Introduction

Replenishing the groundwater aquifers through artificialrecharge was carried out in various parts of the worldfor the last six decades (Babcock and Cushing   1942;Barksdale and Debuchanne 1946; Beeby-Thompson1950; Buchen  1955; Todd  1959). However, the impor-tance of artificial recharge was realized in India onlyabout four decades ago (Karanth  1963). In the recentyears, many studies concentrated on application of remote sensing and GIS for artificial recharge (Sharma1992; Anbazhagan 1994, unpublished PhD thesis;Ramasamy and Anbazhagan   1997, Anbazhagan andRamasamy  2001).

The study area ‘Ayyar basin’ is a sub-basin of themajor ‘Cauvery’ river basin in Tiruchirappalli district,

Tamil Nadu state,  India (Fig.  1). The aerial extent of thebasin is 1,167 km2 and it incorporates two administra-tive taluks called Musiri and Thuraiyur. Approximatelyone-fifth of the area is covered by hilly terrain (Kolli andPachamalai hills). Geologically, the basin is predomi-nantly covered by gneissic and charnockitic rock types.The majority of the irrigated land in the basin is beingcultivated with the help of groundwater augmented fromdug wells and bore wells to the maximum possible ex-tent. In this circumstance, aquifer replenishmentthrough artificial recharge is necessary for this region.The Central and State governments are spending aconsiderable amount of money for construction of artificial recharge structures like percolation ponds andcheck dams. However, detailed scientific analysis needs

S. AnbazhaganS. M. RamasamyS. Das Gupta

Remote sensing and GIS for artificialrecharge study, runoff estimation andplanning in Ayyar basin, Tamil Nadu, India

Received: 23 September 2004Accepted: 7 March 2005Published online: 11 June 2005  Springer-Verlag 2005

Abstract  This paper focuses onartificial groundwater rechargestudy in ‘Ayyar basin’, Tamil Nadu,India. The basin is covered by hardcrystalline rock and overall has poorgroundwater conditions. Hence, anartificial recharge study was carriedout in this region through a projectsponsored by Tamil Nadu StateCouncil for Science and Technology.The Indian Remote Sensing satellite1A Linear Imaging Self ScanningSensor II (IRS 1A LISS II) satelliteimagery, aerial photographs andgeophysical resistivity data wereused to prioritize suitable sites forartificial recharge and to estimatethe volume of aquifer dimensionavailable to recharge. The runoff water available for artificial rechargein the basin is estimated through Soil

Conservation Service curve numbermethod. The land use/land cover,hydrological soil group and stormrainfall data in different watershedareas were used to calculate therunoff in the watersheds. Theweighted curve number for eachwatershed is obtained through spa-tial intersection of land use/landcover and hydrological soil groupthrough GeoMedia 3.0 ProfessionalGIS software. Artificial rechargeplanning was derived on the basis of availability of runoff, aquiferdimension, priority areas and watertable conditions in different water-sheds in the basin.

Keywords  Artificial recharge   Æ

Remote sensing  Æ  GIS  Æ  Runoff estimation  Æ  Curve number   Æ  India

Environ Geol (2005) 48: 158–170DOI 10.1007/s00254-005-1284-4   O R I G I N A L A R T I C L E

S. Anbazhagan (&)  Æ  S. Das GuptaDepartment of Earth Sciences,Indian Institute of Technology Bombay,Powai, Mumbai, 400076, IndiaE-mail: anban@iitb.ac.inTel.: +91-022-25767255Fax: +91-022-25723480

S. M. RamasamyCenter for Remote Sensing,Bharathidasan University,Tiruchirappalli, 620023, India

 

to be done before, construction of such structures.Hence, a comprehensive research work was carried outin this region with the help of the Tamil Nadu StateCouncil for Science and Technology (TNSCS&T). Theresearch work comprises four phases: selection of suit-able sites, identification of site-specific mechanisms,surface runoff estimation and prioritization of artificialrecharge practices based on different criteria.

The suitable sites for artificial recharge were identifiedby analysis of geological, geomorphological, subsurfacegeological and water-level fluctuation data throughthematic as well as statistical modeling (Ramasamy andAnbazhagan   1997; Anbazhagan and Ramasamy  2001,2005). In the second phase, various methods of artificialrecharge were identified based on different controllingterrain parameters. Desiltation of existing tanks, flood-ing and dendritic furrowing, percolation ponds, en-echelon dams, injection wells and subsurface dams wererecommended in the priority areas (Ramasamy andAnbazhagan   1996). Before implementing any artificialrecharge schemes, it is necessary to estimate the avail-able precipitation and runoff in the basin. The analysisof 16 years, rainfall data in the basin has shown an

average of 500-mm rainfall in the southern part andmore than 790-mm rainfall in the central and northernparts of the basin. In the third phase, the volume of surface runoff available in the basin for artificial re-charge was estimated through an SCS curve method(Anon  1973). In the final stage, artificial recharge plan-ning was done on the basis of availability of runoff,aquifer dimension and water table conditions in differentwatersheds in the basin.

Methodology 

The current study has been focused on artificial rechargesite selection process and runoff estimation through re-mote sensing and GIS techniques. The digitally pro-cessed IRS 1A LISS II (Indian Remote Sensing satellite1A Linear Imaging Self Scanning Sensor II) satellitedata and aerial photographs were used for the genera-tion of various thematic maps on geology and geomor-phological parameters. The thematic maps includepervious and impervious lithology, rock-soil contact,

Fig. 1  Location map of Ayyarbasin

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lineament, lineament density, structure, fluvial and de-nudational geomorphology.

In addition, the Survey of India (SOI) topographicmaps, geophysical resistivity and field investigation datawere used for generation of geological, geomorphologi-cal, subsurface geological and hydrological database.Followed by thematic map generation, thematic mapintegration was performed through manual as well asstatistical analysis, from which the watershed wise vol-ume of the aquifer dimension was estimated.

Satellite data were mainly used to generate land useand land cover information. Such land use and landcover detail, hydrological soil group and storm rainfalldata were used for calculating the runoff through theSCS method. After estimating the volume of runoff available in each watershed, the artificial rechargeplanning was carried out. The methodology adopted inthe study is demonstrated in Fig.  2.

Artificial recharge site selection

Most of the artificial recharge studies focused on selec-tion of suitable sites for aquifer replenishment (Johnsonand Sneigocki 1967; Warner and Moreland  1972; Vec-chioli et al.  1974; Cochran  1981;  Murakami  1982; Cookand Walker   1990, Sharma   1992; Ramasamy and An-bazhagan  1997; Anbazhagan and Ramasamy  2001). Inthe recent years, the role of remote sensing and GIS hasreceived much attention in artificial recharge studies.The geological, geomorphological, subsurface geologicaland hydrogeological data were analyzed in the processof suitable site selection for artificial recharge.

Database

The database generated for identifying the suitable sitesfor artificial recharge can be grouped into geological,geomorphological, subsurface geological and hydro-

geological parameters. Under geology, thematic mapson rock–soil contact, folded structures, lineaments andsoil types were generated. In aerial photographs, thebarren and vegetative rock exposures normally showlight tone and medium to coarse texture, high peakedhills and features with relief, whereas the soil-coveredzones exhibit medium to darker tone, fine texture andmoderate drainage patterns.

The structural trend lines like fold axis, orientation of the hills, soil tonal variations, the bedding planes or thefoliations exhibiting linear and curvilinear lines wereinterpreted from both satellite imagery and aerial pho-tographs. The broad third-dimensional configurations of the structural trends were determined on the basis of shadow and breaks in slope observed in the aerial pho-tographs. In addition, the strike and dip measuredduring field visits were used for structural trend line andfold mapping. The final fold map has a series of anti-clines and synclines with a general trend of NE–SW toE–W direction in the basin.

In hard rock terrain, lineaments act as better con-duits for groundwater movement and accumulation.The major lineaments were interpreted from IRS 1AFalse Colour Composite (FCC) and also from the fil-tered image. The FCC of Ayyar basin is shown inFig.  3. Linearity in soil tonal contrast, straight drain-age courses and vegetation linearities are the key ele-ments used in interpreting the lineaments from theFCC image. The minor lineaments were interpretedfrom black and white panchromatic aerial photo-graphs. The lineaments interpreted from satelliteimagery and also from aerial photographs were inte-grated together and the final lineament map was pre-pared. From lineament, the lineament density map wasprepared. Soil type is one of the important parameters,which directly controls the infiltration condition inan area. A soil map was prepared with the help of data collected from the Soil Survey and Land useorganization.

Fig. 2  Methodology

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In geomorphology, slope, drainage density and de-nudational geomorphology were studied in detail. Theslope of a terrain reveals the runoff and infiltrationcondition in a basin. The area of a lesser slope favorshigh infiltration and is suitable for aquifer replenish-ment. In Ayyar basin, the slope varies from less than 2%to more than 20%. The drainage pattern is the bestindicator of the porosity and permeability of a terrain. If the drainage density is less in an area, then it can beinferred that the rock type may be porous and possesshigh infiltration. However, the high drainage densityindicates the zone of impervious lithology. The SOItopographic maps were used for the generation of drainage density maps.

The pediments and pediplains are the denudationallandforms suitable for artificial recharge as the rocks arecomparatively weathered in condition. The pediments,which are deeply weathered, are called weathered pedi-ments. Such weathered pediments were selected fromsatellite imagery and obviously suited for artificial re-charge. The fluvial geomorphic landforms are betterrechargeable areas owing to their highly enrichedunconsolidated sediments. The fluvial geomorphic

landforms were interpreted from digitally processed IRS1A satellite data. Mostly three types of fluvial landformsidentified in the study area are piedmont zone, colluvialfills and floodplains. All these landforms are expected tohave high amounts of unconsolidated sediments, andhence, must have a higher rate of infiltration andfavorable areas for artificial recharge (Fig.  4).

The subsurface geology is equally important in theselection of suitable sites for artificial recharge. Hence, thesubsurface geology like the thickness of soil, thickness of weathered zone, thickness of fractured zone and depth tobedrock were measured through detailed well inventoryand geophysical resistivity survey. The water level andwater-level fluctuations are equally important in artificialrecharge and considered site selection procedure.

Data integration and prioritization

Data integration and prioritization were performedthrough manual thematic map integration (Ramasamyand Anbazhagan  1997) and statistical analysis (Anbazh-agan and Ramasamy   2005). In this process, every

Fig. 3  False Color Compositeof Ayyar basin

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thematic map represented certain zones as favorable forartificial recharge. In thematic map integration, the geo-logical, geomorphological, subsurface geological andhydrogeological data were analyzed separately and inte-grated. For example, soil-covered areas from rock–soilcontact, synclinal structures from fold map, high linea-ment density zones andpervioussoil types were integratedtogether and wherever all parameters coincided, theyweredemarcated as suitable areas for artificial recharge, as faras the geological component is concerned. Similarly,suitable areas were identified from geomorphology, andsubsurface geological components. Finally, the suitableareas identified from geology, geomorphology, subsur-face geology and water-level data were superposed oneover theother. In such thematic integration,suitableareasidentified from water-level components were consideredas the mandatory parameter as deeper water-level zonesare prerequisite condition for artificial recharge.Depending upon the number of controlling terrainparameters, the suitable areas were demarcated as priorityarea one, two and least priority areas.

Followed by thematic map integration, more refinedstatistical terrain analysis was carried out (Anbazhaganand Ramasamy   2005). For this statistical analysis, anumerical database was created for 63 sampling pointson water level, lineament density, slope, drainage den-sity, soil types, thickness of soil, thickness of weatheredzone, thickness of fractured zone and depth to bedrock.Through this process, based on number of loading fac-tors, areas were prioritized for artificial recharge of groundwater in the basin (Fig.  5).

Estimation of aquifer dimension

Ayyar basin was divided into five watersheds; Uppili-yapuram, Puliyansolai, Thuraiyur, Tattaiyangarpettaiand Tirumanur (Fig.  5). To effectively practice the artifi-cial recharge in the basin, it is necessary to estimate theaquifer dimension available for recharge. Estimatedaquifer dimension in each watershed will further facilitateto prioritize the watershed for artificial recharge

Fig. 4  Fluvial geomorphology

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implementation. The aquifer dimension is estimated withthehelp of data collectedduringfield visit and geophysicalresistivity survey. To begin, the unsaturated zone avail-able for artificial recharge was estimated. The averagedepth of water level in a watershed is considered as theaverage thickness of the unsaturated zone. For example,the average thickness of the unsaturated zone in the Tat-taiyangarpettai watershed is 13.43 m. The lowest valuefalls in Puliyansolai watershed, i.e. 7.65 m. If averagethickness of the unsaturated zone is 13.43 m, the maxi-mum of 11.43-m water storage is possible. If we rechargemore than 11.43 m, the water level arises within 2-mzonesfrom the ground level, which affects the root-zone growthof cultivation and creates problems. Hence, the unsatu-rated thickness is reduced by 2 m by allottingthe 2-mzoneas the root-growth zone. Next, the aerial extent of priorityarea one and priority area two in different watersheds wascalculated. The volume of the unsaturated zone availablefor artificial recharge in each priority zone was calculatedby multiplying the aerial extent and thickness of theunsaturated zone in each watershed (Table  1). The finaloutput has shown that the available volume of aquiferdimension in million cubic meter (only unsaturated zone)in each watershed for artificial recharge.

Runoff estimation

An artificial recharge project does not stop with thedetection of suitable sites, but yet another importantfactor is the estimation of available water (as runoff) forsuch artificial recharge work. Hence, in the next phase of study, an analysis was performed to estimate the runoff available in each watershed in Ayyar basin. Followed byrunoff estimation, watershed areas were prioritized forartificial recharge based on available volume of waterand aquifer dimension in each watershed. The followingdatabase: aerial coverage of different land use and landcover, hydrological soil group and rainfall are requiredfor estimating runoff in the watershed areas.

Database

Land use/land cover

The land use/land cover is an important characteristic of the runoff process that effects the infiltration, erosionand evapotranspiration. The infiltration, evapotranspi-ration and runoff vary from one land cover to another.

Fig. 5  Watershed-wise priorityareas for artificial recharge

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For example, the area covered by forest comprises in-creased infiltration and reduced runoff components. Theloose soil structure, good aeration and high organiccontent in the soil enhances the function of infiltration ina forested catchment. The runoff yield is increasedgradually from forest cover, grassland, farmland, barrenland and urban built-up land (Yannian   1990). In thepresent study, the remote sensing method was adoptedfor interpreting various land use/land cover in the basin.Several studies have been conducted to demonstrate thefeasibility of interpreting the land-use categories fromremotely sensed data and further used as input data in ahydrologic modeling for estimating the runoff (Raganand Jackson 1980; Slack and Welch  1980; Kathryn et al.1986; Jackson et al.   1996). In the present study, thevarious land-use and land-cover units were interpretedfrom IRS 1A LISS II FCC satellite imagery. In the FCCimagery, the forest cover shows thick red color with highrelief. On the other hand, the forest plantation in the flatterrain exhibits a brownish red color with a definedboundary. The wet crop area identified all along thefloodplain and drainage courses with thick red tonalcontrast. Scrublands are manifested with yellow to red-dish green colors which are typically associated withuplands and rocky outcrop areas. Dry crops are rela-tively associated with pediment zone, in yellow tonalcontrast. Barren rocky outcrops were interpreted withthe help of sharp boundaries, smooth or coarse texture,associated with poor vegetation and structural orienta-tion. Fallow lands are pale to dark green in color in theFCC image. In total, eight land-use and land-cover unitswere interpreted from the satellite imagery and latergrouped into four categories as dry crop, wet crop,natural vegetation and barren/built-up land. The land-use/land-cover categories interpreted from satellite datawere scanned and imported to Geomedia 3.0 Profes-sional GIS software (Fig.  6). The area under differentland-use and land-cover categories in each watershedwere calculated (shown in Table  2).

Hydrological soil group

The initial infiltration and transmission of surface waterinto an aquifer system is a function of soil type and its

texture. The knowledge of soil cover and subsoil con-ditions is essential for prediction of runoff or rechargecondition in a basin. Based on infiltration rate, texture,depth, drainage condition and water transmissioncapacity, soils have been classified into different hydro-logical soil groups: A, B, C and D. The criteria adoptedfor such classification is illustrated in Table  3   (Chowet al  1988; Viessman et al.  1989). In Ayyar basin, forgeneration of the database on the hydrological soilgroup, soil data were collected from the Soil survey andLand Use Organization. There are 11 soil series in Ayyarbasin and each series has been grouped into a particularhydrological soil group. The area under a differenthydrological soil group in each watershed was estimatedand is shown in Table  4. Overall, the hydrological soilgroup ‘B’ occupies the major portion of the basin(Fig.  7). Thus, this indicates that the Ayyar basin hasmoderate runoff potential.

Rainfall 

The daily rainfall data for 4 years from 1998 to 2001were collected from the Groundwater Department forthree rain gauge stations, namely Tattaiyangarpettai,Thuraiyur and Musiri. For calculating the area of influence of a particular rain gauge station in a wa-tershed, Thessien polygons were drawn. The initialabstractions (I a) were calculated for each watershed(explained under the Soil Conservation Services (SCS)curve method). If a storm event is less than the initialabstraction value, there is no runoff available for thatrainfall event. Hence, for a period of 4 years, the stormevents, which are higher than the initial abstractions ineach watershed, were considered for further runoff estimation.

SCS curve number for runoff estimation

In earlier decades, the runoff was estimated as a per-centage of storm rainfall, where the percentage of runoff increases with the increase in rainfall (Linsleyet al. 1958). The SCS has developed a widely usedrunoff curve number procedure for estimating the

Table 1   Available aquiferdimension for artificial rechargein different watersheds

Watersheds Average Thicknessof unsaturatedzone (m)

Area of unsaturatedzone in priority

Volume of unsaturated zonein priority

Area 1(km2)

Area 2(km2)

Area 1(million m3)

Area 2(million m3)

Puliyansolai 5.65 12.4 11.47 70.06 64.81Uppiliyapuram 7.83 15.43 70.81 120.82 554.44Thuraiyur 7.92 – 50.88 – 402.97Tattaiyangarpettai 11.43 124.99 79.94 1428.64 913.71Tirumanur 9.23 3.61 132 33.32 1481.70

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runoff, in which the effect of land use and land cover,various soil cover and antecedent moisture conditionwere considered. If more than one land use or soilcover occurs in a basin, the composite curve numbermethod was adopted (Anon   1973; SCS). The basicassumption of the SCS curve number is that, for asingle storm event, potential maximum soil retention isequal to the ratio of direct runoff to available rainfall.This relationship, after algebraic manipulation andinclusion of simplifying assumptions, results in thefollowing equations (USDA-SCS   1985), where, curvenumber represents a convenient representation of po-tential maximum soil retention (Ponce and Hawkins1996).

Q ¼ð P   0:2S Þ2

 P  þ 0:8S   ;   ð1Þ

where,   Q  direct flow volume expressed as a depth,   Ptotal rainfall,   S  potential maximum soil retention, CNcurve number value used to estimate potential maximumsoil retention (S)

S ¼25; 400

CN  254   ðwater depth expressed in mmÞ:   ð2Þ

The CN values were tabulated according to the Na-tional Engineering Handbook for various land coversand soil textures. These values were developed from

Table 2  Area of different landuse and land cover inwatersheds

Watersheds Land-use and Land-cover type

Barren andbuilt-up area(km2)

Dry crop(km2)

Naturalvegetation(km2)

Wet crop(km2)

Puliyansolai – 24.19 162.92 27.62Uppiliyapuram – 94.08 95.92 44.791Thuraiyur 9.64 126.52 85.82 86.15Tattaiyangarpettai 24.55 77.89 49.61 79.11Tirumanur 20.2 162.6 34.85 128.44

Fig. 6  Land-use/land-covermap of Ayyar basin—inter-preted from IRS 1A satellitedata

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annual flood rainfall–runoff data from the literature fora variety of watersheds generally less than one squarekm in area (USDA-SCS  1985). For runoff estimation ina basin, the results: curve number (CN), potentialmaximum soil retention (S ), initial abstraction (I a) andantecedent moisture condition are required.

Spatial intersection and derivation of curve number

The advantage of Geographic Information Systems(GIS) is spatial analysis through intersection andmanipulation. Therefore, to obtain a weighted CN foreach watershed, it is necessary to intersect the land use/land cover and hydrological soil group in each wa-tershed. The areas under different land use/land coverand hydrological soil group are already shown in theTables  2 and  4, respectively. For spatial intersection, theGeomedia Professional (3.0) GIS software developed byIntergraph is used. The spatial intersections were carriedout for five watersheds, in the basin. The combinedoutput with different land use/land cover, hydrologicalsoil group and corresponding curve numbers (CN) forPuliyansolai watershed is shown in Table  5.

Once the curve numbers were identified for differentland units, the weighted curve numbers were calculatedfor each watershed area in the following manner.

Weighted curve number

¼

PðCN 1 a1 þ CN 2 a2 þ ::: þ CN nanÞ

Pa

  ;

ð3Þ

where, CN1  curve number for particular land unit 1,  a1area for that particular land unit 1,  Ra sum of total area

The weighted curve number for different watershedsin the basin is given in Table  6.

After calculating the weighted curve number, thepotential maximum soil retention (S ) was calculated foreach watershed by using the following formula:

S  ¼25; 400

CN  254:

The potential maximum soil retention for differentwatershed units is given in Table  6. Followed by po-tential maximum soil retention estimation, the initialabstractions (I a) are calculated. Initial abstractions arewater losses, e.g. plant interceptions, infiltration andsurface storage which occur prior to runoff and are thensubtracted from the total runoff (USDA-SCS  1985). Thestandard assumption is that

 I a  ¼ 0:2S 

If rainfall is greater than .2  S , then there is a possi-bility of runoff. Otherwise, if rainfall is less than 0.2S ,runoff will be zero. Hence, the rainfall events, which aremore than 0.2S , were considered for further runoff estimation. The initial abstractions for different water-sheds are given in Table  6.

Estimation of antecedent moisture condition

The curve number varies for different antecedent fieldconditions. To estimate the antecedent moisture condi-

Table 3   Criteria for classification of hydrological soil group

Character Hydrological soil group

A B C DInfiltration rate High Moderate Slow Very slow

Texture Sand / Gravel Moderately coarseto moderately fine

Moderately fineto fine

Clay

Depth Deep Moderately deepto deep

Moderately deep Shallow over animpervious layeror clay pan or highwater table

Drainage Well to excess Moderately welldrained to welldrained

Moderately drainedto slow

Very slow

Watertransmission

High Moderate Slow Very slow

Remarks Low runoff  potential

Moderate runoff potential

Moderate runoff potential

High runoff potential

Table 4   Area of different hydrological soil groups in watersheds

Watersheds Hydrological soil group

A (km2) B (km2) C (km2) D (km2)

Puliyansolai – 177.06 15.26 22.41Uppiliyapuram 45.911 124.3 8.52 56.06Thuraiyur 26.55 168.84 1.48 111.26Tattaiyangarpettai 69.59 56.22 9.55 95.8Tirumanur 65.68 49.95 82.51 147.95

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tion for each storm event, five previous day’s dailyrainfall data values were added. Based on total rainfallvalue and the USDA-SCS method, the antecedentmoisture conditions were calculated (Table  7). With thehelp of these antecedent moisture conditions, theweighted curve numbers were adjusted. If the antecedentmoisture condition is I (dry), the curve number is ad- justed down by using the following formula

CN ¼ 0:39 CN   expð0:009 CNÞ ð4Þ

and if the antecedent moisture condition is III (wet), thecurve number is adjusted up by using the followingequation.

CN ¼ 1:95 CN   expð0:00663 CNÞ ð5Þ

Suppose the antecedent moisture condition is II(damn), the same weighted curve number is used forrunoff estimation.

Table 5  Spatial intersection and derivation of curve number forPuliyansolai watershed

Land-use/land-cover type Soil type Area (km2) Curve number

Dry crop B 6.25 81Dry crop C 10 88Dry crop D 6.25 91Dry crop B 4.47 81Natural vegetation B 148.89 55Wet crop B 1.02 71Wet crop B 15 71Wet crop C 3.53 78Wet crop C 1.73 78Wet crop B 1.71 71Wet crop D 15 81Wet crop B 0.88 71

Table 6   Watersheds and their weighted CN, retention parameterand initial abstraction

Watersheds Weightedcurve number

Retentionparameter—S(mm)

Initialabstraction—Ia(mm)

Puliyansolai 63 151 30Uppiliyapuram 70 111 22Thuraiyur 74 89 18Tattaiyangarpettai 73 92 18Tirumanur 79 67 13

Fig. 7  Hydrological soil groupsin different watersheds

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Runoff estimation for different watersheds

After calculating the curve number (CN), potentialmaximum soil retention (S ), initial abstraction (I a) andantecedent moisture condition, runoff was calculated foreach watershed in the basin (Table  8). For example, thevolume of runoff for Uppliyapuram watershed is cal-culated as follows: the number of storm events 55 and46, respectively, for Thuraiyur and Tattaiyangarpettairain gauge stations considered for a 4-year period. Fromsuch storm events, the rainfall in millimeter was calcu-lated for each station and the weighted curve numberswere adjusted according to the antecedent moistureconditions available in the watershed. Then, using Eq. 1,the direct flow volume was calculated for each stormevent and those were added up for both the rain gaugestations separately. Through Theissen polygon, the areaof influence of each rainfall station had already beencalculated. The total runoff volume in a watershed wascalculated by multiplying the aerial coverage of respec-tive rain gauge stations and direct flow volumes. Thetotal volume of runoff available in Uppliyapuram wa-tershed was calculated as follows. Direct flow volume forThuraiyur station = 326.16 mmDirect flow volume forTattaiyangarpettai station = 199.31 mmArea of influ-ence of Thuraiyur rain gauge station = 98.92 km2Areaof influence of Tattaiyangarpettai rain gauge station =117.47 km2

Volume of runoff in Uppliyapuram

¼ 326:16 103 98:92 106 þ 199:31

103 117:47 106 m3

¼ 55; 624; 450 m3 ¼ 55:6 million m3

Recharge planning 

From runoff estimation, it was inferred that about110.17 million m3 runoff per annum is available forartificial recharge in Ayyar basin. The available aquiferdimension for artificial recharge in the priority area is4718.29 million m3 . Hence, enough volume of unsatu-rated aquifer zone is available in each watershed area.Among the five watersheds, the Tirumanur watershedhas the highest average runoff per annum. The availableaquifer dimension is comparatively higher than theavailable runoff in each watershed. Therefore, the runoff water can be utilized in the respective watershed. Arti-ficial recharge planning can be suggested in the followingways: on the basis of availability of volume of runoff oron the basis of priority areas/aquifer dimensions in thewatersheds. On the basis of runoff availability, theartificial recharge implementation can be prioritized inthe following sequences: 1. Tirumanur 2. Thuraiyur 3.Tattaiyangarpettai 4. Uppliyapuram 5. Puliyansolai(Table  9). If the aquifer dimension is followed, the se-quence is as follows:

1. Tattaiyangarpettai priority area 12. Uppliyapuram priority area 13. Puliyansolai priority area 14. Tirumanur priority area 15. Tirumanur priority area 26. Tattaiyangarpettai priority area 27. Uppliyapuram priority area 28. Puliyansolai priority area 29. Thuraiyur priority area 2

The watershed area can be prioritized on the basis of percentage of volume of runoff water when compared tototal volume of available aquifer dimension: 1. Thur-aiyur, 2. Puliyansolai, 3. Tirumanur, 4. Uppliyapuram,5. Tattaiyangarpettai (Table  9).

Artificial recharge requirement is first needed forthe watershed where there is high water table deple-tion. Hence, artificial recharge practices can be prior-itized on the basis of water table conditions in thewatershed area. Accordingly, the watersheds can beprioritized as follows: 1. Tattaiyangarpettai, 2. Tiru-

Table 8   Rainfall and estimated runoff in different watershed, Ayyar basin

Watersheds 1998 1999 2000 2001 Averagerainfall(mm)

Averagerunoff (million m3)Rainfall

(mm)Runoff volume(million m3)

Rainfall(mm)

Runoff volume(million m3)

Rainfall(mm)

Runoff volume(million m3)

Rainfall(mm)

Runoff volume(million m3)

Puliyansolai 388 10.02 171 1.24 478 10.8 362.4 7.59 349.85 7.41Uppiliyapuram 667.2 27.49 342.66 5.52 556.28 11.47 451.74 11.19 504.47 13.92Thuraiyur 906.01 75.98 521.92 14.79 599.73 15.52 550.28 23.08 644.48 32.34Tattaiyangarpettai 528.23 20.1 330.98 9.63 594.7 22.59 554.86 12.58 502.19 16.22Tirumanur 377.27 52.7 556.23 49.14 525.36 19.06 607.84 40.22 516.68 40.28

Table 7   Antecedent moisture condition classification

Antecedent moisture condition Rainfall range (mm)

I (dry) <36II (normal) 36–53III (wet) >53Source : USDS-SCS, 1985

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manur, 3. Thuraiyur, 4. Uppliyapuram and 5. Puli-yansolai. When compared to other planning, prioriti-zation based on water-level conditions is anappropriate method. Depending upon fund availabil-ity, implementation can be started with priory areasone in the watersheds.

Conclusions

The remote sensing based integrated terrain analysis isuseful for identifying and prioritizing the suitable sitesfor artificial recharge. Further, the land-use and land-cover information interpreted from satellite data isused as one of the main input parameters for esti-mating runoff through the SCS curve method. TheGIS technique is useful in spatial intersection of dif-ferent land use and land cover with various hydro-logical soil groups in the watershed areas. The resultsof spatial intersection were used for calculating the

weighted curve number (CN) in each watershed. It isessential to calculate the runoff potential prior toimplementing an artificial recharge project in a watertable depleted area. In addition to estimation of vol-ume of runoff, the available aquifer dimensions werealso estimated for all watersheds in the basin. In thisstudy, watershed areas were prioritized on the basis of available runoff, available aquifer dimension, percent-age of runoff with total area and watershed condi-tions. Prioritization of watershed on the basis of watertable conditions is a realistic approach for artificialrecharge implementation. In future, prioritization of watersheds including socio-economic factors will give amore refined procedure for artificial recharge imple-mentation.

Acknowledgements   The authors acknowledge the Tamil NaduState Council for Science and Technology for sponsoring the re-search project. The authors also acknowledge the Soil Survey andLand Use Organization and the Groundwater Department forproviding soil and rainfall data, respectively.

Table 9   Artificial recharge planning in different watersheds, Ayyar basin

Watersheds Priorityareas

Aquiferdimension(million m3)

Total volumeof aquifer dimension(million m3)

Average runoff (million m3)

Percentage runoff with reference toaquifer dimension

Priority basedon availablerunoff 

Puliyansolai 1 70.05 134.83 7.41 5.5 52 64.78

Uppiliyapuram 1 120.82 675.15 13.92 2.06 42 554.33

Thuraiyur 2 50.88 50.88 32.34 63.56 2Tattaiyangarpettai 1 1428.72 2342.48 16.22 0.69 3

2 913.76Tirumanur 1 33.26 1514.95 40.28 2.66 1

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