Vol. 1 Issue 4, pp: (79-91), July 2016. Available online at: http://www.prudentjournals.org/IRJAFS

Full Length Research Paper

Assessment of Irrigation Performance Using Remote Sensing Technique at Tono irrigation

Area in the Upper East Region of Ghana

Jerry Asaana1 and Adams Sadick2*

1Bolgatanga Polytechnic, Bolgatanga, Ghana.

2Department of Soil Chemistry and Mineralogy, Soil Research Institute, Kumasi, Ghana.

*Corresponding author. E-mail: a.sadick@csir-soilresearch.org

Received 25 February, 2016; Accepted 14 June, 2016.

ABSTRACT A research was conducted at Tono irrigation system in the Upper East Region of Ghana to evaluate

the irrigation performance of the system based on some selected indicators with the help of GIS and

Remote Sensing Techniques. The indicators, namely Overall Consumed Ratio (OCR), Relative

Water Supply (RWS), Relative Evapotranspiration (RET), Depleted Fraction (DF) and Crop Water

Deficit (CWD) were used at 3 command areas, Bonia, Korania and Chuchuliga. Potential

evapotranspiration and actual evapotranspiration were estimated with Penman Monteith method and

Surface Energy Balance System (SEBS) using Aster Satellite image, respectively. The seasonal

average values of the irrigation performance indicators showed that water delivery system at Tono

irrigation project based on the selected command areas is poor. Assessment of the irrigation

performance of the other command areas is highly recommended.

Keywords: Irrigation Performance, Remote Sensing, Aster Image, Evapotranspiration.

INTRODUCTION

Sufficient availability of fresh water in terms of

quality and quantity has been a major problem

over the years (. Management of fresh water

resources in many countries has emerged as

one of the significant challenges of waters

users, planners and all concerned. The position

of water as a social, economic and life

supporting good should be reflected in demand

management mechanisms and be implemented

through resource evaluation, water conservation

and reuse (FAO, 1996).

Irrigation is exceptionally the largest sector that

uses water. It is an area where a significant

amount of fresh water is needed. About 70

percent of the world’s total withdrawals of water

are for irrigation, and it contributes to 30-40

percent of the world’s food production.

Therefore the use of fresh water resources

requires efficient methods and management.

Significant production of agricultural fields does

not depend upon larger volume of water

supplied to the field, but the quality and the

amount required by the crop. The excessive

International Research Journal of Agricultural and Food Sciences Article Number: PRJA65801986 Copyright ©2016 Author(s) retain the copyright of this article Author(s) agree that this article remain permanently open access under the terms of the Creative Commons

Attribution 4.0 International License.

supply of water to the agricultural fields may

cause flood leading to low yield (Bastiaanssen

et al., 2000).

Irrigation project started after Ghana’s

independence, under the management of many

government and quasi-government bodies

(Gyarteng, 1994). Due to mismanagement, the

conservation of the irrigation dams in the

country became very low in the 1960’s. This is

evidenced in the rather small size of the canals

provided in dams constructed especially in the

upper east region of Ghana where climatic

conditions are rather harsh. The management

of irrigation projects according to Gyarteng,

1994, began with the Land Planning and Soil

Conservation Unit in the Ministry of Food

Agriculture (MOFA). During 1965 and 1974, the

unit was put under the Irrigation, Reclamation

and Drainage Division of MOFA. This division

was changed to the Irrigation Department of

MOFA from 1974-1977.

In Ghana, there are few irrigation projects to

support farming activities to improve food

production ensure food security (Adams et al.,

2014). There are many areas with great

potentials to benefit from dams which can be

used for irrigation to enhance agricultural

activities in the country (Adams et al., 2014).

This has not been the case currently, and those

that exist, not much research have been done

on the water usage and it implication on soil

fertility and agricultural production.

The main objective of this research was to

determine the irrigation performance of Tono

irrigation scheme based on some parameters

with the help of GIS and remote sensing.

MATERIALS AND METHOD

Location and Climate of the Study Area

The project is located in the guinea savannah

ecological zone of Ghana and is located in the

Upper East Region and lying between latitude

10° 45’N and longitude 1° W. It has a potential

area of about 3840ha with a developed area of

about 3450ha. The project area comprises eight

(8) command areas, namely Bonia, Gaani,

Korania, Wuru, Yigania, Yigwania, and

Chuchuliga zone A and B. (Adams et al., 2014)

as shown in figure 1

Figure 1: Map of Ghana showing the location of Tono Irrigation Area

80 Int. Res. J. Agric. Food Sci.

The total annual rainfall in the study area is

around 950mm which normally starts in May,

reach a peak in August then drop sharply in

October Figure 2. Thereafter, there is a long dry

season period from November to the end of

April during which period only negligible amount

of rain is received (Adams et. al. 2014)

Figure 2: Average rainfall distribution of Tono Irrigation Area

Average monthly temperatures remain high throughout the year only falling around 26oC in August and September at Navrongo (Figure 3). March and April experience the hottest months recording nearly 32oC. Absolute minimum

temperature of around 16oC is usually recorded in December or January with absolute maximum temperatures of about 35oC recorded in March and April (Adams et. al. 2014).

Figure 3: Average temperature distribution of Tono Irrigation Area

Relative humidity for the study area is high during rainy season in particular, from July to September, and low in the dry season period from January to February as presented in

figure 4. Usually, humidity during the noon to 15:00 hour’s period may be 20 to 30 percent lower than at 09:00 hours (Adams et. al. 2014).

Asaana and Sadick 81

Figure 4: Average temperature distribution of Tono Irrigation Area

It has a potential area of about 3840ha with a developed area of about 3450ha (the developed area is the same as the irrigable area). The source of water in the dam is from the river Tono and rain-fed.

The irrigation system is based on gravity flow (Furrow irrigation), but the surrounding villages also extract water from the reservoir using pumping machine for domestic purpose. The office of the Tono irrigation project does not have official records on how much water is used for domestic purpose.

The top of dam embankment and wave wall are 182.57m and 183.20m (Picture 1). The gross storage capacity of the reservoir is 7574ha-metre and the dead water capacity is 2097ha-metre. The system has a maximum emergency discharge capacity of 8.4m3/s. The spillway level is 179.22 and beyond this level the water spill over. The spill over is normally observed between August and September. In 2007, the spill over was significant and this was due to high rainfall in the month of August.

Picture 1: Showing Tono Reservoir

82 Int. Res. J. Agric. Food Sci.

The canal system is divided into three groups: main canal, lateral and sub-lateral. The main canal consists of Right and Left bank canal which have lengths of approximately 8.83km and 12.15km. The lateral and sub-lateral have lengths of approximately 44.8km and 42.2km. During the field visit it was revealed that most of the laterals leading to command areas were

broken down and large volumes of water were wasted (Picture 2).

The main canal which stretches from the reservoir to all command areas had been rehabilitated and plans were far advance to rehabilitate the laterals at the time of visit (Picture 2).

Picture 2: Showing Broken Laterals

Picture 3: Showing Rehabilitated Main Canal

Asaana and Sadick 83

Irrigation Performance

Irrigation schemes need to be more productive, equitable and sustainable. Irrigation is outstandingly the largest area of water consumption. So, unless efficient use of water comes into practice in irrigation schemes, water resource management is simply out of the question. To understand the efficiency of the irrigation systems, irrigation performance analysis was determined according to the following indicators of overall consumed ratio (OCR), relative water supply (RWS), relative evapotranspiration (RET), Depleted Fraction (DF) and Crop Water Deficit (CDW) (Bastiaanssen et al., 2001) The indicators help to describe the efficiency of the irrigation schemes by means of indicators related to a reference (Bastiaanssen et al., 2001). In this study, irrigation performance was assessed using the data obtained in 2008 (Figure 5).

The overall consumed ratio (OCR) which defines the efficiency of the scheme, quantifies the degree to which the crop irrigation requirements are met by irrigation water in the irrigated area (Bos and Nugteren, 1974; Willardson et al., 1994). The ratio is defined as:

1

Where ETc = Potential crop evapotranspiration (mm/day), Peff = Effective rainfall (mm) was calculated using USDA soil conservation method and V = Irrigation supply (mm). A target overall consumed ratio should be set within an existing irrigated area, and compared to the actual ratio on a monthly and seasonal basis 1.0, can be accepted as the target value at the field level in the conditions of study area (Bos et al., 2005).

The relative water supply (RWS), used as an indicator of adequacy of irrigation water delivery, compares the amount of the water supply with that of water demand. It is the ratio of total water supply (i.e., irrigation + total rainfall) to total water demand by crop (i.e., potential crop evapotranspiration, ETc). It is computed as:

2

Where P = Total rainfall and ETc = Potential crop evapotranspiration in millimetres. The target value of RWS indicator was considered 2.0 (Molden et al., 1998).

To evaluate the adequacy of irrigation water delivery to a selected command area as a function of time, the dimensionless ratio of ETa over ETc gives valuable information to the water user/manager and is described as relative evapotranspiration (RET). It is a ratio of ETa to ETc.

3

Higher value of relative evapotranspiration tells that

crop is in lesser stress. A value of RET ≥ 0.75 is quite acceptable for irrigated agriculture in the growing season, although this is not constant over time (Molden et al., 1998).

The depleted fraction (DF) is defined as the fraction of available water that is depleted and not available for other water consumption processes. The depletion in an irrigation scheme is governed by ETa. DF is estimated as follows (Molden, 1997):

4

Where ETa is actual evapotranspiration in millimetres. DF should be considered a function of time. For semi-arid and arid regions, the threshold value of the depleted fraction averages about 0.6 (Bos et al., 2005). 0.6-1.1 is accepted range for DF (Bastiaanssen et al., 2001).

Crop water deficit (CWD) over a period is determined by the difference between ETc and ETa of the cropping pattern within an area. The period used is 1 month. An average CWD of 30mm/month is accepted as the critical. CWD is defined as follows (Bastiaanssen et al., 2001)

5

84 Int. Res. J. Agric. Food Sci.

Figure 5: Flow Chart for Determining Irrigation Performance

Estimation of Evapotranspiration using ASTER satellite data and Penman Monteith Methods

Aster images (Path-194/Row-053) covering the whole study area with the dates of 15th November and 10th December 2008, 15th January, 15th February, 11th March and 20th April 2009, the irrigation period (dry season) of

the study area, were acquired, and downloaded from the website (http://earthexplorer.usgs.gov ) These acquisition dates had a Julian day of 329 and almost the same over pass time.

ASTER data is used herein this study for remote sensing analyses and its characteristics are given in Table 1 below.

TABLE 1: ASTER data characteristics used in this study.

Spectral range Number of Bands Spatial Resolution(m)

Visible-Near (VNIR) 3 (1, 2, 3n) 15

Shortwave infrared

(SWIR)

6 (4, 5, 6, 7, 8, 9) 30

Thermal infrared (TIR) 5 (10, 11, 12, 13, 14) 60

Description of coordinate systems used in all of the maps and images in this study were UTM and WGS 84.

Aster level-1B images used in the study were imported into ILWIS software, pre-processed in order to correct geometric distortions, calibrate the data radiometrically and to eliminate the noise and clouds present in the data (Su et al., 2001). After the images were pre-processed, ETa maps were obtained using ILWIS software

according to Surface Energy Balance System (SEBS). The ETa of the study area for the irrigation period (dry season) was estimated (Figure 6 and 7) from the generated maps for each month and this was added up to get the ETa value for the whole irrigation period (Su et al., 2001). Three command areas namely, Bonia, Korania and Chuchuliga were considered in the study.

Asaana and Sadick 85

Figure 6: Flow Chart for estimating ETa from SEBS

Figure 7: Daily actual Evapotranspiration of the Study Area for November 15

The reference crop evapotranspiration, which is the potential evapotranspiration of a well-watered grass crop with an assumed height of

0.12m, a fixed surface resistance of 70s/m and an albedo of 0.23 (Allen et al., 1998), was estimated first using Penman-Monteith method

86 Int. Res. J. Agric. Food Sci.

and multiplied crop coefficient of each crop of the study area to get potential crop

evapotranspiration. The Penman-Monteith method is given by the relation:

Where: ETo= Reference crop evaporation (mmday-1)

Rn = Net radiation at the crop surface (MJm -2day-1)

G = Soil heat flux density (MJm -2day-1)

T = Mean daily air temperature at 2m height (°C)

U2= Wind speed at 2m height (ms-1)

Saturated vapor pressure (kPa)

Actual vapor pressure (kPa)

Saturated vapor pressure deficit (kPa)

Slope vapor pressure curve (kPa°C-1)

Psychrometric constant (kPa°C-1)

Therefore Potential crop evapotranspiration (mm/day) is given by:

Where Kc is crop coefficient

Kc is specific for a particular crop and varies as local climatic condition varies. The single crop coefficient approach is used here to determine Kc. This was calculated for each crop on the field in each month and added together to get the total ETc. The double crop coefficient approach is impossible here because of lack of daily water balance data for the surface soil layer. The standard crop coefficient (Kc) values of each growing stage for each crop was selected from FAO-56 document, table 12.

Figure 8: Flow Chart for Estimating ETc from Penman-Monteith

Asaana and Sadick 87

RESULTS AND DISCUSSION The parameters for the estimation of the

irrigation performance indicators of the

command areas are presented in the table 2

below, likewise, the indicators for estimating

irrigation performance are also presented in the

table 3 below. It is of much interest to know that the command areas are close to each other hence, ETc, ETa

and rainfall measured are the same. The size of

the command areas is not the same hence the

amount of water supplied to these areas is not

the same (Table 2). In every irrigation scheme, the total water

supply to command areas is among the very

first values that should be considered, therefore,

the overall consumed ratio is the first indicator

that should be available for each irrigated area (Bos, 1997). In cases of waterlogging and salinity, the critical

groundwater depth is mostly dependent on the

effective rooting depth of the crop, the overall

consumed ratio of irrigation water use and the

hydraulic characteristics of the unsaturated soil

(Bos et al., 2005). When the ratios are low, the

non-consumed fraction of the water will cause

the groundwater table to rise (Bos et al., 1991), while during the periods with high ratios, above

1; groundwater must be pumped and stored to

avoid water shortage. In 2008/2009 irrigation period, the Overall

Consumed Ratios of Bonia, Korania and

Chuchuliga were 0.52, 0.47 and 0.34

respectively, which were less than the target

value indicating that more water was supplied to

the field than the demand of the crops. The amount of water supplied to the field was much higher in February than the other months

(Table 2), because the dry season was at its

peak in February and appreciable amount of

water was needed to meet the crop water

requirement. The relative water supply (RWS) is a basic

indicator that informs the irrigation managers of

under-supply as well as over- supply in the field

(Wolters 1992). This does not explain the degree of water scarcity in the crop because it

does not take into account the groundwater

supply (Bastiassen et al., 2001). For further

analysis, the relative evapotranspiration takes

the groundwater into account. There is a

negative relationship between OCR and RWS

(Bastiassen et al., 2001). From Table 3-5, the

average RWS of Bonia, Korania and

Chuchuliga were found to be 1.97, 2.21 and

2.76 respectively, which were around the target value of 2.0, according to Molden et al., 1998,

except Chuchuliga area. The values of RET, DF and CWD of the

command areas do not conform to the target

values of 0.75, 0.6 and 30mm/month indicating

that there was poor delivery of water in the

irrigation area. This is partly because during the

fieldwork it was observed that most of the

command areas had broken canals and laterals, and much of the water went into waste. Even

though huge amount of water was supplied to

the field in these areas which could have

affected the crops but this was not the case. For proper irrigation system, the crop water

requirements of every crop are normally taken

into consideration but this was not the case at

Tono irrigation system. Irrigation was normally

done on timely basis. Tono Irrigation project has knowledgeable

project engineer and staff who can manage the

system efficiently but lack of support from the

government has greatly affected the system.

The Tono dam, which supplies water to about

3840ha of land, is under-utilized and the

expected annual yield is not met.

88 Int. Res. J. Agric. Food Sci.

Table 2: Parameters for Estimating Irrigation Performance Indicators

Bonia Korania Chuchuliga P Peff

Month V ETc ETa V ETc ETa V ETc ETa mm mm

Nov 600 290.3 2.73 650 290.3 2.73 950 290.3 2.73 13.10 12.30

Dec 690 350.4 2.52 800 350.4 2.52 1050 350.4 2.52 1.70 1.70

Jan 800 450 2.33 950 450 2.33 1200 450 2.33 1.20 1.20

Feb 750 440 2.33 850 440 2.33 1050 440 2.33 0.90 0.90

Mar 730 400.01 2.75 750 400.01 2.75 890 400.01 2.75 0.00 0.00

April 610 250.3 3.01 690 250.3 3.01 750 250.3 3.01 0.00 0.00

Total 4180 2181.01 15.67 4690 2181.01 15.67 5890 2181.01 15.67 16.90 16.10

Table 3: Indicators for estimating irrigation performance for Bonia Area

Month OCR RWS RET DF CWD

(mmmonth-1)

Nov 0.47 2.11 0.009 0.005 9.58

Dec 0.52 1.97 0.007 0.004 11.22

Jan 0.56 1.78 0.005 0.003 14.44

Feb 0.59 1.71 0.005 0.003 15.09

Mar 0.55 1.82 0.007 0.004 12.82

April 0.45 2.44 0.012 0.005 8.24

Average 0.52 1.97 0.008 0.004 11.90

Asaana and Sadick 89

Table 4: Indicators for estimating irrigation performance for Korania Area

Month OCR RWS RET DF CWD

(mmmonth-1)

Nov 0.43 2.28 0.009 0.004 9.59

Dec 0.44 2.29 0.007 0.003 11.22

Jan 0.47 2.12 0.005 0.003 14.44

Feb 0.59 1.93 0.005 0.003 15.09

Mar 0.53 1.88 0.006 0.004 13.24

April 0.36 2.76 0.012 0.004 8.24

Average 0.47 2.21 0.007 0.004 11.97

Table 5: Indicators for estimating irrigation performance for Chuchuliga Area

Month OCR RWS RET DF CWD

(mmmonth-1)

Nov 0.29 3.32 0.009 0.003 9.59

Dec 0.33 3.00 0.007 0.002 11.22

Jan 0.37 2.67 0.005 0.002 14.44

Feb 0.42 2.34 0.005 0.002 15.09

Mar 0.45 2.23 0.007 0.003 12.82

April 0.33 3.00 0.012 0.004 8.24

Average 0.37 2.76 0.008 0.003 11.9

CONCLUSION

The irrigation performance of the command

areas studied was poor. The poor performance

is as a result of operational and physical

deficiencies in the system.

Most of the canals and laterals leading to the

command areas were broken down and this has

become difficult to assess irrigation

performance. Data for estimating most of the

indicators are missing at the time of visit. There

was no data on groundwater supply and this

play important role when considering the

amount of water supply to the system.

No research was done on the irrigation

performance of the Tono irrigation system with

the help of GIS and Remote Sensing and

therefore it is very difficult to get literature on

these studies.

CONFLICT OF INTEREST

The authors have declared no conflict of interest.

90 Int. Res. J. Agric. Food Sci.

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