wrdm journal

J. Indian Water Resour. Soc. Vol. 26 No. 1-2, Jan.-April, 2006

51

Volume 26 Number 1-2 January-April, 2006

Journal ofIndian Water

Resources Society

ISSN O970-6984


52

JOURNAL OF INDIAN WATER RESOURCES SOCIETYGUIDELINES FOR AUTHORS

GENERAL INFORMATION

The Indian Water Resources Society (IWRS) is a multi-disciplinary organization dedicated to the advancement of thescience and technology of water resources development and management. The IWRS Journal publishes original papers onscientific, engineering and socio-economic aspect that are clear, concise and presented in a style readily understood by aninternational audience. Before publication, the papers are reviewed by the Editor/ reviewers. Detailed instructions for preparingmanuscripts are included in the following. A review of previous issues will be helpful in organizing the manuscript.

The text of the paper should be well organized and presented in a logical manner. The appropriate use of subheadings,especially in long sections, enhances the readability and quality of paper. Repetition of data given in tables and figures should beavoided. The paper should be written so that it will be of interest to persons in the wide variety of disciplines represented byIWRS’s membership. Complex sentences and the excessive use of highly technical jargon are prime offenders in detracting thereaders. The articles should have well-defined objectives, discussions, applications and conclusions that are easily understood.The papers not complying w these guidelines will be returned to the authors for improvement or publication elsewhere.

The acceptance or rejection of a paper is based on appraisal by the reviewers who examine the paper for its originality,relevance, adequacy and conciseness of the presentation. Depending on the results of reviewer, a manuscript may be returned tothe authors for revision. If the authors suitably revise the manuscript, it is accepted for publication. If the review comments areextensive, the authors should include a reply to the reviewer, in addition to making changes to the manuscript.

Submit two copies of the manuscript typed double spaced on A4 size paper, with 2.5 cm margin on all sides along withclear and legible figures and tables to the Editor, Indian Water Resources Society, Water Resources Development & ManagementDepartment, Indian Institute of Technology, Roorkee-247 667. Uttarakhand. (Add line numbers in the text of your manuscript).The references and abstract must also be double-spaced. Include a CD-ROM with text, tables, and figures. Single-spacedmanuscripts, those clumsily typed, or those with inadequate marginal space or unreadable illustrations and tables will be returned.Retain the original manuscript and illustrations and send the same to IWRS when your manuscript is approved for publication.

PREPARATION OF MANUSCRIPT

Title page :The title should be short, informative and should clearly reflect the content of the paper. The title should not exceed 15

words in length. Terms like Preliminary Investigations, Contributions to, Studies on etc., should be avoided.

The title page should also include the name(s) of the author(s); The affiliation and mailing address of each author; Thee-mail address, telephone and fax numbers of the corresponding author.

Abstract :

The abstract should be concise, and complete in itself, without reference to the text of the paper. It should state thegeneral problem and objective(s), summarize the results, and state general implications. The abstract should be in single paragraphof not more than 200 words. Up to five keywords should be given after the Abstract for indexing purposes

References :

Cite references to published literature in the text sorted by author(s) and year, for example, Prasad (1994). Avoid using anumbering system. List all references in alphabetical order in the Reference section. Give the complete title of the reference and thesource. Please follow the sample styles shown below

Books :Gupta, S.K., 1999. Engineering Hydrology. Tata Mc Graw-Hill Publishers, New Delhi.

Continued on Inside Back Cover


43


Journal ofIndian Water Resources Society

ISSN O970-6984

President

Er. M. GopalakrishnanSecretary General, ICID

Editorial Board

Prof. S. K. MajumdarProf. S. K. TripathiProf. Nayan SharmaDr. Z. AhmadEr. Chetan PanditEr. Avinash Agarwal

IWRS as a body accepts no resoponsibility forthe statements made by the individuals/authors.

Further. views expressed by authors need notnecessary be the views of the organisation towhich they belong.

Reprints of any portion of this publication may bemade, provided that reference thereto is quoted.

This Journal is for private circulation only.

Principal Office at :

Deptt. of Water ResourcesDevelopment & ManagementIndian Institute of Technology RoorkeeROORKEE - 247 667, Uttarakhand, India

From President’s deskDear friends,

I am happy to present before the IWRS family, the ‘Jan-April 2006’ issueof our Journal. This issue contains seven interesting research papers coveringdifferent aspects of Water Resources Development and Management. I am surethat the members will find these papers interesting. The Editorial team seeksyour valuable comments on further improvement of the technical content of theJournal in line with its objectives.

As you may be aware of, a new Executive Committee of IWRS for theterm 2007-09 took over recently (the back cover brings out the new officebearers); we are fortunate to have in this new team Prof. Brijesh Chandra andDr. Ashish Pandey as Editor and Joint Editor (Journal) and Dr. Vijay K.Labhsetwar, Joint Editor (News Letter). A fresh vigour has already set in theprocess of bringing out the journal, as one could see with the current issue, witha view to improve the presentation. This is in an era of competing environ andpublishing is no exception. I hope that your advice would help them to improveupon further and enhance the value of the Journal.

Water sector as a whole is facing immense challenges. There is a growingrecognition that a ‘multi-disciplinary participation’ will be a key factor to facethe future challenges adequately. This calls for giving more and more space fornot only the conventional issues that we normally address in engineering aspectsbut also issues beyond like water sector policies, aspects in management withsocial relevance, equity in water allocation etc. Participatory irrigationmanagement and transfer of irrigation systems to water users’ associations havebrought in new dimensions in respect of governance and sustainability: ourJournal should welcome papers reflecting varied experiences from different partsof the country. Following Maharashtra, other States like U.P, Gujarat besidesKarnataka and Andhra Pradesh (and several others) are in the process ofintroducing Regulatory mechanism to manage water sector in one form or other.We should enrich the society by new perceptions by way of contributions onthese matters.

Many of you must have seen our efforts in parallel to bring out a NewsLetter; the maiden issue was already sent to all of you. There had been somedelay in bringing out the subsequent issues. The News Letters will also begetting frequently in future with the identification of the Joint Editor and a roleassigned to him to handle this aspect; forthcoming events in water sector will begetting reflected in it regularly. IWRS web site too needs some efforts to make itvibrant and this will be looked into simultaneously. Put together, ourcommunication efficacy will be aimed to be improved upon with the supportfrom each one of you.

The Editorial team has already accommodated certain advice ofmembers on enhancing the Journal get-up and the current issue is the result.Please feel free to provide your feed back on the new visage to the Editor directly.

(M. Gopalakrishnan)President, IWRS


44

Journal ofIndian Water Resources Society


CONTENTS

S. Paper Page No.No.

1. Effect of Wash Load on Field Performance of Geotextile 1-6Filter in EmbankmentR. K. Sharma

2. Flow Past Tapered Submerged Vanes 7-13Umesh P. Gupta, C. S. P. Ojha, Nayan Sharma

3. Crop Coefficient Models of Wheat and Maize for Irrigation 14-15Planning in Gandak CommandJeetendra Kumar, A. K. P. Singh

4. Effect of Converging Boundary on Radial Flow Through 16-23Homogeneous Porous MediaN. Bhanu Prakasham Reddy, G. N. Pradeep Kumar,P. Rama Mohan Rao

5 Topological Insides for Study of Spatio-Temporal Changes in 24 -29The Planform of the Brahmaputra RiverR. N. Sankhua, Nayan Sharma, A.D. Pandey, P. K. Garg

6. Runoff Production on Hill Slopes Under Different Land Uses 30-38K. K. Satapathy, R.K. Panda

7. Correlation Between Pan Evaporation and Meteorological Parameters Under the Climate 39-42Conditions of Jorhat (Assam)D. Jhajharia, S. B. Kithan, A. K. Fancon


1

EFFECT OF WASH LOAD ON FIELD PERFORMANCE OFGEOTEXTILE FILTER IN EMBANKMENT

R.K. SharmaCivil Engineering Department, NIT Hamirpur (H.P.)

ABSTRACT

The functions of a filter layer in river protection embankment are to prevent the fines from washing out ofsubsoil without any excess hydrostatic pressure build-up upstream. Filtering being the main process, primaryfunction of a geotextile filter is, therefore, based upon its permeability. In most cases, a geometric closed tilteris chosen based upon the criterion that apparent opening size of geotextile filter should be smaller than thediameter of soil grain below which 85% of the soil particles fall. This criterion ensures building up a naturalsoil filter behind the boulder rip rap, if the geotextile filter possesses certain minimum permeability. However,if the filter is clogged by wash load coming with flood water, its permeability is reduced. In this paper, the effectof blinding of geotextile filter installed in an embankment by the slurry-loaded flood water on its perfomancehas been presented. The deposition of slurry over the surface of geotextile filter and interlocking of the core soilparticles into the filter tend to reduce its permeability by more than 95%. The reduction in permeability of thegeotextile filter due to interlocking of core soil particles is 35 to 39% and the reduction in filter permeabilitydue to deposition of slurry carried by flood water over it is nearly 60%. The mass of the slurry deposited overthe filter surface may be as high as 12 to 15 times the mass of the soil particle interlocked in the filter. Thepurpose of providing a geotextile filter may thus be defeated as the development of seepage pressure takesplace at such low permeability values. While selecting a geotextile filter for flood protection works, the effectof slurry deposition by flood water should be an important criterion.

KEY WORDS: Flood protection embankment, Slurry deposition, Geotextile filter performance.

INTRODUCTION

Geotextile filter is considered to functionsatisfactorily if it retains most of the soil particles at theinterface allowing water to percolate through it and soil poreswithout any hydrostatic pressure build-up on the upstreamside. Many filter criteria for geotextiles have been proposedby a number of research workers (Calhoun, 1972; Ogink, 1975;Mckeand, 1977; Schober & Teindl, 1979; Giroudetal, 1988;Watson & John, 1999; Lafleur, 1999; Heibaum, 1999; FaureetaI,1999). The filtration performance has been studiedexperimentally and mathematical model on mass of soil passingthrough nonwoven geotextile has been established by someresearchers (Palmeira, 2002; Faureetal, 2005; Wuetal, 2006;Liu and Chu, 2006). The long-term performance of thegeotextile filter is considered to depends primarily upon:

(i) properties of the soil, e.g. particle size distribution, soilstructure and soil chemistry;

(ii) properties of the geotextile filter particularly pore sizeand pore structure;

(iii) permeability characteristics of geotextile and theconditions of seepage flow.

The amount of soil passing through the geotextile filteris dependent upon:

(a) number and sizes of pores in geotextile filter comparedto the in-situ soil particle size;

(b) soil structure and inter-particle bonding of in-situ soilparticles.

(c) seepage forces.

However, no study is found in literature indicatingthe effect of slurry-laden flood water (wash load as per IS:4410 Part-3 - 1988) on the performance of geotextile filter basedupon filter permeability. The penneability studies only accountfor the clogging of the filter due to backfill embankment soil(assuming flow of clear water in the river channel) and theeffect of deposition of fine-grained slurry on filter is notconsidered. This slurry may blind the pores of the geotextilefilter thus reducing its permeability and rendering it useless.The paper highlights that while designing a geotextile filterfor flood protection embankment, presence of slurry in theform of fine-grained soils (CL, ML, SC, etc.) in the flood watercoming from the river catchment should be considered asone of the important criterion.

Journal of Indian Water ResourcesSociety Vol. 26 No. 1-2, Jan.-April, 2006


2

Consolidated undrained test

Consolidated drained tesl

Sample Classification (as per IS: 1498 - 1970)

Maximum dry density (g/cm2)

Optimum moisture content (%)

Permeability (cm/s)

Cohesion c Kg/cm2

φ0 Cohesion c Kg/cm2

φ0

I SC 1.85 12.4 6.5x I0-6 0.12 16.2 0.10 12.5

II sc 1.84 12.5 6.1x 10-6

0.14

15.0

0.11

12.0

III SC 1.87 12.9 5x I0-6 0.13 18.4 0.11 9.0

IV CL 1.84 13.8 8x 10-7 0.21 8.0 0.14 5.0

V CL 1.85 13.4 8.8x 10-7 0.20 9.2 0.12 5.5

VI CL 1.83 13.6 9.4x 10-7 0.28 6.6 0.20 4.5

VII CL-ML 1.78 15.2 5.3x 10-5 0.12 14.4 0.09 12.0

VIII CL ML 1.76 15.4 5.2x 10-5 0.10 16.5 0.06 12.5

IX CL-ML 1.75 15.5 6.0 x 10-5 0.13 17.2 0.09 13.0

STUDY AREA

The field performance study was conducted on thegeotextile laid as a filter on the river bank protection workalong the bank of Swan river. Swan river causes heavy lossof life and property due to floods. The river is fed by 73tributaries covering an area of 1400 square kilometers andhas a maximum discharge of 5300 cumecs. Floods in the riverinundate land area of more than 1260 hectares. Protectionembankments have been constructed on both the banks ofthe river spaced 775 metres apart under the flood managementand integrated development project. The embankmentconsists of good earth core and an outer layer of local soil. Ageotextile filter is provided over the outer layer sloping 1:2over which boulder rip-rap contained in steel wires is provided.The characterstics of core earth, local soil and the filter havebeen determined and their suitability in embankment has beenascertained. In order to study the field performance ofgeotextile filter, the samples were taken from field after morethan one year of its installation after monsoon season.

(1) CORE SOIL CHARACTERISTICS

The core soil samples were collected from a numberof borrow areas and characteristics of soil used are given inTable 1. Soil samples VII to IX were not recommended for usein the core of the embankment whereas samples IV to V1 wererecommended for use after removal of the organic matter. Thesamples I to III were recommended to be used after removalof grit and sandstone pieces. The field density testsconducted on embankment gave satisfactory density valuesas per IS: l2926-1995.

(2) CHARACTERISTICS OF OUTER LAYER SOIL

The local soil was hauled up to form the outer coreof the embankment. Soil investigations were carried out onthe local soil up to 3.75 m depth to observe the soil profile.The soil contains on an average of 4.5% fines and can beclassified as SP. The silt factor of the soil varied from 1.025 to1.09. A typical particle size distribution curve of the soil isshown in Figure 1. The soil consists of fine sand with siltcontents and the chances of liquefaction exist in the soil.

The soil samples I to III above used in the core weretaken from the soil existing in the catchment area of the river.The soil found in the bed of the river was used in the outerlayer of the embankment. Therefore, the wash load of theriver contains sandy clay in addition to the poorly gradedfine silty sand. These fine soils constitute the slurry cainedby the flood water which is deposited on the geotextile filterresulting in the blinding of the filter.

(3) FILTER CHARACTERISTICS

The geotextile filters were tested for their suitabilityof using in the embankment. The characteristics of the filteralong with the standard design requirements are given inTable 2.

The filter samples A and B were recommended foruse after modifications in the weight of sample A andthickness of sample B.

Table 1 Characteristics of Core Soil

SC

5.0x 10-6

8.0x 10-7

Cohesion cKg/cm2

Consolidateddrained test


3

FUNCTION OF GEOTEXTILE FILTER

Geotextile filter in river bank protection work is usedto stabilize the soil grain skeleton (structure) during thedissipation of seepage pressure. The dissipation of seepagepressure avoids the deformation of the embankment causedby seepage forces. The formation of a soil filter behind thegeotextile filter requires attainment of equilibrium with respectto system permeability and ceasing the migration of fine soilparticles. However, this requires that the water front surfaceof geotextile (containing boulder rip-rap) does not get cloggedby the slurry present in flood water and permeability of thefilter is not reduced.

FIELD STUDY

In the present field study, it was observed that theriprap-covered surface of geotextile filter was blocked due todeposition of very fine silt and clay particles flowing with theflood water. The flood water rises to more than 1.2m alongriprap and finer particles accompanied by water from the rivercatchment predominantly containing SC, CL, ML, SP, etc. aredeposited in layer over the filter surface. This tends todecrease the permeability to very small values thus increasingthe seepage pressure on the riprap thereby leading tosettlement of boulder riprap at certain locations.

In order to assess the decrease in geotextilepermeability, a number of geotextile filter samples werecollected from different locations along the river. Thedeposition of fines in the form of slurry on the geotextilesurface takes place after the monsoon floods and affects theattaining of equilibrium of filter system. The deposited finesoil particles get trapped in front of the geotextile filter layerthereby causing a remarkable reduction in permeability. Theperformance of a filter is changed into that of a lining system.In such case, the geotextile filter causes a greater troubleleading to the accumulation of fine soil filter particles overthe geotextile filter and establishes a soil filter with muchsmaller permeability values less than the desired one. Thisphenomenon is found not only in suffosive soil base but

may happen in more or less uniform silty sand. Since the soilfound in the river basin is uniform fine silty sand, therefore,the chances of blocking of the geotextile filter are very high.In order to assess the reduction in permeability values,samples of laid geotextile filter were collected from a numberof locations at every 15 m along the pitch guide bank.

FILTER PERFORMANCE

The samples were found to contain thick slurrydeposition on their surface. The permeability values ofgeotextile samples were studied under three conditions :

(i) Intact sample as obtained from field containing slurrydeposit to estimate the total reduction in permeabilitydue to interlocking of the outer core particles in thefilter as well as the deposition of slurry over the filtersurface.

(ii) Visible surface dry soil scratched to determine the effectof cleaning of the filter surface due to subsequent clearwater flow in the river.

(iii) Throughly washed sample so that all visible soilparticles are removed but the sample not squeezed toavoid removal of particles interlocked in the filter, i.e.,to assess the minimum permeability if equilibrium isattained resulting in the formation of the graded soilfilter behind the geotextile filter and no slurry isdeposited on surface of filter.

The percentage reduction in permeability comparedto that of a fresh filter sample for three conditions describedabove is given in Table 3. The reduction in permeability valuesis reported as an average for a set containing three samplesof the geotextile filter collected from each location.

The deposition of slurry over the surface ofgeotextile filter and interlocking of the core soil particles intothe filter tend to reduce by more than 95%. The purpose ofproviding a geotextile filter may thus be defeated as thedevel opment of seepage pressure takes place at such low

Table 2 Characteristics of Geotextile Filter

Filter

Material Weight (g/m2)

Air permeability (CFM)

Thickness (mm)

Cone drop test (mm)

Breaking strength (Kgf)

Elongation at break (%)

along

Across

along

across

A 100% Poly-propylene

380.0 184.5 2.52 8.45 67.5 48.9 2 1 .5 24.5

46.8

B

100°/o Poly-propylene

270.0

192.0

2.50

8.90

60.6

42.3

52.5

Slandard Codal requirements

275.0 ± 10 %

190 ± 20

3.00 ± 0.5

8.00 ±2.0

65± 10

45± 10

20± 10

50± 10

24.5

Type

190±20 3.00±0.5 8.00±2.0 65±10 45±10 20±10 50±10

across


4

permeability values. Since the local soil used in the outerlayer of the embankment is cohesionless; (cohesion, c = 0and angle of internal friction, φ = 300 at placement density of16kN/m3); the failure of the embankment closer to the toe insmall pockets was observed. The in-situ density of the soilbeing small and water table being shallow; it was observedduring conducting dynamic cone penetration tests in the fieldthat the soil liquefied and densification occurred due to thevibrations produced by the dynamic load.

Even when the surface slurry is removed off thesurface of the filter due to washing by clear water flowingsubse quently in the river, reduction in permeability is largerthan 90% which indicates clogging of the filter pores. Thereduction of permeability to less than 10% severely affectsthe filter performance. It is, thus, established that flood watercarrying silty sandy clay particles (SC, SM, CL, etc.) tends toclog the filter as it rises along the embankment. Even if thefilter samples are washed to remove fine-grained clay/siltparticles, average reduction in permeability is more than 35%indicating the interlocking of the fine soil particles from outercore in the geotextile filter. Thus, the attainment of equilibriumresulting in the formation of a graded soil filter behind thegeotextile filter will reduce its permeability by nearly one-third. However, the filter performance is stabilized at this levelof reduction in permeability as it helps in the formation of anatural graded soil filter layer behind the geotextile filter.

Also, Table 4 shows a comparison of the slurry massdeposited and the outer core soil mass interlocked in thegraded filter. The mass of the slurry deposited over the filtersurface may be as high as 12 to 15 times the mass of the soilparticle interlocked in the filter.

Figure 2 indicates that whereas the reduction inpermeability of the geotextile filter due to interlocking of coresoil particles is 35 to 39%, the reduction in filter permeabilitydue to deposition of slurry carried by flood water over it isnearly 60%. Therefore, the presence of wash load containingslurry should form an important criterion for the design ofgeotextile filter.

CONCLUSIONS

The slurry deposition on the geotextile by floodwaters severely affects the geotextile filter performance causedby large reduction in permeability. However, it is impossibleto control slurry deposition in flooded areas of theembankment particularly in the rivers carrying fine sediment-laden waters due to the presence of fine soils in the rivercatchment. In such case, proper diversion spurs (boulderwire crates) may be used to channelise the river flow awayfrom the side embankments so that minimum flood waterstrikes the embankment. For ensuring good filter performance,slurry deposition of the geotextile filter should be avoided asfar as possible.

Moreover, in literature there is no study indicatingthe effect of slurry-laden flood water on the performance ofgeotextile filter based upon filter permeability. The permeabilitystudies only consider the clogging of the filter due to backfillembankment soil (assuming flow of clear water in the riverchannel) whose effect does not cover all the parameters.Therefore, while selecting a geotextile filter for flood protectionworks, one of the important criterion is the presence of fine-grained soils (CL, ML, SC, etc.) in the river catchment.

SampleSet No.

Average mass of geotextile filter samples (g/m2) Average percentage reduction in permeabilityof geotextile filter (%)

Slurrydeposited

field samples

Surface soilscratchedsamples

Washedsamples

Actualinstalled

filter

Washedsamples


Slurrydeposited

field samples

I

II

III

IV

V

VI

2785.0

2550.0

2099.4

2347.2

3197.8

2357.4

2048.0

2021.6

1868.4

1886.2

2170.0

1901.4

563.86

519.06

561.80

501.88

571.28

508.52

91.81

91.52

90.59

90.95

92.40

91.05

97.87

97.51

96.98

97.25

98.03

97.40

380.0

380.0

380.0

380.0

380.0

380.0

36.67

37.50

36.24

37.09

38.71

37.35

Table 3 Reduction in permeability of geotextile filter


5

REFERENCES

1. Calhoun, C. (1972). Development of design criteria andacceptance specifications for plastic clothes. U.S. ArmyWaterway Experiment Station, Vicksberg, Miss.

2. Faure, Y. H. B. Delmas, Farkouh Ph. and Nancey, A.(1999). Analysis of geotextile filter behaviour after 21years in Valcros dam. Geotextiles and Geomembranes,17(5-6), 353-370.

3. Faure, Y. H.; Pierson, A.; Baudoin P. and Ple, O. (2005).A contribution for predicting geotextile clogging duringfiltration of suspended solids. Geotexti1es andGeomembranes, 24 (1) , 11-20.

4. Giroud, J.P. and Noiray L., (1981). Geotextile -reinforced unpaved road design. Proceedings of theASCE Journal of Geotechnical Engineering Division.107( ‘0. GT 9), 1233-1254.

5. Heibaum. M. H. (1999). Coastal scour stabilisationusing granular filter in geosynthetic nonwovencontainers. Geotextiles and geomembrances, 17 ( 5-6),341-352.

6. IS : 1498-1970. Classification and identification of soilsfor general engineering purposes. Bureau of IndianStandards, Manak Bhawan, New Delhi.

7. IS : 4410 (Part-3) - 1988. Glossary of terms relating toriver valley projects. Bureau of Indian Standards, ManakBhawan, New Delhi.

8. IS : 12926 - 1995. Construction and maintenance ofguide banks in alluvial rivers guidelines. Bureau ofIndian Standards, Manak Bhawan, New Delhi.

Table 4 Slurry deposited over geotextile filter by flood water

SampleSet No.

Average mass of geotextile filter samples (g/m2) Total soil including slurry deposited expressedas a ratio of original filter mass

Slurry depositedfield samples

Surface soilscratched samples

Washedsamples

Washedsamples


Slurrydeposited

field samples

I

II

III

IV

V

VI

2405.0

2170.0

1719.4

1967.2

2817.8

1977.4

1668.0

1641.6

1488.4

1506.2

1790.0

1521.4

183.86

139.06

181.80

121.88

191.28

128.52

4.389

4.32

3.917

3.964

4.711

4.004

6.329

5.711

5.051

5.177

7.415

5.204

0.484

0.366

0.478

0.321

0.503

0.338

9. Lafleur, J. (1999). Selection of geotextiles to filterbroadly graded cohesionless soils. Geotextiles andGeomembranes, 17(5-6), 299-312.

10. Liu, Li Fang and Chu, Cai Yuan (2006). Modeling theslurry filtration performance of nonwoven geotextiles.Geotextiles and Geomembranes, 24(5), 325-330.

11. McKeand E. (1977). The behaviour of non-woven fabricfilters in sub-drainage applications. Proceedings of theInternational Conference on the use of Fabrics inGeotechnics, Paris, 2,171-176.

12. Ogink, H.J.M. (1975). Investigations on the hydrauliccharacteristics of synthetic fabrics. Delft LaboratoryPublication No. 146.

13. Palmeira, Ennio M.(2002). Drainage & filtrationproperties of non-woven geotextiles under confinementusing different experimental techniques. Geotextiles andGeomembranes, 20(2), 97-115.

14. Schober, W. and Teindl, H. (1979). Filter criteria forgeotextiles. Proceedings of the Seventh EuropeanConference on Soil Mechanics and FoundationEngineering. Brighton, 2, 121-129.

15. Watson, P. D. J. and John, N. W. M. (1999). Geotextilefilter design and simulated bridge formation at the soilgeotextile interface. Geotextiles and Geomembranes,17(5-6), 265-280.

16. Wu, Cho-Sen; Hong, Yung-Shan; Yan, Yun-Wei andChang, Bow-Shung (2006). Soil-nonwoven geotextilefiltration behavior under contact with drainagematerials. Geotextiles and Geomembranes, 24(1), 1-10.


6

Fig 1 Particle size distribution curve for soil sample from Swan river

Fig 2 Effect of slurry depositon and interlocking of outer layer soilparticles on permeability of geotextile filter

Practicle Size mm

0.1 101

% F

iner

0

0.01

2040

6080

100


7


FLOW PAST TAPERED SUBMERGED VANES

Umesh P. Gupta C. S. P. Ojha Nayan SharmaMorphology Directorate Professor, Civil Engg. Dept., Professor, WRD&MCentral Water Commission Indian Institute of Technology Indian Institute of TechnologyNew Delhi (India) Roorkee (India) Roorkee (India)

ABSTRACT

Tapered submerged vanes are installed in Wapsipinicon river bend in the U.S.A. and outside a new waterintake in Nepal. Tapering the leading edge of the submerged vanes is to deflect floating debris impinging on thevane in low to medium flows. Taper angle is the angle made by leading edge of vane with horizontal in verticalplane. With the increase of taper angle, strength of vane induced secondary circulation in terms of dimensionlessmoment of momentum also increases but the plot does not follow the linear trend. Strength of vane induced flowis maximum in terms of dimensionless moment of momentum when the leading edge of submerged vane is verticali.e. 900 (rectangular vane).

KEY WORDS : Submerged vanes, Taper angle, Moment of momentum, secondary circulation.

INTRODUCTION

Submerged vanes are submerged foils of low heightstructures, which are constructed in river at angle of attack tothe flow to modify the near-bed flow pattern and redistributeflow and sediment transport within the channel cross section(Fig. 1). The initial height of vanes are 0.2 - 0.4 times localwater depth (d) at design stage. Normally, aspect ratio (H/L)of submerged vane is 0.25 to 0.5.

Submerged vanes are frequently used as vortexgenerating devices that have several applications for thesediment management, such as protection of erosion (Jansenet al. 1979; Odgaard and Kennedy, 1983; Odgaard andMosconi, 1987; Odgaard and Wang, 1991 a,b); maintainingdepth in navigation channel (Odgaard and Spoljaric, 1986);maintaining the pump-intake bays sediment free (Nakato etal.,1990), sediment control at lateral diversions (Barkdoll etal., 1999), sediment control at water intakes (Wang et al., 1996)and control of scour at vertical wall abutments (Johnson etal., 2001).

In the last two decades, there has been an increasein the use of submerged vanes as sediment managementdevices. The submerged vanes function by generatingsecondary circulation in the flow, which alters the magnitude,and direction of the bed shear stresses and causes a changein the distributions of velocity, depth and sediment transportarea affected by vanes.

Submerged vanes with tapered leading edge areinstalled in Wapsipinicon river bend in the U.S.A. and outsidea new water intake in Nepal. Probably, the rationale behind

tapering the leading edge of the submerged vanes is to deflectfloating debris impinging on the vane. Also, possibly stuckup debris etc. at the leading edge in low to medium flows ismore readily removed with the rising stage if the edge istapered than vertical.

The effect of tapering the leading edge of submergedvanes on the strength of vane-induced secondary currentshas not been investigated so far.

Thus it is important to investigate the effect oftapering the leading edge of the vanes on the strength ofvane-induced secondary current. According to Marelius andSinha(1998), the rectangular submerged vane without collarhas maximum strength of secondary flow at optimal angle ofattack 400. Gupta (2003) introduced collar around the leadingedge of rectangular and trapezoidal vanes at optimal angle ofattack at the bed level in order to reduce the local scour aroundit. Gupta et al. (2006) found that optimal angle of attack forrectangular vane with collar is still 400. The present paperhighlights the effects of taper angle on the vane-inducedstrength of vortex, when collar collar was introduced aroundthe leading edge of vanes. For this, three types of taperangles were taken for the investigations (Fig. 2 and Table 1).Taper angle is the angle made by leading edge of vane withhorizontal in vertical plane. A rectangular vane of length, L(18 cm) and three trapezoidal vanes were considered forinvestigations. All the vanes were made of plastic sheetswith thickness 4 mm and exposed height of vane, H (6 cm).Top and bottom lengths of the trapezoidal vane were takensuch that its average length equals 18 cm. Experimentalprogramme has been shown in Table 2.


8

ASSESMENT OF STRENGTH OF VERTEX

For this purpose, 3 cm × 3cm grids across the flumehad been taken at the distance of 15 cm downstream from thecentre of the vanes. At each grid points all the componentsof velocity were measured using ADV (Acoustic DopplerVelocimeter). The velocity at each grid point is therepresentative velocity of the grid area 3 cm × 3cm. Fig. 3shows the layout of grids in flow area cross-section. Velocitynear the wall of the flume was not considered for thecalculation of strength of vortex in order to neglect the walleffect on the generation of secondary flow due to thesubmerged vanes. A definition sketch for velocity has beenshown in Fig. 4 Fig. 5 shows typical profiles of transverse(Vy) and streamwise velocity (Vx) along the height from bedlevel along grid 6-39 downstream of submerged vane. FromFig.5, it can be seen that streamwise velocity gets reduced inthe zone of centre of vortex. The reason is submerged vaneinduces the component of streamwise velocity in transversedirection of flow. In the zone of centre of vortex, transversevelocity is dominent and hence streamwise velocity getsreduced. Fig. 5 also reveals the centre of vortex at z = 0.9H.

The origin was taken at the mid of the average vanelength at initial bed level. For a mass m concentrated at pointA (Fig. 4), one can write the following expression for momentof momentum, MOMA

)VR)(mass(MOM A ×= (1)

where, R represents the location vector of point A with

respect to centre of vortex C and V is local velocity..

The local vector of point A with respect to origin O is given

as AO ,where,

kzjyAO += (2)

In eq. 2, y and z are coordinates of grid points and j and

k are unit vectors along Y and Z directions, respectively..With the centre of vortex at C, one can write

kH9.0CO = (3)

From eqs. (2) and (3), location vector of point A with respectto point C, can be written as

COAOACR −==

kH9.0kzjy −+=

k)H9.0z(jy −+= (4)

Thus, MOM of mass m at point A with respect tocentre of vortex C, can be expressed as

( ){ } ( )[ ]kVzjVykH9.0zjymMOM A +×−+=

( )[ ]VyH9.0zVzyim −−=

( ){ }[ ]VyH9.0zVzyim −−+= (5)

In Eq. (5), i indicates the direction of MOM along the

direction of flow of fluid (here water). In eq. 5, (m y Vz) isMOM due to vertical velocity and {-m (z-0.9H) Vy} is MOMdue to transverse velocity.

For grid area as 3cm × 3cm and length of flume, L1 as 1 cm andwater density, ρw as 1 gm/cm3 , mass m can be computed as

m = 1 x 3 x 3 x 1 = 9 gm (6)

Using eqs. (5) and (6), one can write

( ){ }[ ]VyH9.0zVzyi9asMOM A −−+= (7)

Thus, total MOM can be expressed as

MOMiMOMTotal44

1i∑

=

= (8)

In Table 3, MOM ad different grid points has been presented.

DIMENSIONAL CONSIDERATIONS

MOM can be considered to depend on a wide rangeof variables, such as angle of attach, α; vane height, H; vanelength, L; pre-vane flow depth, d; water density, ρw;acceleration due to gravity, g; dynamic viscosity, µ; thicknessof vane, t; velocity components in x direction, Vx; velocitycomponents in Y direction,Vy; velocity components in Zdirection, Vz; vane shape; taper angel etc. Thus, in a functionalform, the dependence of MOM in terms of these variablescan be written as follows :

MOM = f (α, H, L, d, ρw, g, µ, Vx, Vy, Vz, vane shape, taperangle) (9)

For the constant values of α, ρw, g, t, vane shapeand taper angle; eq. 9 reduce to

MOM = f (H, L, d, µ, Vx, Vy, Vz) (10)

Here same fluid has been considered i.e. µ is constant.Therefore, eq. 10 reduce to

MOM = f (H, L, d, Vx, Vy, Vz) (11)Linear Momentum, LM may be given as


9

LM = ρw AL1 U (12)

where, A is cross sectional area of flow, flow lengthL1 assumed as 1 cm for computation of mass, and U is meanflow velocity over whole stream section, which equals meanvalue of Vx.

From eqs. 11 and 12, one can write

MOM = f (H, L, d, Vy, Vz) (13)

From eq. 13, it is apparent that total number ofdimensionaless groups, which can be formed as

*MOMdLM

MOM1 =

×=π (14)

**MOMHLM

MOM2 =

×=π (15)

***MOMLLM

MOM3 =

×=π (16)

MOM*, MOM**, and MOM*** are dimensionlessnumbers, therefore, single plot of MOM* versus taper angleof submerged vanes has been shown in Fig. 6.

EXPERIMENTS

The flume used was eleven metre long tilting flume,made of mild steel with side walls made of transparent perspexsheet. Flume had an in-built up stream tank of 40 cm x 90 cmx 115 cm dimensions. The depth of flume was 50 cm and thewidth was 50 cm. At the upstream end, there were threenumber of baffle walls, one at upstream and others were at18 cm spacing. The vane location was about 3 m from theupstream end of the channel. The baffle walls and longdistance of the vane location from the upstream end of thechannel allowed the flow enter smoothly and fully developedbefore it reached the test area. Experiments were performedwith sediment having median diameter as 0.225 mm ofgeometric standard deviation 1.42. The relative density ofsand was 2.65.

Flume was adjusted to required slope. The depth ofsediment bed layer of the test section was fixed at 15 cm.Uniform flow without sediment motion corresponding to aselected discharge was established with the help of tail gate.Before placement of submerged vanes, the sediment bed offlume was leveled using spirit level. After placement ofsubmerged vanes, the sediment bed of flume was againlevelled around the submerged vane. Flow was introduced

in the flume very slowly by closing the tail gate so that noscouring occurred around the submerged vanes due tooperation. After the same period of run in case of vanes withcollar, the three dimensional components of velocity weremeasured by means of Acoustic Doppler Velocimeter (ADV).The sampling rate used in the experiments was 20 Hz. Aminimum of 800 values was taken at each grid point, and themean value of these measurements was taken asrepresentative quantity. The flow velocity in the flume waskept close to 90% of the critical velocity for bed sedimententrainment.

DISCUSSIONS AND CONCLUSIONS

A plot of taper angle and MOM* has been shownin the Fig.6. A rectangular vane can be considered as taperedvane with taper angle 900. It can be seen from the trend ofplot (Fig. 6) that with the increase of taper angle, strength ofvane induced secondary circulation in terms of dimensionlessmoment of momentum also increases but the plot does notfollow the linear trend. Its strength is maximum when theleading edge of submerged vane is vertical i.e. 900 (rectangularvane). Strength of vane induced secondary flow is minimumat taper angle, 4H: 2V. Thus, if the taper angle of vane is zerothen the strength of vane induced vortex will be also zero,which is quite justified practically as with zero taper anglethere will be no existence of vane above the bed level.Therefore, the leading edge of submerged vanes should notbe too tapered. Here, the average length of vane was 18 cm.However, effect of tapered angle on generation of strengthof vane induced vortex should be explored without changingthe original aspect ratio with wide range of taper angles.Dimensionless MOM may also be investigated as the loss inlinear momentum times the length over which the linearmomentum loss was measured. The group behaviour of arraysof tapered submerged vanes may be considered for futurestudies.

REFERENCES

1. Barkdoll, B.D.; Ettema, R. and Odgaard, A.J. (1999).Sediment control at lateral diversions: limits andenhancements to vane use. Journal of HydraulicEngineering, ASCE, 125(8), 862-870.

2. Gupta, U. P. (2003). Study on performance ofsubmerged vanes with collar. Ph. D. Thesis, IndianInstitute of Technology, Roorkee (India).

3, Gupta, U.P., Ojha, C.S.P. and Sharma, Nayan. (2006).Vorticity with different shapes of submerged vanes.Journal of Hydraulic Engineering, Indian Society forHydraulics, 12(1), 13-26.

4. Jansen, P. Ph., van Bendegom L., Van Den Berg J., deVries, M., and Zanen A. (1979). Principles of RiverEngineering. Pitman Publishing Limited, London, U.K.


10

5. Johnson, P.A.; Hey, R.D.; Tessier, M. and Rosgen, D.L.(2001). Use of vanes for control of scour at verticalwall abutments. Journal of Hydraulic Engineering,ASCE, 127(9), 772-778.

6. Marelius, F. and Sinha, S.K. (1998). Experimentalinvestigation of flow past submerged vanes. Journal ofHydraulic Engineering. ASCE, 124(5), 542-545.

7. Nakato, T., Kennedy, J.F. and Baurely, D. (1990). Pump-station intake-shoaling control with submerged vanes.Journal of Hydraulic Engineering, ASCE, 116(1), 119-128.

8. Odgaard, A.J. and Kennedy, J.F. (1983). River-bendbank protection by submerged vanes. Journal ofHydraulic Engineering. ASCE, 109(8), 1161-1173.

9. Odgaard, A.J. and Mosconi, C.E. (1987). Stream bankprotection by Submerged vanes. Journal of HydraulicEngineering, ASCE, 113(4), 520-536.

10. Odgaard, A.J. and Spoljaric, A. (1986). SedimentControl by submerged vanes. Journal of hydraulicengineering, ASCE, 112(12), 1164-1181.

11. Odgaard, A.J. and Wang, Y. (1991a). Sedimentmanagement with submerged vanes. I: Theory. Journalof Hydraulic Engineering, ASCE, 117(3), 267-283.

12. Odgaard, A.J. and Wang, Y. (1991b). Sedimentmanagement with submerged vanes. II: Applications.Journal of Hydraulic Engineering, ASCE, 117(3), 284-302.

13. Wang, Y., Odgaard, A.J., Melville, B.W. and Jain, S.C.(1996). Sediment control at water intakes. Journal ofHydraulic Engineering, ASCE, 122(6), 353-356.

Table 2 Experimental Programme

TAPER ANGLE

TOP LENGTH, B1

(CM)

BOTTOM LENGTH, B2

(CM)

AVERAGE LENGTH, (B1+ B2)/2

(CM)

1H:1V 15 21 18

3H:2.5V 14.4 21.6 18

4H:2V 12 24 18

EXP

T.

NO.

VANE

TYPE

TAPER

ANGLE

FLOW

RATE

(CUMEC

)

FLOW

DEPTH

(CM)

FROU

DE

NO.

ANGLE OF

ATTACK

1 Rectangular - 0.0154 18 0.13 400

2 Trapezoidal 1H:1V 0.0154 18 0.13 400

3 Trapezoidal 3H:2.5V 0.0154 18 0.13 400

4 Trapezoidal 4H:2V 0.0154 18 0.13 400

Table 1 Dimensions of trapezoidal vane

EXPTNO.

FLOWRATE

(CUMEC)

FROUDENO.

AVERAGE LENGTH,(B1 + B2)/2

(CM)


11

Fig 3 Grid points for the collection of data

40o

Fig 4 Definition sketch for velocity

Flow

Angle of attack

Bed sediment movement direction

Vane induced circulation

Vane

Fig 1 Definiton sketch of submerged vane

Fig 2 Trapezoidal vane

b1

b2

HFlow

Taper angle Vane Mobile Bed Level

Installationdepth of vane


12

Fig 5 (a)

0

3

6

9

12

15

0 5 10 15 20Height from bed level, cm

Stre

amwi

se ve

loci

ty (V

x), c

m/s

( a

long

gri

d 6-

39)

Fig 5 (b)

Flow

dire

ctio

n

Pres

sure

side

Suct

ion

side

Vane

Flume walls

Angle of attack

0

3

6

9

12

15

-6 -4 -2 0 2 4 6 8Transverse velocity (Vy), cm/s (along grid 6-39)

Hei

ght f

rom

bed

leve

l, cm

Fig 5 (c)Fig 5 Velocity distribution downstream of rectangular submerged vane (taper angle 900)

(a) A typical transverse velocity profile along grid 6-39(b) A typical streamwise velocity profile along grid 6-39

(c) Pressure and suction sides of vanes

Fig 6 Effect of taper anle on MOM*


13

Table 3. Moment of momentum at different nodes Coordinates Velocity Grid

points Symbols Values Vy Vz Moment of Momentum

1 y1, z1 2.5H, 0.5H Vy1 Vz1 9H[2.5Vz1 + 0.4Vy1]2 y2, z2 2H, 0.5H Vy2 Vz2 9H[2Vz2 + 0.4Vy2]3 y3, z3 1.5H, 0.5H Vy3 Vz3 9H[1.5Vz3 + 0.4Vy3]4 y4, z4 1H, 0.5H Vy4 Vz4 9H[1Vz4 + 0.4Vy4]5 y5, z5 0.5H, 0.5H Vy5 Vz5 9H[0.5Vz5 + 0.4Vy5]6 y6, z6 0H, 0.5H Vy6 Vz6 9H[0Vz6 + 0.4Vy6]7 y7, z7 -0.5H, 0.5H Vy7 Vz7 9H[-0.5Vz7 + 0.4Vy7]8 y8, z8 -1H, 0.5H Vy8 Vz8 9H[-1Vz8 + 0.4Vy8]9 y9, z9 -1.5H, 0.5H Vy9 Vz9 9H[-1.5Vz9 + 0.4Vy9]

10 y10, z10 -2H, 0.5H Vy10 Vz10 9H[-2Vz10 + 0.4Vy10]11 y11, z11 -2.5H, 0.5H Vy11 Vz11 9H[-2.5Vz11 + 0.4Vy11]12 y12, z12 2.5H, 1H Vy12 Vz12 9H[2.5Vz12 + (-0.1)Vy12]13 y13, z13 2H, 1H Vy13 Vz13 9H[2Vz13 + (-0.1)Vy13]14 y14, z14 1.5H, 1H Vy14 Vz14 9H[1.5Vz14 + (-0.1)Vy14]15 y15, z15 1H, 1H Vy15 Vz15 9H[1Vz15 + (-0.1)Vy15]16 y16, z16 0.5H, 1H Vy16 Vz16 9H[0.5Vz16 + (-0.1)Vy16]17 y17, z17 0H, 1H Vy17 Vz17 9H[0Vz17 + (-0.1)Vy17]18 y18, z18 -0.5H, 1H Vy18 Vz18 9H[-0.5Vz18 + (-0.1)Vy18]19 y19, z19 -1H, 1H Vy19 Vz19 9H[-1Vz19 + (-0.1)Vy19]20 y20, z20 -1.5H, 1H Vy20 Vz20 9H[-1.5Vz20 + (-0.1)Vy20]21 y21, z21 -2H, 1H Vy21 Vz21 9H[-2Vz21 + (-0.1)Vy21]22 y22, z22 -2.5H, 1H Vy22 Vz22 9H[-2.5Vz22 + (-0.1)Vy22]23 y23, z23 2.5H, 1.5H Vy23 Vz23 9H[2.5Vz23 + (-0.6)Vy23]24 y24, z24 2H, 1.5H Vy24 Vz24 9H[2Vz24 + (-0.6)Vy24]25 y25, z25 1.5H, 1.5H Vy25 Vz25 9H[1.5Vz25 + (-0.6)Vy25]26 y26, z26 1H, 1.5H Vy26 Vz26 9H[1Vz26 + (-0.6)Vy26]27 y27, z27 0.5H, 1.5H Vy27 Vz27 9H[0.5Vz27 + (-0.6)Vy27]28 y28, z28 0H, 1.5H Vy28 Vz28 9H[0Vz28 + (-0.6)Vy28]29 y29, z29 -0.5H, 1.5H Vy29 Vz29 9H[-0.5Vz29 + (-0.6)Vy29]30 y30, z30 -1H, 1.5H Vy30 Vz30 9H[-1Vz30 + (-0.6)Vy30]31 y31, z31 -1.5H, 1.5H Vy31 Vz31 9H[-1.5Vz31 + (-0.6)Vy31]32 y32, z32 -2H, 1.5H Vy32 Vz32 9H[-2Vz32 + (-0.6)Vy32]33 y33, z33 -2.5H, 1.5H Vy33 Vz33 9H[-2.5Vz33 + (-0.6)Vy33]34 y34, z34 2.5H, 2H Vy34 Vz34 9H[2.5Vz34 + (-1.1)Vy34]35 y35, z35 2H, 2H Vy35 Vz35 9H[2Vz35 + (-1.1)Vy35]36 y36, z36 1.5H, 2H Vy36 Vz36 9H[1.5Vz36 + (-1.1)Vy36]37 y37, z37 1H, 2H Vy37 Vz37 9H[1Vz37 + (-1.1)Vy37]38 y38, z38 0.5H, 2H Vy38 Vz38 9H[0.5Vz38 + (-1.1)Vy38]39 y39, z39 0H, 2H Vy39 Vz39 9H[0Vz39 + (-1.1)Vy39]40 y40, z40 -0.5H, 2H Vy40 Vz40 9H[-0.5Vz40 + (-1.1)Vy40]41 y41, z41 -1H, 2H Vy41 Vz41 9H[-1Vz41 + (-1.1)Vy41]42 y42, z42 -1.5H, 2H Vy42 Vz42 9H[-1.5Vz42 + (-1.1)Vy42]43 y43, z43 -2H, 2H Vy43 Vz43 9H[-2Vz43 + (-1.1)Vy43]44 y44, z44 -2.5H, 2H Vy44 Vz44 9H[-2.5Vz44 + (-1.1)Vy44]


14


CROP COEFFICIENT MODELS OF WHEAT AND MAIZE FOR IRRIGATIONPLANNING IN GANDAK COMMAND

ABSTRACT

In the Gandak command area, an investigation was carried out to develop crop coefficient model forwheat and maize. With the obtained crop coefficient values, crop coefficient curve was derived as a function ofdays after sowing and polynomial model was fitted. Using the derived polynomial equations, crop coefficientvalues of these crops for any day after sowing can be estimated for Gandak command. The equations of theregression model of crop coefficient can therefore, be used for estimation of water requirement of these cropsgrown in Gandak command area and for other areas having similar climatic conditions where such data areeither not generated experimentally or not at all available.

INTRODUCTION

Wheat (Triticum aestivum L.) and maize areprominent food crops grown in the Gandak command area ofNorth Bihar. For better crop production, water should beapplied according to consumptive demand (cropevapotranspiration) of the crops. Estimation of cropevapotranspiration is necessary for efficient planning andproper management of irr igation water. The cropevapotranspiration estimates require specific values of cropcoefficient for a particular crop. Crop coefficients are theempirical ratios of crop evapotranspiration (ETc) to estimatedor measured reference evapotranspiration (ETo). The valuesof crop coefficient vary mainly with the crop characteristics,crop sowing or planting date, rate of crop development,length of growing season and prevailing climatic conditions.Wright (1982) and Hussain and Pawade (1990) worked outcrop coefficient values for different crops. For water balanceirrigation scheduling, crop evapotranspiration are estimatedfrom crop coefficient curves, which reflect the changing ratesof crop water use over the growing season. Steele et al (1996)and Hanskar (1999) derived crop coefficient curves as afunction of day past planting for different crops using fifthorder polynomial.

Present study was undertaken to determineconsumptive use and crop coefficient values and to developcrop coefficient curve for wheat and maize crops.

MATERIALS AND METHODS

The present experiment was conducted at the WaterManagement Research Farm of Rajendra AgriculturalUniversity, Bihar, Pusa during the Rabi season of 2000-2001.

The experimental area is located at 25.980 N latitude, 85.670 Elongitude and at an attitude of 52.0 meters above the MeanSea Level. The climate of the area concerned is humid sub-tropical.

The experiment was laid out with wheat (UP-262)and maize (Laxmi) crops. These crops were sown onNovember 14, 2000 and harvested on April 12 and May 5,2001, respectively. The measured quantity of irrigation waterusing a 7.5 cm parshall flume was applied time to time inorder to bring the soil moisture level to field capacity. Soilmoisture content was measured using gravimetric methodfor which soil samples were collected from 0-30, 30-60, 60-90and 90-120 cm soil depths on different dates during thegrowing season. Soil moisture depletion from the effectiverootzone depth for different periods between two successivesoil sampling was calculated.

In order to determine crop evapotranspiration (ETc)for any time periods between two successive soil moisturemeasurement dates, components of water balance equationwere monitored. Reference evapotranspiration (ETo) for allthe periods were estimated as the product of pan evaporationand pan coefficients (Kp). Crop coefficient values (Kc) for allthe time periods were determined using following equation:

o

cc ET

ETK = (1)

Where, cET = Crop evapotranspiration (mm) and oET =Reference evapotranspiration (mm)

The crop coefficient values were plotted with respect to time(days after sowing). While plotting the crop coefficient

A.K.P. SinghPrincipal ScientistDepartment of Irrigation & Drainage Engg.R.A.U., Pusa, Bihar

Jeetendra KumarResearch Associate,ICAR Research Complex for Eastern RegionWALMI Complex, Phulwarisharif,Patna - 801 505, Bihar


15

values for a particular period, the mid point of that particularperiod was taken. Polynomial function was fitted to thesedata, keeping in view the scatter of the crop coefficient (Kc)values, with respect to time (Days after sowing).

RESULTS AND DISCUSSION

Evapotranspiration of wheat and maize crops showed anincreasing trend with the advancement in crop growth up tophysiological development and after that it started declining.The mean crop evapotranspiration over the growing seasonfor wheat and maize were computed to be 1.0 mmday-1 and1.36 mmday-1 over the growing season, the maximum valuebeing 1.83 mmday-1 (80 to 94 days after sowing) and 3.03mmday-1 (121 to 135 days after sowing), respectively.

Development of Crop Coefficient Model

Crop coefficient values of wheat and maize were obtained asthe ratio of crop evapotranspiration (ETc) and referenceevapotranspiration (ETo) and plotted against days aftersowing that are presented in Fig. 1 and 2, respectively. It isrevealed from the results that crop coefficient values of wheatand maize increased gradually from a low initial value of 0.07and 0.09, respectively to a maximum of 1.02 (80 to 94 daysafter sowing) and 1.03 (103 to 121 days after sowing) as thecrop growth advanced and after that the value starteddeclining to attain a value of 0.22 and 0.29, respectively atthe time of harvest. Polynomial function was fitted to thecrop coefficient values and fourth order polynomial equationyielded high value of coefficient of determination (R2). Thepolynomial models of crop coefficients (Kc) as a function oftime (days after sowing) are given below:

Wheat, =cK 2.84 X 10-8 t4- 8.64 X 10-6 t3+6.74 X 10-4 t2-1.24 X 10-3 t+0.0235,R2=0.976 (2)

Maize, =cK 3.05 X 10-9 t4-1.30 X 10-6 t3+5.15 X 10-5 t2+1.53X 10-2 t - 0.067, R2=0.949 (3)

Using these polynomial equations crop coefficientvalue for any day after sowing can be estimated.

CONCLUSIONS

The present study was undertaken to determinethe crop coefficient values and to develop crop coefficientmodels for wheat and maize under the agro-climaticconditions of Gandak command in Bihar. The results revealedthat crop coefficient values were low initially, which increasedto a maximum of 1.02 and 1.03 as the crop physiologicallyfully developed and thereafter decreased to 0.22 and 0.29 atthe time of harvest for wheat and maize crops, respectively.Polynomial model was fitted to the crop coefficient valuesand fourth order polynomial equation was found to be bestfitted. The study will be helpful for deciding the irrigationrequirement and irrigation scheduling during the life cycleof the crops.

REFERENCES

1. Hunskar, D.J. (1999). Basal crop coefficients and wateruse for early maturity cotton. Trans. ASAE 42 (4), 927-936

2. Husain, I. and Pawade, M.N. (1990). Crop coefficientfor summer groundnut. Agric. Eng. Today, 14 (3&4), 28-30.

3. Steele, D.D.A; Sajid, H. and Prunty, L.D. (1996). Newcorn evapotranspiration crop curves for southeasternNorth Dakota. Trans. ASAE 39 (3), 931-936

4. Wright, J.L. (1982). New evapotranspiration cropcoefficients. J. Irrig. and Drain. Div. ASCE 108 (1), 57 74.

0

0.2

0.4

0.6

0.8

1

1.2

0 20 40 60 80 100 120 140 160

Days after sowing, t

Cro

p co

effI

cien

t, K

c

Fig 1 Crop coefficient curve for wheat.

0

0.2

0.4

0.6

0.8

1

1.2

0 20 40 60 80 100 120 140 160 180

Days after sowing, t

Cro

p co

effI

cien

t, K

c

Fig 2 Crop coefficient curve for maize.


16


EFFECT OF CONVERGING BOUNDARY ON RADIAL FLOW THROUGHHOMOGENEOUS POROUS MEDIA

ABSTRACT

Behavior of flow through porous media has been the subject of study for a long time. The relationshiprelating friction factor (fR) and Reynolds number (RR) using hydraulic radius as the characteristic length isexamined for flow in porous media with converging boundaries. This paper presents the results of experimentsconducted on Convergent Flow Permeameter using crushed rock of size 4.73mm as the media and water as fluid.Theoretical curves, similar to the Moody diagram used in pipe, relating fR and RR for different CR values takenas the third parameter have been developed using hydraulic radius as the characteristic length for differentratios of the radii.

KEY WORDS : Convergent Flow, Friction Factor, Reynolds Number, Hydraulic Radius and Porous media.

N. Bhanu Prakasham ReddyAssoc.Prof.,Department of Civil Engg.,N.B.K.R.Institute of Sci. & Tech.,Vidyanagar-524 413,Nellore Dist., A.P., India.

G.N. Pradeep KumarProfessor.,Department of Civil Engineering.,S.V.U. College of Engineering.,Tirupati-517 502,Chittoor Dist., A.P., India

P. Rama Mohan RaoProfessor,Department of Civil Engg.,Institute of Engg. & Tech.,Kukatpally, Hyderabad,A.P., India.

INTRODUCTION

The study of the flow of fluids through porous mediais important in Civil Engineering as flowing in the area adjacentto a pumping well, flow through fissured rocks, flow throughrock fill dams and banks, and other fields like geology,petroleum etc. In the last five decades, the investigation onlinear and non-linear flow in porous media between parallelboundary have been carried out extensively. Further, aqualitative comparison of nature of radial flow with that ofparallel flow signifies the practical importance of convergingflow. Hence the same is cited wherever it is found necessary.

Wright (1968) published the results of research on aconverging permeameter using sand as a medium and air asthe fluid and compares the results relating coefficient ofresistance and Reynolds number. Ward (1964) employed themethod of dimensional analysis to obtain the expression forDarcy and non-Darcy parameter and obtained a single curvefor a constant Cw value for all the media. McCorquodale(1970) analysed the effect of convergence in a horizontalpermeameter by applying finite element method and appliedporosity and wall corrections for the data. Nasser (1970) carriedout experiments on the effect of convergence in a verticalpermeameter. McCorquodale (1970) and Nasser (1970)analysed the experimental data on the assumption thatconvergence of streamlines mainly affects only non-Darcycomponent of Forchhimer (1901) equation and assumes thatDarcy parameter is same for both parallel and convergingflow. Bhanu Prakasham Reddy (2003, 2004); Thiruvengadam

and Pradip kumar (1997); Venkata Raman and Rama MohanRao (1998, 2000) conducted some experiments on convergingpermeameter and studied the effect of convergence on Darcyand non-Darcy parameter.

In the case of convergent flow, for a given rate offlow through a known size of the medium packed, the gradientof head loss is a point function. A separate expression forhydraulic gradient taking into account the effect of variationin velocity. i.e., convective component, is therefore, derived.

Darcy (1856) related velocity of flow and hydraulicgradient by conducting experiments and arrived at anequation given by

V = KI (1)

Where V = velocity of flow, I = hydraulic gradient,and K is the coefficient of permeability, which depends uponthe particle size, shape and many other factors like void ratio,structure of soil mass, fluid properties etc. It has beenobserved that the relation given by Eq. (1) is valid only if theflow through porous medium is laminar. However, in general,for flow through coarse sand, gravel and boulders, the actualrelationship between the velocity and the hydraulic gradientis non-linear.

Forchheimer (1901) conducted experiments on asand-box model and proposed an equation in a quadraticform as,I = aV+bV2 (2)


17

for the non-Darcy regime of flow, in which a and b are thecoefficients determined by the properties of the fluid andporous media and are known as Darcy and non-Darcyparameters.

The investigations carried out by Ward (1964)require special attention. Ward (1964) expressed dimensionallythe equation for both laminar and turbulent flows in porousmedium as

kgVC

gkVI

2w+=

ρµ

(3)

in which I is hydraulic gradient and g is acceleration due togravity. Comparing Forchheimer (1901) Eq. (2) with Eq. (3),Ward (1964) obtained expressions for a and b as

gka

ρµ

= (4)

kgC

b w= (5)

where k = intrinsic permeability; ρ = density of the fluid andCw = media constant.

Defining friction factor fk as 2VkIg

and Reynolds number

Rk as ν

kV, and using square root of intrinsic permeability

k as the characteristic length, Ward (1964) obtained therelationship between friction factor and Reynolds number as

wk

k CR1f += (6)

Venkata Raman and Rama Mohan Rao (1998, 2000)expressed theroreticallly the relation between friction factorand Reynolds number using hydraulic radius (R) ascharacteristic length. By applying dimensional analysis oneobtained for hydraulic gradient, I may be written in terms ofhydraulic radius R as

gRVC

gRCVI

22

21

+=ρµ

(7)

where C1 and C2 are dimensionless constant ofproportionality and hydraulic radius R is defined as e/S0, in

which e is void ratio related to the porosity n by the relatione=n/(1-n) and S0, is specific surface defined as surface areaper unit volume, and takes the general form D/α , where Dis the particle dimeter and α is a coefficient depending uponthe shape of the particle: for sphere α = 6.0 and for irregularshaped particles, it has to be determined experimentally aftermeasuring the surface area of the particles. In this paper thevalue of α for crushed rock is taken as 8.8 as reported byPradip Kumar and Bhanu Prakasham Reddy (1997).

Comparison of Eq. (8) with Forchheimer Eq. (2)indicates taht

21 gRC

aρµ

= (8)

and

(9)

Multiplying both sides of Eq. (8) by 21

VgRC

, it becomes

RR

R CR1f += (10)

in which fR is the friction factor equal to 21

VRIgC

and RR is

the Reynolds number equal to νVR

.

EXPERIMENTAL PROCEDURE

Fig. 1 shows the dimensional details of theconverging flow permeameter used in the present study.Experiments were conducted on a convergent permeater of1000 mm high, 150 mm thick and of width varying from 750mm at top and 150mm at bottom and the angle of convergenceis 0.76 radians. The porous media of size 4.73 mm was retainedbetween two perforated screens. One screen was placed at aradius 1262mm at the inlet of the permeameter, while the otherwas located at a radius of 215 mm near the exit.

Pressure taps provided at different point along thethree radial lines of the permeameter at 50mm spacingconnected to a set of piezometers, permitted the measurementsof piezometric heads at these points. Water was suppliedfroma 25mm diameter inlet pipe to the permeameter through aheader tank of size 300mm x 150mm x 1050mm. A fixed flowwas maintained in the system through a constant head in theheader tank. Once the steady state conditions were obtained,the corresponding discharge was measured by the volumetricmethod for every run of the medium.


18


Evaluation of Linear Parameter (a) and Non-LinearParameter (b)

For media of certain size, the approach section atradius R1 and an exit section at radius R2 are arbitrarily selectedon any radial flow line. Based on the flow rates and thepiezometric heads at these two points, the seepage velocityand the hydraulic gradient are computed. The values of thecoefficients a and b for this R1/R2 ratio for that particularradial flow line are then obtained from a plot of I/V versus V,where V is seepage velocity at section at R1 and is equal toflow rate (Q) / flow area, (A1), at the approach section, whichis a straight line. A linear equation fitted to this line by themethod of least squares yields the values of a and b for thatparticular R1/R2 ratio and radial flow line. This procedure isrepeated for different ratios of R1/R2 to get different values ofa and b for the same media and radial flow line. A similaranalysis was carried out for the two other radial flow lineswith the same media. Results of the experiments are presentedfor the crushed rock sample of 4.73 mm in Table 1. Figs. 2(a-c)show plots of I/V vs V for the experimental data of the presentstudy for 4.73 mm crushed rock for three radial flow lines. It isseen from the Fig. 2(a-c) that I/V, increases as seepage velocityis increased for any R1/R2 ratio and I/V decreased as the R1/R2ratio decreases. It may be observed that the experimentaldata of the media for three radial flow lines, lie along separatestraight lines. Each follows a trend yielding different valuesof a and b for different radial flow lines of the same size of themedia.

Relation Between Head Loss (HL) and Seepage Velocity (V)

Figs. 3 (a-c) shows the variation of head loss (HL)with seepage velocity (V) for different R1/R2 ratio for eachradial line. It is seen from Figs.3(a-c), for each radial line, HLincreases with increasing R1/R2 ratio and also HL increaseswith increase of seepage velocity (V).

VARIATION OF fR and RR

The values of fR and RR are computed for a givenseepage velocity using the values of a and b. these computedof fR and RR values are plotted for each radial line for differentR1/R2 ratio area shown in Figs. 4(a-c). Fig. 5(a-c) shows thevariation of fR and RR for each R1 /R2 ratio for different radiallines. It is seen from Figs. 4(a-c) and Figs. 5(a-c) that for anyradial line and R1 /R2 ratio, RR increases with decreasing fRand fR decreases as the R1 /R2 ratio decreases for the crushedrock of size 4.73 mm. Eq.(10) is used for the computation ofdifferent values of RR by assuming different values for CRand fR. Figs. 6(a-c) shows the comparison between frictionfactor and Reynolds number for each CR value for the sameR1 /R2 ratio and for different radial lines. Figs. 6(a-c) showsthe theoretical plot of Eq. (10) with CR as third parameter. In

Figs. 6(a-c) the range of CR values is shown on the theoreticalcurve against which the experimental points of fR and RR wereplotted. The inclined dashed line in Figs. 6(a-c) demarcates,approximated, the RR at which the flow changes from nonlinear transition to wholly turbulent flow.

CONCLUSIONS

Experiments have been conducted on a covergingpermeameter and the values of a and b are obtained from aplot of I/V vs V. It is observed that the I/V, which is a measureof total energy loss in the medium increases as seepagevelocity is increased for any R1/R2 ratio and for any radialflow lines and also the total energy loss decreases as the R1/R2 ratio decreases for both crushed rock sizes. the relationbetween fR and RR, using the square root of intrinsicpermeability as the characteristic length shows that Reynoldsnumber (RR) increases as the friction factor (fR) decreases forany R1/R2 ratio and the friction factor (fR) and Reynoldsnumber (RR) decrease as the distance of any radial linesincreases from the converging boundaries. Further, it is seenfrom the experiments that for any radial flow line Reynoldsnumber (RR) increases with decreasing friction factor (fR) forany R1/R2 ratio and that the friction factor (fR) decreases asthe R1/R2 ratio decreases. The variation of fR and RR fordifferent CR values for different radial lines and for differentratios of radii are compared with the experimental and observedlie on the theoretical curve. The relation between fR and RRfor experimental data, using the hydraulic radius as thecharacteristics length and CR as a parameter is shown to besimilar to the Moody diagram for pipe flow.

ACKNOWLEDGEMENT

The author wish to thank the Ministry of Science &Technology, Department of Science and Technology, NewDelhi, authorities for the financial support (Grant No.:SR/FTP/ETA-22/2005) rendered by them for carrying out the study.The author also wishes to acknowledge the encouragementgiven by Sri N. Bhanusekar Reddy, correspondent, and Dr. C.Subba Rao, Principal, N.B.K.R. Institute of Science &Technology during the course of study.

REFERENCES

1. Bhanu Prakasham Reddy, N. and Rama Mohan Rao, P.(2003). Behaviour of non-linear flow and applicationof neural network in convergence boundaries. ISHJournal of Hydraulic Engineering, 9, No.2, September2003.

2. Bhanu Prakasham Reddy, N. (2004). Convergence effecton the flow resistance in porous media. IE(I) Journal.CV-1, 85, 36-43., May 2004

3. Darcy, H. (1856). Les Fontaines Publiques de la vill deDijon. Dalmont, Paris, 1856.


19

4. Forchheimer, P. (1901). Wasserbewegung durch boden.Z.Ver. Deutsch, Ing., 45, 1782-1788.

5. McCorquodale, J. A (1970). Finite element analysis ofnon-Darcy flow. Ph.D. thesis, University of Windsor,Windsor, Canada.

6. Nasser, M.S.S. (1970). Radial non-Darcy flow throughporous media. Master of Applied Science Thesis,University of Windsor, Windsor, Canada.

7. Scheidegger, A.E. (1963). The physics of flow throughporous media. University of Toronto Press, Toronto,Canada.

8. Thiruvengadam, M. and Pradip Kumar, G.N. (1997).Validity of Forchheimer equation in radial flow throughcoarse granular media. J. Engrg. Mech. ASCE, 123(7),696-705.

9. Venkataraman, P. and Rama Mohan Rao, P. (1998).Darcian, transitional, and turbulent flow throughporous media. J. Hydr. Engg., ASCE, 124(8), 840-846.

10. Venkataraman, P. and Rama Mohan Rao, P. (2000).Validation of Forchheimer's law for flow through porousmedia with converging boundary. J. Hydr. Engg.ASCE,126(1), 63-71.

11. Ward, J. C. (1964). Turbulent flow in porous media. J.Hydr. Div. ASCE, 90(5), 1.

12. Wright, D.E. (1968). Nonlinear flow through granularmedia. J. Hydr. Div., ASCE, 94, 1968.

NOTATIONS

The following symbols are used in this paper :

A = Cross sectional area;a = Darcy parameter or linear parameter;b = non-Darcy parameter or non-linear parameter;C1/C2 = constants;

Cw = media constants;e = void ratio;fk = friction factor using k as the characteristics length;fR = friction factor using R as the characterstics length;g = acceleration due to gravity;I = hydraulic gradient;Q = rate of flowR = hydraulic radius;Rk = Reynolds number using k as the characteristic length;RR = Reynolds number using R as the characteristic length;S0 = specific surface;V = macroscopic velocity or seepage velocity;α = shape factor;µ = dynamic viscosity;ν = kinematic viscosity; andρ = density of the fluid;

Fig 1 Converging flow permeameter

Table 1 Experimental Results for Crushed Rock Sample of Size 4.73 mm.


20

Fig 2(a) I/V vs V for 4.73mm crushed rock

Fig 2(b) I/V vs V for 4.73mm crushed rock

Fig 2(c) I/V vs V for 4.73mm crushed rock

Fig 3(a) Variation of head loss (HL) with velocity (V)

Fig 3(b) Variation of head loss (HL) with velocity (V)

Fig 3(c) Variation of head loss (HL) with velocity (V)


21

Fig 4(a) Plot between fR and RR for 4.73mm crushed rock

Fig 4(b) Plot between fR and RR for 4.73mm crushed rock

Fig 4(c) Plot between fR and RR for 4.73mm crushed rock

Fig 5(a) Plot between fR and RR for 4.73mm crushed rock

Fig 5(b) Plot between fR and RR for 4.73mm crushed rock

Fig 5(c) Plot between fR and RR for 4.73mm crushed rock

REYNOLDS NUMBER (RR)


22

Fig 6(a) Variation of friction factor (fR) with Reynolds Number (RR) fortheoretical values and for experimental values

Fig 6(b) Variation of friction factor (fR) with Reynolds Number (RR) fortheoretical values and for experimental values


23

Fig 6(c) Variation of friction factor (fR) with Reynolds Number (RR) fortheoretical values and for experimental values


24


TOPOLOGICAL INSIDES FOR STUDY OF SPATIO-TEMPORAL CHANGESIN THE PLANFORM OF THE BRAHMAPUTRA RIVER

ABSTRACT

The paper presents prediction of changes in the channel pattern with time of a braided river, theBrahmaputra. The procedure addresses the selection of input parameters from satellite images of IRS LISS-IIIsensor, comprising of 32 scenes for the years 1990, 1997, 2000 and 2002, from chainage 17.34 km (measuredfrom Indo-Bangladesh border) at Dhubri to 640 km at Kobo. Deployment of GIS technique has been made toextract the parameters to derive the alpha, beta and gamma indices for the entire study reach. Variations ofdifferent topological parameters with time and also indices have been studied and analysed in the paper.

KEY WORDS: Brahmaputra, topological indices, morphology, satellite images

R.N. SankhuaResearch Scholar

Nayan SharmaProfessor, WRD&M

A.D. PandeyAsstt.Professor

P.K. GargProfessor

Indian Institute of Technology Roorkee - 247667, India

INTRODUCTION

The channel geometry of a large braided streamwith mega-energy environment like the Brahmaputra riverdisplays highly variable and intricate morphologicalcharacteristics with rapid and substantial changes in planform. Changes in the channel pattern with time for themeandering streams have been studied by numerous workers(Anderson, 1967, Berge, 1962, Ferguson, 1977, Hickin et al,1975). However, only a few investigations of changes indistributary channel patterns of braided streams are available(Coleman, 1969). These studies deal with variation in channelpatterns over short periods. The Brahmaputra, a highlybraided river, has been surveyed in post monsoon floodperiods many times because of its caparious nature ofshifting its channels rapidly.

THE BRAHMAPUTRA RIVER

The Brahmaputra is a major international rivercovering a drainage basin of 580,000 km2, extending from82°E to 97° 50' E longitudes and 25° 10' to 31° 30' N latitudes.Its basin spans over an area of 293,000 km2 (50.51%) in Tibet(China), 45,000 km2 (7.75%) in Bhutan, 194,413 km2 (33.52%)in India and 47,000 km2 (8.1%) in Bangladesh. Its basin inIndia is shared by Arunachal Pradesh (41.88%), Assam(36.33%), Nagaland (5.57%), Meghalaya (6.10%), Sikkim(3.75%) and West Bengal (6.47%) (Goswami, 1985).Originating in a great glacier mass at an altitude of 5,300 mjust south of the lake Konggyu Tso in the Kailas range,about 63 km southeast of Mansarovar lake in southern Tibet,the Brahmaputra flows through China (Tibet), India and

Bangladesh for a total distance of 2880 km, before emptyingitself into the Bay of Bengal through a combined water coursewith the Ganga. Table-1 depicts the country and Indian state-wise break-up of basin area and channel length.

Table 1 The Brahmaputra River: Country and Indian state-wise break-up of basin area and channel length

THE BRAHMAPUTRA RIVER – ITS GEOLOGICAL ANDGEOMORPHOLOGICAL SETTINGS

The Brahmaputra valley in Assam is underlain byrecent alluvium approximately 200-300 m thick, consisting ofclay, silt, sand, and pebbles (Geological Survey of India,1974). The valley is developed over the fore deep in betweenthe peninsular mass and the Tethyan geosynclines. The foredeep is characterized by some complicated tectonic featuresrepresenting a series of faults and thrusts and extending inthe NE-SW direction from the eastern margin of the

S.No. Country Basin area Channel(Km2) Length (Km)

1. Tibet (China) 293,000 1,6252. Bhutan 45,000 -3. India 194,413 918

(a) Arunachal Pradesh 81,424 278(b) Assam 70,634 640(c) Nagaland 10,803 -(d) Meghalaya 11,667 -(e) Sikkim 7,300 -(f) West Bengal 12,585 -

4. Bangladesh 47,000 337


25

Meghalaya plateau across the North Cachar Hills to TirapDistrict of Arunachal Pradesh. These thrusts are originatedat the time of the late Himalayan-Patkai-Naga Hills orogenyand pushed the tertiary deposits into folds and faults. Thefore deep is believed to be under the sea till the sub-recentperiod received deposits during all the periods of the tertiaryand quaternary ages. The tertiary deposits consist mainly ofsandstones, shale, grit, conglomerate and lime stones.

Towards the close of the Pleistocene period,alluvium began to be deposited in the form of sand, pebblesand gravels especially along the northern foothills of theBrahmaputra valley. These valley deposits of reddish brownsandy clay with some pockets of unasserted pebble, cobble,sand and silt have been identified as older alluvium. Thetertiary beds of the valley are overlain by a thick layer ofnewer alluvium composed of sand, silt and clay, which arebeing brought down from the rising Himalayas in the north,the Patkai Naga ranges in the east and south-east and theMeghalaya plateau in the south by numerous tributaries ofthe Brahmaputra. The characteristic geological and tectonicframework coupled with structural complexities has renderedthe Brahmaputra basin geo-morphologically a mostcomplicated one. A variety of landform under varied climaticconditions has formed over the geologic and tectonic baseof the region. The peri-glacial, glacio-fluvial, and fluvialprocesses are dominantly operative in the basin at varyingaltitudes.

The higher elevations of the Himalayas experienceperi-glacial and glacio-fluvial erosion and deposition. Thebare relief of the sub-Himalayas and greater Himalayas sufferfrom immense sheet erosion owing to peri-glacial solifluction.The low hill ranges with hot and humid climate and heavyrainfall concentrated to a few months of the year experiencesolifluction, sheet erosion and landslides.

Fluvial processes are, on the other hand,significantly dominant on the valley bottoms and plainswhere alluvial deposition takes place due to erosion of thehigher surface by rivers and flooding in the valleys. Theerosional and depositional processes conspicuouslyintensified by copious rainfall and frequent seismicmovements, however, play a dominant role in creating variousfluvio--geomorphic environments in the basin.

The Brahmaputra river is characterized by highintensity flood which flows during the monsoon season,June through September, with an average annual flooddischarge of 48,160 m3/sec. The highest flood dischargerecorded in the Brahmaputra at Pandu (Assam) was of theorder of 72,148 m3/sec (in year 1962), which had a recurrenceinterval of 100 years (WAPCOS, 1993). The daily hydrographof the river at Pandu exhibits drastic fluctuations in dischargeduring the monsoon season, whereas the time series of annual

maximum flood events for the period 1955-2000 do not indicateany perceptible trend (Goswami, 1998).

THE STUDY AREA

Considering the river flows, the confluence of rivertributaries, and for convenience in computing the segments,the study area has been divided into thirteen blocks fromchainage 17.34 km( Cross section-2) at Dhubri to 640 km(Crosssection 65) at Kobo. The reach length in between five crosssections is considered as one block (Figure-1).

Fig 1 Blocks in the Entire Reach

TOPOLOGICAL ANALYSIS

The analysis of the plan form changes of theBrahmaputra river has been carried out from the IRS LISS-IIIdigital satellite data comprising of 32 scenes for the years1990, 1997, 2000 and 2002. Since a braided channel ischaracterised by (i) channel segments (anabranches),(ii)nodes where segments branch or join, and (iii) islandsenclosed by segments, their network can be studied byusing Topological theory as suggested by Howard et al (1970)and Orme and Krumbein(1972). Accordingly, the followingtopological parameters for various blocks have beenmeasured for different years from the satellite images. Figure-2 shows a typical sketch of the block -3 (1990) of the differentparameters.

Fig 2 Typical Sketch of Block 3 (1990)

t, total number of segments, including segments lyingentirely within the block and those bisected by the linesbounding the block,

e, total number of bisected segments,c, total number of entire segments,

t = 86c = 75e = 11n = 52i = 28p = 9


26

i, total number of unbisected islands,p, total number of islands bisected by the bounding lines,n, total number of nodes.

In addition, topological indices α , β andγ describing the degree of connection between the nodeson a graph have been calculated. These are defined as follows-

5)(21)(Index )( Alpha

−+++−

=enent

α

ent+

=Index )( Beta β

)2(3Index )( Gamma

−+=

entγ

The alpha index is the ratio of the observed numberof islands to the greatest possible number of islands for agiven number of nodes. The higher the alpha index, the morea network is connected. Simple networks will have a value of0. A value of 1 indicates a completely connected network.

Beta (β) Index measures the level of connectivityand is expressed by the relationship between the number oflinks (t) over the number of nodes (n). More complex networkshave a value greater than 1. In a network with a fixed numberof nodes, the higher the number of segments, the higher thenumber of channels possible in the river network. Complexnetworks have a high value of Beta.

The gamma (γ) index is the ratio of the observednumber of channel segments to the greatest possible numberof segments for a given number of nodes (Berge, 1962) andGarrison and Marble, 1962). The value of gamma is between0 and 1 where a value of 1 indicates a completely connectednetwork and would be extremely unlikely in reality.

RESULTS AND INTERPRETATIONS

Variations of different topological parameters aredepicted in Table-2 and indices with time in different blocksare shown in Figure -3 to Figure -5. The indices are plottedon simple arithmetic paper. The study showed that the degreeof braiding of individual reaches fluctuates in the short-termdue to morphological response to the magnitude andduration of monsoon runoff events. The following interestingobservations can be made from these figures and table.

(i) For all the years, variables t, c, i, e and n show distinctdecrease in values in block 5, 10 and 11. The lowest

trend is marked in block 5. In contrary, block 4, 7, 9and 12 showed increase in their values. The indices

α β and γ are characterised by approximatelysimilar decrease in values in blocks 5, 9 and 11.

(ii) Comparison of trends for the different years indicatesthat t, c, n and i values increased in the upstreamdirection for from block 2 for the years 1990, 1997,2000 and 2002 and this trend is gradual for the year2002. Probably, the trend has been decelerated afterthe construction of the Narnarayan Bridge atPancharatna, at cross section 9, which is pronouncedfor these blocks. Similar trend has been observed atblock 8, which may be due to the Kalia Bhomara Bridgenear Tezpur.

(iii) It is noted that, the decrease in values in block 13 oft, c, n and i for the years 1990, 2000 and 2002 showedthe intensity of non-braiding tendency. The braidingintensity is high in blocks 4, 7, 9 and 12, indicatingthat the island formations are more in these reaches.

(iv) The study of α , β and γ indices over the entirestretch revealed that their values in blocks 2 and 4are very low as compared to the other blocks.

An increase in the values of the parameters andindices discussed above, suggests an increase in intensityof braiding and decrease in their values indicates a tendencytowards non-braiding. Another reason for low values of theseindices in blocks 5, 8 and 9 may be attributed due to theexistence of the hills on the sides of the river, therebyrestricting the flow and constraining of the formation of morechannels.

The average values and indices for the entire stretchare found to be 0.222, 1.401 and 0.487 for the year 2000 and0.215, 1.390 and 0.482 for 1990 respectively. The years 1990,1997 and 2002 show less channelization of the plan form ascompared to the year 2000.

THRESHOLDS OF THE INDICES

The parameters discussed above wield a profoundinfluence on the intensity of braiding. Thus, after a criticalanalysis of the trends of the variation of α , β and γindices in the entire reach of the river Brahmaputra, thefollowing thresholds are identified to provide a classificationof the braiding phenomena as well as to make them usefulfor practical applications subsequently.


27

Values of parameters in the years

Blocks 1990 1997 2000 2002

t c e n i t c e n i t c e n i t c e n i

1 61 52 9 35 19 45 37 8 27 14 62 53 9 32 22 35 27 8 22 9

2 54 42 12 30 14 70 58 12 43 21 52 40 12 30 15 53 43 10 30 14

3 86 75 11 52 28 87 73 14 51 25 108 94 14 64 36 55 44 11 31 15

4 116 106 10 64 44 115 106 9 70 38 144 134 10 84 53 103 94 9 61 36

5 22 14 8 12 5 40 33 7 23 12 24 18 6 14 6 25 19 6 14 6

6 82 73 9 46 28 102 93 9 64 32 57 47 10 33 16 61 53 8 35 20

7 105 95 10 59 36 115 105 10 69 37 59 51 8 33 19 123 113 10 72 41

8 54 46 8 31 18 107 98 9 63 36 57 52 5 34 21 93 82 11 56 28

9 77 70 7 50 32 125 116 9 82 43 84 79 5 52 30 104 94 10 62 34

10 80 70 10 47 27 76 67 9 44 26 63 54 9 36 20 72 65 7 43 25

11 70 59 11 41 20 68 57 11 37 22 76 63 13 42 24 60 50 10 33 18

12 134 123 11 79 45 169 157 12 106 59 154 139 15 96 55 132 119 13 75 48

13 86 72 14 51 24 222 204 18 130 75 123 111 12 71 41 144 130 14 86 45

Table 2 Values of t, c, e, n and i parameters

Indices Alpha Index (α ) Beta index ( β ) Gamma Index (γ )

Less Braided < 0.15 < 1.25 < 0.44

Moderately Braided 0.15 – 0.20 1.25 - 1.38 0.44 - 0.47

Highly Braided 0.20-0.25 1.38 -1.46 0.47 - 0.5 0

Very Highly Braided > 0.25 > 1.46 > 0.50


28

1.000

1.100

1.200

1.300

1.400

1.500

1.600

1 2 3 4 5 6 7 8 9 10 11 12 13

Block

β

1990 1997 2000 2002

0.400

0.420

0.440

0.460

0.480

0.500

0.520

0.540

0.560

1 2 3 4 5 6 7 8 9 10 11 12 13Block

γ

1990 1997 2000 2002

Fig 4 Variation of Beta index in different blocks

Fig 5 Variation of Gamma index in different blocks

0.050

0.100

0.150

0.200

0.250

0.300

1 2 3 4 5 6 7 8 9 10 11 12 13

Block

α

1990 1997 2000 2002

Fig 3 Variation of alpha index in different blocks


29

CONCLUSIONS

In conclusion, the present study has indicated thepromising use of the topological indices in being able topredict channel change, at least qualitatively. The braidingin the river Brahmaputra is mainly due to high energy fluvialenvironments, large and variable discharges, dominant bedload transport and non cohesive banks lacking stabilizationby vegetation. It seems that the portions of the river (blocks4, 6 and 10 to 12) are the locus of the maximum sedimentationzones, where as the portions comprising blocks 2 and 5 aremarked as the low sedimentation rates. As the Brahmaputraillustrates; of vital importance to the usefulness of the studyis an empirically derived indices of braiding, which can takeinto account constraints on plan form change. These indicestruly modulate the effect of plan form changes on channelmigration and exert significant effect on river morphology. Itis also important to consider complicating factors such asislands and multi-channel flow, which may be important forthe Brahmaputra river.

SCOPE FOR FUTURE STUDY

The paper has illustrated the application oftopological indices for study of spatio-temporal changes inthe planform of the river Brahmaputra. For planning suitablemeasures for the river Brahmaputra, one has to keep in mindthe essential stochasticity involved in the behaviour of theriver. However, what is needed now is a complete quantitativeassessment of channel change along the Brahmaputra interms of the appropriate input parameters, which can beextracted from GIS technique. Only, a plan for control ofbraiding cannot, therefore, be a rigid one but has to be flexiblebased on the projection of the past in near future andexperimentation through neuromorphic model studies inconsultation with ground truth verification, to evolve asuitable medium and long term measures for planning andmanagement.

REFERENCES

1. Anderson, A.G, (1967). On the development of streammeanders. Proceedings of 12th Congress of IAHR, FortCollins.

2. Berge, J.C. (1962). Theory of graphs and itsapplications, John Wiley, New York.

3. Brice, J.C. (1960). Index for Description of ChannelBraiding. Bulletin of the Geological Society ofAmerica, 71, (1833).

4. Coleman, J.M, (1969). Brahmaputra river: ChannelProcess and sedimentation, Sedimentary Geology, Vol-3.

5. Ferguson, R.I (1981). Channel Form and ChannelChanges. In ‘British Rivers’ by Lewin, J. (Editor), Allenand Unwin, London, pp.90-125.

6. Garrison, R I, (1977). Meander Migration: Equilibriumand change in river Channel changes, in river channelchanges edited by Gregory, K.J John Wiley and sons,New York.

7. Geological Survey of India publication, (1974) BulletinSeries B

8. Goswami, D.C., (1985). Brahmaputra River, Assam,India : Physiography, Basin Denudation, and ChannelAggradation, Water Resources Research, 21, (959-978).

9. Goswami, D.C., (1998). Fluvial regime and FloodHydrology of the Brahmaputra River Assam. In: KaleV. S. (ed.) Flood studies in India, Geol. Soc. India,Memoir 41, (53-75).

10. Gupta, N.C., Prakash, B and Singhal B.B.S.,Topological changes with time in the plan form of theKosi river in north Bihar and Nepal, Proceedings ofInternational Workshop on Alluvial River Problems,Roorkee, 1980.

11. Hickin, E.J and Nansen,G.C.(1975). The character ofchannel migration on the Britten river. North eastBritish Columbia, Canada, Bulletin of GeologicalSociety, America, Vol.86.

12. Howard, A.D., Keeth, M.E. and Vincent, L.C.(1970).Topological and Geometrical Properties ofBraided Streams. Water Resources Research, 6, (1674-1688).

13. Krumbein, W. C. and Orme, A.R. (1972). Field Mappingand Computer Simulation of Braided Stream Networks.Bulletin of Geological Society of America, Vol 83.

14. Morphology study of the Brahmaputra river , WAPCOS,(1993).


30


RUNOFF PRODUCTION ON HILL SLOPES UNDERDIFFERENT LAND USES

K.K. Satapathy R.K. PandaPrincipal Scientist, ProfessorICAR Research Complex for NEH Region Indian Institute of TechnologyUmaim, Meghalaya Khargpur

ABSTRACT

The rainfall runoff relationship varies with many factors of which land use practices and conservationmeasures are most important. Nine micro watershed with areas varying from 0.52 ha to 3.8 ha were instrumentedin the experimental farm of ICAR (Indian Council of Agricultural Research) located at Barapani in Mehgalayato study the effect of land use patterns on hill slope runoff - the principal erosive agent. Considering thepotentialities of land uses in the hilly region of North East India, the farming sytems studies were: live stockbased farming sytem, timber plantations, agro forestry, agriculture on bench terraces, agri-horti-silvi-pastoralsystem, horticulture, natural vegetation, shifting cultivation and pine afforestation. Bench terraces, contourtrenches, contour bunds, half moon terraces were the major soil conservation measures. Surface runoff from theundisturbed billy watersheds was very small. Large intense rainfall events with high antecedent moisture contentin soils generated most of the runoff from the undisturbed and treated watersheds. As expected. the watershedtreated with shifting cultivation yielded the highest peak runoff, while the one left undisturbed with naturalvegetation yielded the minimum runoff. Mixed land use systems with appropriate soil conservation measures,namely bench terraces, contour trenches etc. were most effective in checking erosion and retaining 90-100% ofannual rainfall in situ. The runoff data indicated that even after best land, water and crop management practices,on an average 17.48-28.98 mm went out as runoff annually from agricultural and agri-horti-silvipastoralwatersheds, which can be stored either for fishery or for supplemental irrigation in the donor waershed. Soilerosions from well-managed watersheds were negligible. The storm runoff data were utilised to derive unithydrographs for ungauged watersheds. The average 30-minute unit hydrograph for all the watersheds werederived and compared using selected storms. The conservation factor was evolved to accommodate the combinedeffect of conservation measures, land use as well as human or animal interferences. The study also quantified themajor hydrologic parameters of water harvesting tanks in the lower reaches of the hill slopes using a waterbalance approach. the subsurface flow (inter flow) from the upper slopes contibuted for 82.90% of annual inflowinto the tanks. A graphical solution has been proposed to estimate the availability of water for water harvestingprojects on hilly watersheds.

KEY WORDS : Runoff, Unit hydrograph, Watershed, Land use, Hilly region, Conservation measures, Farmingsystems, Shifting cultivation.

INTRODUCTION

One of the accepted methods of controlling soilerosion is to arrest its movement at its origin. In order toprepare a comprehensive erosion control programme, oneshould quantify the erosion agent (mostly runoff) that anywatershed is being subjected to and also its behaviouralchanges. The rainfall- runoff relationship varies with manyfactors of which land use practices and conservationmeasures are most important. The complexity of hill slopehydrology has long been recognised. There are large numberof process formulations that have been devised to facilitatethe prediction of runoff rates. Development of watershed

scale models compatible with hydrology of hill slopes shouldhelp minimize the unproductive approaches. Many studieshave been directed correlating yearly runoff with rainfall usingparameters defined in terms ofland use, soils and topography.These studies have resulted in prediction equations that areuseful for simulating watershed behaviour for differentcombination of these parameters and estimating water yield.For a few micro watersheds, there exist stream-gaugingrecords of sufficient length to make an accurate assessmentof their water yield characteristics. Such studies in the NorthEastern region are, however, rare owing to the remoteness ofthe area and inadequate documentation as well asunavailability of required data base. The present study aims


31

at evaluating the effect of watershed based mixed land usesystem along with soil conservation measures on runoff yieldin hilly micro watersheds. The study also quantified the majorhydrological parameters ofthe water harvesting tanks in thelower reaches of hill slopes.

DATA AND METHODOLOGY

The site of the current study was at the ICARResearch complex for North Eastern Hills Region situated atBarapani in the state of Meghalaya. Barapani is locatedbetween 25° 41', N latitude and between 91° 54',and 91° 63', Elongitude and is 22 Kms away from Shillong (Meghalaya).The area is a part of East Khasi hills and comprises of rollingterrains and steep slopes interspersed with valleys andplateaus. The area consisted of typical hilly undulatingterrain with the altitude varying between 952 and 1082 metersabove mean sea level. The soil belonging to typical paleaudalfseries with clay loam texture has pH ranging from 5.4 to 6.2.Nine micro watersheds with areas ranging from 0.52 ha to 3.8ha were identified to determine the effect ofland use systemson runoff yield. The average slope of the experimentalwatersheds varied from 32.02 to 53.18 percent. Consideringthe potentialities of land uses in the hilly regions of NorthEast India, the farming systems studied were: live stock based

Table 1 Details of experimental watersheds under various land use systems

farming system (W1), timber plantation (W2), agro- forestry(W3), agriculture in bench terrace (W4), agri- horti-silvipastoral system (W5), horticulture (W6), naturalvegetation (W7), shifting cultivation (W8), natural vegetationalong with pine plantation (AEW). Bench terraces, contourtrenches, contour bunds, half moon terraces were the majorsoil conservation measures. Details of the experimentalwatersheds under various farming systems are presented inTable 1.

Hydrological gauging stations were installed at theoutlet of all the experimental watersheds. The gaugingstations consisted of F type water stage level recorders, Hflumes of appropriate sizes, Coshocton wheels with relatedstructures and so on. The stage level recorder ensuredcontinuous measurement of discharge rates with the help ofdischarge rating for the H flume size. The depth and volumeof runoff computed by this process included surface flow aswell as base flow; the surface flow and base flow componentof total flow was computed daily as well as for every storm.A water harvesting tank constructed in the lower reaches ofhill slopes was used to investigate the hydrologicalbehaviour for development of norms of generalapplicability.

Experimental watersheds under details

W1 W2 W3 W4 W5 W6 W7 W8 AEW

Land use

Agriculture (fodder)

Fores try (fuel, fodder)

Agro-

forestry

Agri culture (food crops)

Agri- horti- silvi-

pastoral)

Horti

culture

Natural

vegetation

Agri Culture (shifting

cultivation)

Pine plantation & natural vegetation

Total area (ha)

1.39

3.80

2.94

0.64

1.58

3.13

1.03

0.52

3.54

Watershed relief (m)

99.00 100.00 100.00 82.00 89.00 138.00 91.00 65.00 120.00

Average slope (%)

32.00 38.00 33.00 32.18 32.42 41.77 53.18 54.87 32.37

Maximum length (m)

301.00 320.00 295.00 240.00 260.00 515.00 250.00 185.00 464.00

Maximum width (m)

65.00 230.00 175.00 65.00 85.00 85.00 70.00 48.00 126.00

Drainage Good Good Good Good Good Good Good Good Good

Soil Clay Clay Clay Clay Clay Clay Clay Clay Clay

Texture Loam Loam Loam Loam Loam Loam Loam Loam Loam

Land Capability class

Vile Vile Vile Vile Vile Vile Vile Vile Vile

Conservation factor

61.33 75.80 70.81 57.34 62.91 73.62 80.00 36.73 80.00


32

CONSERVATION FACTOR

The effects of conservation measures, land use aswell as human or animal interference have beenaccommodated in conservation factor evolved by Singh(1987) for calculating watershed runoff. Leaving rainfall as aseparate factor, land use, soil conservation measures andhuman or animal activities are the major factors that governthe amount of runoff and soil loss from slope. The combinedeffect of these factors has been termed as conservation factor(C). The factor has been modified by assigning prioritynumbers 5 to 50 for major land uses and soil conservationmeasures in order of risk involved for soil erosion: thenumbers have been arrived through trial and error after ittallied with the order of effectiveness of land uses in thearea. The conservation factor (C) for the mixed land usesystems are computed by

( ) ( )n1

annnn1a111

A.....................ANHNCNLA.........NHNCNLA

C++

++++++= (1)

where,A1, .......... An = area under various land uses in haNL1, .......NLn = number assigned to various land use(Table -2)NC1........NCn = numbers assigned to different conservationmeasuresNHa1........NHan = numbers assigned to various human andanimal activities

The conservation factor of various watershedcomputed by using the above formula has been presentedin Table-1.

Table 2 Numerical values assigned to various items of conservation factor


Land use and Surface Runoff

Hydrological behaviour of watersheds for a nineyear period in terms of total water yield, base flow and peakrate of flow have been presented in Table 3. Surface runofffrom the undisturbed hilly watersheds and those withsubstantial vegetative cover were very small. Large intenserainfall events with high antecedent moisture content in soilsgenerated most of the runoff from the undisturbed and treatedwatersheds. Mixed land use systems with appropriate soilconservation measures, namely, bench terraces, contourtrenches etc. were most effective in retaining 90-100% annualrainfall in situ and simulated the effects of natural forests.This lower percentage of water yield can be attributed to thehigh infiltration rates maintained by crop and forest canopyas well as conservation measures. Land use and conservationpractices varied, however, in their effectiveness forcontrolling surfacerunotf. The mean water yield recordedfrom the watersheds varied from 0.43% to 16.78% of annualrainfall. Surface runoff from silvipastoral system and mixedblock forest plantation with no physical soil conservationmeasures was 15 -16 % of the total water yield. Rainfallamount, intensity, duration and frequency of occurrence

caused considerable variation in storm flow. Most of thetime precipitation was too small or too infrequent to generatestorm flow. The runoff data indicate that even after best landand crop management practices, on an average 17.47-28.98mm went out as runoff annually from agricultural and agrihorti- silvipastoral watersheds which can be stored eitherfor fishery or for supplemental irrigation in the donorwatersheds. The contributions to stream flow in thewatersheds having substantial area under natural forest isprimarily by subsurface flow (base flow). Three of the ninewatersheds, with relatively large areas, namely, W2 (3.8 ha),W3 (2.94 ha), AEW (3.59 ha) and substantial area under foresthad continuous base flow which appeared on the upperreaches of the gauging stations. These watersheds on anaverage had continuous flow for 156, 116 and 190 daysrespectively in a year. The annual base flow from thesewatersheds constitutes about eighty percent of the totalwater yield. As expected, the watershed (W8) treated withjhum (shifting cultivation) yielded highest peak runoff (86.10mm/hr) while the one left undisturbed with natural vegetation(W7) gave the minimum peak runoff (4.49 mm/hr) during theperiod. However, the provision of trenches in fodder basedagriculture most effectively conserved moisture andproduced peak runoff 7.81mm/hr during the period.

Land use Assumed number

Conservation measure

Assumed numerical value

Human/Animal activity

Assumed numerical value

Agriculture/shifting cultivation 20

No measure

10

Intensive

5

Horti culture/silvi pasture/plantation

30 Contour bund/contour

bench

20 Moderate 10

Forest/natural vegetation 50 Bench terrace 30 Negligible 20


33

Table 3 Annual water yield, base flow and peak flow from different watersheds

Rainfall-Runoff Relations

The values of the small annual runoff from theexperimental watersheds shown above is misleading relativeto the potential, since much of the runoff are resulted from asmall number of large intensity rainfall with high antecedentsoil moisture content. Loague (1985) found that of all models,simple linear regression model is marginally better inpredicting runoff depth from small upland catchments thanother models.

The regression models are of from:

D1D aPaQ += (2)

where,PD = total rainfall depth (cm)QD = total runoff depth (cm)a1, a2 are the equation parameters

The rainfall runoff records of some selected stormsfrom the study watersheds were subjected to regressionanalysis using a regression package (Table 4). The stormswith antecedent rainfall of more than 5.25 cm were selectedfor the study. .

The relations are more or less similar to the annualrunoff trend except for the W2 watershed where some of thestorms produced high runoff following the clearing of thearea for plantation. These regression equations weredeveloped from the selected storm events during first 9 years.The equations were tested using the storm events of 10th yrfor five watersheds W1,W2, W6, and AEW, where sufficientnumber of data sets were available. The comparison ofobserved and predicted runoff values (Fig. 1), though

displays moderate degree of correlation, the models(equations) can be used as first approximation of storm runoffin the watersheds. Unlike physically based models, theequations require minimum input, but are applicable only tothe watersheds from which they have been developed.However, when these empirical models are tailored to specificwatershed conditions, results may be comparable to thosefrom more complex models. Rainfall runoff data for the stormsproducing maximum runoff coefficient also has beenpresented in Table 4.

Fig 1 Relationship between predicted and observed storm runoff

Watershed Annual water yield range (mm)

Mean water yield (mm)

Mean water yield as % of annual rainfall

Baseflow range (mm)

Mean baseflow as % of mean water yield

Maximum peak flow (mm/hr)

W1 0-66.69 9.56 0.37 - - 7.81

W2 67.42-1013.88 371.90 4.73 55.04-774.02 83.11 13.54

W3 39.31-648.26 241.14 9.55 34.65-542.77 85.20 12.87

W4 0.60 - 62.49 12.47 0.69 - - 20.71

W5 0.24-121.91 28.98 1.14 - - 12.07

W6 6.41-556.55 108.06 4.28 - - 11.40

W7 0-51.39 11.77 0.46 - - 4.49

W8 0-517.72 102.94 4.07 - - 86.10

AEW 257.61- 1311.11

696.78

27.60

232.50- 1071.82

85.50

9.40


34

Table 4 Rainfall-runoff relations and maximum runoff coefficients of different watersheds

P = storms railfall depth (cm) R = Direct surface runoff, cm. r=correlation coefficient, and n = no. of storm eventsused for developing equation.

Modelling land use effect on runoff

The unit hydrograph model attempts to establish arelationship between the effective rainfall of a storm and theresulting direct runoff hydrograph for a given drainage basinwithout directly involving the losses of rainfall in the model.Standard unit hydrograph shapes are of special concern toaccurately evaluate the hydrologic response of the directrunoff. Furthermore, in the hilly areas where storm waterdetention must be provided to control the effects of landuse conversion, the accuracy of the shape of the hydrographis an important determinant of the value of required storage.The average 30-minute unit hydro graph from selected stormswere prepared following standard procedures. The observeddirect runoff hydrograph and those computed by usingderived unit hydrographs of experimental watersheds alongwith the corresponding rainfall data of some selected stormswere compared as have been presented in Fig. 2.

It can be seen that predicted hydrographs are veryclose to the observed ones. It indicates that from small hillywatersheds having varying hydrological characters, unithydrographs could be used as the basis for generating runofffrom an effective rainstorm event. Unit hydrograph synthesisfor the ungauged basins is based on empirical expressions,which relate pertinent physical characteristics of thewatershed to the geometric aspect of the unit graph. Theunit hydro graph parameters derived for each of the ninewatersheds were subjected to multiple regression analysisto yield best regression equation. The definition sketch andderived unit graph (30 - minute) parameters- Qp (peak runoffrate), Tp (time to peak), Tb ( time base). T50 (time to 50% peakdischarge), D50 (unit hydro graph width at 50% peakdischarge) have been presented in Fig 3 and Table 5.

Fig 2 Observed and derived direct surface runoff

It can be seen that predicted hydrographs are veryclose to the observed ones. It indicates that from small hillywatersheds having varying hydrological characters, unithydrographs could be used as the basis for generating runofffrom an effective rainstorm event. Unit hydrograph synthesisfor the ungauged basins is based on empirical expressions,which relate pertinent physical characteristics of thewatershed to the geometric aspect of the unit graph. Theunit hydro graph parameters derived for each of the ninewatersheds were subjected to multiple regression analysisto yield best regression equation. The definition sketch andderived unit graph (30 - minute) parameters- Qp (peak runoffrate), Tp (time to peak), Tb ( time base). T50 (time to 50% peakdischarge), D50 (unit hydro graph width at 50% peakdischarge) have been presented in Fig 3 and Table 5.

Watershed Relationship Maximum runoff coefficient

W1 R= 0.04p -.06(r=.63, n=20) 0.09

W2 R= 0.1 6p -.24(r=.64, n=40) 0.41

W3 R=.014p-.27(r=60, n=37) 0.34

W4 R=0.12p-.21(r=.81,n=18) 0.12

W5 R=0.07p-.14(r=.65, n=37) 0.15

W5 R=0.15p-.31(r=.66,n=39) 0.21

W7 R= O.OSp -.74 (r=80, n=10) 0.08

W8 R=0.46p-.74(r=.77, n=21) 0.53

AEW R=0.01p-.19(r=63, n=47) 0.16


35

Table 5 Unit hydrograph parameters of various watersheds

Fig 3 Unit hydrograph parameters; definition sketch

Watershed

Qp (cumec)

Tp(hr)

Tb (hr)

T50 (hr)

D50 (hr)

W1 0.0379 0.58 3.8 0.350 0.750 W2 0.1081 0.70 6.0 0.400 0.675 W3 0.0847 0.67 5.0 0.400 0.725 W4 0.0142 0.52 3.6 0.325 0.825 W5 0.0430 0.58 4.5 0.375 0.750 W6 0.0933 0.60 5.0 0.350 0.675 W7 0.0252 0.50 3.8 0.300 0.750 W8 0.0183 6.40 2.5 0.250 0.700 AEW 0.8370 0.70 5.8 0.400 0.775


36

The regression equation of the parameters, namely,Qp, Tp, T50, D50 (Fig. 3) in terms of watershed area,conservation factor, average slope obtained with multiplecorrection analysis using the log transformed values are asfollows:

787.0392.022.1P CSA156.Q −= (3)

(n = 9, r = .997)

252.0360.0128.0P CSA696.T −= (4)

(n = 9, r = .99)

411.0212.0227.0P CS.A49.1T −= (5)

(n = 9, r = .98)

225.0401.0094.050 C.S.A55.T −= (6)

(n = 9, r = .98)

263.0251.0121.050 CSA64.D −−= (7)

(n = 9, r = .93)

where,QP = peak discharge (m3/sec)TP = time to peak discharge (hr)Tb = time base of unit graph (hr)T50 = time of 50% peak discharge (hr)D50 = Unit graph width at time T (hr)A = area of the watershed (hectare)S = average slope ofthe watershed (percent)C = conservation factor.

These equations would help to determine theparameters necessary for sketching unit graphs of microwatersheds in the area.

The unit hydro graph shape reflects manycombinations of watershed characteristics. According to theabove equations, watersheds with large area should havegreater peak flow, time base and time to peak. It is the mostdominant factor influencing the peak flow from thewatersheds. Generally larger area, milder slope and largerconservation factor, increase the magnitude of timeparameters; where as steeper slopes, lower conservationfactors decrease the magnitude of time parameters andincreased the peak. As can be seen from Equation 7, with theincrease in area, the hydrograph becomes narrower at theupper portion with sharp peak, indicating steep sloppyterrains having low channel storage. From the data tp/tr (tr =unit graph duration) ratio ranged from 0.8 to 1.7. However,the ratio is generally increased with increase in drainagearea, decrease in average slope and increase in conservationfactor. The data analysis performed in this study for the ninewatersheds indicate that the values from the topographicdata closely agree with those from the hydrologic data. Thissuggests that the procedure outlined here for deriving unithydro graph from the topographic and land use data is avery reasonable method. The hydrologic effects of land coverconversion from forested to agricultural land use are ofspecial concern to those involved in hydrologic analysis.The concept of conservation factor is unique of its kind,though there exist factors, which are akin to conservationfactors but are not exactly the same. The models containingthis conservation factor are statistically significant and cangenerate data, which are very close to the observed values.

Hydrological Water Balance of Water harvesting Tank

A water balance analysis was conducted for thewater-harvesting tank located at the lower reaches of thewatersheds to calculate inflows through rainfall and runoffand losses through over flow, seepage and evaporation.Inflow outflow analysis, considering all components shownin Fig. 4 was employed.

Fig 4 Schematic representation of pond inflows and outflows


37

The tank as a system with inputs, output and loss could berepresented as :

LL ESS0I ++±= (8)where,

I = inflow into the pond0 = out flow from the pondS = change in storage capacitySL = surface lossEL = evaporation loss

The water balance of the tank for the first eightyears was worked out and presented in Table 6.

The table reveals that during the period, the directrain contributed 0.17 ha-m to 1.19 ham annually to the pondstorage constituting 4.13 to 13.57% of the total annual inflowinto the pond. From the well managed watersheds whichconstituted the catchment areas of the tanks, inflow due torunoff ranged between 0.35 - 6.47 % ofthe total inflow. Interflow from the watersheds through the pond bed and sideswere the major contributor to the pond inflows. The annualinter flow constituted 81.61-89.72% of the annual pondinflows. The results are in agreement with that obtained inother studies conducted on hill slopes in different in places(Whipkey, 1965; Tusu naboto etal, 1988). According to thesestudies, top layer of the forest soil is very permeable due tothe presence of root holes, and other structural channels,and the bottom layer is relatively impermeable. Rainwaterinfiltrates vertically into the top layer, and after reaching theimpeding layer, it moves laterally towards the stream. Thepresent study also proves that the subsurface flow (interflow) as the main mechanism by which stream flow isproduced in hills. Most of the pipes are maintained byfrequent flow of water and passage of insects and smallanimals.

Inter Flow and Sizing of Farm Pond

In deep and well drained soils, inter flow is that part

Table 6 Water balance of water harvesting tank

of the rainfall which vertically infiltrates into the soil in theup slopes and while moving downstream areas is, forced tocome to surface after reaching saturated zone which normallyoccurs in the lower reaches near the valley. The datapresented in Table 6 demonstrated the importance ofsubsurface flow in production of runoff on hill slopes. In theupper slope segment, soils do not get saturated even after asubstantial amount of cumulative rainfall, while lower downrelatively small amount of rainfall was enough to producesaturation to soil. Digging trenches on hill slope profile canalso trap the interflow. In the three adjacent experimentalmicro watersheds (W2, W3, AEW) the base flow emergedabove the gauging station resulting continuous stream flowof 116 -190 days annually. Unlike surface runoff, the amountof the base flow is somewhat consistent and varies with theannual rainfall. Comparison, therefore, could be drawn torelate the base flow of the watersheds and the interflow intothe pond. A single regression of the annual base flow(W2,W3, AEW watersheds) in term of annual rainfall yieldedthe following equation.I= 0.846 R3.815 (9)(r =0.69)

Where,I = annual base flow ( cm)R = annual rainfall (meter)

The above equation was used to compute the interflow into pond during first eight years using its catchmentarea of 11.10 ha. The simulated and observed inter flow ispresented in Fig 5. In well-managed hilly watersheds, thecapacity of the water harvesting structures can be estimatedon the basis of interflow. With the above relation (Eqn.9) itwould be possible to estimate the inter flow into the pond ata certain probability level of annual rainfall. A any desiredlevel of probability, runoff volume can be obtained as theproduct of runoff depth and catchment size, using the aboveequation. In general, the capacity of the tanks increases as

Year Rainfal 1 (mm)

Direct rain (ham)

Surface flow (ham)

Total inflow (ham)

Evaporation (ham)

Seepage (ham)

Over flow (ham)

Inter flow (ham)

Inter flow as percentage of total in flow

1. 2194.6 0.557 0.029 4.25 0.112 4.11 3.64 85.65

2. 2233.7 0.420 0.045 3.50 0.116 3.37 3.04 86.86

3. 2309.1 0.345 0.050 3.82 0.048 2.20 1.06 3.42 89.53

4. 2705.8

0.674 0.029 7.30 0.127 3.56 3.03 6.55 89.53

5. 3323.8 1.190 0.636 11.34 0.192 4.78 5.92 9.52 83.95

6. 2770.1 0.782 0.371 5.71 0.160 3.69 0.84 4.66 81.61

7. 1982.7 0.117 0.048 1.26 0.040 0.90 1.10 87.35

8. 2737.1 0.910 0.770 11.68 0.146 3.52 6.99 1.00 85.63


38

the probability level of assured interflov decreases. Furtherthe volume of available water per unit tank capacity increasesas the probability level increase for various sizes of tank(Fig. 6) presents a monogram, which gives the directrelationship between catchments size, and runoff volume.This graphical form could be used to estimate availability ofrunoff for water harvesting project in small hilly watershedsif annual rainfall records are available.

Fig 5 Observed and computed interflow of water harvesting tank

Fig 6 Catchment area and interflow at differentprobability levels.

interflow, ham

CONCLUSIONS

As expected, the hilly watershed treated withshifting cultivation yielded the highest peak runof (86.10mm/hr), while the one left undisturbed with natural vegetationgave the minimum peak runoff (4.49 mm/hr) However,provision of trenches in fodder based agriculture mosteffectively conserved moisture and produced; peak runoffof 7.81 mm/hr. Maximum peak flow rate did not differ in mixedblock forest, silvi-pastoral system an agri- horti-silvi-pastoralsystem showing the effectiveness of suitable soilconservation and appropriate land USI systems on hillslopes. Simple (linear) regression model relating rainfall andrunoff showed acceptable predictivi power in simulatingstorm runoff. The contributions to stream flow in thewatersheds having substantial area un de natural forest isprimarily bv subsurface flow. The watersheds havingcontinuous stream flow characteristic generated base flow

to the extent of 70-90% of its total water yield. The highestbase flow was obtained in the pine afforested undisturbedwatershed, which constituted on an average 23.5% of annualrainfall. Five-unit hydro graph parameters have beenidentified which defined satisfactorily the hydro graph shapeof hilly micro watersheds with different land uses andconservation measures. Regression equations of theseparameters in terms of watershed factors have shown veryhigh correlation, which can be used for synthesis of unitgraphs for un gauged areas. The conservation factor seemsto be very effective in predicting unit hydro graph parameters.Experiences on water harvesting in dugout- cum-embankment type of pond in hilly region in North East Indiaclearly indicate the feasibility of harvesting runoff fromwatersheds up to an extent of 38% of monsoon rainfall.Contribution of subsurface flow from upper slopes accountsfor 82-90% of the annual inflow into the water-harvestingpond located in the lower reaches and only 10-18% comesfrom direct interception of rainfall and collection of surfacerunoff. The soil in the area has extremely low water holdingcapacity and the seepage losses are very high. Thus waterstorage may be seasonal or perennial depending on the sitecondition. The study indicated the decline of seepage ratewith age of the pond and stabilizes in a period of7 - 8 years.The annual interflow into the pond can be predicted by theavailability of runoff for water harvesting in small hillywatersheds. Partial emptying of the farm pond is possible toirrigate crops during dry spells in monsoon and stored waterhas more scope for fish production. Limited water availablefor irrigating winter crops should be used at the earliestopportunity to reduce seepage and evaporation losses.

REFERENCES

1. Loague, K.M. and Freeze, A. (1985). A comparison ofrainfall runoff modelling techniques on small uplandcatchments. Water resources research, 21 (2), 229 -248.

2. Prasad, R.N., Singh, A and Verma, A. (1986). Problemsof hill land and their management in North Eastern India.Indian Journal of Soil Conservation 14 (3), 66-72

3. Singh, A. and Singh, MD. (1981). Soil erosion hazard inNorth Eastern Hill Region. Research Bulletin No. 10.ICAR Research Complex for North Eastern Hill Region,Shillong, India

4. Singh, A. (1987). Studies on some aspects of soil andwater in relation to resource management in NorthEastern Hills region. Ph.D. thesis, Bidhan ChandraKrishi Viswa Vidyalaya, Kalyani, West Bengal, India.

5. Singh, K.P. (1976). Unit hydrograph for design floodhydro graphs. Water Resources Bulletin 26 (6), 901-911.

6. Tusu Kumoto, Y., Ohta T. (1988). Runoff processes on asteep forested slope. J Hydrol 2, 165-178.

7. Whipkey, Q.Z. (1965). Susurface storm flow from forestedslopes. IASH Bulletin 10, 74- 85.


39


CORRELATION BETWEEN PAN EVAPORATION AND METEOROLOGICALPARAMETERS UNDER THE CLIMATIC CONDITIONS OF JORHAT (ASSAM)

D. Jhajharia S. B. Kithan A. K. Fancon Lecturer Ex-students; Ex-students;

ABSTRACT

The influence of various meteorological parameters on the pan evaporation has been examined under theclimatic conditions of Jorhat, Assam. The monthly meteorological data were collected from Tocklai Tea ResearchStation, Jorhat from 1970 to 1998. The four regression methods namely linear, exponential, power and logarithmichave been used to correlate the pan evaporation with the meteorological parameters at Jorhat, Assam. The stepwiseregression method was used to observe the combined effect of various meteorological parameters on pan evaporation.The wind speed, the sunshine duration and the temperature were found to have significant positive influence onthe evaporation. But, the relative humidity has no significant influence on evaporation. It is observed that theevaporation is found to be mainly influenced by the combined effect of the wind speed and the maximum airtemperature at Jorhat. The developed regression model for predicting the pan evaporation under climatic conditionsof Jorhat is 124.59168.1094.3 max −×+×= WSTE pan . The predicted values obtained from the developedevaporation model of Jorhat matched closely with the observed pan evaporation values.

Keywords: Correlation, Pan Evaporation, Meteorological parameters, Jorhat, Assam.

INTRODUCTION

Evaporation is one of the major processes in thehydrological cycle. Evaporation takes place from all wetbodies of vegetation and land surfaces including water fromlakes, ponds, reservoir, oceans and rivers. The process ofevaporation is influenced by air temperature, relative humid-ity, wind speed and bright sunshine hours. Several research-ers (Singh et al. 1981; Khan, 1992; Singh et al., 1992; Khanikar& Nath, 1998; Xu & Singh, 1998; Shrivastava et al., 2000;Hordofa et al., 2004 and Jhajharia et al., 2005) studied theinfluence of meteorological parameters in different parts ofthe world and conclusions were drawn depending on theeffect of the various meteorological factors on evaporation.

The dependence of pan evaporation rate on meteo-rological parameters has not yet been investigated at Jorhat.In the present study, the influence of meteorological param-eters on pan evaporation has been examined at Jorhat, Assam.Four different regression methods i.e. linear, exponential,power and logarithmic have been used to correlate pan evapo-ration with the meteorological parameters. The regressionanalysis was also performed to observe the combined effectof all the meteorological parameters on pan evaporation. Theobserved pan evaporation and the estimated evaporationusing Penman Monteith FAO-56, revised Blaney Criddle,Thornthwaite and Christiansen models were compared with

the predicted evaporation obtained from the developed re-gression model for Jorhat, Assam. The pan evaporation (Epan)is related to the evapotranspiration (ET) by the pan coeffi-cient (Kp). The same relationship is used to obtain Epan fromthe above four ET models with the help of a suitable value ofpan coefficient.

MATERIALS AND METHODSStudy Area

Tocklai Tea Research Station (latitude: 26°47′ N; lon-gitude: 94°12′ E and altitude: 96.5 m above msl.) is situated inJorhat, Assam. Assam (area: 78,438 km²) is surrounded by therest of the Seven Sister States: Arunachal Pradesh, Nagaland,Manipur, Mizoram, Tripura and Meghalaya. Assam alsoshares international borders with Bhutan and Bangladesh.With the Tropical Monsoon Rainforest Climate, Assam is atemperate region and experiences heavy rainfall and highhumidity. The monthly data were collected from 1970 to 1998.The mean monthly rainfall varied from 11.2 mm (December) to381.2 mm (July). The mean monthly maximum temperaturevaried from 22.3

0C (January) to 32.2

0C (July), whereas the

minimum temperature varied from 9.40C (January) to 24.6

0C

(July). The monthly pan evaporation and sunshine hoursvaried from 37.3 mm (December) to 118.1 mm (May) and 4.5hours (June) to 6.7 hours (March), respectively.

Department of Agricultural EngineeringNorth Eastern Regional Institute of Sci. & Tech.,

Nirjuli-791109, Arunachal Pradesh (India)


40

Correlation between Evaporation and Meteorological Param-eters

To establish the relationship between pan evapora-tion and other meteorological parameters, the method of re-gression as suggested by Mendenhall and Sincich (1989) isadopted. The individual regression equations are obtainedfrom linear, logarithmic, power and exponential methods. Ineach case, the significance of the leading coefficients (as theleading coefficients dominate the relation) is tested using t-test. Here, the null hypothesis is b1 = 0 and the alternatehypothesis is b1 # 0. The t-value is given by t = b1/s1 where b1is the leading coefficient of the particular regression equa-tion, and s1 is the standard error of estimation of that particu-lar coefficient. For a negative t-value, the coefficient is sig-nificant if t <- tx/2, whereas for a positive value, the coefficientis significant if t > tx/2. Here tx/2 is the table value of t and x isthe level of significance. If x is the level of significance then(1-x)× 100 is the level of confidence. In the present paper, x =0.05 for all the tests. If t-value is significant for more than oneregression model, the overall utility of the model has beentested using the analysis of variance (F-test) as,

kRknR

knRkRF

)1()1(

)]1(/[)1(/

2

2

2

2

−−−

=+−−

= (1)

Where R2, is the coefficient of determination ofmodel; k, number of coefficients in the regression equationexcluding the intercept; n – (k+1), degree of freedom; and n isthe total number of values (n =12 for monthly basis). If lead-ing coefficient is significant for more than one model, modelhaving higher F value (which implies higher confidence level)is taken as the best model provided F value is greater than fx,k, (n-k-1) (the table value of f at x level with numerator degreeof freedom k and denominator degree of freedom n-k-1). Ingeneral, reliability of any regression model is observed fromthe R2 value. Adding higher degree term or more parametersalways improves the R2 value but this may lead to some insig-nificant coefficients and/or low utility value (F value). Thesignificance of coefficient and F value were considered toselect the best model.

In order to observe the combined effect, a multiplelinear regression model was developed. The stepwise regres-sion method was used for the multiple regression analysis bytaking pan evaporation as dependent variable and other me-teorological parameters as independent variables(Mendenhall and Sincich, 1989). The meteorological data from1970 to 1997 were used for the multiple regression analysisand the data of 1998 were used for the validation purpose.The meteorological data of 1998 were fitted into the devel-oped regression model to obtain the predicted pan evapora-tion values. The linear curve was also fitted between theobserved and predicted evaporation values. The PenmanMonteith FAO-56 (Allen et al., 1998), revised Blaney Criddle

(Doorenboss & Pruitt, 1977), Thornthwaite (1948) andChristiansen (1968) models were selected for the comparisonbetween the estimated pan evaporation and the observedevaporation at Jorhat. The pan evaporation (Epan) is related tothe evapotranspiration (ET) by the pan coefficient (Kp). The

relationship, which is given as panp EKET ×= , is used toobtain Epan from the above four ET models. The evapotrans-piration is a climatic parameter expressing the evaporatingpower of the atmosphere at a specific location and time of theyear. The pan evaporation responds in almost similar fashionto the same climatic factors affecting the evapotranspiration.


The results of the study on the correlation betweenpan evaporation and meteorological parameters under theclimatic conditions of Jorhat are as follows:

It is evident from table 1.0 that out of the eight pa-rameters, parameters viz; WS (wind speed), Tmax (maximumtemperature), Tmin (minimum temperature), Tmean (mean tem-perature) and SH (sunshine hours) have significant influ-ence on pan evaporation. However, relative humidity has non-significant influence on evaporation. For the individual rela-tionship of SH with pan evaporation, the best method is thelogarithmic method. For the individual relationships of Tmin,Tmax and Tmean, the best method is the power method. For theindividual relationships of WS, the best method is found tobe linear. Air temperature, sunshine duration and wind speedwere found to have significant positive influence on evapo-ration at Jorhat, Assam i.e. evaporation increases with theincrease in wind speed. It also holds true that evaporation isdirectly related to air temperature i.e. evaporation increasesas the air temperature increases.

Combined Effect of Meteorological Parameters on Evapora-tion

In order to observe the combined effect of all themeteorological parameters on evaporation, a multiple linearregression model was developed. The multiple regressionanalysis was carried out using stepwise method at signifi-cant level of 5%. The meteorological data from 1970 to 1997were used for the multiple regression analysis and the data of1998 were used for the validation purpose. The developedregression model of evaporation (R2 = 0.984) for Jorhat, Assamis 124.59168.1094.3 max −×+×= WSTE pan , where Tmax isthe maximum temperature and WS is wind speed. The meteo-rological data of 1998 were fitted into the developed regres-sion model to obtain the predicted pan evaporation values.The comparison between the observed and the predicatedvalues of pan evaporation is given in Fig. 1.0. The linearequation (correlation coefficient 0.9) obtained during the vali-dation is X90.000.3Y ×+= ; where, Y is the evapora-


41

tion obtained from the developed regression model and X isthe observed pan evaporation. The average percentage errorbetween the observed pan evaporation and the predictedpan evaporation is found to be 7 percent at Jorhat.

The monthly observed pan evaporation, the esti-mated evaporation and the predicted evaporation (using de-veloped model for Jorhat) values are given in Fig. 2.0. Theevaporation values were obtained from Penman MonteithFAO-56, revised Blaney Criddle, Thornthwaite andChristiansen models by using the relationship between evapo-transpiration, pan coefficient and pan evaporation. It is ob-served that the developed regression model’s values matchedclosely with the observed pan evaporation and the estimatedevaporation values obtained from Penman Monteith FAO-56and revised Blaney Criddle models. The Christiansen andThornthwaite models overestimated the evaporation. Thus,the developed regression model can be used to predict theevaporation in the absence of pan evaporimeters for the otherparts of northeast India having similar climate as that of Jorhat,Assam.

CONCLUSIONS

Effect of air temperature, relative humidity, sunshineduration and wind speed was studied on evaporation at Jorhat.The important conclusions of this study are as follows:1) The wind speed, the sunshine duration and the air tem-

perature were found to have positive influence on evapo-ration. However, no significant influence was observedin case of relative humidity.

2) The pan evaporation was found to be mainly influencedby the combined effect of the maximum temperature andthe wind speed. The developed pan evaporation modelfor the climatic conditions of Jorhat is given

as 124.59168.1094.3 max −×+×= WSTE pan .3) The developed regression model’s evaporation values

matched very closely with the observed pan evaporationvalues at Jorhat, Assam.

ACKNOWLEDGEMENT

Authors are grateful to the Tocklai Tea ResearchStation, Jorhat for providing the meteorological data.

REFERENCES

1. Allen, R. G., Pereira, L. S., Raes, D. and Smith, M. (1998).Crop evapotranspiration. Guidelines for computing cropwater requirements, Irrig. Drain. Paper No. 56, FAO,Rome, Italy, pp.300.

2. Blaney, H. F. and Criddle, W. D. (1962). Evaporationfrom free water surface at high Altitudes, Trans. ASCE,123: 243-265.

3. Doorenbos, J. and Pruitt W.O. (1977). Guidelines forpredicting crop water requirement”, Revised 1997. FAOIrrig. Drain. Paper No. 24, FAO, Rome, Italy, 193 pp.

4. Hordofa, T., Sharma, A., Singh, R. and Dashora, P. K.(2004). Influence of meteorological variables onmonthly pan evaporation under sub-humid climaticconditions of Ethopia, Ind. J. Soil Cons. 32(1), 1-4.

5. Jhajharia, D., Fancon, A. K. and Kithan S. B. (2005).Relationship between USWB Class A pan evaporationand meteorological parameters under humid climaticconditions of Umiam, Meghalaya, In: Proc. ofInternational Conference on Recent advances in WaterResources Development and Management, Nov. 23-25,2005, IIT Roorkee, Allied Pubs. Pvt., 71-83.

6. Khan, M.A. (1992). Evaporation of water from free watersurface, Ind. J. Soil Cons. 20(1/2), 22-27.

7. Khanikar, P.G. and Nath, K.K. (1998). Relationship ofopen pan evaporation rate with some importantmeteorological parameters, Agricultural Sci. Soc.North-East India. 11(1), 46-50.

8. Mendenhall, W and Sincich, T. (1989), Statistics forEngineering and Computer Science, McMillan (2nd

edition), London.

9. Shrivastava, S.K., Misra, S.K., Sahu, A.K. and Bose, D.(2000). Correlation between pan evaporation andclimatic parameters for Sunderbans–A case study. IE(I) Journal. AG81, 55-58.

10. Singh, R., Bishnoi, O.P. and Niwas, R. (1992).Relationship between evaporation from US Class A openpan evaporimeter and meteorological parameters atHisar, Haryana Agricultural University J. Res., 22(2),97-98.

11. Singh, R.V., Chauhan, H.S. and Ali, A.B. (1981). Panevaporation as related to meteorological parameters,J. Agricultural Engg. 18, 48-53.

12. Thornthwaite, C. W. (1948). An approach toward arational classification of climate, The GeographicalReview. 38(1), 55-94.

13. Xu, C.Y. and Singh, V.P., (1998). Dependence ofevaporation on meteorological variables at differenttime-scales and intercomparision of estimation methods,Hydrol. Processes. 12, 429-442.


42

30.0

40.0

50.0

60.0

70.0

80.0

90.0

100.0

110.0

30.0 40.0 50.0 60.0 70.0 80.0 90.0 100.0 110.0Observed

Pred

icte

d

Fig 1 Comparison between Observed (mm)

and Predicted Evaporation (mm)

20

40

60

80

100

120

140

160

180

200

220

1 2 3 4 5 6 7 8 9 10 11 12

Month No.

Evap

orat

ion

(mm

)

Christiansen Blanney Criddle ThornthwaiteObserved Regression Model FAO-56

Fig 2 Monthly Estimated, Observedand Predicted Evaporation at Jorhat

Coefficients Meteorological Parameters Methods R2 F value S. E. b0 b1

Linear 0.90 92.3F* 8.57 6.69 1.7 (9.60) S* Logarithmic 0.89 86.76 8.82 -133.27 57.6 (9.30) S*

Power 0.89 87.12 0.14 2.57 0.90 (9.30) S* Wind (WS)

Exponential 0.87 72.23 0.15 24.04 0.02 (8.50) S*

Linear 0.39 6.32 21.47 185.45 -19.15 (-2.51) S* Logarithmic 0.42 7.1F* 20.98 274.43 -114.47 (-2.66) S*

Power 0.37 5.91 0.34 1397.28 -1.71 (-2.42) S* Sunshine hours

(SH) Exponential 0.35 5.31 0.35 367.34 -0.28 (-2.30) S*

Linear 0.73 27.23 14.22 -1.97 3.97 (5.22) S* Logarithmic 0.75 29.48 13.8 -125.10 68.52 (5.40) S*

Power 0.78 34.7F* 0.21 2.760 1.10 (5.89) S*

Minimum Temperature

(Tmin) Exponential 0.75 29.53 0.22 20.39 0.64 (5.44) S* Linear 0.78 35.36 12.88 -111.87 6.62 (5.95) S*

Logarithmic 0.78 35.99 12.79 -520.41 178.63 (6.0) S* Power 0.81 42.1F* 0.19 0.01 2.88 (6.49) S*

Maximum temperature

(Tmax) Exponential 0.80 39.71 0.19 3.48 0.11 (6.30) S* Linear 0.75 30.55 13.62 -44.48 5.01 (5.53) S*

Logarithmic 0.76 32.08 13.37 -277.38 111.77 (5.66) S* Power 0.79 37.1F* 0.20 0.240 1.80 (6.09) S*

Mean Temperature (Tmean)

Exponential 0.77 33.40 0.21 10.320 0.08 (5.78) S*

Linear 0.285 3.99 23.19 -47.64 1.78 (2.0) N* Logarithmic 0.257 3.45 23.65 -395.43 111.32 (1.86) N*

Power 0.248 3.30 0.37 0.04 1.73 (1.82) N*

Minimum Relative Humidity (RHmin)

Exponential 0.27 3.84 0.36 10.28 0.02 (1.96) N* Linear 0.070 0.77 26.43 390.24 -3.54 (-0.89) N*

Logarithmic 0.070 0.76 26.44 1472.14 -311.22 (-0.89) N* Power 0.070 0.75 0.42 2.7E+11 -4.91 (-0.87) N*

Maximum Relative Humidity

(RHmax) Exponential 0.07 0.76 0.42 10047.0 -0.05 (-0.87) N* Linear 0.160 1.90 25.17 -103.56 2.25 (1.40) N*

Logarithmic 0.150 1.70 25.35 -654.35 166.85 (1.3) N* Power 0.140 1.63 0.40 0 .01 2.59 (1.28) N*

Mean Relative Humidity (RHmean)

Exponential 0.150 1.80 0.40 4.30 0.03 (1.33) N*

S. E. is standard error, N* → non-significant, S*→ Significant, F* → the highest value of F amongst all the regression method, which are significant. Parenthesis denotes t- test values.

Table 1 Correlation between Pan Evoporation and Meteorological Parameters at Jorhat


45

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Journal Article :Rao, S. S., 1979. Flood Control Regulation of Reservoirs. Journal of Indian Water Resources Society, 1 1(2), 19-26.

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EXECUTIVE COMMITTEEPresident Er. M. GopalkrishnanVice-President Dr. S. K. TripathiVice-President Sri R.K.KhannaVice-President Er. N.K.JainSecretary Dr. Z. AhmadJt. Secretary Dr. S. A. KulkarniTreasurer Dr. Nayan SharmaJt. Treasurer Er. Ramesh KumarEditor Prof. Brijesh ChandraJt. Editor (Journal) Dr. Ashish PandeyJt. Editor (News Letter) Er. V.K.Labhshetwar

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ChairmanSri. M. S. Mundhe-SriM. M. MahodayaSri G. Ganapathy SubramanianSri R. K. KnarjnaSri J.B.PatelSri P. NeogDr. D. P. KatariaSri A.K. SojaiiaSri Jagdish MbhanEr. S. K. KumarSri M. N. Narse GowdeSri V. N.WasadeSri D.K.SrivastavaEr. P.K. BhargavSri S. G. ShirkeSri C. P. Mahajan

Printed &. Published by Dr. Zulfequar Ahmad, Secretary, IWRS on behalf of the Indian Water Resources Society.Department of Water Resources Development & Management, Indian Institute of Technology, Roorkee-247 667, (UK)India Telephone : Office PBX (01332-285423, 286690)Printed at: Jain Printing Press, Main Bazar, Roorkee, Ph. : 262722, 269999Editor: Prof. Brijesh Chandra, E-mail : [email protected]

National Price for Individual Members Rs. 10/-

ConvenorSri A. S. GarudkarSri Rajan NairSri B. 0. JoshiSri R. SubramanianSri R. K. KhannaSri D. H. Patel-Dr. Pratap SinghDr. R. K. SrivastavaSri Virendra PalSri A. P. AgarwalSri N. Srinivas MurthySri P. K. JainSri Braj Bhushan Prasad SinghSri Hardan SinghSri R. K. SuryavanshiSri C. M. Walia

MEMBERSEr. A.S.DhingraEr. P.K.BhargavaDr. A.G.BholeEr. M.M.MahodayaEr. R.K.SuryavanshiSri. Som Dutt GuptaEr. A.K.SinhaEr. S.K.KumarEr. Ashok R. JadhavEr. C.NagarajanDr. Arun Goel

Dr. Devendra Kumar

CO-OPTED MEMBERProf. S.K.MazumderMiss Jaya SoodProf. Gopal ChauhanSri G.N.MathurProf. B.R.YadavEr. Jagdish MohanSri K.N.SharmaDr. D.Satya MurtyEr. Ajit B. Jain

wrdm journal

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