed that in future the use of solar energy system will be common and hence, the

installation of groundwater pumping units in the area will increase. Consequently, it will

rapidly decline the watertable of study area and would cause the failure of already

installed pumps.

Table 4.20: Installation trend of groundwater pumps in the study area

Year of installation No. of pumps Percent of total pumps

1985-1990 00 0.00

1991-1995 04 7.41

1996-2000 16 29.63

2001-2005 05 9.26

2006-2010 21 38.89

2011-2013 08 14.81

Total 54 100

Fig. 4.1: Yearly basis installation of groundwater pumps in the study area

4.1.6 Yield of crops

0.0

10.0

20.0

30.0

40.0

50.0

60.0

1992

1993

1994

1995

1996

1997

1998

1999

2000

2001

2002

2003

2004

2005

2006

2007

2008

2009

2010

2011

2012

2013

No. of

pum

ps

Year of installation

No. of pumps

Cumulative pumps

% Annaul increase

102

The command area of Mithawan hill torrent is very fertile and produces high yield

of crops. The yield of various crops obtained by the farmers during the wet cropping year

(2012-13) and dry cropping year (2013-14) are shown in Table 4.21. The average yields

of cotton, wheat, onion, gram, sorghum, millet, brassica, arugula and guar cultivated by

the farmers in the study area were 2291, 3848, 20849, 1991, 1693, 1365, 813, 927 and

958kg/ha, respectively. Only one farmer cultivated sunflower crop but was unable to

respond the yield. While the average yields of cotton, wheat, gram, sorghum, millet,

brassica and guar obtained from other spate irrigated areas of the country were 490, 1078,

789, 455, 564, 760 and 692kg/ha, respectively (Steenbergen et al., 2008). The average

yields of crops obtained from other spate irrigated area of Pakistan was less than that of

the study area. In Pakistan, the overall yields of cotton, wheat, onion, gram, sorghum,

millet, brassica and rapeseed/mustard were 773, 2797, 12999, 487, 601, 634, 1040 and

914 kg/ha, respectively (Wasti, 2014), which were also less as compared to the yield of

crops obtained from the study area. The yields of sorghum, millet, gram, oilseeds and

wheat found by Ahmad and Choudhry (2005) in the study area were 565, 520, 576, 562

and 1230kg/ha, respectively. The results indicate that the yield of spate irrigated crops

had huge variation between 2005 and 2012-14. This difference in yield could be the result

of occurrence of hill torrent, its management and rainfall for subsequent irrigation water

requirement of the crops during the specific years. It means that the study area has great

agricultural production potential. If, hill torrents for spate irrigation are efficiently utilized

then more yield may be obtained than that of other irrigated areas of Pakistan. The

graphical presentation of yield comparison for various crops is given in Fig. 4.2.

Table 4.21: Yield of various crops cultivated in the study area

Crop No. of respondents Minimum

(kg/ha)

Maximum

(kg/ha)

Mean

(kg/ha)

Cotton 07 1483 2718 2291

Wheat 26 1977 4942 3848

Onion 11 12602 27181 20849

Gram 31 618 3954 1991

Sorghum 23 741 3954 1693

Millet 17 618 1977 1365

Brassica 11 247 1112 813

Arugula 02 741 1112 927

Guar 02 432 1483 958

103

Fig. 4.2: Comparison of crop yields cultivated in the study area

4.2 Sediment load in hill torrent flow

Heavy sediment load in hill torrent flow has been a major problem in its

management. It happens due to high velocity of hill torrent flow and drier catchment area.

The methodology given by Wren et al. (2000) was used to estimate the sediment load in

the flow of selected hill torrent. The sediment load found in the flow of hill torrent during

study period is given in Table 4.22. A sediment load of 100g/L was found in the channel

at upstream of command area, 60g/L at the middle and 30g/L at the tail of command area.

The sediment load was decreased with the length of torrent and found minimum at the tail

of command area. Ahmad (2003) reported that average sediment load measured in the

irrigated fields/bunds at different locations was about 34g/L, which is close to that

measured in the channel flowing through the tail of command area.

Table 4.22: Sediment load in the flow of hill torrent at different reaches of channel

Location of channel Volume of

sample (ml)

Wt. of

sediment (g)

Sediment load

(g/L)

At upstream of command area 1120 111.94 99.95

In the middle of command area 1095 65.10 59.45

At the tail of command area 650 18.97 29.18

4.3 Benefit cost ratio of the crops

Table 4.23 shows the results of farmers’ assessment on cost of production for

various crops cultivated in the study area. The cost of production of canal water and/or

groundwater irrigated crops was higher than that of irrigated with spate water. The total

cost of production included the cost of inputs, labor, machinery and cultural practices.

0

3000

6000

9000

12000

15000

18000

21000

Cro

p y

ield

, k

g/h

a

Crop

Average crop yield of study area

Overall yield of crops in Pakistan

104

The cost of production of cotton ranged from Rs. 0.094 to Rs. 0.122 million per hectare,

wheat Rs. 0.056 to Rs. 0.096 million per hectare, onion Rs. 0.213 to Rs. 0.361 million per

hectare, gram Rs. 0.027 to Rs. 0.063 million per hectare, sorghum Rs. 0.018 to Rs. 0.046

million per hectare, millet Rs. 0.018 to Rs. 0.033 million per hectare, brassica Rs. 0.013

to Rs. 0.034 million per hectare, arugula Rs. 0.020 to Rs. 0.027 million per hectare and

guar Rs. 0.020 to Rs. 0.068 million per hectare. The average cost of production was

assessed as; cotton Rs. 0.105, wheat Rs. 0.078, onion Rs. 0.297, gram Rs. 0.040, sorghum

Rs. 0.029, millet Rs. 0.025, brassica Rs. 0.024, arugula Rs. 0.024 and guar Rs. 0.044

million per hectare. The investment on canal water and/or groundwater irrigated crops

was higher than that of spate irrigated crops.

Table 4.23: Investment of the farmers for cultivation of crops

Crop No. of

respondents

Minimum

(Million Rs./ha)

Maximum

(Million Rs./ha)

Mean

(Million Rs./ha)

Cotton 07 0.094 0.122 0.105

Wheat 26 0.056 0.096 0.078

Onion 11 0.213 0.361 0.297

Gram 31 0.027 0.063 0.040

Sorghum 23 0.018 0.046 0.029

Millet 17 0.018 0.033 0.025

Brassica 11 0.013 0.034 0.024

Arugula 02 0.020 0.027 0.024

Guar 02 0.020 0.068 0.044

Table 4.24 shows the income from the crops cultivated in the study area. Income

from the crops varied from about Rs. 0.093 to Rs. 0.164 million per hectare for cotton,

Rs. 0.058 to Rs. 0.156 million per hectare wheat, Rs. 0.265 to Rs. 0.625 million per

hectare onion, Rs. 0.018 to Rs. 0.156 million per hectare gram, Rs. 0.039 to Rs. 0.157

million per hectare sorghum, Rs. 0.015 to Rs. 0.065 million per hectare millet, Rs. 0.015

to Rs. 0.081 million per hectare brassica, Rs. 0.028 to Rs. 0.044 million per hectare

arugula and Rs. 0.026 to Rs. 0.212 million per hectare for guar. The average income from

crops obtained by the farmers of study area were cotton Rs. 0.136, wheat Rs. 0.116, onion

Rs. 0.468, gram Rs. 0.079, sorghum Rs. 0.070, millet Rs. 0.041, brassica Rs. 0.042,

arugula Rs. 0.036 and guar Rs. 0.119 million per hectare. High income from the guar was

due to high price of guar grain in the international market during 2012. Generally, the

farmers of study area obtained high income from gram crop cultivated by the spate

irrigation. Graphical comparison of the cost of production and income for various crops at

the study area is given in Fig. 4.3.

105

Table 4.24: Income from the crops cultivated in the study area

Crop No. of

respondents

Minimum

(Million Rs. /ha)

Maximum

(Million Rs. /ha)

Mean

(Million Rs. /ha)

Cotton 07 0.093 0.164 0.136

Wheat 26 0.058 0.156 0.116

Onion 11 0.265 0.625 0.468

Gram 31 0.018 0.156 0.079

Sorghum 23 0.039 0.157 0.070

Millet 17 0.015 0.065 0.041

Brassica 11 0.015 0.081 0.042

Arugula 02 0.028 0.044 0.036

Guar 02 0.026 0.212 0.119

Fig. 4.3: Comparison of the cost of production with total income from the crop

The Benefit Cost Ratio (BCR) of crops cultivated in the study area is given in

Table 4.25. The BCR of cotton, wheat, onion, gram, sorghum, millet, brassica, arugula

and guar were 1.29, 1.50, 1.57, 2.00, 2.39, 1.63, 1.67, 1.49 and 2.22, respectively. The

crops cultivated using canal water and/or groundwater had less BCR than that of the crops

cultivated by the spate irrigation. The maximum BCR of guar was due to high prices of

guar grains during the study period but normally the BCR of gram remained higher than

that of other crops. Therefore, the gram crop was considered a major valuable crop of

study area cultivated by the spate irrigation.

050000

100000150000200000250000300000350000400000450000500000

Rs.

/ha

Crop

Cost of productionTotal income from the crop

106

Table 4.25: Benefit Cost Ratio of the crops in Mithawan hill torrent command area

Crops No. of respondents Minimum Maximum Mean

Cotton 07 0.98 1.51 1.29

Wheat 26 0.98 2.21 1.50

Onion 11 1.05 2.01 1.57

Gram 31 0.65 4.62 2.00

Sorghum 23 1.57 3.43 2.39

Millet 17 0.71 2.31 1.63

Brassica 11 0.98 2.40 1.67

Arugula 02 1.40 1.59 1.49

Guar 02 1.30 3.14 2.22

4.4 Contribution of irrigation water sources to crop water requirement

The volume of water applied to the crops through groundwater and canal water

supplies as given in Table 4.26. The quantity of water applied to the wheat crop ranged

from about 1837m3/ha to 9264m3/ha, cotton 4409m3/ha to 15430m3/ha, onion 2202m3/ha

to 14293m3/ha, sunflower 5189m3/ha to 5691m3/ha, tobacco 5604m3/ha to 5871m3/ha,

maize 3717m3/ha to 7348m3/ha and fodder 3306m3/ha to 10270m3/ha. However, the

average volumes of water applied to the crops were as; wheat about 4787m3/ha, cotton

8493m3/ha, onion 6361m3/ha, sunflower 5429m3/ha, tobacco 5738m3/ha, maize

5533m3/ha and fodder 6082m3/ha. The results indicate that the volume of water applied to

cotton crop was more than the other crops, which was mainly due to lengthy growing

period as well as hot climatic conditions of the season.

Table 4.26: Volume of water applied to the crops

Crop No. of respondents Minimum

(m3/ha)

Maximum

(m3/ha)

Mean

(m3/ha)

Wheat 46 1836.94 9264.32 4786.69

Cotton 22 4408.66 15430.31 8493.37

Onion 22 2201.66 14293.45 6360.92

Sunflower 03 5189.47 5690.96 5429.05

Tobacco 02 5604.23 5871.10 5737.66

Maize 02 3717.47 7347.77 5532.62

Fodder 26 3306.50 10269.97 6081.85

The quantity of water applied to crops as given in Table 4.26 included the

groundwater and canal water, whereas the total water available may include effective

rainfall as well. Table 4.27 shows the total volume of water applied to the canal water

and/or groundwater irrigated crops in the study area. The total water available to the

wheat, cotton, onion, sunflower, tobacco, maize and fodder were 5212, 9860, 7569, 5896,

6322, 6295 and 6926m3/ha, respectively.

107

Table 4.27: Total volume of water available to the crops

Crop Canal water

(m3/ha)

Groundwater

(m3/ha)

Effective rainfall

(m3/ha)

Total

(m3/ha)

Wheat 1266.08 3520.62 424.86 5211.56

Cotton 4008.03 4485.35 1366.25 9859.63

Onion 1252.47 5108.46 1208.24 7569.16

Sunflower 2571.75 2857.31 466.71 5895.77

Tobacco 0.00 5871.10 451.16 6322.26

Maize 3673.66 1858.96 762.86 6295.48

Fodder 1060.07 5021.79 844.31 6926.16

The total water available to crops was utilized to assess the relative contribution of

available sources of irrigation. Table 4.28 gives the detail of percentage of water applied

through different sources to the crops cultivated through canal water and/or groundwater

in the study area. However, the mean relative contribution of canal water, groundwater

and direct rainfall to crop water requirement was 28, 61 and 11%, respectively. The

results indicate that the maximum crop water requirement was satisfied by the

groundwater irrigation. If, hill torrent water is not efficiently utilized for spate irrigation,

in future, the current rate of groundwater abstraction would lower the watertable to a

serious level. Therefore, to avoid the decline of watertable in study area, there is dire need

to efficiently utilize the hill torrent water for spate irrigation.

Table 4.28: Water applied to the crops through different sources

Crop Canal water (%) Groundwater (%) Rainfall (%)

Wheat 24 68 08

Cotton 41 45 14

Onion 17 67 16

Sunflower 44 48 08

Tobacco 00 93 07

Maize 58 30 12

Fodder 15 73 12

Overall average 28 61 11

4.5 Irrigation application efficiency

Generally, the farmers of Mithawan hill torrent command area had a number of

problems while applying water into their fields. Some of those problems include high cost

of diversion structures, field leveling and high running cost of groundwater irrigation

pumps. Farmers apply more irrigation water to crops than the requirement. The over

irrigation tends to increase the cost of production as well as salts concentration in root

zone. On the other hand, application of the required amount of water to crops decreases

farmers’ problems regarding cost of production, minimize salt concentration in root zone

108

and play important role in maintaining the balance watertable. The amount of water

required by the crops cultivated in the study area during a wet and dry year is as given in

Table 4.29. The amount of water required for wheat crop excluding effective rainfall was

1794m3/ha, cotton 6471m3/ha, onion 2909m3/ha, sunflower 4677m3/ha, tobacco

3229m3/ha, maize 1314m3/ha and fodder 2490m3/ha.

Table 4.29: Water requirement of crops cultivated in the study area, (m3/ha)

Crop

Rabi

season,

2012-13

Kharif

season,

2013

Rabi

season,

2013-14

Kharif

season,

2014

Average

Wheat 1791 - 1797 - 1794.0

Cotton - 6099 - 6843 6471.0

Onion 2687 - 3130 - 2908.5

Sunflower 4794 - 4559 - 4676.5

Tobacco 3493 - 2964 - 3228.5

Maize - 915 - 1712 1313.5

Fodder

Barley, oat (Rabi) 1933 - 1960 - 1946.5

Berseem/lucerne (Rabi) 2881 - 2697 - 2789.0

Sorghum (Kharif) - 2487 - 2983 2735.0

Average (fodder) 2490.2

Irrigation efficiency of a farm represents the beneficial use of water delivered

from irrigation system to the field. The amount of water lost or saved by the farmers of

study area in contrast with recommended efficiencies described by the FAO in “Irrigation

Water Management: Irrigation Scheduling Training Manual No. 4” is given in Table 4.30.

The irrigation efficiency of the study area was 37, 76, 46, 86, 56, 24 and 41% for wheat,

cotton, onion, sunflower, tobacco, maize and fodder, respectively, with an overall farm

irrigation efficiency of 52%. Twenty percent of water to be applied to the crop was lost

due to over irrigation of wheat, 90% for maize and 10% for fodder. Similarly, 41% of the

water to be applied to the crop was saved due to under irrigation of cotton, 2% in onion,

48% in sunflower and 20% in tobacco cultivation. The loss of water was found in basin

method of irrigation while saving was found in crops, which were cultivated by furrow

method of irrigation. Thus, it was concluded that the farmers lost water in basin method

but saved in furrow method of irrigation.

109

Table 4.30: Irrigation efficiency (distribution and application) in the study area

Crop

Irrigation

required

(m3/ha)

Irrigation

applied

(m3/ha)

Irrigation

efficiency

(%)

Irrigation to

be applied

(m3/ha)

Irrigation

adequacy

(%)

Wheat 1794 4787 37 3987 +20

Cotton 6471 8493 76 14380 -41

Onion 2909 6361 46 6463 -02

Sunflower 4677 5429 86 10392 -48

Tobacco 3229 5738 56 7174 -20

Maize 1314 5533 24 2919 +90

Fodder 2490 6082 41 5534 +10

4.6 Water productivity of crops

The water productivity of hill torrent/spate irrigated crops was compared with

canal water and/or groundwater irrigated crops. The results of water productivity of crops

cultivated in the study area are given in Table 4.31. The water productivity of canal water

and/or groundwater irrigated crops namely; onion, cotton and wheat were 3.28, 0.27 and

0.80kg/m3, respectively. More water productivity of onion was mainly due to high yield

not because of the efficient use of irrigation. While, all spate irrigated crops namely;

gram, sorghum, millet, brassica, arugula and guar had water productivity of 0.19, 0.16,

0.13, 0.08, 0.09 and 0.09kg/m3, respectively. The low water productivity of spate irrigated

crops was due to excessive ponding (0.61-1.68m) in case of spate water and low yield

than potential due to various stresses during crop growth period. The water productivity

of spate irrigated crops can be increased by applying only required amount of water and

conserving moisture in the field for long time. Thus, there is need to determine the depth

of water to be applied to the bund for efficient use of spate water, improve water

productivity and bring more area under cultivation.

Table 4.31: Water productivity of crops cultivated in the study area

Crop Yield

(kg/ha)

Volume of water applied

(m3/ha)

Water productivity

(kg/m3)

Cotton 2291 8493 0.27

Wheat 3848 4787 0.80

Onion 20849 6361 3.28

Gram 1991 10475 0.19

Sorghum 1693 10475 0.16

Millet 1365 10475 0.13

Brassica 813 10475 0.08

Arugula 927 10475 0.09

Guar 958 10475 0.09

110

The results given in Table 4.25 and Table 4.31 shows that the benefit cost ratio of

spate irrigated crops were more than canal water and/or groundwater irrigated while, the

water productivity of spate irrigated crops were less than canal water and/or groundwater

irrigated crops. If water productivity of spate irrigated crops is improved then more

income may be generated through spate irrigation than canal water and/or groundwater

irrigation.

4.7 Impact of irrigation applications on soil physical properties

This section of study shows the comparative impact of hill torrent and

groundwater irrigation application on soil properties of selected hill torrent command

area. Table 4.32 shows minimum, maximum and average values of different quality

parameters of Mithawan hill torrent irrigation water. The average value of EC was

0.61dS/m while the value for pH was 8.16, Na was 2.12me/L, Ca+Mg was 4.02me/L, Cl

was 1.80me/L, CO3 was 0.39me/L, HCO3 was 2.90me/L, SAR was 1.50 and RSC was

0.00me/L.

Table 4.33 shows the results of quality parameters of groundwater of the study

area. It was found that the average value of EC was 1.59dS/m, pH was 8.12, Na was

4.14me/L, Ca+Mg was 10.05me/L, Cl was 4.77me/L, CO3 was 0.68me/L, HCO3, was

6.31me/L, SAR was 1.90 and RSC was 0.00me/L. The quality parameters of hill torrent

water as well as groundwater of the study area show that both the waters were fit for

irrigation with minor differences. The water quality parameters of hill torrent and

groundwater irrigation waters as given in the Table 4.18 and Table 4.19 indicate that

50% of the groundwater was fit for irrigation and 50% unfit while, hill torrent irrigation

water was found 100% fit for irrigation. Therefore, the application of unfit and marginally

fit groundwater irrigation in selected hill torrent command area caused undesired impact

on soil properties.

111

Table 4.32: Water quality analysis of Mithawan hill torrent flow

Quality parameter No. of sample Min. Max. Mean

EC (dS/m) 6 0.48 0.73 0.61

pH 6 7.91 8.34 8.16

Na (me/L) 6 1.67 2.67 2.12

Ca+Mg (me/L) 6 3.42 4.34 4.02

Cl (me/L) 6 1.04 2.10 1.80

CO3 (me/L) 6 0.00 1.00 0.39

HCO3 (me/L) 6 2.14 3.90 2.90

SAR 6 1.13 1.83 1.50

RSC (me/L) 6 0.00 0.00 0.00

Table 4.33: Quality analysis of groundwater

Quality parameter No. of samples Min. Max. Mean

EC (dS/m) 12 0.62 3.50 1.59

pH 12 7.03 8.54 8.12

Na (me/L) 12 1.02 8.00 4.14

Ca+Mg (me/L) 12 5.22 20.90 10.05

Cl (me/L) 12 0.70 8.14 4.77

CO3 (me/L) 12 0.00 1.20 0.68

HCO3 (me/L) 12 3.80 16.38 6.31

SAR 12 0.53 3.80 1.90

RSC (me/L) 12 0.00 0.00 0.00

The minimum, maximum and mean values of EC of fields irrigated by the hill

torrent and groundwater application for sample depth are given in Table 4.34. The Mean

values of EC of samples at 0-15cm, 15-30cm and 30-45cm depth of fields irrigated by hill

torrent water were 0.84dS/m, 0.77dS/m and 0.82dS/m, respectively. The mean values of

EC for groundwater irrigated fields were 1.25dS/m, 1.21dS/m and 1.17dS/m for 0-15cm,

15-30cm and 30-45cm depth of soil samples, respectively. The comparison of results as

shown in Fig. 4.4 indicates that the EC of fields irrigated with the hill torrent flow at each

sample depth were close to the ideal value i.e. 0.75dS/m but the value was relatively

higher for the fields where irrigation was applied with the groundwater. Similarly, the

comparison of EC mapping of study area as shown in Fig. 4.5 indicates that the extent of

area ideally fit for cultivation (up to 0.75dS/m) was very little in the groundwater

irrigated field, while more for hill torrent irrigated field. The rest of the area of all hill

torrent irrigation was within the mapping class of 0.75 – 1.08dS/m, which is considered

good for cultivation while the extent of area under this class was low in case of

groundwater irrigation system. The large area of groundwater irrigation was under the

112

map class of 1.08 – 1.79dS/m and there was no area under this class in hill torrent

irrigation system.

The groundwater irrigated fields in this study were not always irrigated with the

groundwater but whenever, the farmers found an opportunity, they irrigated their fields

with hill torrent water. In case, the farmers are unable to manage the hill torrent irrigation

or continuously use groundwater for irrigation, the EC of fields may rapidly increase to

hazardous level and cultivation of crops may be negatively affected.

Table 4.34: EC of fields irrigated by the hill torrent and groundwater

Source of irrigation Sample depth (cm) No. of

sample

Min.

(dS/m)

Max.

(dS/m)

Mean

(dS/m)

Hill torrent

0-15 12 0.49 1.18 0.84

15-30 12 0.27 0.99 0.77

30-45 12 0.24 1.40 0.82

Groundwater

0-15 12 0.37 1.85 1.25

15-30 12 0.39 1.81 1.21

30-45 12 0.38 1.70 1.17

Fig. 4.4: EC comparison of hill torrent and groundwater irrigated field

0.00

0.20

0.40

0.60

0.80

1.00

1.20

1.40

0-15 15-30 30-45

EC

(dS

/m)

Depth of Soil Sample (cm)

Hill Torrent Irrigated Fields Groundwater Irrigated Fields

113

(a) (b)

Fig. 4.5: EC map of hill torrent (a) and groundwater (b) irrigated fields

The pH of soil is an important indicator of its salinity and shows either the soil is

acidic or basic in qualities. The minimum, maximum and mean values of soil pH for

study area are given in Table 4.35 and its graphical comparison between hill torrent and

groundwater irrigated fields is shown in Fig. 4.6. The average values of pH for hill torrent

irrigated fields were 7.64, 7.76 and 7.78 at 0-15cm, 15-30cm and 30-45cm depth of soil,

respectively. However, in contrast, groundwater irrigated fields pH were found 8.20, 8.18

and 8.31 for 0-15cm, 15-30cm and 30-45cm depth of soil, respectively, which was

relatively higher as compared to the hill torrent irrigated fields. Similarly, the comparison

of pH maps of hill torrent and groundwater irrigation as shown in Fig. 4.7 indicate that if

fields are irrigated by hill torrent flow the pH of the whole study area falls in the

range/class 7.5 – 8.0. Whereas, the pH map of groundwater irrigation shows that a little

area falls in the range 7.5 to 8.0 while the rest of the area falls in the range/class 8.0 – 8.5.

Thus it was concluded that pH of all the hill torrent irrigated fields were normal but

groundwater irrigated fields were found at initial level of alkalinity. It may be due to more

concentration of Na in groundwater of the study area as compared to the concentration of

Na in the hill torrent water. Therefore, the continuously application of groundwater for

irrigation may further deteriorate the soil fertility and quality.

114

Table 4.35: pH of fields irrigated by the hill torrent and groundwater

Source of irrigation Sample depth

(cm)

No. of

sample Min. Max. Mean

Hill torrent

0-15 12 7.30 7.78 7.64

15-30 12 7.60 7.98 7.76

30-45 12 7.67 7.97 7.78

Groundwater

0-15 12 7.80 8.45 8.20

15-30 12 7.95 8.31 8.18

30-45 12 7.84 8.70 8.31

Fig. 4.6: pH comparison of hill torrent and groundwater irrigated fields

(a) (b)

Fig. 4.7: pH map of hill torrent (a) and groundwater (g) irrigated fields

7.20

7.40

7.60

7.80

8.00

8.20

8.40

0-15 15-30 30-45

pH

Depth of Soil Samples (cm)Hill Torrent Irrigated Fields Groundwater Irrigated Fields

115

Table 4.36 shows the concentration of Na present in the soils of the command area

of selected hill torrent and its comparison between hill torrent and groundwater irrigated

fields. The results are graphically shown in Fig. 4.8. Sodium was found to vary with

depth. The mean value of concentration of Na was found 2.45me/L at 0-15cm of soil

depth, 3.20me/L at 15-30cm depth of soil and 1.66me/L from 30-45cm depth of soil

samples at hill torrent irrigated fields. The average concentrations of Na in groundwater

irrigated fields were 9.61me/L from 0-15cm depth of soil, 7.99me/L from 15-30cm depth

and 8.56me/L from 30-45cm depth of fields.

Fig. 4.9 shows the comparison of Na concentrations as affected by hill torrent and

groundwater irrigation in the study area. The concentration of sodium in the study area

due to hill torrent irrigation was observed in the range of 1.21 – 4.12me/L. A very low

part of the study area had this range as a result of groundwater irrigation. The map

indicates high concentration of Na from 4.16 – 15.96me/L due to groundwater irrigation,

which was far greater than hill torrent irrigation of the study area. This indicates that the

sodium concentration in study area may further increase if groundwater is continuously

applied. This may cause dispersion of soil particles, deteriorate soil structure, decrease

infiltration rate and produce toxicity for the plants and resultantly, crops cannot be grown

successfully to get higher yield.

Table 4.36: Na analysis of fields irrigated by the hill torrent and groundwater


(cm)

No. of

samples

Min.

(me/L)

Max.

(me/L)

Mean

(me/L)

Hill torrent

0-15 12 0.37 5.49 2.45

15-30 12 1.33 8.03 3.20

30-45 12 0.36 3.17 1.66

Groundwater

0-15 12 2.30 15.83 9.61

15-30 12 0.36 15.96 7.99

30-45 12 1.39 16.10 8.56

116

Fig. 4.8: Concentration of Na in hill torrent and groundwater irrigated fields

(a) (b)

Fig. 4.9: Na map of hill torrent (a) and groundwater (b) irrigated fields

The spatial variation of Ca+Mg concentration in the study area is given in Table

4.37. A comparison of Ca+Mg between hill torrent and groundwater irrigated fields is

shown in Fig. 4.10. The average concentration of Ca+Mg was found 4.94me/L at 0-15cm

depth of soil, 5.11me/L at 15-30cm depth and 4.12me/L from 30-45cm depth of soil

samples at hill torrent irrigated fields. Whereas, the average results of Ca+Mg in

groundwater irrigated fields were 6.74me/L from 0-15cm depth of soil, 7.31me/L from

15-30cm depth and 7.37me/L from 30-45cm depth of fields. The results indicate that the

concentration of Ca+Mg in groundwater irrigated fields were higher than hill torrent

irrigated fields.

0.00

2.00

4.00

6.00

8.00

10.00

12.00

0-15 15-30 30-45

Na

(me/

L)

Depth of Soil Samples (cm)


117

Table 4.37: Ca+Mg analysis of fields irrigated by the hill torrent and groundwater


(cm)

No. of

sample

Min.

(me/L)

Max.

(me/L)

Mean

(me/L)

Hill torrent

0-15 12 2.85 7.10 4.94

15-30 12 3.20 10.92 5.11

30-45 12 3.02 6.50 4.12

Groundwater

0-15 12 3.35 9.65 6.74

15-30 12 1.70 12.16 7.31

30-45 12 3.55 10.52 7.37

Fig. 4.10: Concentration of Ca+Mg in hill torrent and groundwater irrigated fields

Soil analysis indicated that the minimum and maximum concentration of Cl in

Mithawan hill torrent command area was as given in Table 4.38 and comparison between

hill torrent and groundwater irrigated fields is shown in Fig. 4.11. The average

concentration of Cl was found as 4.18me/L at 0-15cm depth of soil, 3.98me/L at 15-30cm

depth and 3.16me/L from 30-45cm depth of soil samples at hill torrent irrigated fields.

The average values of Cl concentration in groundwater irrigated fields were 8.13me/L

from 0-15cm depth of soil, 7.61me/L from 15-30cm depth and 6.76me/L from 30-45cm

depth of fields. The results indicated that concentration of Cl in groundwater irrigated

fields was higher than that in the hill torrent irrigated fields.

0.00

1.00

2.00

3.00

4.00

5.00

6.00

7.00

8.00

0-15 15-30 30-45

Ca+

Mg (

me/

L)

Depth of Soil Samples (cm)


118

Table 4.38: Cl analysis of fields irrigated by the hill torrent and groundwater


(cm)

No. of

sample

Min.

(me/L)

Max.

(me/L)

Mean

(me/L)

Hill torrent

0-15 12 0.70 6.70 4.18

15-30 12 2.16 6.70 3.98

30-45 12 1.52 5.00 3.16

Groundwater

0-15 12 3.64 15.88 8.13

15-30 12 1.00 21.76 7.61

30-45 12 2.20 13.00 6.76

Fig. 4.11 Concentration of Cl in hill torrent and groundwater irrigated fields

Table 4.39 shows that there was no CO3 found in any of the tested soil samples

collected from hill torrent or groundwater irrigated fields.

Table 4.39: CO3 analysis of fields irrigated by the hill torrent and groundwater


(cm)

No. of

sample

Min.

(me/L)

Max.

(me/L)

Mean

(me/L)

Hill torrent

0-15 12 0.00 0.00 0.00

15-30 12 0.00 0.00 0.00

30-45 12 0.00 0.00 0.00

Groundwater

0-15 12 0.00 0.00 0.00

15-30 12 0.00 0.00 0.00

30-45 12 0.00 0.00 0.00

Generally, all of the soil samples indicated presence of HCO3. The results of

minimum, maximum and average values of HCO3 are given in the Table 4.40 and a

comparison between hill torrent and groundwater irrigated fields is shown in the Fig.

4.12. The average concentration of HCO3 was found 2.51me/L at 0-15cm depth of soil,

0.00

1.00

2.00

3.00

4.00

5.00

6.00

7.00

8.00

9.00

0-15 15-30 30-45

Cl,

me/

L

Depth of Soil Samples, cm


119

2.64me/L at 15-30cm depth and 1.99me/L from 30-45cm depth of soil samples at hill

torrent irrigated fields. The average results of HCO3 in groundwater irrigated fields were

5.94me/L from 0-15cm depth of soil, 5.94me/L from 15-30cm depth and 5.71me/L from

30-45cm depth of fields. The results indicated that the concentration of HCO3 in

groundwater irrigated fields was higher than that in the hill torrent irrigated fields.

Table 4.40: HCO3 analysis of fields irrigated by the hill torrent and groundwater


(cm)

No. of

sample

Min.

(me/L)

Max.

(me/L)

Mean

(me/L)

Hill torrent

0-15 12 1.74 3.54 2.51

15-30 12 1.22 6.98 2.64

30-45 12 1.54 3.08 1.99

Groundwater

0-15 12 2.00 9.76 5.94

15-30 12 0.90 10.96 5.94

30-45 12 2.00 9.67 5.71

Fig. 4.12 Concentration of HCO3 in hill torrent and groundwater irrigated fields

The results of minimum and maximum SAR of the soil samples are given in Table

4.41 and a comparison between hill torrent and groundwater irrigated fields is shown in

Fig. 4.13. The average SAR was found 1.56 at 0-15cm depth of soil, 2.00 at 15-30cm

depth and 1.18 from 30-45cm depth of soil samples at hill torrent irrigated fields.

Whereas, average results of SAR in groundwater irrigated fields were 5.29 from 0-15cm

depth of soil, 4.02 from 15-30cm depth and 4.42 from 30-45cm depth of fields. The GIS

map comparison of SAR between hill torrent and groundwater irrigation is shown in the

Fig. 4.14. The fields irrigated with hill torrent irrigation system have only SAR class from

0.00

1.00

2.00

3.00

4.00

5.00

6.00

7.00

0-15 15-30 30-45

HC

O3, m

e/L

Depth of Soil Samples, cm


120

0.91 – 2.38, while a little part of the field(s) irrigated by the groundwater was under this

class. However, the maximum number of fields irrigated by the groundwater had SAR

from 2.39 – 8.08. The SARs for hill torrent irrigated fields were less than groundwater

irrigated fields but in both cases it was less than 10, which was considered safe limit for

the cultivation.

Table 4.41: SAR analysis of fields irrigated by hill torrent and groundwater


(cm)

No. of

sample Min. Max. Mean

Hill torrent

0-15 12 0.28 3.48 1.56

15-30 12 0.77 5.25 2.00

30-45 12 0.26 1.98 1.18

Groundwater

0-15 12 1.61 9.09 5.29

15-30 12 0.39 7.96 4.02

30-45 12 0.95 7.19 4.42

Fig. 4.13 Comparison of SAR of hill torrent and groundwater irrigated fields

0.00

1.00

2.00

3.00

4.00

5.00

6.00

0-15 15-30 30-45

SA

R

Depth of Soil Samples, cmHill Torrent Irrigated Fields Groundwater Irrigated Fields

121

(a) (b)

Fig. 4.14: SAR of hill torrent (a) and groundwater (b) irrigated fields

Table 4.42 shows the RSC of hill torrent and groundwater irrigated fields of the

study area. Accordingly, RSC of hill torrent irrigated fields remained zero at various

sampling depths, while RSC for groundwater irrigated fields was as given in the table

4.43 with an average values of 0.16, 0.06 and 0.13 for 0-15cm, 15-30cm and 30-45cm

depth of soil, respectively.

Table 4.42: RSC of fields irrigated by the hill torrent and groundwater


(cm)

No. of

samples

Min.

(me/L)

Max.

(me/L)

Mean

(me/L)

Hill torrent

0-15 12 0.00 0.00 0.00

15-30 12 0.00 0.00 0.00

30-45 12 0.00 0.00 0.00

Groundwater

0-15 12 0.00 0.98 0.16

15-30 12 0.00 0.66 0.06

30-45 12 0.00 1.47 0.13

122

4.8 Groundwater fluctuation

The watertable data collected during the study period as given in Appendix-E

shows that the water level of all observation wells raised during the period from April to

September and dropped during the period from October through March each year.

Generally, during the months from April to September less cultivation, more rainfall and

hill torrent occurrence, and full supply of water in the DG Canal was observed, which

raised the groundwater level of the study area. While, during the period from October to

March, there was more cultivation, less rainfall and hill torrent occurrence, low/no flow

of water in the DG Canal, and more groundwater pumping for irrigation of the study area.

Considering the existing groundwater conditions, the MODFLOW model was run for a

period from June 01, 2014 to May 31, 2024, with the simulation length consisting of 20

stress periods under different scenarios.

4.8.1 Simulation of existing pattern (Scenario-I)

Under this scenario, the water level fluctuation of the study area was predicted by

the calibrated model keeping the groundwater abstraction, and spatial recharge due to

rainfall, hill torrent (that vary every year) and field level irrigation constant up to the year

2024. Fig. 4.15 shows the model predicted result of an observation well No.1. This

observation well was located at a distance of about 0.65km at right bank of DG Canal and

hydraulically connected with it. Normally, the water level of this well was low at the time

of canal closure and high at the time of canal flow at its full supply. Therefore, the water

level of this OW-1 fluctuated greatly with the flow of canal. The area adjacent to right

bank of canal was mainly irrigated by the canal water lift irrigation. The groundwater was

pumped only during the canal closure days. The decline in groundwater level was

replenished by the canal. However, the model predicted a decline of water level at the rate

of about 1.78m/simulation period (10 years) for this observation well.

123

Fig. 4.15: Predicted groundwater head for an OW No. 1 under the Scenario-I

Fig. 4.16 shows the predicted water level for an observation well No. 2. It was

located at a distance of about 1.9km on right bank of DG Canal. Only few farmers of this

zone used canal water lift irrigation and most of them applied groundwater for crops

irrigation. However, the model predicted water level of this well was at the rate of about

2.56m/simulation period (10 years).


Fig. 4.17 shows the predicted water level for an observation well No. 3. It was

located at a distance of about 2.75km on right bank of DG Canal. Only few farmers of

this area used canal water lift irrigation and most of them applied groundwater for crops

irrigation. However the model predicted water level of this well was at the rate of about


102

104

106

108

110

112

114

116

Dec

, 2014

Jun, 2015

Dec

, 2015

Jun, 2016

Dec

, 2016

Jun, 2017

Dec

, 2017

Jun

, 20

18

Dec

, 2018

Jun, 2019

Dec

, 2019

Jun, 2020

Dec

, 2020

Jun, 2021

Dec

, 2021

Jun, 2022

Dec

, 2022

Jun

, 20

23

Dec

, 2023

Jun, 2024

Gro

undw

ater

hea

d, m

Time period

102

104

106

108

110

112

114

116

Dec

, 20

14

Jun, 20

15

Dec

, 20

15

Jun, 20

16

Dec

, 20

16

Jun, 20

17

Dec

, 20

17

Jun, 20

18

Dec

, 20

18

Jun, 20

19

Dec

, 20

19

Jun, 20

20

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, 20

20

Jun, 20

21

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, 20

21

Jun, 20

22

Dec

, 20

22

Jun, 20

23

Dec

, 20

23

Jun, 20

24

Gro

undw

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hea

d, m

Time period

124


The observation well No. 4 was located at a distance of about 2.5km away from

right bank of DG Canal. Fig. 4.18 shows the predicted hydrograph of water level at this

point and its water level will decline at the rate of about 4m/simulation period (10 years).


The observation well No.5 was located at a distance of about 4.3km away from

right bank of DG Canal. At this point all of the farmers cultivated crops with groundwater

irrigation application but the cultivation at this site was quite less. Fig. 4.19 shows the

predicted hydrograph of water level of this well and its water level of this zone will

decline at the rate of about 3.91m/simulation period.

102

104

106

108

110

112

114

116

Dec

, 2014

Jun, 2015

Dec

, 2015

Jun, 2016

Dec

, 2016

Jun, 2017

Dec

, 2017

Jun, 2018

Dec

, 2018

Jun, 2019

Dec

, 2019

Jun, 2020

Dec

, 2020

Jun, 2021

Dec

, 2021

Jun, 2022

Dec

, 2022

Jun

, 20

23

Dec

, 2023

Jun

, 20

24

Gro

undw

ater

hea

d, m

Time period

102

104

106

108

110

112

114

116

Dec

, 2014

Jun,

2015

Dec

, 2015

Jun, 2016

Dec

, 2016

Jun, 2017

Dec

, 2017

Jun, 2018

Dec

, 2018

Jun, 2019

Dec

, 2019

Jun, 2020

Dec

, 2020

Jun, 2021

Dec

, 2021

Jun, 2022

Dec

, 2022

Jun, 2023

Dec

, 2023

Jun, 2024

Gro

undw

ater

hea

d, m

Time period

125


Fig. 4.20 shows the predicted water level (hydrograph) for an observation well

No. 6. It was located at a distance of about 3.5km on right bank of DG Canal. Only few

farmers of this area used canal water lift irrigation and most of them applied groundwater

for crops irrigation. However, the model predicted water level of this well that its water

level will decline at the rate of about 4.03m/simulation period. The maximum drop in

water level at this observation well is due to more cultivation at this location.


Fig. 4.21 shows the predicted water level (hydrograph) for an observation well

No. 7. It was located at a distance of about 6km on right bank of DG Canal. None of the

farmer of this location used canal water lift irrigation and total cultivation at this point

102

104

106

108

110

112

114

116

Dec

, 2014

Jun, 2015

Dec

, 2015

Jun, 2016

Dec

, 2016

Jun, 2017

Dec

, 2017

Jun

, 20

18

Dec

, 2018

Jun, 2019

Dec

, 2019

Jun, 2020

Dec

, 2020

Jun, 2021

Dec

, 2021

Jun, 2022

Dec

, 2022

Jun, 2023

Dec

, 2023

Jun, 2024

Gro

undw

ater

hea

d, m

Time period

102

104

106

108

110

112

114

116

Dec

, 2014

Jun, 2015

Dec

, 2015

Jun, 2016

Dec

, 2016

Jun, 2017

Dec

, 2017

Jun, 2018

Dec

, 2018

Jun, 2019

Dec

, 2019

Jun, 2020

Dec

, 2020

Jun, 2021

Dec

, 2021

Jun, 2022

Dec

, 2022

Jun, 2023

Dec

, 2023

Jun, 2024

Gro

undw

ater

hea

d, m

Time period

126

was through groundwater irrigation. The model predicted that the water level of this well

will drop at the rate of about 3.31m/10years of simulation period.


Fig. 4.22 shows the predicted water level (hydrograph) of an observation well No.

8. It was located at a distance of about 5km on right bank of DG Canal. None of the

farmer of this location used canal water lift irrigation and total cultivation in this area was

through groundwater irrigation. The pumping at this point was low than OW No. 7.

Therefore, the model predicted that the water level of this well will decline at the rate of

about 2.46m/simulation period.


102

104

106

108

110

112

114

116

Dec

, 2014

Jun, 2015

Dec

, 2015

Jun, 2016

Dec

, 2016

Jun, 2017

Dec

, 2017

Jun, 2018

Dec

, 2018

Jun, 2019

Dec

, 2019

Jun, 2020

Dec

, 2020

Jun, 2021

Dec

, 2021

Jun, 2022

Dec

, 2

022

Jun, 2023

Dec

, 2023

Jun, 2024

Gro

undw

ater

hea

d, m

Time period

102

104

106

108

110

112

114

116

Dec

, 2014

Jun, 2015

Dec

, 2015

Jun, 2016

Dec

, 2016

Jun, 2017

Dec

, 2017

Jun, 2018

Dec

, 2018

Jun, 2019

Dec

, 2019

Jun, 2020

Dec

, 2020

Jun, 2021

Dec

, 2021

Jun, 2022

Dec

, 2022

Jun, 2023

Dec

, 2023

Jun, 2024

Gro

undw

ater

hea

d, m

Time period

127

Fig. 4.23 shows the predicted water level (hydrograph) of an observation well No.

9. It was located at a distance of about 8.5km on right bank of DG Canal. None of the

farmer of this location could use canal water lift irrigation. The water level at this point

was at greater depth and hence it was not economical for the farmers to use groundwater

irrigation. Only 2 farmers surrounding to this point were using groundwater irrigation for

about total 5 hectares of land to cultivate the crops. The model predicted that the water

level for this well will drop at the rate of about 0.14m/10years simulation period.


Fig. 4.24 shows the comparison of predicted water levels of all observation wells.

The decline and replenish of water level of all the wells is at the same pattern. The water

level of observation wells No. 1 and 9 was at about same elevation but the depth of

watertable at OW No.1 was less than OW No.9. There was more pumping at OW No. 1

and no/low pumping at an OW No.9. Therefore, there was minimum decline in observed

as well as predicted water level of OW No.9 than all other observation wells. All the other

observation wells were between OW Nos. 1 and 9. In each in between OWs the decline of

water level was affected by the pumping of groundwater. Table 4.43 shows the change in

water level for all the observation wells for the simulation time period of 10 year under

constant existing conditions. It was predicted by the model that there will be decline in

water level from 0.14 to 4.03m/simulation period with an average decline of


102

104

106

108

110

112

114

116

Dec

, 2014

Jun, 2015

Dec

, 2015

Jun, 2016

Dec

, 2016

Jun, 2017

Dec

, 2017

Jun, 2018

Dec

, 2018

Jun, 2019

Dec

, 2019

Jun, 2020

Dec

, 2020

Jun, 2021

Dec

, 2021

Jun,

2022

Dec

, 2022

Jun, 2023

Dec

, 2023

Jun, 2024

Gro

undw

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hea

d, m

Time period

128

Fig. 4.24: Predicted groundwater heads for OW No. 1-9 under the Scenario-I

Table 4.43: Predicted groundwater heads at OW No. 1-9 under the Scenario-I

Well name Initial head (m) Final head (m) Initial head-final head (m)

OW-1 115.58 113.80 1.78

OW-2 113.56 111.00 2.56

OW-3 112.17 108.70 3.47

OW-4 112.80 108.80 4.00

OW-5 111.01 107.10 3.91

OW-6 109.33 105.30 4.03

OW-7 110.41 107.10 3.31

OW-8 110.16 107.70 2.46

OW-9 116.34 116.20 0.14

Average groundwater head 2.85

4.8.2 Increased groundwater pumping following the historic trend under

current conditions (Scenario-II)

Under this scenario, all the stress factors were assumed constant except

groundwater abstraction, which increases @ 5% of last year. Figs. 4.25-4.33 show the

graphical presentation of MODFLOW simulated groundwater heads for this scenario. A

groundwater decline of 2.27, 3.30, 4.46, 5.13, 4.93, 5.18, 4.16, 3.17 and 0.19m/10years

(from 2014-24) was simulated for OW number 1, 2, 3, 4, 5, 6, 7, 8 and 9, respectively.

102

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116

Dec

, 2

014

Jun, 2015

Dec

, 2015

Jun

, 20

16

Dec

, 2016

Jun, 2017

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, 2

017

Jun, 2018

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, 2018

Jun

, 20

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, 2019

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, 2020

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, 2021

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, 2022

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, 2023

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Gro

undw

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hea

d, m

Time period

OW1OW2OW3OW4OW5OW6OW7OW8OW9

129

Fig. 4.25: Predicted groundwater head for an OW No. 1 under the Scenario-II



102

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Dec

, 2014

Jun, 2015

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, 2015

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, 2016

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, 2017

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, 2018

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Gro

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Dec

, 2014

Jun, 2015

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, 2015

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, 2016

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, 2017

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, 2018

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, 2019

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, 2020

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, 2021

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, 2022

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, 2023

Jun, 2024

Gro

undw

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Dec

, 2014

Jun

, 2015

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, 2015

Jun, 2016

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, 2016

Jun, 2017

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, 2017

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, 2018

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, 2019

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, 2019

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, 2020

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, 2021

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, 2022

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, 2023

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Time period

130




102

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Fig. 4.34: Predicted groundwater heads for OW No. 1-9 under the Scenario-II

Table 4.44 shows the decline in groundwater heads for all the observation wells

for the simulation time period of 10 year under Scenario-II. It was predicted by the model

that there would be decline in water level from 0.19-5.18m/simulation period with and an

average decline of 3.64m/simulation period (from the year 2014 to 2024).

Table 4.44: Predicted groundwater heads at OW No. 1-9 under the Scenario-II

Well name Initial head (m) Final head (m) Initial head-final head (m)

OW-1 115.58 113.31 2.27

OW-2 113.56 110.26 3.30

OW-3 112.17 107.71 4.46

OW-4 112.80 107.67 5.13

OW-5 111.01 106.08 4.93

OW-6 109.33 104.15 5.18

OW-7 110.41 106.25 4.16

OW-8 110.16 106.99 3.17

OW-9 116.34 116.15 0.19


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4.8.3 Current rate of groundwater pumping and hill torrent water

resources management (Scenario-III)

The rate of groundwater pumping and recharge through irrigation except hill

torrent was assumed constant at the current rate. There was no record of the hill torrent

duration for each hill torrent occurrence with the concerned department. Thus, it was

difficult to estimate the volume of water available from the selected hill torrent during

each year. The water utilized for irrigation was estimated by the depth of water stored in

the field multiply by the area irrigated through hill torrent. About 50% of hill torrent

water is lost every year due to mismanagement. Hence, the recharge through efficient

(100%) utilization of hill torrent for irrigation increased to 3.745 MCM (double of

existing situation) under this scenario. Figs. 4.35-4.43 show the predicted water level

under this scenario.

Fig. 4.35: Predicted groundwater head for an OW No. 1 under the Scenario-III


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Fig. 4.44: Predicted groundwater heads for OW No. 1-9 under the Scenario-III

Table 4.45 shows the decline in groundwater heads of all the observation wells for

the simulation time period of 10 year under Scenario-III. It was predicted by the model

that there would be decline in water level from 0.46-1.19m/simulation period from OW

No. 1-8 and there will be a raise in the water level of OW No.9 at the rate of

0.01m/10years, which is at upstream of all due to no/low pumping and more recharge

through hill torrent water resources management. However, there would be an average

decline of 0.73m/simulation period in the whole study area.

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Table 4.45: Predicted groundwater heads at OW No. 1-9 under the Scenario-III

Well number Initial head (m) Final head (m) Initial head-final head (m)

OW-1 115.58 115.12 0.46

OW-2 113.56 112.98 0.58

OW-3 112.17 111.35 0.82

OW-4 112.80 111.81 0.99

OW-5 111.01 109.82 1.19

OW-6 109.33 108.39 0.94

OW-7 110.41 109.38 1.03

OW-8 110.16 109.61 0.55

OW-9 116.34 116.35 -0.01


The comparison of decline in groundwater heads under different scenarios is

shown in Table 4.46. The results of Scenario-I indicate that there was a decline in

groundwater heads from 0.14-4.03m/10years of simulation period with an average decline

of 2.85m/10 years. Similarly, the results of Scenario-II show the decline in groundwater

head from 0.19-5.18m/10years of simulation period with an average decline in head of

3.64m/10years. Under the Scenario-I and II, the model predicted a rapid decline in

groundwater heads. However, the simulated results of model under Scenario-III indicate

the decline in head from OW Nos. 1-8 and rise in head at observation well No. 9. The

overall decline in groundwater heads was 0.73m/10years of simulation period, which is

very low rate of decline in groundwater head as compared to Scenario-I and II. Therefore,

the model prediction indicates rising of water level at upstream area of selected study area

by the proper management of hill torrent water resources for irrigation as well as

groundwater recharge contribution in the study area.

Table 4.46: Comparison of decline in groundwater heads under different scenarios

Scenario No. of observation wells Minimum Maximum Mean

I 9 0.14 4.03 2.85

II 9 0.19 5.18 3.64

III 9 -0.01 1.19 0.73

138

4.9 Management strategies for the efficient use of water resources

Considering the results of present study, the following management strategies are

recommended for the existing water resources of Mithawan hill torrent command area of

Dera Ghazi Khan District of the Punjab, Pakistan.

1. The farmers of study area preferred to use hill torrent flow for irrigation but generally

could not utilize due to washing away of the poor quality of diversion structures.

Therefore, the construction of permanent diversion structures would facilitate the

farmers to divert hill torrent flow for irrigation and bring more area under cultivation.

2. The benefit cost ratio of hill torrent irrigated crops was more than that of groundwater

irrigated crops. Further, the hill torrent irrigation had no adverse affects on soil type of

the area while the groundwater irrigation had quite negative impacts on the soil

fertility and groundwater depletion. There was a significant decline in groundwater

head because of excessive groundwater pumping to meet the crop water requirements.

Therefore, the efficient utilization of hill torrents for irrigation would have positive

impact on socio-economic condition of the farmers and environment of the area.

3. Presently, a limited number of farmers adjacent to right bank of DG Canal have

provision of canal water lift irrigation while the majority of farmers are restricted to

use this water. The provisions of canal water lift irrigation to all of the farmers

adjacent to right bank of DG Canal would reduce the groundwater pumping and

improve soil fertility at this belt.

4. Pumping policy and proper selection of location for the installation of tubewells

should be developed to avoid the deterioration of soil fertility and increase of soil

salinity.

139

CHAPTER 5

CONCLUSIONS AND RECOMMENDATIONS

5.1 Conclusions

1. Cropping intensity of the study area varied with the occurrence of hill torrent. During

a wet cropping year (2012-13), the cropping intensity was 90% and for dry year

(2013-14) it was 70%. However, an average cropping intensity of the selected hill

torrent command area was observed as about 80%, which was far less than the

average cropping intensity of 173% of irrigated areas of Punjab, Pakistan.

2. About 92% farmers had the opportunity of using hill torrent flow and remaining 8%

had no access due to non-existence of channel system, conflicts between the farmers

regarding hill torrent irrigation and sand dunes. Similarly, 80% of the famers of study

area had the facility of groundwater extraction and 38% had access of canal water lift

irrigation.

3. Often, the majority of farmers could not divert hill torrent water into their field

because of the poor diversion structures and peak flow. High investment was required

by the farmers to construct heavy duty diversion structures and repairing of bund to

divert water only once in as season into the bund. The expanses paid by the farmers to

irrigate their fields with hill torrent flow varied from Rs. 9000 to 857100 with an

average amount of about Rs. 194360. However, an average investment for unit area

was about Rs. 8527 per hectare (2014).

4. Sediment load in the channel flow of hill torrent was 100g/L at upstream, 60g/L at the

middle and 30g/L at the tail of command area.

5. The installation rate of groundwater pumping units was increasing at 5%/annum as

compared to previous year. It was found that 50% of the pumped water was fit for

irrigation and 50% was unfit. Almost 100% of the farmers were interested to install

solar energy system for the running of their irrigation pumps, if available at successful

performance.

6. Generally, the crops, such as cotton, wheat, onion, sunflower, tobacco, maize and

fodder were irrigated by the canal water and/or groundwater irrigation while gram,

sorghum, millet, brassica, arugula and guar were irrigated by the hill torrent

flow/direct rainfall. The cost of production of canal water and/or groundwater

irrigated crops were higher than hill torrent irrigated crops. The benefit cost ratio

140

(BCR) of crops cultivated with canal water and/or groundwater irrigation were less

than the crops cultivated by hill torrent irrigation.

7. The relative contribution of canal water, groundwater and rainfall to meet the crops

water requirement was 28, 61 and 11%, respectively.

8. Irrigation efficiency of crops cultivated with canal water and/or groundwater was 37,

76, 46, 86, 56, 24 and 41% for wheat, cotton, onion, sunflower, tobacco, maize and

fodder, respectively.

9. Average EC of hill torrent and groundwater was 0.61 and 1.59dS/m, while SAR was

1.5 and 1.9, respectively. However, the RSC was zero in both hill torrent and

groundwater. Similarly, the average EC of fields irrigated with hill torrent and

groundwater was 0.81 and 1.21dS/m, respectively. The average SAR for soil samples

were 1.58 and 4.58 for hill torrent and groundwater irrigated fields, respectively.

There was no RSC in hill torrent irrigated fields but found 0.12 in groundwater

irrigated fields.

10. The MODFLOW model predicted an average decline in groundwater head of 2.85m

for 2014-24 considering all the stress factors constant at existing rate. The model also

simulated an average decline in groundwater head of 3.64m for 2014-24 when

pumping rate increased to 5% of last year while all other stress factors were assumed

constant. In contrast, the model predicted a raise of 0.01m water level at upstream

while average decline of 0.73m at middle and downstream of command area for 2014-

24 at 100% increase in the recharge through efficient utilization of hill torrent for

irrigation.

5.2 Recommendations

1. There is a need to make an amendment in the water rights for uniform and equitable

distribution of water among the shareholders of hill torrent command area.

2. Heavy sediment load is the biggest problem in the storage of hill torrent water.

Therefore, the watershed management should be prioritized. The watershed

management can be done by vegetation, terracing and check dam. By this, the peak of

flood would decrease and diversion of water into the bunds at the command area

would become easy and cheap. Similarly, watershed erosion risk mapping would also

help in the management of watershed and control of erosion.

3. Groundwater irrigation had bad impacts on the soil as well as crop yield. Therefore,

the priority must be given to hill torrent irrigation, which produced more yields and

141

had more benefit cost ratio of crops. The construction of permanent diversion

structures and proper channelization at hill torrent command would have beneficial

effects on soil, crop yield, watertable, environment and socioeconomic condition of

the farmers.

4. The sequence of farmers’ preference to use irrigation water in the selected hill torrent

command area was hill torrent, canal water and groundwater. Therefore, along with

hill torrent water resources management, the farmers whose are adjacent to the right

bank of DG Canal should be given the right of canal water lift irrigation. By this,

groundwater pumping at the tail of command area will decrease and the deterioration

of soil fertility, and decline in water level would decrease.

5. Owing to spatial variation in groundwater quality and quantity, farmers made a

number of attempts to make suitable borehole. The development of groundwater

pumping policy and proper selection of location for the installation of groundwater

pumps would avoid the deterioration of soil fertility and development of soil salinity.

142

CHAPTER 6

SUMMARY

The issue of water crisis has become a serious challenge for water managers. No doubt,

the proper management of river flows can be beneficially utilized to cope with future

need of increasing population. But, to safeguard the country from water short category,

the management of existing water resources including hill torrent is most important in this

era. Management of hill torrent generated water being the cheapest source of irrigation is

important to agriculture, because drought and severe shortage of water are causing food

scarcity in the country. The farmers of hill torrent command areas are facing a number of

problems, such as high cost of diversion structures, poor financial resources, damages

through peak floods, heavy sediment load, low yield of crops, less attention by the

researcher and government etc. Crop yield in the hill torrent command areas is less than

potential, mainly due to poor irrigation practices. Hill torrent irrigation is applied once

before the sowing of crop and subsequent irrigation water requirements based rainfall,

which satisfy less than 15% of requirement.

Although, agricultural activities in the country for crop production utilize the

canal and groundwater resources, yet the hill torrents provide a valuable source of water

at the plains, depending on the seasonal rain storms. A very limited research has been

conducted to best manage the water resources of hill torrent of Pakistan. Thus, the present

study was conducted to investigate the issues related to the irrigated agriculture in

Mithawan hill torrent command area of Pakistan. In Mithawan hill torrent command area,

watertable exists at a greater depth and has poor quality of groundwater. Irrigation with

pumped water is reliable but costly and its continuous application is deteriorating the

upper surface of soil and declining the watertable in the area. The dependence on

groundwater in the study area has been significantly increased. Therefore, the

management of water resources and its utilization need to be improved through efficient

harvesting of hill torrents and adopting groundwater recharge techniques to mitigate the

effects of extensive pumping. For this purpose, data were collected through field visits/

observation and farmers’ interviews regarding the available water resources, cropping

patterns, groundwater pumping activities, watertable fluctuations and irrigation practices

to develop the optimal management strategies. The data collected through farmers’

interview were analyzed using SPSS. The crop water requirement was assessed using

143

CROPWAT model to estimate the irrigation efficiencies of the system. A 3-D finite

difference model “MODFLOW” was used to simulate the groundwater head of the study

area under three different scenarios.

Cropping intensity of the study area varied with the occurrence of hill torrent.

During a wet cropping year (2012-13), the cropping intensity was 90% and a dry year

(2013-14) had 70%. About 92% of the farmers had the availability of hill torrent flow and

remaining 8% had no access due to non-existence of channel system, farmers’ conflict of

hill torrent irrigation, sand dunes etc. Similarly, 80% of the farmers had the facility of

groundwater extraction and 38% of farmers had access of canal water lift irrigation.

Often, the majority of farmers of selected hill torrent command area could not divert the

flow of hill torrent into their fields because of poor diversion structures and peak flows. It

needed high investment to construct heavy duty diversion structures and embankments of

the bunds. In this regard, the expanses paid by the farmers for each hill torrent irrigation

application varied from Rs. 9000 to 857100 with an average amount of about Rs. 194360.

However, the average investment for unit area was about Rs. 8527/ha.

It was assessed that the groundwater pumps installation in the study area was

increasing every year at about 5% of last year pumps. It was found by the laboratory

analysis of groundwater samples that 50% of the water was fit for irrigation and 50% was

unfit. However, 100% of the farmers were interested to install solar energy system for the

running of their irrigation pumps, if available at successful performance. Generally,

cotton, wheat, onion, sunflower, tobacco, maize and fodder were irrigated by the canal

water and/or groundwater irrigation and gram, sorghum, millet, brassica, arugula and guar

were irrigated by the hill torrent flow/ direct rainfall. The average yield of cotton, wheat,

onion, gram, sorghum, millet, brassica, arugula and guar was 2291, 3848, 20849, 1991,

1693, 1365, 813, 927 and 958kg/ha, respectively. The cost of production of canal water

and/or groundwater irrigated crops were higher than hill torrent irrigated crops. Thus the

benefit cost ratio (BCR) of canal water and/or groundwater irrigated crops were less than

that of hill torrent irrigated crops i.e. cotton, wheat, onion, gram, sorghum, millet,

brassica, arugula and guar were 1.29, 1.50, 1.57, 2.00, 2.39, 1.63, 1.67, 1.49 and 2.22,

respectively.

The relative contribution of canal water, groundwater and rainfall to meet the

crops water requirement was 28, 61 and 11%, respectively. It showed that maximum

dependence of canal water and/or groundwater irrigated crops was on groundwater

irrigation. Whereas, the farm irrigation efficiency of canal water and/or groundwater

144

irrigated crops in the study area was 37, 76, 46, 86, 56, 24 and 41% for wheat, cotton,

onion, sunflower, tobacco, maize and fodder, respectively.

Average EC of hill torrent and groundwater was 0.61 and 1.59dS/m, while SAR

was 1.5 and 1.9, respectively. However, the RSC was zero in both hill torrent and

groundwater. Similarly, the average EC of fields irrigated with hill torrent and

groundwater was 0.81 and 1.21dS/m, respectively. The average SAR for soil samples

were 1.58 and 4.58 for hill torrent and groundwater irrigated fields, respectively. There

was no RSC in hill torrent irrigated field but found 0.12 in groundwater irrigated fields.

The simulation of groundwater head under the existing conditions (Scenario-I)

showed the average decline of 2.85m/10years (from 2014-24). Considering the increasing

trend of pumps installation at 5% of previous year (Scenario-II), it was simulated by the

model that there would be an average decline of 3.64m/10years. There was no record for

duration of the hill torrent at concerned department. So, it was difficult to estimate the

volume of water available through hill torrent during each year. More than 50% of hill

torrent water is lost every year due to mismanagement. By the 100% utilization of hill

torrent flows (Scenario-III) the model predicted a recharge of 0.01m at upstream and

average decline of 0.73m at the middle as well as tail of the study area for 2014-24.

In view of the results of present study, the following guidelines are recommended

for the best management of existing water resources of Mithawan hill torrent command

area, DG Khan District of the Punjab, Pakistan.

1. The efficient utilization of hill torrents for irrigation would have positive impacts on

socio-economic condition of the farmers and environment of the area.

2. Provisions of canal water lift irrigation to all of the farmers adjacent to the right bank

of canal would reduce the groundwater pumping at this belt and hence the soil fertility

along the right bank of canal could be maintained.

3. Groundwater pumping policy and proper selection of location for the installation of

tubewells should be examined to avoid the deterioration of soil fertility and

development of soil salinity.

134

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APPENDIX-A

Appendix-A1: Questionnaire; agricultural practices of the farmers under

Mithawan hill torrent command area, DG Khan-Pakistan

Name of the farmer:

Education: Uneducated/Primary/Matriculation/Intermediate/Graduate/Higher Education

Address/ Mauza: Cell No.

Landholding (ha) Culturable Area (ha) Unculturable Area (ha)

Sr.

No.

Crop

sown

Area cultivated

during a wet

year, 2012 (ha)

Source of

irrigation

Area cultivated

during a dry

year, 2013 (ha)

Source of

irrigation

Kharif season

1 Cotton

2 Sorghum

3 Millet

4 Onion

5 Guar

6 Maize

7 Fodder

Rabi season

1 Wheat

2 Grams

3 Brassica

4 Arugula

5 Sunflower

6 Onion

7 Tobacco

8 Fodder

Sources of irrigation: Canal Water/ Groundwater/ Hill Torrent/ Other

A. Cultivation with hill torrent irrigation system

Area irrigated through hill torrent (ha): Method(s) of irrigation:

Size of field/ Bund (ha):

Annual cost of repairing of bunds and construction of diversion structure (Rs./ha):

No. of sowing seasons in a year:

Depth of water applied in bund by the hill torrent flow (m):

Crops utilizing the flow of hill torrents:

How often Rod Kohi/ Hill Torrent occurred in a year?

Inputs applied to the crop and cost of production

Crop Inputs

applied

Cost of inputs

(Rs./ha)

Cost of labor and machinery

(Rs./ha)

Total cost

(Rs.)

142

Income from the crop

Crop Yield

(kg/ha)

Price

(Rs./kg)

Income of

yield (Rs.)

Income of by-

product (Rs.)

Total income

(Rs.)

Do you sow the crop(s) without irrigation/ direct rainfall: (Yes/No)

If yes, name the crop

Does hill torrent create problems/damages/ troubles for you? Yes No

If yes, name the problems/ damages/ troubles:

B. Cultivation with groundwater in hill torrent command area

Number of Water Supply Units:

Type of Pump(s): Tubewells/ Submersible Pumps/ Deep Well Turbine

Stages of Pump: Size of pump/ delivery pipe (inches):

Source of energy: Diesel Engine/ Tractor/ Electricity/ Other

Source of energy preferable and economical to you: Solar energy/ Biogas / any other

If available in the market, would you like to install it for the pumping unit?

Ownership Status: Owned/ Rented Rate of Water (Rs. /hour):

When did you install the pumping unit?

If no, are you willing to install the pumping unit?

Depth of well bore (m): Depth of turbine/submersible pump (m):

Current depth of watertable (m): Depth of watertable at the time of well drilling (m):

No. of sowing seasons in a year: Area irrigated by groundwater (ha):

Wherein season you prefer to use groundwater irrigation and why?

If already have a pump, do you want to extend the installation for another area? Yes/ No

Did anytime you face the problem of lowering of watertable? Yes/ No

If yes, what did you do to overcome the situation?

Are you single owner of the pump/ turbine: Yes/ No

If no, then how many partners are involved in it?

Did anytime the well bore fail? Yes/ No If yes, what was the reason(s)?

How many bores have failed so far?

Is there any adverse effect of groundwater on soil physical properties or yield? Yes/ No

If yes, what changes you observed?

What did you do to overcome the problems?

Irrigation practices through groundwater application

Crop

No. of

irrigation

applied

Duration of

irrigation application

(hr/ha)

Discharge of

pump

(m3/sec)

Volume of

water applied

(m3/ha)

143

Inputs applied to the crops and cost of production

Crop Inputs

applied

Cost of inputs

(Rs./ha)

Cost of labor and

machinery (Rs./ha)

Total cost

(Rs.)

Income of crop yield

Crop Yield

(kg/ha)

Price

(Rs./kg)

Income of

yield (Rs.)

Income of by-

product (Rs.)

Total income

(Rs.)

144

C. General information regarding the hill torrent area

Soil type:

No. of hill torrent occurred during the year 2012?

Price of land per acre (Now) Rs. (Ten years ago) Rs.

Reasons for increase in the price of land

Why do you invest money in this area?

Problems and constraints that you faced in farming in this area

145

Appendix-A2: Educational status and landholding of the farmers of study area

Sr.

No.

Name of the

farmer Qualification

Landholding

(ha)

Culturable

area

(ha)

Uncultiv

able area

(ha)

1 Muhammad Yousif Primary 6.07 6.07 0.00

2 Abdul Kareem Matriculation 16.59 16.59 0.00

3 Muhammad Azam Matriculation 20.64 20.64 0.00

4 Ghulam Rasool Primary 43.30 43.30 0.00

5 Muhammad Nawab Matriculation 20.23 20.23 0.00

6 Saeed Ali Primary 40.47 40.47 0.00

7 Ghahi Khan Uneducated 5.06 5.06 0.00

8 Gulsher Khan Uneducated 1.62 1.62 0.00

9 Abdul Kareem Primary 60.70 60.70 0.00

10 Muhammad Umar Matriculation 20.23 20.23 0.00

11 Abdul Khaliq Matriculation 20.23 20.23 0.00

12 Nazar Hussain Primary 17.81 17.81 0.00

13 Kalo Khan Uneducated 1.42 1.42 0.00

14 Abdul Qadir Primary 6.68 6.68 0.00

15 Kareem Bakhsh Uneducated 42.90 42.90 0.00

16 Mukhtiar Hussain Uneducated 91.06 70.82 20.23

17 Fauj Ali Uneducated 6.07 6.07 0.00

18 Abdul Rehman Primary 40.47 40.47 0.00

19 Muhammad Ishfaq Matriculation 2.02 2.02 0.00

20 Mureed Hussain Uneducated 2.02 2.02 0.00

21 Allah Ditta Khan Uneducated 10.12 10.12 0.00

22 Bahram Khan Uneducated 10.12 10.12 0.00

23 Sonhara Khan Uneducated 20.23 20.23 0.00

24 Muhammad Jaffar Uneducated 2.83 2.83 0.00

25 Saeed Khan Uneducated 25.29 25.29 0.00

26 Shahbaz Khan Uneducated 3.44 3.44 0.00

27 Ghulam Shabbir Matriculation 6.98 6.98 0.00

28 Kareem Bakhsh Uneducated 12.14 12.14 0.00

29 Haji Shafee Uneducated 8.09 8.09 0.00

30 Tagia Khan Uneducated 4.05 4.05 0.00

31 Kamal Buzdar Intermediate 44.52 44.52 0.00

32 Faiz Muhammad Middle 2.02 2.02 0.00

33 Nazar Hussain Uneducated 8.09 8.09 0.00

34 Gh. Akbar Buzdar Intermediate 40.47 40.47 0.00

35 Ghulam Shabbir Uneducated 13.15 13.15 0.00

36 Eisa Khan Uneducated 8.09 8.09 0.00

37 Nihal Khan Matriculation 10.12 10.12 0.00

38 Sher Muhammad Middle 60.70 60.70 0.00

39 Haji Ilahi Bakhsh Primary 30.35 30.35 0.00

40 Gh. Yaseen Khan Matriculation 13.35 13.35 0.00

41 Tagia KhanRmdani Primary 121.41 121.41 0.00

146

42 Kashif Raza Intermediate 5.06 5.06 0.00

43 Muhammad Sharif Uneducated 1.82 1.82 0.00

44 Ghulam Farid Uneducated 7.28 7.28 0.00

45 Wahid Bakhsh Uneducated 33.18 33.18 0.00

46 Mitha Khan Uneducated 2.83 2.83 0.00

47 Ghulam Rasool Primary 70.82 70.82 0.00

48 Ibrahim Khan Uneducated 40.47 40.47 0.00

49 Haq Nawaz Graduate 30.35 30.35 0.00

50 Wahid Bakhsh Uneducated 20.23 20.23 0.00

Appendix-A3: Area cultivated with different crops during Kharif season, 2012 (ha)

Sr. No. Onion Cotton Maize Sorghum Millet Arugula Fodder

1 0.00 3.24 0.00 0.00 0.00 1.01 0.00

2 0.00 0.00 0.00 4.05 3.04 0.00 0.00

3 0.81 14.16 0.00 0.00 0.00 1.21 0.00

4 0.00 17.60 1.01 3.64 1.01 0.00 0.00

5 2.43 8.09 0.00 1.62 2.02 2.02 0.00

6 0.00 5.06 0.00 0.00 9.11 0.00 0.00

7 0.00 0.00 0.00 1.21 1.82 0.00 0.00

8 0.00 0.00 0.00 1.62 0.00 0.00 0.00

9 2.43 0.00 0.00 1.21 0.00 0.00 0.00

10 0.00 4.05 0.00 4.05 4.05 0.00 0.00

11 8.09 16.19 0.00 0.00 0.00 0.00 0.00

12 1.01 7.69 0.00 0.00 0.00 0.00 0.20

13 0.00 0.00 0.00 0.00 0.00 0.00 0.00

14 0.00 1.01 0.00 0.00 0.00 0.00 0.00

15 0.00 10.12 0.00 0.00 0.00 0.00 0.40

16 10.12 0.00 0.00 10.12 12.14 4.05 0.00

17 0.51 0.00 0.00 0.00 0.00 0.20 0.20

18 0.00 8.09 0.00 8.09 8.09 0.00 0.00

19 0.00 0.00 0.00 0.40 0.00 0.00 0.00

20 0.00 0.00 0.00 0.00 0.00 0.00 0.00

21 0.00 0.00 0.00 2.02 0.81 0.00 0.00

22 0.00 0.00 0.00 5.06 0.00 0.00 0.00

23 0.00 0.00 0.00 0.00 0.00 0.00 0.00

24 0.00 0.00 0.00 0.00 0.00 0.00 0.00

25 0.00 0.00 0.00 1.62 0.81 0.00 0.00

26 0.00 2.63 0.00 0.00 0.00 0.00 0.00

27 0.00 0.00 0.00 0.00 0.00 0.00 0.00

28 0.00 0.00 0.00 0.00 0.00 0.00 0.00

29 0.00 0.00 0.00 0.00 0.00 0.00 0.00

30 0.00 1.62 0.00 0.00 0.00 0.00 0.00

31 0.00 28.33 0.81 0.40 0.00 0.00 0.00

147

32 0.00 2.02 0.00 0.00 0.00 0.00 0.00

33 0.00 0.00 0.00 0.40 0.00 0.00 0.00

34 0.00 0.00 0.00 0.00 8.09 0.00 0.00

35 0.00 0.00 0.00 0.00 0.00 0.00 0.00

36 0.00 0.00 0.00 0.00 0.00 0.00 0.00

37 0.00 0.00 0.00 0.40 0.00 0.00 0.00

38 8.09 0.00 0.00 0.00 0.00 0.00 0.00

39 0.00 0.00 0.00 8.09 0.00 0.00 0.00

40 3.24 0.00 0.00 0.00 0.00 0.00 0.00

41 0.00 13.35 0.00 0.00 0.81 0.00 0.81

42 0.00 0.00 0.00 1.01 0.20 0.00 0.00

43 0.00 0.00 0.00 0.81 0.00 0.00 0.00

44 0.00 0.00 0.00 1.62 1.21 0.00 0.00

45 1.21 2.02 0.00 0.30 0.00 0.00 0.00

46 0.00 0.00 0.00 1.42 0.00 0.00 0.00

47 7.69 0.00 0.00 0.00 0.00 0.00 0.00

48 0.00 0.00 0.00 6.07 4.05 0.00 0.00

49 0.00 0.00 0.00 4.05 6.07 0.00 0.00

50 6.07 1.42 0.00 0.00 1.01 0.00 0.00

Appendix-A4: Area cultivated with different crops during Rabi season, 2012-13 (ha)

Sr. No. Wheat Gram Tobacco Sunflower Brassica Arugula Fodder

1 5.06 0.00 0.00 0.00 0.00 0.00 0.00

2 0.00 6.27 0.00 0.00 0.00 0.00 0.00

3 16.19 0.00 0.00 0.00 1.21 0.00 0.00

4 17.60 10.12 0.00 0.00 4.05 1.62 4.05

5 9.31 4.05 0.00 0.00 2.02 0.00 0.40

6 12.14 0.00 0.00 0.00 0.00 0.00 0.00

7 0.00 2.83 0.00 0.00 0.00 0.00 0.00

8 0.00 0.00 0.00 0.00 0.00 0.00 0.00

9 0.00 2.43 0.00 0.00 0.00 0.00 0.00

10 4.05 8.09 0.00 0.00 0.00 0.00 0.00

11 16.19 0.00 4.05 8.09 0.00 0.00 0.00

12 5.67 0.00 0.00 0.00 0.00 0.00 0.20

13 1.21 0.00 0.00 0.00 0.00 0.00 0.00

14 1.01 6.07 0.00 0.00 0.00 0.00 0.00

15 10.12 6.07 0.00 0.00 3.04 0.00 0.40

16 8.09 50.59 0.00 0.00 4.05 3.04 0.00

17 1.32 2.23 0.00 0.00 0.40 0.20 0.00

18 10.12 10.12 0.00 0.00 2.43 0.00 0.00

19 0.00 1.21 0.00 0.00 0.40 0.00 0.00

20 0.00 0.00 0.00 0.00 0.00 0.00 0.00

21 4.05 2.02 0.00 0.00 0.00 0.00 0.20

148

22 0.00 0.00 0.00 0.00 0.00 0.00 0.00

23 0.00 8.09 0.00 0.00 4.05 0.00 0.00

24 0.00 0.00 0.00 0.00 0.00 0.00 0.00

25 0.00 1.62 0.00 0.00 0.40 0.00 0.81

26 2.63 0.00 0.00 0.00 0.00 0.00 0.00

27 6.27 0.00 0.00 0.00 0.00 0.00 0.00

28 0.00 12.14 0.00 0.00 0.00 0.00 0.00

29 1.82 2.23 0.00 0.00 0.20 0.20 0.00

30 3.04 0.00 0.00 0.00 0.00 0.00 0.00

31 36.42 3.24 0.00 0.00 4.45 0.00 0.40

32 2.02 0.00 0.00 0.00 0.00 0.00 0.00

33 0.00 7.69 0.00 0.00 0.00 0.00 0.40

34 20.23 0.00 0.00 0.00 0.00 0.00 0.00

35 0.81 11.74 0.00 0.00 0.00 0.00 0.61

36 1.01 6.88 0.00 0.00 0.00 0.00 0.20

37 0.00 5.06 0.00 0.00 2.23 2.43 0.00

38 40.47 4.05 0.00 0.00 2.02 0.00 0.81

39 0.00 10.12 0.00 0.00 1.62 0.40 0.00

40 0.00 10.12 0.00 0.00 0.00 0.00 0.00

41 13.35 8.09 0.00 0.00 1.21 0.00 0.81

42 0.81 2.83 0.00 0.00 0.20 0.00 0.00

43 0.00 0.00 0.00 0.00 0.00 0.00 0.00

44 0.00 0.00 0.00 0.00 0.00 0.00 0.00

45 4.05 8.09 0.00 0.00 4.86 0.40 0.00

46 0.00 0.00 0.00 0.00 0.00 0.00 0.00

47 2.43 60.70 0.00 0.00 0.00 0.00 0.00

48 0.00 30.35 0.00 0.00 0.00 0.00 0.00

49 0.00 20.23 0.00 0.00 0.00 0.00 0.00

50 3.44 0.00 3.24 0.00 2.23 0.00 0.40

149

Appendix-A5: Area cultivated with different crops during Kharif season, 2013 (ha)

Sr.

No. Onion (Aug.-Sep.) Cotton Maize Sorghum Millet Guar Fodder

1 0.00 0.00 0.00 1.82 2.02 0.00 0.00

2 0.00 0.00 0.00 0.00 0.00 0.00 0.00

3 8.50 10.52 0.00 0.00 0.00 0.00 0.00

4 0.00 6.07 2.23 0.00 0.00 0.00 0.00

5 2.83 10.12 0.00 0.00 0.00 0.00 0.00

6 0.81 0.00 0.00 0.00 0.00 2.23 0.00

7 0.00 0.00 0.00 0.00 0.00 0.00 0.00

8 0.61 0.00 0.00 0.00 0.00 0.00 0.00

9 0.00 0.00 0.00 0.00 0.00 0.00 0.00

10 0.00 2.43 0.00 0.00 0.00 0.00 0.00

11 8.09 16.19 0.00 0.00 0.00 0.00 1.62

12 2.83 2.63 0.00 0.00 0.00 0.00 0.00

13 0.00 0.00 0.00 0.00 0.00 0.00 0.00

14 3.24 0.00 0.00 0.00 0.00 0.00 0.00

15 0.00 20.23 0.00 0.61 0.00 0.81 0.00

16 8.09 30.35 0.00 0.00 0.00 0.00 0.00

17 1.82 0.00 0.00 0.00 0.00 0.00 0.00

18 0.00 8.09 0.00 0.00 0.00 0.00 0.00

19 0.00 0.81 0.00 0.00 0.00 0.00 0.10

20 0.00 0.00 0.00 0.00 0.00 0.00 0.00

21 0.00 0.00 0.00 0.00 0.00 0.00 0.00

22 0.00 0.00 0.00 0.00 0.00 0.00 0.00

23 3.04 0.00 0.00 0.00 0.00 0.00 0.00

24 0.00 0.00 0.00 0.00 0.00 0.00 0.00

25 0.00 0.00 0.00 0.00 0.00 0.00 0.00

26 0.00 1.82 0.00 0.00 0.00 0.00 0.00

27 0.00 0.00 0.00 0.00 0.00 0.00 0.00

28 0.00 0.00 0.00 0.00 0.00 0.00 0.00

29 0.00 1.21 0.00 0.00 0.00 0.00 0.00

30 0.00 3.95 0.00 0.00 0.00 0.00 0.10

31 2.43 10.32 0.40 0.00 4.45 0.00 0.00

32 8.09 0.00 0.00 0.40 0.00 1.82 0.00

33 0.81 0.00 0.00 1.21 0.00 0.00 0.00

34 4.05 0.00 0.00 0.00 6.98 2.02 2.23

35 0.00 0.00 0.00 0.40 0.00 0.00 0.00

36 0.40 0.00 0.00 0.40 0.00 0.00 0.00

37 0.00 0.00 0.00 0.00 0.00 0.00 0.00

38 12.75 4.45 0.00 0.00 0.00 0.00 0.00

39 0.00 0.00 0.00 0.00 0.00 0.00 0.00

40 4.86 0.00 0.00 0.00 0.00 0.00 0.00

41 4.05 16.19 0.00 3.24 0.00 0.00 0.00

42 0.00 0.00 0.00 0.00 0.00 0.00 0.00

150

43 0.00 0.00 0.00 1.01 0.00 0.00 0.00

44 0.00 0.00 0.00 0.00 0.00 0.00 0.00

45 2.63 12.14 0.00 0.00 0.00 0.00 0.00

46 0.00 0.00 0.00 0.00 0.00 0.00 0.00

47 5.06 0.00 0.00 0.40 0.00 0.00 0.00

48 0.00 0.00 0.00 10.12 0.00 0.00 0.00

49 0.00 0.00 0.00 0.00 0.00 0.00 0.61

50 0.00 0.00 0.00 0.00 0.00 0.00 0.00

Appendix-A6: Area cultivated with different crops during Rabi season, 2013-14 (ha)

Sr.

No. Wheat

Onion

(Dec.Jan.) Gram Brassica Arugula

Tobac

co

Sunfl

ower Fodder

1 3.44 0.00 0.00 0.00 0.00 0.00 0.00 0.40

2 2.53 0.00 0.00 0.00 0.00 0.00 0.00 0.00

3 10.52 0.00 0.00 0.00 0.00 2.02 0.00 0.00

4 32.38 0.00 0.00 0.00 0.00 0.00 0.00 0.00

5 10.12 0.00 0.00 0.00 0.00 2.02 0.00 0.00

6 11.13 0.00 0.00 0.00 0.00 0.00 0.00 0.00

7 1.82 0.00 0.00 0.00 0.00 0.00 0.00 0.00

8 4.05 0.00 0.00 0.00 0.00 0.00 0.00 0.00

9 6.07 0.00 0.00 0.00 0.00 0.00 0.00 0.00

10 6.88 0.00 0.00 0.00 0.00 0.00 0.00 0.00

11 30.35 4.05 0.00 0.00 0.00 0.00 0.00 0.00

12 16.59 0.00 0.00 0.00 0.00 0.00 0.00 0.61

13 0.61 0.00 0.00 0.00 0.00 0.00 0.00 0.00

14 4.05 0.00 0.00 0.00 0.00 0.00 0.00 0.00

15 24.28 0.00 10.12 5.26 0.00 0.00 2.23 0.81

16 30.35 0.00 0.00 1.82 0.00 0.00 0.00 2.43

17 4.05 0.00 0.00 0.00 0.00 0.00 0.00 0.10

18 8.09 0.00 0.00 0.00 0.00 0.00 0.00 0.00

19 0.81 0.00 0.00 0.00 0.00 0.00 0.00 0.20

20 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00

21 6.07 0.00 0.00 0.00 0.00 0.00 0.00 0.00

22 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00

23 4.45 0.00 0.00 0.00 0.00 0.00 0.00 0.00

24 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00

25 0.00 0.00 0.81 0.00 0.00 0.00 0.00 0.00

26 1.01 0.00 0.00 0.00 0.00 0.00 0.00 0.00

27 6.88 0.00 0.00 0.00 0.00 0.00 0.00 0.00

28 8.09 0.00 0.00 0.00 0.00 0.00 0.00 0.40

29 2.63 0.00 0.00 0.00 0.00 0.00 0.00 0.20

30 3.84 0.00 0.00 0.00 0.00 0.00 0.00 0.20

31 20.23 0.51 0.00 0.00 0.00 0.00 0.00 0.00

32 8.09 0.00 0.00 0.00 0.00 0.00 0.00 0.40

33 4.86 0.81 0.00 0.00 0.00 0.00 0.00 0.81

151

34 18.21 0.00 0.00 0.00 0.00 0.00 0.00 0.00

35 5.46 0.00 0.00 0.00 0.00 0.00 0.00 0.40

36 3.24 0.00 0.00 0.00 0.00 0.00 0.00 0.20

37 2.02 0.00 0.00 0.00 0.00 0.00 0.00 0.40

38 40.47 0.00 0.00 0.00 0.00 0.00 0.00 0.00

39 6.07 0.00 1.01 1.01 0.81 0.00 0.00 0.00

40 2.83 0.00 0.00 0.00 0.00 0.00 0.00 0.00

41 16.19 0.00 0.00 0.00 0.00 0.00 0.00 4.05

42 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00

43 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00

44 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00

45 20.23 0.00 0.00 0.00 0.00 0.00 4.05 0.00

46 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00

47 6.48 0.00 0.00 0.00 0.00 0.00 0.00 0.81

48 16.19 0.00 6.07 0.81 0.00 0.00 0.00 2.02

49 12.14 0.00 0.00 0.61 0.00 0.00 0.00 1.21

50 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00

Appendix-A7: Sources of irrigation and pumping units of the farmers

Sr.

No. Source of irrigation No. of GW

pumping

units

No. of

owners

No. of bore

failed

Preferable

source of power CW GW HT

1 1 1 1 1 3 0 1

2 0 1 1 1 3 0 1

3 1 1 1 1 3 0 1

4 1 1 1 2 5 1 1

5 1 1 1 2 5 4 1

6 0 1 1 1 2 2 1

7 0 1 1 1 3 0 1

8 0 1 1 1 2 0 1

9 0 1 1 1 1 2 1

10 1 1 1 1 4 0 1

11 1 1 1 1 1 2 1

12 0 1 0 1 1 3 1

13 0 1 0 1 4 1 1

14 1 1 1 1 2 0 1

15 1 1 1 1 2 0 1

16 1 1 1 2 2 0 1

17 0 1 1 1 3 0 1

18 1 1 1 1 3 2 1

19 0 1 1 1 2 1 1

20 0 1 1 1 4 0 1

21 0 1 1 1 10 0 1

22 0 0 1 0 N/A N/A N/A

23 0 1 1 2 6 0 1

152

24 0 0 1 0 N/A N/A N/A

25 0 0 1 0 N/A N/A N/A

26 1 0 0 0 N/A N/A N/A

27 1 0 1 0 N/A N/A N/A

28 0 1 1 1 3 0 1

29 1 1 1 2 5 2 1

30 1 1 1 1 8 1 1

31 1 1 1 3 3 1 1

32 1 0 0 0 N/A N/A N/A

33 0 1 1 1 2 0 1

34 1 1 1 1 2 0 1

35 0 1 1 1 1 0 1

36 0 1 1 2 1 0 1

37 0 0 1 0 N/A N/A N/A

38 0 1 1 2 4 3 1

39 0 1 1 1 3 0 1

40 0 1 1 1 6 0 2

41 1 1 1 1 6 1 1

42 0 0 1 0 N/A N/A N/A

43 0 0 1 0 N/A N/A N/A

44 0 1 1 1 1 0 1

45 1 1 1 2 3 1 1

46 0 0 1 0 N/A N/A N/A

47 0 1 1 5 10 5 1

48 0 1 1 1 6 0 1

49 0 1 1 1 2 1 1

50 0 1 1 1 1 1 1

0 = No

1 = Yes

N/A =

Not

applica-

ble

1 = Solar Energy

System

2 = Biogas +

Solar Energy

System

153

Appendix-A8: Year and specification of the pumping units installed in the area

Pump

type

Year of

installation

Pump

stages

Dia. of delivery

pipe (cm)

Sources

of power

Cost of GW

(Rs./hr)

GW

quality

1 2006 9 12.70 1 450 1

1 2005 11 10.16 1 325 1

1 1997 7 15.24 3 200 1

1 2001 5 15.24 1 450 1

1 2008 12 10.16 1 450 1

1 1998 9 12.70 2 350 1

1 2006 9 12.70 2 350 1

1 1998 7 12.70 3 200 2

1 2011 5 12.70 1 350 1

0 2003 - 5.08 3 350 1

1 2010 10 10.16 1 350 1

1 1998 8 10.16 1 575 1

1 1996 7 12.70 3 500 0

1 1993 9 12.70 3 400 1

1 2009 7 10.16 1 400 1

1 2009 7 10.16 1 450 1

1 2001 9 12.70 1 650 1

1 1998 9 15.24 1 600 1

1 1998 9 15.24 1 600 1

1 2011 9 12.70 1 600 1

1 1998 9 12.70 1 600 1

0 2007 - 10.16 3 500 1

1 1998 9 12.70 1 500 0

1 2009 9 12.70 1 400 2

1 1996 13 12.70 1 600 1

1 2011 9 10.16 1 600 1

1 2008 6 12.70 1 450 1

1 2008 9 10.16 1 600 0

1 2008 9 12.70 1 600 0

1 1998 9 15.24 1 500 2

1 2007 9 15.24 1 700 1

1 2007 9 12.70 1 700 1

1 2007 9 10.16 1 700 1

1 2009 9 12.70 1 450 1

1 2004 9 12.70 3 350 2

1 2009 13 10.16 1 450 1

1 2008 14 10.16 1 550 1

1 2008 14 10.16 1 550 1

1 1992 11 12.70 3 350 2

1 1995 11 12.70 3 350 2

1 2013 13 15.24 1 600 1

1 1998 12 10.16 1 500 1

154

1 1998 12 10.16 1 500 1

0 2013 - 5.08 3 300 1

1 1997 9 10.16 1 550 1

1 1997 7 12.70 1 550 1

1 1995 12 12.70 1 400 1

1 2008 12 10.16 1 400 1

1 2011 12 10.16 1 400 2

0 2013 - 5.08 4 500 1

0 2013 - 5.08 4 500 1

1 1997 11 12.70 1 700 1

1 2007 9 12.70 1 350 2

1 2009 11 12.70 3 500 1

0 =

Subm-

ersible

pump

1=

Deep

well

turbine

pump

1 =

TR+DE

2 =

EL+TR+

DE

3 = EL

4 = SE

0 =

Unfit

1= Fit

2 =

Margin

ally Fit

Appendix-A9: Well drilling and depth of watertable in the study area

Depth of bore (m) Depth of wt (m) Depth of turbine (m) Decline in wt (m)

91.46 15.24 27.44 0.00

106.71 39.63 51.83 3.05

91.46 18.29 33.54 3.05

85.37 12.20 22.87 0.00

85.37 17.68 42.68 6.10

83.84 16.77 39.63 1.52

83.84 16.77 39.63 1.52

91.46 18.29 36.59 0.00

91.46 22.87 39.63 0.00

91.46 21.34 39.63 1.52

91.46 22.87 36.59 0.00

91.46 15.24 33.54 0.00

91.46 19.82 30.49 0.00

76.22 19.82 42.68 9.15

106.71 16.77 39.63 1.52

76.22 18.29 36.59 0.00

91.46 11.59 27.44 3.05

103.66 21.34 42.68 0.00

103.66 12.20 21.34 0.00

91.46 22.87 33.54 0.00

91.46 21.34 39.63 3.05

91.46 30.49 57.93 0.00

155

85.37 30.49 51.83 3.05

91.46 24.39 36.59 0.00

99.09 21.34 42.68 1.52

106.71 21.34 48.78 1.52

91.46 33.54 42.68 6.10

91.46 18.29 36.59 1.52

91.46 18.29 36.59 1.52

91.46 12.20 30.49 1.52

82.32 13.72 30.49 1.52

82.32 16.77 36.59 1.52

82.32 24.39 54.88 1.52

91.46 21.34 39.63 1.52

92.99 33.23 45.73 1.22

97.56 39.63 51.83 1.52

88.41 36.59 45.73 0.00

88.41 36.59 45.73 0.00

91.46 38.11 51.83 7.62

91.46 38.11 53.35 7.62

102.13 51.83 51.83 1.52

91.46 36.59 45.73 0.61

91.46 36.59 45.73 0.61

152.44 60.98 83.84 0.00

91.46 20.43 36.59 4.57

91.46 20.43 36.59 4.57

106.71 42.68 48.78 0.00

106.71 42.68 48.78 0.00

106.71 42.68 48.78 0.00

106.71 42.68 60.98 0.00

106.71 42.68 60.98 0.00

91.46 42.68 48.78 0.00

106.71 36.59 51.83 1.52

99.09 30.49 51.83 1.52

156

Appendix-A10: Method of irrigation and frequency of hill torrents occurrence in the

study area

Sr.

No.

Method of

irrigation

Frequency span of occurrence

of the hill torrent

Frequency of occurrence of

hill torrent during 2012

1 1 0 5

2 1 0 13

3 1 0 0

4 1 3 3

5 1 0 2

6 1 0 0

7 1 3 4

8 1 2 0

9 1 2 0

10 1 2 2

11 1 1 18

12 1 1 3

13 1 0 5

14 1 2 13

15 1 2 7

16 1 1 5

17 1 0 8

18 1 2 5

19 1 1 8

20 1 7 0

21 1 2 3

22 1 7 7

23 1 2 3

24 1 1 9

25 1 0 6

26 1 0 3

27 1 1 4

28 1 3 3

29 1 2 4

30 1 0 0

31 1 2 3

32 1 0 18

33 1 1 7

34 1 0 1

35 1 1 7

36 1 1 16

37 1 2 4

38 1 7 1

39 1 1 17

40 1 2 5

41 1 1 2

157

42 1 1 17

43 1 1 7

44 1 1 9

45 1 4 5

46 1 2 6

47 1 1 1

48 1 1 6

49 1 0 3

50 0 0 0

0 = N/A

1 = Bund

1 = Every year

2 = After two years

3 = After three years

4 = After four year

5 = After five or more years

158

APPENDIX-B

Appendix-B1: Discharge measurement of 6ʺx7ʺ centrifugal pumps installed at DG

canal for irrigation of the study area using cut-throat flume of 10x90cm size

Sr.

No.

Source of

power

Distance of

opening (km)

Ha

(m)

Hb

(m) S = Hb/Ha Ha-Hb

Q

(m3/s)

1 MF-240 Tractor 0.75 0.265 0.105 0.40 0.160 0.032

2 Peter Engine 0.25 0.300 0.120 0.40 0.180 0.041

3 Peter Engine 2 0.275 0.125 0.45 0.150 0.035

4 MF-240 Tractor 1.5 0.275 0.125 0.45 0.150 0.035

5 Peter Engine 0.25 0.310 0.160 0.52 0.150 0.043

6 MF-240 Tractor 0.5 0.330 0.185 0.56 0.145 0.048

7 MF-240 Tractor 0.25 0.350 0.250 0.71 0.100 0.051

8 MF-240 Tractor 1.07 0.265 0.195 0.74 0.070 0.031

9 MF-240 Tractor 3.05 0.265 0.223 0.84 0.043 0.028

10 MF-240 Tractor 0.25 0.435 0.370 0.85 0.065 0.069

Appendix-B2: Discharge measurement of the pumps installed in the study area

using cut-throat flume of 10x90cm size

Sr.

No. Source of power Ha (m) Hb (m) S = Hb/Ha Ha-Hb Q (m3/s)

Deep well turbine pump of 4ʺ delivery pipe

1 Peter engine 0.141 0.030 0.21 0.111 0.0101

2 Peter Engine 0.127 0.029 0.23 0.098 0.0083

3 Peter Engine 0.135 0.035 0.26 0.100 0.0093

4 MF-240 Tractor 0.160 0.116 0.73 0.044 0.0121

Deep well turbine pump of 5ʺ deliver pipe

1 MF-240 Tractor 0.159 0.030 0.19 0.129 0.0126

2 Peter engine 0.165 0.102 0.62 0.063 0.0135

3 Electric Motor 0.190 0.120 0.63 0.070 0.0175

4 MF-240 Tractor 0.165 0.111 0.67 0.054 0.0129

5 Electric Motor 0.235 0.170 0.72 0.065 0.0246

6 Peter Engine 0.145 0.125 0.86 0.020 0.0089

Deep well turbine pump of 6ʺ deliver pipe

1 Peter engine 0.260 0.146 0.56 0.114 0.0312

2 Tractor 0.217 0.135 0.62 0.082 0.0223

Submersible pump of 5ʺ delivery pipe

1 Electric Motor 0.270 0.220 0.81 0.050 0.0299

2 Electric Motor 0.260 0.190 0.73 0.070 0.0295

Submersible pump of 4ʺ delivery pipe

1 Electric Motor 0.225 0.128 0.57 0.097 0.0239

2 Electric Motor 0.236 0.165 0.70 0.071 0.0249

Appendix-B3: Discharge measurement of 2-submersible pumps of 2ʺ delivery pipe

dia. of each installed in the study area using volumetric method

Sr. No. Source of power Q (m3/s)

1 Solar energy system 0.007

2 Solar energy system 0.009

159

APPENDIX-C

Appendix-C1: Economic value of wheat crop cultivated in the study area

Total cost (Rs./ha) Yield (kg/ha) Total income (Rs./ha) Benefit/cost

74690.92 4447.80 114901.50 1.54

73013.11 3706.50 112430.50 1.54

59333.65 3953.60 130963.00 2.21

86823.53 4447.80 134916.60 1.55

79363.58 3212.30 96677.88 1.22

66331.52 3953.60 117125.40 1.77

83739.72 4694.90 155673.00 1.86

75802.87 3953.60 115148.60 1.52

77253.34 4942.00 148260.00 1.92

58903.70 1976.80 57821.40 0.98

91765.53 4447.80 134916.60 1.47

75802.87 3953.60 115148.60 1.52

92889.83 3459.40 102299.40 1.10

55619.74 2965.20 101311.00 1.82

79556.32 3706.50 97604.50 1.23

85281.62 4151.28 139364.40 1.63

68387.40 3953.60 103287.80 1.51

75802.87 3953.60 115148.60 1.52

77836.50 3953.60 130963.00 1.68

92131.24 3953.60 117619.60 1.28

95785.84 4447.80 148260.00 1.55

83420.96 3953.60 116137.00 1.39

81157.52 4942.00 143318.00 1.77

93823.87 3459.40 111195.00 1.19

68459.06 2485.83 70816.39 1.03

71093.14 2965.20 90932.80 1.28

Appendix-C2: Economic value of gram crop cultivated in the study area


39219.71 1976.80 77589.40 1.98

32263.85 1111.95 44725.10 1.39

37628.39 741.30 30640.40 0.81

27437.98 617.75 17914.75 0.65

43195.55 2006.45 81187.18 1.88

38021.28 1087.24 37262.68 0.98

41045.78 2100.35 80183.95 1.95

41342.30 1482.60 60292.40 1.46

56662.50 3459.40 143318.00 2.53

32177.36 2100.35 79133.78 2.46

41574.58 1976.80 75612.60 1.82

42100.90 1976.80 73635.80 1.75

160

26718.92 2965.20 123550.00 4.62

39311.14 1976.80 75612.60 1.92

30949.28 1976.80 81543.00 2.63

33469.70 1729.70 69929.30 2.09

35757.84 1976.80 77589.40 2.17

32118.06 1779.12 70077.56 2.18

38199.19 1729.70 68199.60 1.79

42958.34 1235.50 52508.75 1.22

38031.16 1482.60 61775.00 1.62

37554.26 1976.80 78577.80 2.09

43430.30 2471.00 93898.00 2.16

54386.71 2471.00 116137.00 2.14

47971.99 1976.80 82407.85 1.72

41942.75 1976.80 81543.00 1.94

32926.08 1976.80 73704.99 2.24

34319.72 2471.00 96369.00 2.81

39716.38 1976.80 77589.40 1.95

46553.64 2965.20 113666.00 2.44

62921.54 3953.60 155883.04 2.48

Appendix-C3: Economic value of brassica crop cultivated in the study area


26140.71 741.30 39536.00 1.51

24037.89 494.20 23474.50 0.98

25174.55 988.40 42007.00 1.67

29921.34 1111.95 55288.63 1.85

33914.48 988.40 81543.00 2.40

23210.10 790.72 32123.00 1.38

17810.97 617.75 32123.00 1.80

28243.53 1111.95 60539.50 2.14

21986.96 864.85 37065.00 1.69

25330.22 988.40 46949.00 1.85

13363.17 247.10 14826.00 1.11

Appendix-C4: Economic value of arugula crop cultivated in the study area


27484.93 1111.95 43613.15 1.59

20257.26 741.30 28416.50 1.40

Appendix-C5: Economic value of sorghum crop cultivated in the study area


45792.57 3953.60 157217.38 3.43

23400.37 988.40 47504.98 2.03

27811.11 864.85 49111.13 1.77

28913.17 1667.93 68879.13 2.38

161

31631.27 1030.41 49753.59 1.57

34102.27 1976.80 93959.78 2.76

27418.22 1532.02 52545.82 1.92

24645.75 1853.25 61466.13 2.49

28048.32 1976.80 78145.38 2.79

25673.69 1976.80 76168.58 2.97

23793.26 1482.60 48493.38 2.04

28651.25 1482.60 60354.18 2.11

33951.54 1976.80 76168.58 2.24

17736.84 741.30 39597.78 2.23

21445.81 1235.50 55906.38 2.61

32211.96 2223.90 90006.18 2.79

24658.11 1482.60 55906.38 2.27

29108.38 1482.60 61836.78 2.12

30657.70 1976.80 79072.00 2.58

21124.58 1606.15 51891.00 2.46

34020.73 1482.60 93898.00 2.76

34126.98 1976.80 78145.38 2.29

36345.94 1976.80 90191.50 2.48

Appendix-C6: Economic value of millet crop cultivated in the study area


24433.25 988.40 39536.00 1.62

21631.13 617.75 15443.75 0.71

22456.45 1334.34 40030.20 1.78

21989.43 1235.50 37065.00 1.69

20321.50 988.40 22733.20 1.12

27200.77 1976.80 59304.00 2.18

17882.63 988.40 27675.20 1.55

24781.66 1482.60 37065.00 1.50

30986.34 1976.80 54362.00 1.75

33301.67 1976.80 65234.40 1.96

24692.70 1729.70 38053.40 1.54

25641.57 1482.60 59304.00 2.31

20296.79 1235.50 32740.75 1.61

25473.54 1235.50 34594.00 1.36

30657.70 1976.80 59304.00 1.93

26422.40 988.40 49420.00 1.87

23669.71 988.40 29652.00 1.25

162

Appendix-C7: Economic value of guar crop cultivated in the study area


20450.00 432.43 26563.25 1.30

67636.21 1482.60 212506.00 3.14

Appendix-C8: Economic value of cotton crop cultivated in the study area


111078.86 2718.10 152893.13 1.38

108247.10 2619.26 163703.75 1.51

94214.29 1482.60 92662.50 0.98

94733.20 2471.00 142082.50 1.50

100957.65 1976.80 118608.00 1.17

121696.75 2594.55 155673.00 1.28

102862.79 2174.48 125032.60 1.22

Appendix-C9: Economic value of onion crop cultivated in the study area


280925.52 22683.78 426908.74 1.52

253166.31 12602.10 264644.10 1.05

212634.49 14826.00 324244.62 1.52

258474.01 24611.16 492223.20 1.90

303191.70 19768.00 434896.00 1.43

319423.70 23951.40 550882.27 1.72

347496.73 23474.50 617614.10 1.78

361371.40 20015.10 377885.09 1.05

310824.62 20459.88 625049.33 2.01

315546.70 27181.00 597982.00 1.90

303191.70 19768.00 434896.00 1.43

163

APPENDIX-D

Appendix-D1: Electrical conductivity and pH of hill torrent water samples

Sample No. EC (dS/m) pH

1 (at U/S of Darrah) 1.09 8.28

2 (at D/S of Darrah) 0.48 8.34

3 (at middle of the command area) 0.64 8.21

4 (at middle of the command area) 0.61 8.18

5 (from field at tail of command area) 0.73 7.91

6 (from field at tail of command area) 0.60 8.02

Appendix-D2: Water samples analysis of hill torrent flow

Sample No. Ca+Mg

(meL-1)

Na

(meL-1)

CO3

(meL-1)

HCO3

(meL-1)

Cl

(meL-1) SAR

RSC

(meL-1) Remarks

1 8.38 3.57 0.32 3.96 5.02 1.74 Nil Marginally Fit

2 3.42 2.34 Nil 2.14 2.10 1.79 Nil Fit

3 4.34 1.67 1.00 2.72 1.90 1.13 Nil Fit

4 4.02 2.12 0.40 2.89 1.76 1.50 Nil Fit

5 4.26 2.67 0.6 2.80 2.00 1.83 Nil Fit

6 4.04 1.80 Nil 3.90 1.04 1.27 Nil Fit

Appendix-D3: Electrical conductivity and pH of groundwater samples of the study

area

Sample No. EC (dS/m) pH

1 1.99 8.24

2 1.96 8.31

3 0.76 8.54

4 0.82 8.43

5 0.89 8.27

6 1.66 8.17

7 1.41 8.23

8 1.77 7.99

9 3.50 7.03

10 2.91 7.90

11 0.62 8.52

12 0.83 7.86

164

Appendix-D4: Groundwater samples analysis of the study area

Sample No. Ca+Mg

(meL-1)

Na

(meL-1)

CO3

(meL-1)

HCO3

(meL-1)

Cl

(meL-1) SAR

RSC

(meL-1) Remarks

1 10.92 7.18 0.80 8.76 6.34 3.07 Nil Unfit

2 10.38 8.00 1.20 6.62 8.14 3.51 Nil Unfit

3 5.70 2.14 1.00 4.27 1.04 1.27 Nil Fit

4 5.22 2.57 0.76 4.40 1.36 1.59 Nil Fit

5 7.38 1.02 0.80 3.80 2.40 0.53 Nil Fit

6 10.02 4.47 0.60 4.92 5.84 2.00 Nil Unfit

7 10.34 3.04 Nil 4.52 8.00 1.34 Nil Unfit

8 13.96 1.62 Nil 7.78 6.24 0.61 Nil Fit

9 14.10 3.78 0.60 5.76 7.38 1.42 Nil Unfit

10 20.90 6.90 0.82 16.38 7.32 2.13 Nil Unfit

11 5.74 6.44 0.60 4.34 0.70 3.80 Nil Fit

12 5.92 2.55 1.00 4.20 2.44 1.48 Nil Fit

Appendix-D5: Electrical conductivity of soil samples of the fields of study area,

(dS/m)

Field

No.

Sample depth of hill torrent water

irrigated fields (cm)

Sample depth of groundwater


0-15 15-30 30-45 0-15 15-30 30-45

A 1.10 0.96 1.07 1.09 1.09 1.26

B 0.80 0.73 0.64 1.00 0.81 0.96

C 0.81 0.77 0.84 0.92 0.79 0.81

D 0.86 0.87 0.88 1.70 1.72 1.26

E 0.85 0.99 1.40 1.76 1.62 0.99

F 0.49 0.27 0.24 0.37 0.39 0.38

G 1.18 0.88 0.84 1.23 0.97 1.38

H 0.83 0.73 1.03 0.96 1.05 1.19

I 0.84 0.76 0.81 1.01 1.07 1.20

J 0.85 0.94 0.91 1.80 1.74 1.54

K 0.79 0.77 0.65 1.27 1.41 1.40

L 0.68 0.51 0.49 1.85 1.81 1.70

165

Appendix-D6: pH of soil samples of the fields of study area

Field

No.





0-15 15-30 30-45 0-15 15-30 30-45

A 7.74 7.78 7.75 7.80 7.95 8.02

B 7.64 7.79 7.85 8.05 8.03 7.86

C 7.75 7.6 7.79 7.99 8.07 8.21

D 7.65 7.76 7.84 8.12 8.18 8.24

E 7.69 7.78 7.67 8.31 8.29 8.4

F 7.78 7.98 7.70 8.40 8.03 8.69

G 7.61 7.84 7.86 8.12 8.24 7.84

H 7.68 7.98 7.97 8.16 8.24 8.28

I 7.70 7.75 7.74 8.25 8.31 8.50

J 7.30 7.63 7.77 8.45 8.30 8.70

K 7.61 7.60 7.72 8.39 8.28 8.50

L 7.56 7.68 7.73 8.41 8.26 8.52

Appendix-D7: Na concentration in soil samples of the fields of study area, (me/liter)

Field

No.





0-15 15-30 30-45 0-15 15-30 30-45

A 4.60 2.14 2.49 9.32 5.36 1.39

B 1.88 2.92 0.66 2.30 0.36 6.61

C 0.37 2.90 0.36 6.53 2.69 6.45

D 4.93 2.88 3.17 13.72 14.04 13.41

E 3.19 8.03 1.14 15.83 15.96 16.10

F 5.49 2.04 1.77 5.37 5.00 5.22

G 0.71 7.49 1.10 7.18 5.32 6.43

H 1.58 1.51 2.41 7.96 5.36 7.07

I 2.12 2.25 2.38 15.04 14.34 12.13

J 0.40 1.91 1.95 8.16 7.92 6.74

K 1.87 1.33 0.97 10.38 9.28 9.71

L 2.30 2.98 1.56 13.48 10.29 11.45

166

Appendix-D8: Ca+Mg concentration in soil samples of the fields of study area,

(me/liter)

Field

No.





0-15 15-30 30-45 0-15 15-30 30-45

A 4.80 5.85 6.50 3.35 4.52 4.28

B 4.95 4.08 5.06 4.10 1.70 7.18

C 2.85 3.64 3.70 4.82 4.05 4.20

D 4.45 4.80 5.15 9.62 12.16 7.09

E 6.47 10.92 3.12 6.07 8.05 10.03

F 4.98 5.20 3.65 3.63 3.12 3.55

G 5.58 4.07 4.20 9.42 8.74 10.52

H 7.10 3.20 3.02 3.92 7.80 6.26

I 4.34 3.98 3.88 8.98 8.23 7.92

J 4.19 4.93 3.78 7.92 8.00 7.73

K 3.87 5.96 3.66 9.45 10.31 9.63

L 5.64 4.71 3.76 9.65 11.00 9.99

Appendix-D9: Cl concentration in soil samples of the fields of study area, (me/liter)

Field

No.





0-15 15-30 30-45 0-15 15-30 30-45

A 4.74 5.10 5.00 8.10 4.04 2.20

B 3.26 2.80 3.70 3.64 1.00 5.20

C 0.70 3.00 2.70 6.00 3.00 5.70

D 4.28 2.84 3.80 15.88 21.76 10.00

E 5.86 6.70 2.10 14.00 13.50 13.00

F 6.70 3.82 1.52 5.00 3.10 3.20

G 4.00 5.74 2.00 5.70 6.10 5.30

H 4.44 2.16 3.00 5.00 4.78 8.40

I 3.46 3.67 2.98 7.22 8.35 6.53

J 5.01 5.23 4.83 11.50 12.03 7.76

K 3.57 2.91 3.02 9.54 7.85 6.81

L 4.11 3.78 3.27 6.00 5.78 7.00

167

Appendix-D10: CO3 concentration in soil samples of the fields of study area,

(me/liter)

Field

No.





0-15 15-30 30-45 0-15 15-30 30-45

A Nil Nil Nil Nil Nil Nil

B Nil Nil Nil Nil Nil Nil

C Nil Nil Nil Nil Nil Nil

D Nil Nil Nil Nil Nil Nil

E Nil Nil Nil Nil Nil Nil

F Nil Nil Nil Nil Nil Nil

G Nil Nil Nil Nil Nil Nil

H Nil Nil Nil Nil Nil Nil

I Nil Nil Nil Nil Nil Nil

J Nil Nil Nil Nil Nil Nil

K Nil Nil Nil Nil Nil Nil

L Nil Nil Nil Nil Nil Nil

Appendix-D11: HCO3 concentration in soil samples of the fields of study area,

(me/liter)

Field

No.





0-15 15-30 30-45 0-15 15-30 30-45

A 3.50 1.22 1.54 2.58 3.08 2.00

B 2.24 2.62 1.72 2.00 0.90 5.62

C 1.74 1.84 1.80 3.56 2.60 3.56

D 2.80 3.00 2.46 9.76 10.96 8.56

E 3.54 6.98 1.60 5.78 5.85 5.92

F 2.26 2.06 3.08 3.36 3.78 3.06

G 2.22 3.92 2.44 7.66 7.98 7.94

H 3.36 1.60 1.60 4.72 4.94 3.78

I 2.21 2.67 1.97 6.93 7.60 5.87

J 1.89 1.79 1.80 8.90 7.65 6.98

K 2.00 1.90 1.88 9.17 10.00 9.67

L 2.40 2.13 1.99 6.87 5.98 5.56

168

Appendix-D12: SAR of soil samples of the fields of study area

Field

No.





0-15 15-30 30-45 0-15 15-30 30-45

A 2.97 1.25 1.38 7.20 3.57 0.95

B 1.20 2.04 0.41 1.61 0.39 3.49

C 0.31 2.15 0.26 4.21 1.89 4.45

D 3.31 1.86 1.98 6.26 5.69 7.12

E 1.77 3.44 1.15 9.09 7.96 7.19

F 3.48 1.27 1.31 3.99 4.00 3.92

G 0.43 5.25 0.76 3.31 2.54 2.80

H 0.84 1.19 1.96 5.69 2.71 4.00

I 1.44 1.59 1.71 7.10 7.07 6.10

J 0.28 1.22 1.42 4.10 3.96 3.43

K 1.34 0.77 0.72 4.78 4.09 4.43

L 1.37 1.94 1.14 6.14 4.39 5.12

Appendix-D13: RSC concentration in soil samples of the fields of study area,

(me/liter)

Field

No.





0-15 15-30 30-45 0-15 15-30 30-45

A Nil Nil Nil Nil Nil Nil

B Nil Nil Nil Nil Nil Nil

C Nil Nil Nil Nil Nil Nil

D Nil Nil Nil 0.14 Nil 1.47

E Nil Nil Nil Nil Nil Nil

F Nil Nil Nil Nil 0.66 Nil

G Nil Nil Nil Nil Nil Nil

H Nil Nil Nil 0.80 Nil Nil

I Nil Nil Nil Nil Nil Nil

J Nil Nil Nil 0.98 Nil Nil

K Nil Nil Nil Nil Nil 0.04

L Nil Nil Nil Nil Nil Nil

169

APPENDIX-E

Appendix-E1: Observed watertable data of selected observation wells at selected hill torrent command area, (m)

Date of observation OW-1 OW-2 OW-3 OW-4 OW-5 OW-6 OW-7 OW-8 OW-9

03.06.2012 116.03 114.41 113.06 113.83 111.67 110.40 111.50 111.20 116.45

10.06.2012 116.05 114.42 113.01 113.84 111.67 110.41 111.49 111.18 116.45

17.06.2012 116.06 114.43 112.92 113.84 111.68 110.42 111.47 111.14 116.45

24.06.2012 116.13 114.46 112.79 113.86 111.68 110.43 111.44 111.11 116.46

01.07.2012 116.21 114.35 112.67 113.87 111.69 110.43 111.49 111.03 116.47

08.07.2012 116.27 114.61 112.49 113.83 111.48 110.40 111.41 111.09 116.47

15.07.2012 116.32 114.66 112.48 113.85 111.41 110.40 111.44 111.16 116.47

22.07.2012 116.36 114.75 112.51 113.86 111.42 110.44 111.48 111.19 116.48

29.07.2012 116.38 114.79 112.47 113.83 111.34 110.42 111.49 111.20 116.47

05.08.2012 116.21 114.10 112.49 113.79 111.08 110.39 111.37 110.90 116.46

12.08.2012 116.34 114.73 112.47 113.73 110.99 110.34 111.39 111.11 116.47

19.08.2012 116.31 114.61 112.50 113.62 110.88 110.31 111.26 111.02 116.43

26.08.2012 116.28 114.48 112.51 113.60 110.80 110.28 111.02 110.93 116.40

02.09.2012 116.21 113.94 112.44 113.73 110.69 110.22 110.77 110.81 116.37

09.09.2012 116.16 114.18 112.44 113.56 110.88 110.31 110.71 110.68 116.37

16.09.2012 116.16 114.11 112.43 113.67 111.01 110.37 110.66 110.61 116.38

23.09.2012 116.13 113.99 112.41 113.69 111.05 110.39 110.58 110.51 116.37

30.09.2012 116.10 113.84 112.38 113.70 111.10 110.40 110.50 110.40 116.36

07.10.2012 116.05 113.78 112.37 113.60 110.24 109.46 108.96 110.26 116.32

14.10.2012 116.05 113.78 112.18 113.60 110.36 109.96 109.77 110.31 116.37

21.10.2012 116.05 113.64 112.37 113.55 109.24 109.46 108.96 110.26 116.38

28.10.2012 116.06 113.49 112.38 113.48 110.10 108.90 108.96 110.15 116.34

04.11.2012 115.74 113.30 112.30 113.40 110.10 108.75 108.72 109.17 116.30

170


11.11.2012 115.74 113.30 112.40 113.33 110.91 108.05 108.97 109.17 116.28

18.11.2012 115.67 113.30 112.38 113.25 110.10 107.79 108.36 109.08 116.31

25.11.2012 115.59 113.33 112.36 113.21 109.14 108.27 107.68 108.99 116.35

02.12.2012 115.30 112.90 112.25 113.15 109.80 108.44 108.46 109.12 116.34

09.12.2012 115.60 113.40 112.46 113.15 110.78 106.94 108.90 108.99 116.48

16.12.2012 115.56 113.42 112.45 113.10 110.59 107.48 109.35 109.36 116.49

23.12.2012 115.37 113.21 112.47 112.52 110.80 109.01 110.08 109.75 116.49

30.12.2012 115.10 112.99 112.46 113.00 110.92 108.38 109.62 109.52 116.48

06.01.2013 114.71 112.82 112.20 112.53 109.69 108.30 108.38 109.07 116.38

13.01.2013 114.64 112.60 112.42 112.53 111.10 107.01 108.77 109.07 116.44

20.01.2013 114.00 112.61 112.35 112.54 110.97 107.97 109.08 109.42 116.42

27.01.2013 113.32 112.83 112.27 112.54 110.82 108.92 109.42 109.78 116.41

03.02.2013 114.70 112.76 112.27 112.15 109.80 108.44 108.30 109.22 116.41

10.02.2013 114.26 113.35 112.32 112.15 111.12 109.25 109.61 109.88 116.45

17.02.2013 115.17 113.62 112.25 112.90 111.19 109.32 109.66 109.93 116.46

24.02.2013 114.60 113.84 112.27 112.50 111.25 109.50 109.67 109.99 116.48

03.03.2013 115.00 112.89 112.38 112.14 109.90 109.50 108.39 109.35 116.49

10.03.2013 114.31 113.84 111.85 111.77 109.76 108.81 108.65 108.98 116.51

17.03.2013 113.76 113.85 112.30 111.76 109.05 108.44 108.23 109.26 116.52

24.03.2013 115.36 113.90 112.33 112.55 109.89 108.86 108.72 109.53 116.53

31.03.2013 115.60 113.93 112.34 113.14 110.57 109.31 109.14 109.80 116.53

07.04.2013 115.45 113.08 112.46 113.13 110.80 110.20 109.23 110.50 116.55

14.04.2013 115.60 114.00 112.43 113.40 111.46 110.08 109.95 110.27 116.56

21.04.2013 115.17 114.02 112.46 113.47 111.66 110.20 110.23 110.50 116.56

171


28.04.2013 115.10 113.86 112.52 113.48 111.22 110.29 110.70 110.58 116.56

05.05.2013 115.86 113.30 112.65 113.50 110.90 110.52 110.42 110.77 116.57

12.05.2013 115.75 113.13 112.63 113.50 110.65 110.45 111.23 110.72 116.57

19.05.2013 115.86 112.87 112.65 113.50 110.43 110.52 111.42 110.77 116.57

26.05.2013 115.84 113.50 112.64 113.55 110.81 110.54 111.34 110.77 116.57

02.06.2013 116.00 114.10 112.65 113.57 111.02 110.58 111.21 110.77 116.59

09.06.2013 115.83 114.09 112.63 113.58 111.20 110.58 111.22 110.73 116.57

16.06.2013 115.95 114.10 112.62 113.57 111.31 110.58 111.21 110.69 116.57

23.06.2013 116.00 114.10 112.62 113.57 111.40 110.58 111.23 110.65 116.58

30.06.2013 116.05 114.10 112.64 113.58 111.45 110.58 111.22 110.61 116.59

07.07.2013 116.08 114.38 112.65 113.57 110.78 110.49 111.21 110.74 116.57

14.07.2013 116.20 114.11 112.66 113.53 111.04 110.67 111.22 110.60 116.59

21.07.2013 116.30 114.10 112.67 113.48 110.53 110.76 111.21 110.62 116.58

28.07.2013 116.28 114.14 112.67 113.36 110.24 110.85 111.21 110.64 116.57

04.08.2013 116.00 114.28 112.60 113.50 110.49 110.32 111.00 110.60 116.57

11.08.2013 115.98 113.95 112.59 113.47 111.70 108.84 110.90 110.32 116.57

18.08.2013 115.94 114.24 112.70 113.47 111.42 110.82 110.61 109.73 116.48

25.08.2013 116.00 114.14 112.65 113.17 110.60 110.39 110.52 110.17 116.47

01.09.2013 115.94 114.03 112.50 113.39 109.28 109.73 110.33 110.41 116.50

08.09.2013 116.10 113.76 112.57 113.39 109.36 109.98 109.45 110.14 116.48

15.09.2013 116.15 113.46 112.55 113.22 108.95 109.65 108.77 109.85 116.49

22.09.2013 116.20 113.58 112.55 113.31 109.20 109.26 108.89 109.86 116.49

29.09.2013 116.25 113.69 112.57 113.38 109.41 108.85 109.02 109.87 116.48

06.10.2013 116.00 113.75 112.40 113.20 108.90 108.36 109.12 109.88 116.47

13.10.2013 116.25 113.26 112.58 113.44 109.71 107.94 108.96 109.83 116.46

172


20.10.2013 116.20 112.98 112.56 113.46 109.84 107.55 108.79 109.78 116.45

27.10.2013 116.10 112.56 112.57 113.43 110.19 107.73 108.60 109.67 116.41

03.11.2013 115.94 112.96 112.25 112.40 108.78 108.09 108.79 109.78 116.33

10.11.2013 115.50 112.09 112.56 112.30 109.98 108.09 108.26 109.45 116.35

17.11.2013 114.81 111.96 111.96 111.20 109.39 108.28 108.09 109.34 116.33

24.11.2013 114.85 111.97 112.10 111.40 109.02 108.46 107.99 109.20 116.32

01.12.2013 115.30 112.38 112.10 111.77 108.67 108.00 108.40 109.20 116.29

08.12.2013 114.95 112.38 112.12 111.99 109.28 108.63 107.83 109.19 116.31

15.12.2013 115.00 112.02 112.12 111.90 109.40 108.82 108.05 109.31 116.30

22.12.2013 116.05 112.03 112.13 111.79 109.53 109.00 108.40 109.42 116.28

29.12.2013 114.05 112.05 112.13 111.80 109.69 109.19 108.68 109.53 116.27

05.01.2014 114.90 112.13 111.89 111.69 109.00 108.02 108.29 109.10 116.26

12.01.2014 115.10 112.08 112.12 111.77 109.89 109.43 109.02 109.75 116.24

19.01.2014 114.60 112.06 111.99 111.20 109.63 109.16 109.00 109.65 116.26

26.01.2014 113.75 112.05 111.70 110.97 109.43 109.01 108.87 109.54 116.29

02.02.2014 114.70 112.31 111.84 111.80 109.28 108.11 108.60 109.00 116.29

09.02.2014 113.80 111.99 111.55 110.79 109.04 108.60 108.71 109.23 116.30

16.02.2014 113.95 111.98 111.64 110.78 108.79 108.29 108.64 109.03 116.30

23.02.2014 114.00 111.97 111.79 110.80 108.41 108.08 108.60 108.82 116.29

02.03.2014 114.89 112.57 111.96 112.10 109.67 108.20 108.84 109.40 116.32

09.03.2014 114.75 111.92 111.76 111.70 108.97 107.71 109.00 109.00 116.21

16.03.2014 114.89 111.89 111.56 111.77 109.84 107.98 109.19 109.39 116.11

23.03.2014 115.30 112.65 111.85 111.88 110.31 108.19 109.30 109.76 116.23

30.03.2014 115.72 113.61 112.20 112.89 110.77 108.35 109.31 109.99 116.34

06.04.2014 115.30 113.40 112.12 112.30 110.77 108.62 109.76 109.99 116.34

173


13.04.2014 115.59 113.66 112.19 112.87 111.13 108.32 109.97 110.21 116.34

20.04.2014 115.56 113.68 112.24 112.90 111.19 108.32 110.20 110.25 116.35

27.04.2014 115.51 113.69 112.25 112.91 111.25 109.31 110.51 110.27 116.35

04.05.2014 115.58 113.56 112.17 112.80 111.01 109.33 110.41 110.16 116.34

11.05.2014 115.66 113.47 112.15 112.82 110.86 109.35 110.35 110.11 116.34

18.05.2014 115.74 113.44 112.14 112.85 110.83 109.38 110.32 110.10 116.35

25.05.2014 115.83 113.42 112.13 112.87 110.78 109.39 110.31 110.08 116.36

01.06.2014 115.58 113.56 112.17 112.80 111.01 109.33 110.41 110.16 116.34

i

APPENDIX-F

Appendix-F1: Elevation of the top of soil surface of study area wart. mean sea level,

(m) 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32

227 225 223 221 219 217 215 213 211 209 207 205 203 201 199 197 196 194 192 190 188 186 184 182 180 178 176 174 172 170 168 166

223 222 220 218 216 214 212 210 208 206 204 202 200 199 197 195 193 191 189 187 185 183 181 179 178 176 174 172 170 168 166 164

220 218 216 214 212 211 209 207 205 203 201 199 198 196 194 192 190 188 187 185 183 181 179 177 175 174 172 170 168 166 164 162

216 214 213 211 209 207 205 204 202 200 198 197 195 193 191 189 188 186 184 182 180 179 177 175 173 171 170 168 166 164 163 161

213 211 209 207 206 204 202 200 199 197 195 194 192 190 188 187 185 183 181 180 178 176 175 173 171 169 168 166 164 162 161 159

209 207 206 204 202 201 199 197 196 194 192 191 189 187 186 184 182 181 179 177 176 174 172 171 169 167 166 164 162 161 159 157

205 204 202 201 199 197 196 194 192 191 189 188 186 184 183 181 180 178 176 175 173 172 170 168 167 165 164 162 160 159 157 156

202 200 199 197 196 194 192 191 189 188 186 185 183 182 180 179 177 175 174 172 171 169 168 166 165 163 162 160 158 157 155 154

198 197 195 194 192 191 189 188 186 185 183 182 180 179 177 176 174 173 171 170 168 167 165 164 162 161 159 158 157 155 154 152

195 193 192 190 189 187 186 185 183 182 180 179 177 176 175 173 172 170 169 167 166 165 163 162 160 159 157 156 155 153 152 150

191 190 188 187 185 184 183 181 180 179 177 176 174 173 172 170 169 168 166 165 164 162 161 160 158 157 155 154 153 151 150 149

187 186 185 183 182 181 179 178 177 176 174 173 172 170 169 168 166 165 164 162 161 160 159 157 156 155 153 152 151 149 148 147

184 182 181 180 179 177 176 175 174 172 171 170 169 167 166 165 164 162 161 160 159 157 156 155 154 153 151 150 149 148 146 145

180 179 178 177 175 174 173 172 171 169 168 167 166 165 163 162 161 160 159 157 156 155 154 153 152 150 149 148 147 146 145 143

176 175 174 173 172 171 170 169 167 166 165 164 163 162 161 160 158 157 156 155 154 153 152 151 150 148 147 146 145 144 143 142

173 172 171 170 169 168 166 165 164 163 162 161 160 159 158 157 156 155 154 153 151 150 149 148 147 146 145 144 143 142 141 140

169 168 167 166 165 164 163 162 161 160 159 158 157 156 155 154 153 152 151 150 149 148 147 146 145 144 143 142 141 140 139 138

166 165 164 163 162 161 160 159 158 157 156 155 154 153 152 151 150 150 149 148 147 146 145 144 143 142 141 140 139 138 137 136

162 161 160 159 158 158 157 156 155 154 153 152 151 150 150 149 148 147 146 145 144 143 143 142 141 140 139 138 137 136 136 135

158 158 157 156 155 154 153 153 152 151 150 149 148 148 147 146 145 144 143 143 142 141 140 140 139 138 137 136 135 135 134 133

155 154 153 153 152 151 150 149 149 148 147 146 146 145 144 143 143 142 141 140 139 139 138 137 137 136 135 134 133 133 132 131

151 151 150 149 148 148 147 146 146 145 144 143 143 142 141 141 140 139 138 138 137 136 136 135 134 134 133 132 132 131 130 129

148 147 146 146 145 144 144 143 142 142 141 140 140 139 139 138 137 137 136 135 135 134 134 133 132 132 131 130 130 129 128 128

144 143 143 142 142 141 140 140 139 139 138 138 137 136 136 135 135 134 133 133 132 132 131 131 130 129 129 128 128 127 127 126

140 140 139 139 138 138 137 137 136 136 135 135 134 133 133 132 132 131 131 130 130 129 129 128 128 127 127 126 126 125 125 124

137 136 136 135 135 134 134 133 133 133 132 132 131 131 130 130 129 129 128 128 127 127 127 126 126 125 125 124 124 123 123 122

133 133 132 132 132 131 131 130 130 129 129 129 128 128 127 127 127 126 126 125 125 125 124 124 124 123 123 122 122 122 121 121

130 129 129 129 128 128 127 127 127 126 126 126 125 125 125 124 124 124 123 123 123 122 122 122 121 121 121 120 120 120 119 119

126 126 125 125 125 124 124 124 124 123 123 123 122 122 122 122 121 121 121 121 120 120 120 119 119 119 119 118 118 118 117 117

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