Rainfall-Runoff Modelling using Modified NRCS-CN,RS and GIS -A Case Study

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1 P.Sudara Kumar It. Joural of Egieerig Research ad Applicatios RESEARCH ARTICLE OPEN ACCESS Raifall-Ruoff Modellig usig Modified NRCS-CN,RS ad GIS -A Case Study P.Sudara Kumar*, T.V.Pravee**, M.A.Prasad*** *(Research scholar, Adhra Uiversity, Associate Professor, Departmet of Civil Egieerig K.L.Uiversity, Gutur Dist, A.P- Idia) ** (Professor, Departmet of Civil Egieerig, Adhra Uiversity, Vishakhapatam, Idia) *** (Professor, Departmet of Civil Egieerig, Osmaia Uiversity, Hyderabad, Idia) ABSTRACT Study of raifall ad ruoff for ay area ad modelig it, is oe of the importat aspects for plaig ad developmet of water resources. The developmet of water resources ad its effective maagemet plays a vital role i developmet of ay coutry more particularly i Idia, which is a agricultural based ecoomy. Hece it is iteded to develop a model of Raifall ad ruoff to a river basi ad also apply the methodology to Sarada River Basi which has draiage area of Sq.km. The basi is situated i Vishakhapatam district of Adhra Pradesh, Idia. The raifall ad ruoff data has bee collected from the gaugig statios of the basi apart from raifall data from earby statios. MNRCS-CN method has bee adopted to calculate ruoff. Various hydrological parameters like soil iformatio, raifall, lad use ad lad cover (LU/LC) were cosidered to use i MNRCS-CN method. The depth of ruoff has bee computed for differet lad use patters usig, IRS-P4- LISS IV data for the study area. Based o the aalysis, lad use/lad cover patter of Sarada River Basi has bee prepared. The lad use/lad cover patters were also visually iterpreted ad digitized usig ERDAS IMAGINE software. The raster data was processed i ERDAS ad geo-refereced ad various maps viz. LU/LC maps, draiage map, cotour map, DEM (Digital elevatio model) have bee geerated apart from raifall potetial map usig GIS tool. The estimated ruoff usig MNRCS-CN model has bee simulated ad compared with that of actual ruoff. The performace of the model is foud to be good for the data cosidered. The coefficiet of determiatio R 2 value for the observed ruoff ad that of the computed ruoff is foud to be more tha 0.72 for the selected watershed basi. Keywords-Watershed, Lad use/lad cover, MNRCS, Raifall-Ruoff Modellig, DEM,RS ad GIS. I. INTRODUCTION The USDA Soil Coservatio Service curve umber (SCS-CN) method has bee widely accepted world over for its simplicity i applicatio for raifall ad ruoff modellig. It was reported that the cocept of curve umber has origiated from the uit hydrograph theory. The uit hydrograph approach always requires a method for predictig raifall cotributio to the storm ruoff. The SCS-CN method arose out of the empirical aalysis of ruoff particularly from small catchmets ad also suitable for hilly slope areas as per observatios moitored by the USDA [9]. Geographic Iformatio Systems (GIS) has bee applied widely i hydrologic modelig i recet studies. The ruoff estimated whe compared with that of GIS tool idicated that the GIS method is providig satisfactory results ad also as a alterative to the maual method of computatio. Stuebe, Johsto [8] ad Grove et al[3]. Ruoff depth estimates usig distributed CN are reported to be givig better result whe compared with that of composite CN. It was reported that uderestimatio of ruoff depth by CN method may be primarily due to oliear relatioship betwee CN ad ruoff depth ad also whe precipitatio depths are low ad lower rages of curve umbers. The error i estimatio of ruoff whe desig storms are larger ad also whe distributed CNs are adopted is relatively less. Narayaa. V. D. et al. [1], has proposed CNfor estimatio of ruoff values for four Idia watersheds by assumig iitial abstractio as 0.3 times as maximum potetial retetio ad he has reported that estimated value was i close agreemet with that of observed value. Mogle[6], Mishra, S.K., Sigh, V.P[5] used the US Departmet of Agriculture, Natural Resources Coservatio Service Curve Number (USDA-NRCS-CN) method for determiig the ruoff depth successfully. They have adopted ruoff curve umber which was determied based o the factors of hydrologic soil group, lad use, lad treatmet, ad hydrologic coditios. GIS ad remote sesig were used to provide quatitative measuremets of draiage basi morphology for iput ito ruoff models so as to estimate ruoff respose (Hjelmfelt. A. T. Jr[2], Mogle [6], Melesse ad Shih [4]. The results provided as a meas that GIS ca be effectively used as a alterative to covetioal methods. They have also attempted to derive the weighted Curve Number (CN) ad ruoff 54 P a g e

2 P.Sudara Kumar It. Joural of Egieerig Research ad Applicatios for the watershed. Their study cocluded that by adoptig a itegrated approach of RS, GIS ad SCS model it is possible to make maagemet plas for usage ad developmet of water resources. Mishra ad Sigh modified the existig NRCS-CN method by takig 0.5(P-Ia) i place of (P-Ia). The existig NRCS-CN method ad the proposed modificatios were compared ad the modified versio was foud to be more accurate tha the existig NRCS-CN method. The objectives of the preset study are to calculate daily ruoff usig NRCS ad MNRCS-CN ad also to create ruoff potetial map for Sarada River Basi usig GIS. It is also iteded to develop lad use ad lad cover map for the area usig RS ad GIS Arc Ifo-software. II. STUDY AREA Cosiderig the availability of meteorological, hydrological, soil ad other data, the preset study has bee udertake o Sarada River Basi. This site is located i Vishakhapatam district of Adhra Pradesh state i Idia. The Sarada River Basi is located withi E & logitude ad & N ad latitude. The total area of the study basi is aroud km2. This river basi forms a part of Survey of Idia (SOI) sheets Nos. 65 O/1, 2, 3 ad 6 ad 65 K/13, 14 ad 15 the scale of 1: The Idex map of the study area is show i Fig. 1. After the recoaissace survey, the watersheds were delieated o the basis of draiage lie, lad slope ad outlet poit. Furthermore, o the basis of draiage chaels ad lad topography, the river basi is subdivided ito five sub basi Viz., K.Kotapadu, Madugula, Chodavaram, Kasimkota ad Aakapalli. Fig.1: Idex Map of the Study Area III. MATERIALS AND METHODS Soil Coservatio Service Curve Number (SCS- CN) Method Soil Coservatio Service method is oe of the widely used techiques for estimatig direct ruoff depths from storm raifall developed by Uited States Departmet of Agriculture (USDA) Soil Coservatio Service s (SCS), ow is referred as Natural Resources Coservatio Service, (NRCS) Curve Number (CN) method. The U.S. SCS agecy has studied o umber of watersheds of varyig i size; lad use ad lad cover ad the followig relatioships as give i equatio 1 as per Soil Coservatio Service [7]. Q = P I a 2 (1) P I a + S Where, Q is the direct ruoff (mm), P is the depth of raifall (mm), Iais the iitial subtractio (mm) ads is the retetio parameter (mm). The iitial abstractio (Ia) maily icludes iterceptio, ifiltratio, ad surface storage, which occurs before ruoff begis. By usig raifall ad ruoff data from small experimetal watersheds, the followig relatioship was developed US. Soil Coservatio Service [7]. I a = λs (2) where, Iais Iitial abstractio (mm),s is Potetial maximum retetio or ifiltratio (mm) λ is a coefficiet which idicates the amout of storage available i the soil. It is a fuctio of atecedet moisture coditio. Substitutig Equatio 2 i Equatio 1 yields the followig relatioship Q = P 0.2S 2 (for P > 0.2 (3) P + 0.8S where Q = 0 for P 0.2S The potetial maximum retetio storage S of watershed is related to a CN, which is a fuctio of lad use, lad treatmets, soil type ad atecedet moisture coditio of watershed. The CN is dimesioless ad its value varies from 0 to 100. The S-value i mm ca be obtaied from CN by usig the equatio 4. S = (4) CN where, CN is the curve umber which depeds upo lad use, hydrologic soil group. Narayaa [1] recommeded λ equal to 0.3 for most of the regios i Idia except for the regios havig black soils where λ is 0.1. Modificatio of NRCS-CN Method Estimatio of Ruoff usig MNRCS-CN relatioship developed by Mishra ad Sigh [5] Q P = P S + 1 P (5) 2 I geeral, Equatio (5) ca be writte as Q P = P S + ap (6) where a is a coefficiet replacig 1 2 i Equatio (5) Lad Use/ Lad Cover Classificatio Idia Remote Sesig satellite digital image file of year 2010 (Date of pass: 14th February) has bee collected. These images were rectified ad 55 P a g e

P.Sudara Kumar It. Joural of Egieerig Research ad Applicatios geometrically corrected with respect to rectified topo sheet. The classified images of Sarada River Basi are preseted i Fig.2.

Other LU/LCs comprisig of water bodies, barre lad, reserve forest, hilly areas, aquaculture ad settlemet accout for about 16% of the total area of the watershed. The basi has 5.51 % barre lad, 4.

Spatial ad Temporal Variatio i Raifall Daily raifall data has bee collected from six rai gauge statios of Sarada river basi for a period of 2001-2010.

3 P.Sudara Kumar It. Joural of Egieerig Research ad Applicatios geometrically corrected with respect to rectified topo sheet. The classified images of Sarada River Basi are preseted i Fig.2. The Sarada River Basi comprises of eight differet types of LU/LC. However, the major lad use is agriculture (64.72%) followed by Platatio (19.44%). Other LU/LCs comprisig of water bodies, barre lad, reserve forest, hilly areas, aquaculture ad settlemet accout for about 16% of the total area of the watershed. The basi has 5.51 % barre lad, 4.55 % hilly areas, 1.58% reserved forest, 0.82 % water taks ad aquaculture is also preset i that area (0.26 %). I Sarada river basi 3.12 % area is covered by settlemet. Spatial ad Temporal Variatio i Raifall Daily raifall data has bee collected from six rai gauge statios of Sarada river basi for a period of Graphically these data were represeted as plots of magitude vs chroological time i the form of a bar diagram as show i Fig.3. raifall but more tha 25% departure from the average aual raifall. All other years have bee classified as below ormal sice all the gaugig statios were ot cotributig completely for the aual rai fall values. Estimatio of Mea Raifall over the Basi The daily raifall data for raiig moths of the year was used to estimate daily ruoff. The 10 years ( ) daily raifall data of five rai gauge statios have bee utilized to estimate ruoff. The rai gauge represet oly poit samplig of the areal distributio of raifall but raifall over the catchmet is ever uiform.therefore to idetify which rai gauge statios cotribute to mea aual raifall over the etire Sarada River Basi, Theisse polygo method was used. Fig.3: Aual Raifall at Five Rai Gauge Statios of Sarada River Basi Fig.2: LU/ LC Classificatio It was observed from the Fig. 3, that raifall varies with respect to space ad time i the Sarada River Basi to a extet of 800 mm to 1100 mm per year. Based o the data aalysis of raifalls time period i the area ad which has provided the iformatio of average aual raifall of that time period, iformatio of wet years, dry years ad ormal years have bee classified. The years which were above tha average aual raifall ca be classified as wet years. 25% departure from the average aual raifall was also calculated ad preseted as aother bar diagram, as horizotal lie show i Figure 3. The years which were below tha 25% departure from the average aual raifall are classified uder dry years. The years which were i betwee average aual raifall ad 25% departure from the average aual raifall were classified as ormal years. Based o the aalysis of raifalls ( ) i the study area, the year 2010 was characterized as the wet year because all the six statio has a raifall above tha average aual raifall, the year 2009 as the dry year because the raifall at most of the statio was below 25% departure from the average aual raifall ad the year 2004 as the ormal year because raifall at five statios were more tha average aual raifall, oly oe statio has raifall less tha average aual The Arc-GIS software has bee used to develop polygos ad to calculate the area of polygos for better accuracy. The Theisse weightage for each rai-gauge statio was calculated ad used to calculate mea areal raifall over the area. The statistic of Theisse polygo of Sarada River Basi is preseted i Table 2, it was observed that K.Kotapadu rai-gauge statio has most ifluece i the basi followed by Chodavaram. The rai-gauge statio Kotapadu has least ifluece i the basi. Theisse polygo map of Sarada river basi is show i Fig. 4. Fig. 4: Theisse polygo for the study area Table 2: Theisse polygo statistics S. No. Statios Name Area - Km 2 Weightage Factor 1 Chodavaram Madugula K.Kotapadu Aakapalli Kasimkota P a g e

Although the curve umber itself havig o physical meaig but it plays a importat role i defiig hydrological respose of catchmet. Zero curve umber describes the hydrological respose oly with ifiltratio.

4 P.Sudara Kumar It. Joural of Egieerig Research ad Applicatios Curve Number Map Curve umber is oe of the major goverig factors that predomiatly affect the ruoff amout that flows over the lad after satisfyig all losses. Although the curve umber itself havig o physical meaig but it plays a importat role i defiig hydrological respose of catchmet. Zero curve umber describes the hydrological respose oly with ifiltratio. All the raifall water will ifiltrate to become subsurface flow. Whe the Curve Number is 100 it describes the hydrological resposes with o ifiltratio. All the raifall water will flow as surface flow as soil is i saturatio limit that happes i cotiuous raifall evets. As soo as CN has icreased, the ruoff from that watershed will also icrease. The CN is derived from Lad use/lad cover classificatio ad hydrological soil group, the lad use coverage ad soil coverage were merged usig Arc-GIS software. Usig Arc-GIS software total of 78 polygos has bee developed. All these polygos were havig a particular lad use ad hydrologic soil group ad the curve umbers were assiged to these polygos. Thus a curve umber coverage has bee geerated such that differet polygos will have differet curve umber values. The pictorial presetatio of CN for differet areas is preseted i spatial distributio of Curve Number for Sarada River Basi is preseted Fig.5. Fig.5: Spatial distributio of CN Distributed CN Techique The distributed CN techique has bee used to estimate ruoff for Sarada River Basi. The iitial abstractio (Ia) of 0.3S was used, where S is the maximum potetial retetio. The CN value for each polygo was used to calculate maximum potetial retetio S for each polygo by usig Equatio 4. The ruoff of each polygo was estimated with the help of Equatio 1. Therefore, ruoff for 78 polygos were estimated for each day raifall ad the summed up to get the total daily ruoff from the Sarada River Basi. The daily ruoff of all raiig moths is estimated for 10 year period usig daily raifall data of these moths. The ruoff potetial map derived is show i Fig.6. Fig. 6: Ruoff potetial map Model Performace ad Aalysis To achieve the stated objectives, daily precipitatio ad ruoff data for a period of te years, soil data, topographic maps ad satellite imagery data have bee collected for the study area. ERDAS IMAGINE 8.5 ad Arc-GIS 9.2 software packages were used for aalyzig the data. The Survey of Idia topo sheets coverig the study area were scaed, rectified ad digitized for elevatio cotours, draiage etwork, ad promiet lad cover usig Arc-GIS software. The IRS satellite images for the year 2010 was classified usig supervised classificatio (after several groud truth verificatios) with maximum likelihood classificatio algorithm i ERDAS IMAGINE software. Data aalysis The selected basi performace has bee evaluated with three performace measures to evaluate the model performace. The performace measures are Nash-Sutcliffe coefficiet efficiecy (E NS ), root mea square error (RMSE) ad coefficiet of determiatio (R 2 ). (i) Nash-Sutcliffe coefficiet efficiecy (E NS ): It is expressed as i=1 o i p 2 i E NS = 1 o i o (7) i=1 i where, oi ad pi are the observed ad predicted value,o i is the mea of the observed flow; is the umber of data poits. The value of ENS varies betwee - to 1. The closer the value is to 1, the better the model performace. (ii) Root mea square error (RMSE): It is expressed as RMSE = 1 i=1 o i p i 2 (8) (iii) Coefficiet of determiatio: It is expressed as 2 R 2 i=0 o i o i p i p i = (9) o i o 2 i i=0 p i p 2 i where oi is the observed value, o i is the mea of the observed ruoff values, pi is the estimated ruoff value, p i is the mea of the estimated ruoff values. 57 P a g e

5 P.Sudara Kumar It. Joural of Egieerig Research ad Applicatios IV. RESULTS AND DISCUSSIONS The distributed CN techique was used to estimate ruoff i the study area. The CN value for each polygo is used to calculate maximum potetial retetio S for each polygo as per Equatio (4). The ruoff of each polygo thus has bee estimated with the help of Equatio (3) ad Equatio (5). Therefore, ruoff from the 78 polygos has bee estimated as per daily raifall data cumulated to get the total daily ruoff from the study river basi. It is observed from the Table.3 that the predicted ruoff by MNRCS-CN model showed acceptable variatio of tred whe compared with the observed ruoff with certai deviatio durig validatio phase is preseted i Fig.7. The value of coefficiet of determiatio (R2) is foud to be It is also observed that MNRCS-CN has resulted i Nash Sutcliffe efficiecy (ENS) of 70.01%. The higher coefficiet of determiatio values idicates good relatioship betwee the observed ad predicted daily ruoff by the selected model. So, it ca be suggested that MNRCS-CN ca be used for estimatio of ruoff for this ugauged basi. The model has bee successfully applied for loger duratio aalysis ad computatio of aual ruoff depth. Table 3: Statistics for the Observed ad Predicted Ruoff for the Study Area MODEL E NS RMSE R 2 MNRCS-CN V. CONCLUSIONS A rai fall ruoff model has bee successfully developed for a Sarada River Basi i Adhra Pradesh. It is based o the hydrological soil group, Lad use/lad cover ad daily raifall data daily ruoff depth which were estimated by MNRCS-CN method usig distributed CN techique. I the preset study, GIS based MNRCS-CN model is used for the estimatio of u-gauged ruoff i the Sarada River Basi, Vishakhapatam District, Adhra Pradesh, Idia. The coefficiet of determiatio idicates good performace of model with that of simulatio model for ruoff proves the performace of the model. The preset model could be used as meas to estimate ruoff depth i the study area ad also develop ruoff potetial map. REFERENCES [1] Narayaa. V. D, Soil ad Water Coservatio Research i Idia, Idia Coucil of Agricultural Research, KrishiAusadhaBhava, Pusa, New Delhi, 1993, [2] Hjelmfelt. A. T. Jr, Ivestigatio of curve umber procedure. Joural of Hydrologic Egieerig, ASCE, 117(.6), 1991, [3] Grove. M., Harbor, J. ad Egel, B, Composited Vs. distributed curve umbers: effects o estimates of storm ruoff depths,joural of the America Water Resources Associatio (JAWRA),34(5), 1998, [4] Melesse, A.M. ad Shih, S.F, Spatially distributed storm ruoff depth estimatio usig ladsat images ad GIS. Computers ad Electroics i Agriculture, 37(1), 2002, [5] Mishra, S.K., Sigh, V.P, Aother Look at SCS-CN Method, Joural of Hydrologic Egieerig, 4(3), 1999, [6] Mogle, G.E, Effect of orietatio of spatially distributed curve umbers i ruoff calculatios. Joural of the America Water Resources Associatio, 36(6), 200, [7] Soil Coservatio Service, Hydrology. Chapter 9, Hydrologic soil cover complex, Soil Coservatio Service, Natioal Egieerig Hadbook, Washigto D.C., U.S. Departmet of Agriculture, (1972), Sectio -4. [8] Stuebe. M.M., ad Johsto, D.M, Ruoff volume estimatio usig GIS techiques,water Resources Bulleti,26(4), 1990, [9] Uited States Departmet of Agriculture, Soil Coservatio Service. Natioal Egieerig Hadbook. Sectio 4, Hydrology, Washigto, D.C Fig.7: Compariso of Correlatio Coefficiets betwee Observed Ruoff ad Calculated Ruoff MNRCS-CN Model 58 P a g e

Example 3.3: Rainfall reported at a group of five stations (see Fig. 3.7) is as follows. Kundla. Sabli

Example 3.3: Rainfall reported at a group of five stations (see Fig. 3.7) is as follows. Kundla. Sabli 3.4.4 Spatial Cosistecy Check Raifall data exhibit some spatial cosistecy ad this forms the basis of ivestigatig the observed raifall values. A estimate of the iterpolated raifall value at a statio is