Understanding runoff processes using a watershed model—a ...wgbis.ces.iisc.ernet.in/biodiversity/sahyadri_enews/newsletter/issue53... · Understanding runoff processes using a watershed

Understanding runoff processes using a watershed model—a casestudy in the Western Ghats in South India

M.R.Y. Puttya, R. Prasadb,*aDepartment of Civil Engineering, The National Institute of Engineering, Mysore-570 008, India

bDepartment of Civil Engineering, Indian Institute of Science, Bangalore-560 012, India

Received 6 January 1997; accepted 16 December 1999

Abstract

The wet tropical Western Ghat Mountain ranges in South India present an interesting combination of meteorological andphysical characteristics. The results of a watershed model analysis carried out to understand the catchment response and therelative importance of different runoff processes in the region are reported in this paper. A lumped parameter model simulatingsaturated source area runoff, lateral flow through pipes and the saturated zone groundwater flow, has been developed assumingthat source area runoff is the only quickflow component. The model has been calibrated on seven catchments using sufficientlylong records of daily data. A wide range of tests has been used to show that the model performs reliably. The influence ofcatchment characteristics on the relative importance of the flow components and the catchment response has been studied. Themodel simulations have been interpreted to infer that the pipeflow contributions augment the contributions of source area runoffto stream quickflow. Suggestions for further research in the area are given, based on the inferences drawn.q 2000 ElsevierScience B.V. All rights reserved.

Keywords: Wet mountainous catchments; Variable source area theory; Lumped parameter model; Pipe quickflow; Catchment characteristics;Dynamic contributing volumes; Rainfall influence

1. Introduction

A watershed model is a mathematical representa-tion of the catchment processes capable of simulatingstreamflow and other outputs of the catchment system,corresponding to any given values of the inputs,mainly precipitation. Hence, the model is normallyutilised either for generating streamflow or to deter-mine how runoff is affected by factors such as affor-estation (e.g. Aston and Dunin, 1980; Eeles andBlackie, 1993), urbanisation (Smith and Bedient,1981) or rainfall augmentation (Lumb and Linsley,

1971). As shown by several researchers, however, itis possible to utilise the model as an investigative toolalso for learning about catchment response and infer-ring about the runoff processes in the catchment. Forexample, Betson (1964) inferred the existence ofpartial source areas of runoff by his regressionmodel. Freeze (1972) made deductions about soilparameters using a subsurface flow model. Smithand Hebbert (1983) use an unsaturated vertical flowmodel to infer the influence of soil depth and aniso-tropy on source areas and runoff. Ward (1984),comparing streamflow predicted by his catchmentmodel with observed flows, suggests physicalprocesses to which the differences between the twoare linked. McCord et al. (1991) employ their model

Journal of Hydrology 228 (2000) 215–227

0022-1694/00/$ - see front matterq 2000 Elsevier Science B.V. All rights reserved.PII: S0022-1694(00)00141-4

www.elsevier.com/locate/jhydrol

* Corresponding author.E-mail address:[email protected] (R. Prasad).

to determine the cause of the anisotropic behaviourand the impact of geology and topography on the flowthrough sand dunes. The present work, using such anapproach, applies a model to analyse the nature of thecatchment response in the mountainous region of theWestern Ghats (Ghat means mountain in Kannada,the regional language), in South India. This regionsupplies more than 80% of the surface waters ofPeninsular India. Annual rainfall in the region exceeds2500 mm everywhere. But rainfall intensities are mostof the time very low and durations are large, despitethe region being in the tropics. The soil is deep andhas a good structure. Studies on runoff processes insuch conditions have not been reported. The presentwork forms a part of a more detailed researchprogramme undertaken with the intention of learning

about the streamflow generation mechanisms in theregion. This paper reports results of application of awatershed model developed in accordance with thecommonly accepted theories of runoff productionin wet mountainous regions, considered worthpresenting although the model used is likely to requiremodification.

2. The study area

The Western Ghats, locally called ‘Sahyadri Ranges’form an unbroken relief dominating the west coast ofthe Indian peninsula, for almost 600 km, extendingbetween north latitudes of 8 and 218 (Fig. 1).

The area selected for the present study lies betweennorth latitudes 118300 and 148300, along the WesternGhats. Morphologically, this region can be dividedinto three zones: (i) the escarpment of the Ghats,which consists of numerous high altitude peaks (maxi-mum elevation 1800 m above MSL), characterised byrounded crests; (ii) the foot of the escarpments on thewest, towards which the Ghats descend very fast,characterised by very deep and steep valleys; and(iii) the backslope of the Ghats extending about50 km into the South Indian plateau, forming thehilly hinterland characterised by numerous peaks ofintermediate level. The Western Ghat ranges form abarrier to the monsoon winds originating in the Indianocean and moving north-east. Hence rainfall in theregion is very heavy during the south-west monsoon,which lasts between June and October. Annual rain-fall exceeds 6000 mm all along the escarpments, withthe wettest areas in the region recording about7800 mm. Rainfall magnitude decreases steadilytowards east, to a minimum of 1200 mm in areasbordering the Ghats. More than 90% of the annualrainfall occurs during the four monsoon months,with an average number of 120–140 rainy days peryear. During the monsoon, a major portion of the rain-fall is contributed by four to five spells each lasting 8–10 days. During such spells, daily values are veryhigh. However, intensities are relatively moderateand rainfall occurs during most part of the day(Putty, 1994). For example,15-minute intensitiesseldom exceed 80 mm/h and contribute about 2% ofthe annual rainfall, while hourly intensities of 60 mm/hcontribute less than 1% of the annual rainfall.

M.R.Y. Putty, R. Prasad / Journal of Hydrology 228 (2000) 215–227216

Fig. 1. Location details of the Western Ghats (Sahyadri ranges).

Geologically, the study area consists exclusively ofPrecambrian formations with gneiss and intrusivegranites forming the important rock types. The combi-nation of such old rocks and heavy but low intensityrainfall has resulted in a well-developed soil mantlecharacterising most of the slopes of the WesternGhats. Soil thickness in the region varies betweenabout 3 m on grassed slopes and about 20 m onwell-vegetated slopes. Soils in the surface layer areusually sandy loams, characterised by very high infil-tration rates, even on the rounded crests of the hills.Forest vegetation in the Western Ghats can be classi-fied into three types: (i) thick evergreen to semi-evergreen forests occupying vast stretches of thesteep Appalachian slopes; (ii) the evergreen montaneforests confined to the valleys and locally calledShola; and (iii) pastures, covering extensive areas onthe rounded crests of the escarpment of the Ghats.Large areas of forest in the hinterland have beenconverted into cardamom and coffee plantations.Yet, the whole of the study area is a region charac-terised by very high infiltration rates (Putty,1994;Ranganna et al., 1991) and very little surface runoff.

Rainfall in the area being aplenty, numerous peren-nial streams flow through the Western Ghats in smallmeandering channels (except in head reaches) withwide valley floors, where paddy is grown. Streamsexpand their channel during rains and occupy thewhole of the valley floors, during floods. Preliminaryinvestigations in the region (Putty, 1994; Putty andPrasad, 1994a) indicate that the mechanism of streamflow generation in the area is well explained by thetheory of variable source areas (Dunne and Black,1970; Hewlett and Troendle, 1975), according towhich the storm period direct runoff in the stream isprimarily contributed by surface runoff from the satu-rated source areas of the watershed, augmented bysubsurface lateral flow in the near-surface layers ofthe soil mantle from contributing areas riparian to thestream. A survey of the region during rainy seasonshows that the wide valley floors which get saturatedoften during monsoon form potential source areas,and pipe formations, locally calledJala (Putty andPrasad, 1994b), supply substantial quantities ofsubsurface flow. Field investigations also indicatethat delayed groundwater discharge also forms avery important part of streamflow in these regions.However, the relative importance of the various runoff

mechanisms and the nature and variation of the sourceareas can only be understood through an intensivestudy of runoff processes. Such knowledge would beof help in choosing the hydrological design proce-dures and be of importance in planning watershedmanagement strategies. This is particularly so sinceplanning being done presently in the region (CentralWater Commission, 1986; Jain and Ramasastri, 1992;Mallikarjuna et al., 1992; Karnataka Power Corpora-tion, 1994) is completely based on the assumption ofpredominance of infiltration excess overland flow,which is the mechanism widely believed to be activein the humid tropical areas (WMO, 1983), underwhich climatic group the Sahyadri ranges may beclassified.

A watershed modelling study can be the first steptowards the goal of understanding runoff processes.Ward (1984) and others have shown how the analysisof model results can suggest the course of furtherresearch. The present study aims at applying amodel developed in accordance with hypothesesformulated on the basis of field observations, on afew typical catchments in the region, and to discussthe runoff components and the mechanisms of stream-flow generation in the light of the model simulations.It is hoped that the results of the present study willhelp bring to light some important aspects of thehydrology of the region, which suggest revision ofthe hydrological design procedures and a change inthe approach of the watershed managers, whopresently associate soil erosion even on grassed slopeswith Hortonian overland flow.

3. Selection of the model

The Western Ghats form an area of hectic activityas far as water resources development is concerned.Hence, streamflow records pertaining to many smallcatchments of practical importance are available.Further, long and reliable records of rainfall are easilyavailable. However, data is all in terms of daily valuesand little information is available concerning thehydrological parameters of the soil mantle. Giventhe purpose and these data limitations, the best choicewould be a lumped parameter conceptual model,capable of simulating the various components ofstreamflow. Such a model incorporating algorithms

M.R.Y. Putty, R. Prasad / Journal of Hydrology 228 (2000) 215–227 217

and assumptions that are compatible with the princi-ples of hillslope hydrology, explained by the variablesource area theory, has been developed and used in thepresent study. This model, called SAHYADRI, is amodified version of the variable source area modeldeveloped by Moore et al. (1983). The structure ofSAHYADRI is explained below.

4. The model structure

SAHYADRI considers a day’s runoff to be made upof three components, the saturated source area runoff(also called quickflow), the soil zone lateral seepageor flow through pipes and macropores (called lateralflow) and the saturated soil zone discharge (called

groundwater flow). Field observations at numerousroad cuttings (near valley bottoms) showed thateven during heavy rainfall events, lateral flow throughthe soil occurred only through pipes and not throughthe soil matrix. For this reason, lateral flow is referredto as pipeflow hereafter. It was also observed thatareas contiguous to the river, especially where pipesopen on to the surface, become saturated and overlandflow occurs from there. Hortonian overland flow is notconsidered in the model, since infiltration rates almostalways exceed rainfall intensities in the region, andinfiltration excess overland flow is negligibly small(Putty, 1994). Instead, in accordance with the variablesource area theory, saturated areas are assumed todevelop in the neighbourhood of the stream and allthe rainfall over the saturated area becomes directrunoff. The runoff processes are assumed to occur inthree conceptual zones—the interception store, theunsaturated soil store and the saturated groundwaterstore, as shown in the schematic diagram presented inFig. 2. Rainfall (RAIN) in excess of the interceptionstore capacity (CEPM) reaches the ground as through-fall (RAINET). Throughfall on the saturated portionof the catchment (SAF) reaches the stream immedi-ately as source area runoff (SARO). Hence

RAINET� RAIN2 CEP �1�whereCEP is the interception storage, which equalsCEPM whenRAIN is greater thanCEPM, and

SARO� RAINET·SAF �2�It is assumed that the quickflow in the stream,

which is that part of a day’s rainfall which reachesthe catchment outlet the same day, is contributed bythe source area runoff alone. Pipeflow runoff isassumed to be slower, and to reach the gauge siteover a span of a few days. The source (saturated)area starts developing next to the stream. As rainfallcontinues over the catchment, and infiltrates intopipes, parts of the pipes near the valley bottombecome full due to direct infiltration as well as inflowfrom upslope. Areas riparian to the channels get satu-rated as a result, leading to expansion of the sourcearea up the slope. The extent of the source area istherefore a function of net infiltrated water, which isrepresented by the soil moisture and groundwaterstores. Since only a part of the soil moisture (atlower elevations) is in the saturated state, a weighting


Fig. 2. A schematic representation of the model SAHYADRI.

coefficient is to be applied to the soil zone watercontent. The source area (SAF) is modelled as anexponential function of the storage in the soil zone(SZWC) and in the groundwater zone (GZWC),using the expression

SAF� SAKexp��SZWK:SZWC1 GZWC�=SAE� �3�whereSZWKis the soil zone weighting coefficient andSAK and SAE the coefficient and exponent, respec-tively.

The evaporative demand on the storage in the soilzone is

EVPT� EVP2 CEP �4�whereEVP is the potential rate of evapotranspirationandCEP the interception.

Transpiration (ET) from the soil zone is a functionof EVPT and the storage available in the zone(SZWC), which is supplied by infiltration�INFL �RAINET2 SARO�: ET is calculated as

ET � EVPT·�SZWC2 WP�=�SZPC2 WP� �5�

whereWP is the wilting point andSZPCis a para-meter of the soil zone representing its water holdingcapacity. The actual evapotranspiration (AET) is thenthe sum ofCEP andET.

The soil zone storage begins to get depleted due todrainage, when the storage exceeds the field capacity(FC). The rate of drainage (DRAIN) is taken to be theoutflow of a linear reservoir, given by

DRAIN� SZRK·�SZWC2 FC� �6�whereSZRKis the soil zone recession coefficient. Aconstant proportion (SZROK, the pipeflow runoffcoefficient) of the draining water is assumed tobecome pipeflow (SZRO). A non-linear model forDRAIN was found to offer no particular advantage(Putty and Prasad, 1992), and in the interests of keep-ing the number of model parameters low, the linearmodel was adopted. The remaining part (PERCO)percolates down into the groundwater zone.

The groundwater flow (GWRO), which is assumedto form the delayed component of streamflow, ismodelled as outflow from a non-linear store as

GWRO� GZK·�GZWC�GZE �7�whereGZWCis the water content in the zone and theparametersGZK and GZE are, respectively, termedthe coefficient and exponent of the zone.

The daily water balance of each zone is maintainedseparately and the total runoff for any day is calculatedby summing the three components. It can be noted thatthe model takes daily values of rainfall and potentialevapotranspiration as the input variables. In caserecords of daily values of evapotranspiration are notavailable, values calculated empirically as averagesover longer duration may also be used.


Table 1Parameters of SAHYADRI

1. CEPM: Interception store capacity2. SAK: Source area coefficient3. SZWK: Soil zone weighting coefficient for source area4. SZE: Source area exponent5. SZWP: Soil zone wilting point6. SZFC: Soil zone field capacity7. SZPC: Soil zone pore capacity8. SZRK: Soil zone storage recession coefficient9. SZROK: Pipeflow runoff coefficient

10. GZK: Groundwater zone coefficient11. GZE: Groundwater zone exponent

Table 2Catchment detailsa

Catchment/gauge site Area (km2) RF (mm) RO (mm) No. RG Forest (%) Valley (%) RR (%)

1 HonnammanaHalla/Attigundi 4.5 1447 895 1 20 5 16.32 YettinaHole/Harle 27 3044 2099 4 23 13 6.63 KonganaHole/Nadagundi 83 2461 1639 4 26 40 2.24 Lakshmanathirtha/Kanur 179 2428 1667 4 38 20 1.45 Malathi/Kalmane 266 5660 4701 5 28 18 0.56 Harangi/Hudgur 420 2866 1879 6 30 18 2.67 Hemavathi 600 2888 1959 6 30 28 0.9

a RF: monsoon rainfall, RO: monsoon runoff, RG: rain gauges, RR: relief ratio (maximum altitude difference/distance between the points).

The model parameters, a total of 11, are listed inTable 1. Of these, the three concerning the land useand soil characteristics, viz.,CEPM, FC andWP, are,at least in principle, physically based and can be deter-mined from a knowledge of the catchment character-istics. Hence, the number of parameters required to beoptimised is eight, which is quite reasonable (Beven etal., 1984). With this set of parameters, the trial anderror hydrograph matching technique of optimisationitself should suffice. An objective function like thecoefficient of efficiency (Aitken, 1983) may also beused as a guide for proceeding with the optimisation.

5. Calibration of the model

The model SAHYADRI has been calibrated onseven catchments, varying in size from 4.5 to600 km2, in the Western Ghat regions of the State ofKarnataka. The details concerning these catchmentsare furnished in Table 2. In each case, data for 5 years,corresponding to the season of the south westmonsoon (roughly June to September), each consist-ing of about 120 rain days have been utilised for thestudy. Outside this season, there is virtually no rain-fall, and streamflow becomes too small to bemeasured with reasonable accuracy. The dry seasonis therefore not considered. Initial values of the soilzone and groundwater stores used in the model arechosen on an average basis and errors in these valueswill cease to matter after the first few days because ofthe very great increase in these stores once rains start.The physically based parameters are determined usingthe land use data presented in Table 2 and the approx-imate values suggested in Table 3, for each land usetype. The potential evapotranspiration values areinput as weekly average daily values, in accordance

with the information made available by the WaterResources Development Organisation of the State ofKarnataka and Mohan and Prasad (1987) and usingcrop factors, presented in Table 3, for the differentland use types. Calibration of the parameters for thepresent study was carried out by the trial and errorprocedure adopting the split record technique. Ineach case, records of 3 years, showing the greatest,the least and an average value for the differencebetween seasonal rainfall and measured runoff, wereused for calibration and the remaining length of datawas used for validation. The trial and error method isconsidered adequate for the purpose of this paper,which is to analyse the importance of different runoffcomponents. The goodness of the fit of the model wastested by inspection of the scatter diagrams, visualcomparison of the hydrographs of estimated andobserved runoffs, and by calculating the followingthree statistics:

1. coefficient of efficiency, defined by

R2E � 1 2

X�RO2 ROE�2=

X�RO2 ROM�2

h iwhereROE is the runoff estimated correspondingto a day for whichRO is the measured runoff andROM is the mean ofRO;

2. coefficient of determination,R2D which is the square

of the correlation coefficient between estimatedand observed runoff values; and

3. the residual mass curve coefficientR2R; which is the

square of the correlation coefficient between theordinates of the residual mass curves of the esti-mated and observed runoff.

While R2E is a measure of the overall performance

of the model,R2DandR2

R provide information concern-ing the systematic errors (Aitken, 1983) in the model.


Table 3Suggested range of values for physically based parameters of SAHYADRI and for the crop factors (CF)

Land-use Soil-type CEPM (mm) Soil thick (cm) SZFC(%) SZWP(%) CF

Evergreen forest (dense) Sandy clay organic 4.5–5.5 150–200 25–30 10–12 1.20Deciduous/open forest

(plantations)Sandy clay 4.0–5.0 125–175 25–30 10–12 1.00

Scrubby Gravelly sandy loam 2.5–3.5 50–100 15–20 10–12 0.85Grassed Gravelly sandy loam 1.8–2.0 50 10–15 10–12 0.85Paddy (valley) Gravelly sandy loam 1.8–2.0 50 20–25 10–12 1.10

In the present study, these statistics were calculatedcorresponding to both daily values and weekly sums,and for the individual years separately. The results arepresented and discussed below.

6. Model results and simulation

Since soils are deep and very porous in these catch-ments, groundwater storage is large and plays animportant role in runoff generation. HenceSZWKisassumed to be unity. Three other parameters, namelyCEPM, SZFCandSZWPwere given suitable values.The number of parameters to be optimised is thusseven, which is considered reasonable (Beven et al.,1984). The calibrated values of all parameters areshown in Table 4 and the performance statistics inTable 5. The model-estimated means and standarddeviations are close to observed ones and theR2

E

values are high (Table 5). The magnitudes ofR2Dand

R2R suggest the absence of systematic errors. The

simulated and observed hydrographs, groundwater

runoff, rainfall hyetograph and saturated area as afraction of catchment area are shown in Fig. 3(a)and (b) for two streams, namely Konganahole (lowestR2

E� and Malathi (highestR2E� for one of the years.

These are typical of other catchments and otheryears also. The statistics of Table 5 and the hydro-graphs indicate that the model performs well. Usingthe model as an analytical tool, two aspects of catch-ment behaviour, which provide information concern-ing runoff processes and hint at the course of furtherresearch that may be taken towards the goal of under-standing runoff mechanisms, are discussed below.

6.1. Runoff components

The simulated values of the runoff components,averaged over the length of the data, are shown inTable 6. Groundwater runoff contributes between 30and 80% of the total runoff. The values ofGZK andGZE from Table 4 suggest that the daily groundwaterrunoff is of the order of 0.5–1.2% of the groundwaterstorage, which is reasonable considering that almost


Table 4Optimised values of the parameters of SAHYADRI�SZWK� 1:0 for all the catchments)

Parameters CEPM SAK SZE SZFC SZWP SZPC SZRK SZROK GZK GZE

1. HonnammanaHalla 2.00 0.020 400 120 100 360 0.70 0.05 0.0055 1.152. YettinaHole 2.50 0.045 400 300 140 500 0.70 0.1 0.0250 1.003. KonganaHole 2.50 0.015 300 250 100 400 0.60 0.3 0.0100 1.204. Lakshmanatirtha 2.50 0.015 310 250 100 300 0.70 0.3 0.0120 1.205. Malathi 2.50 0.085 310 250 100 300 0.70 0.2 0.0120 1.256. Harangi 2.50 0.038 350 250 120 300 0.70 0.1 0.0050 1.107. Hemavathi 2.50 0.035 350 250 100 300 0.70 0.4 0.0080 1.25

Table 5Results of the tests of goodness of fit: annual values averaged over the record lengtha

Catchment Daily prediction Weekly sums

mo me so se R2E R2

D R2R R2

E R2D R2

R

HonnammanaHalla 7.51 7.33 3.71 3.54 0.75 0.77 0.94 0.85 0.93 0.95YettinaHole 14.7 15.6 17.8 15.0 0.72 0.76 0.94 0.85 0.90 0.96KonganaHole 8.9 9.3 11.4 9.3 0.61 0.63 0.95 0.79 0.81 0.96Lakshmanatirtha 13.4 13.9 14.1 12.0 0.81 0.83 0.94 0.86 0.88 0.94Malathi 36.1 37.9 39.2 35.6 0.86 0.87 0.87 0.94 0.95 0.96Harangi 13.4 13.7 13.9 10.4 0.74 0.76 0.94 0.87 0.89 0.95Hemavathi 15.7 16.2 18.5 15.2 0.81 0.86 0.97 0.91 0.93 0.98

a m: mean runoff,s: standard deviation: for observed (o) and estimated values (e).

the entire rainfall infiltrates into the ground. Otherfactors which also point to a substantial groundwaterrunoff component are the very slow catchmentresponse and the failure of surface runoff modelssuch as the curve number method in simulating runofffrom Western Ghat catchments (Putty and Prasad,1994a).

In order to find possible dependence of the differentrunoff components on catchment characteristics,correlations of the source area runoff, pipe flow andgroundwater runoff as proportions of total runoffagainst catchment rainfall, percent forest area, percent

valley area, percent relief ratio and catchment areawere analysed. The respective coefficients of determi-nation are shown in Table 7. Only source area runoffand rainfall, groundwater runoff and rainfall, andgroundwater runoff and relief ratio are significantlycorrelated. Since almost all the rainfall infiltratesinto the ground over the unsaturated part of the catch-ment, irrespective of whether the land cover is forest,plantation or grass, the runoff components are inde-pendent of catchment area as well as forest area. Thethree significant correlations are plotted in Fig. 4 togetherwith the best fit lines. Groundwater contribution


Fig. 3. Typical hydrographs and temporal variations in the source area: (a) Malathi; and (b) Konganahole.

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Table 6Runoff components estimated by SAHYADRIa

Catchment RF (mm) SARO(mm) SZRO(mm) GWRO(mm) ROE(mm) GWRO/ROE(%) ROE/RF (%) EVPT(mm) RO (mm) ROE/RO (%)

HonnammanaHalla 1447 124 54 704 882 79.8 61.0 220 895 98.5YettinaHole 3044 839 164 1216 2219 54.8 72.9 400 2099 105.7KonganaHole 2461 225 465 1002 1692 59.2 70.0 465 1639 103.2Lakshmanatirtha 2429 211 488 1000 1669 58.9 68.7 438 1667 100.2Malathi 5660 3065 395 1470 4931 29.8 87.1 462 4701 104.9Harangi 3177 1263 128 631 2023 31.2 63.7 442 1929 104.9Hemavathi 2888 453 687 889 2029 43.8 70.3 455 1959 103.6

a RF: rainfall; ROE: estimated total runoff;RO: observed runoff.

decreases with increasing rainfall because more rain-fall is drawn away as source area runoff. Groundwatercontribution increases with the relief ratio. Thisconforms to the principles of the variable sourcearea theory (Dunne, 1978; Anderson and Burt,1990), according to which the chances of develop-ment of saturated source areas are more on the flatterareas. Against expectation, however, the simulatedmagnitude of source area runoff is not related to theextent of the valley bottoms (Table 7), whichwould ordinarily be assumed to form the potentialsource areas of quickflow. A probable explanationfor the above emerges if the extent of the sourceareas as simulated by the model is analysed asbelow.

6.2. The extent of the source areas

The extent of saturated areas in the catchmentscould not be mapped due to infrastructure limitations.But the valley floors are usually planted with rice, andthe experience of the farmers is that during prolongedrainfall events, the whole of the valley floors as wellas small widths across narrow upland valleys get satu-rated. The Konganahole catchment map is shown inFig. 5, with the valley floors marked using survey ofIndia toposheets. These valley floors form 40% of thetotal catchment area. The maximum extent of thesource area (as a fraction of the catchment area) simu-lated by the model and the extent of the valleybottoms in the catchment are compared in Table 8.


Table 7Coefficient of determination between runoff components and catchment characteristicsa

% Relief ratio (%) Valley (%) Catchment area (km2) Forest (%) Rainfall (mm)

Source area runoff 0.111132 0.037308 0.027439 0.004392 0.895453Pipeflow runoff 0.383753 0.331593 0.5366 0.396251 0.023208Groundwater runoff 0.585244 0.055165 0.473669 0.155167 0.616838

a Italicised values significant at 5% level; others not significantly different from zero.

Fig. 4. Influence of catchment characteristics on runoff components.

The simulated source areas are much larger than theflat valley portions, although source area runoff is notthe major contributor to streamflow in five of theseven catchments. Three possibilities which mightaccount for this unexpected behaviour are: (i) contri-butions of infiltration excess overland flow beingsubstantial during periods of high flood; (ii) saturatedsource areas getting developed on slopes, in additionto those covering the valley floors; and (iii) pipeflowbeing itself a contributor to quickflow.

The case of saturated source areas spreading tocover very large portions of the catchment, often thecomplete area, has been reported by Bonell andGilmour (1978) from Australia. In the region studiedby them, rainfall is very intense with daily depthsoften exceeding 25 cm. In contrast, even thoughdaily depths of rainfall do exceed 20 cm on a fewdays in some of the present catchments, rainfall isnever very intense in the Western Ghats. Analysis ofrainfall intensities in the region has shown (Putty,1994) that on days when rainfall exceeds 10 cm, itrains during more than 21 h of the day, on an average.Groundwater levels were monitored (Putty, 1994) atseveral points in the catchments, and it was found thatoutside the valley floors water table is below thesurface, indicating that saturated areas do not extendbeyond the valley floor. With low rainfall intensitiesand deep soils on the slopes, expansion of saturatedareas much beyond the valley floor is improbable in

the Sahyadris. Infiltration capacities measured oncultivated and grassed slopes (Putty, 1994) varybetween 5 and 300 mm/h. Comparison with the 15-minute rainfall intensities at the heaviest rain record-ing station in the region shows that less than 3% of therainfall has chances of generating overland flow onsuch slopes. Infiltration capacities on forested slopesare far higher than rainfall intensities. Actual averageinfiltration rates being higher than infiltration capaci-ties, Hortonian overland flow is not a process toreckon with. The only remaining explanation for thelarge source areas simulated by the model is thereforethat in addition to saturation excess overland flow,quickflow also arrives subsurface (which, in theabsence of observable matrix flow, can only be pipe-flow). This can happen by the formation of what Jones(1979) called ‘dynamic contributing volumes’, whichare saturated soil masses far removed from the streambut draining into pipes leading to the stream. Fieldsurveys indicate that most of the subsurface flow inthe Western Ghats arrives through pipenets (Putty andPrasad, 1994b) and the results of the present analysis(which can be broadly considered a method of sophis-ticated flow separation) show that contributions ofpipeflow to stream-quickflow must be substantial.The results imply that (i) runoff processes in theregion are best explained by Jones’s (1979)extendedform of the variable source area theory propounded byHewlett and Hibbert (1967) and Dunne and Black(1970), and (ii) variable source area models, whenapplied in regions similar to the Western Ghats,need to incorporate a quickflow component throughpipes draining subsurface saturated zones in additionto flow from contributing areas riparian to the chan-nels. That quickflow may also arrive through pipes isalso suggested by the dominant influence of rainfall


Fig. 5. Konganahole catchment showing extent of valley floors.

Table 8Maximum values of source area simulated by SAHYADRIa

Catchment SA ROE RO Valley

HonnammanaHalla 31.2 21.7 22.3 5.0YettinaHole 65.3 50.2 58.4 13.0KonganaHole 28.7 88.6 67.9 40.0Lakshmanatirtha 27.4 57.2 51.2 20.0Malathi 86.8 141.8 128.6 18.0Harangi 69.3 29.4 34.2 18.0Hemavathi 45.3 172.0 133.0 28.0

a SA: source area (%);Valley: area covered by valley floors (%).

magnitude on catchment response. Rainfall magni-tude, which also determines the amount of waterentering the soil mantle in a catchment, has aprofound influence on the depth of the soil, thedevelopment of subsurface pathways like pipes.Greater amounts of infiltration result in higher densi-ties of pipenet, since water entering into the soilhas to find its own pathways to get drained out.This leads to quicker and greater contributions ofsubsurface flow to the stream. Further, rainfallmagnitude also controls the variations in thesurface saturated zones. Higher magnitudes ofrainfall, which mean more number of rainyhours in the Western Ghats, result in saturatedzones being sustained for longer periods (Fig. 3)and contributions of surface runoff being greater.Hence, it can be concluded that in wet mountai-nous areas like the Sahyadris dominated by pipe-flow, the catchment response is shaped more bythe subsurface flow pattern, than by surface flowlengths and drainage densities, in contrast to otherregions. Incidentally, the drainage densities of thecatchments of HonnammanaHalla, Yettinahole,Malathi and Harangi, which exhibit different catch-ment responses, are all nearly the same and liebetween 1.5 and 1.8 km21.

7. Summary and conclusions

The results of the study have established that thethree-component watershed model SAHYADRI,developed in accordance with the postulations of thetheory of variable source areas forms a useful first stepin understanding the response characteristics of thecatchments in the Western Ghat regions of SouthIndia, although the need to add a fourth componentis indicated. The model simulations have shown thatgroundwater flow forms a dominant component ofrunoff and the catchment response is strongly depen-dent on the rainfall magnitude. Two major implica-tions of the study are that (i) flow through pipes fromdynamic subsurface saturated zones may contributesubstantial quantities of quickflow, and (ii) fieldwork necessary for further research must concentrateon pipeflow responses and the influence of rainfall onthe nature of pipenets. A modified model incorporat-ing quickflow through pipes is now under

development at the National Institute of Engineering.Field work on the lines stated above is also beingundertaken.

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