ESTIMATION OF RAINFALL RUNOFF USING SCS-CN AND GIS APPROACH IN PUZHAL WATERSHED

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1 International Journal of Civil Engineering and Technology (IJCIET) Volume 10, Issue 01, January 2019, pp , Article ID: IJCIET_10_01_180 Available online at ISSN Print: and ISSN Online: IAEME Publication Scopus Indexed ESTIMATION OF RAINFALL RUNOFF USING SCS-CN AND GIS APPROACH IN PUZHAL WATERSHED S.Nandhakumar* Assistant Professor, Department of Civil Engineering, Sathyabama Institute of Science and Technology, Jeppiaar Nagar, Rajiv Gandhi Salai, Chennai S.Arsheya Department of Civil Engineering, Sathyabama Institute of Science and Technology, Jeppiaar Nagar, Rajiv Gandhi Salai, Chennai V.K.Kirthika Sri Department of Civil Engineering, Sathyabama Institute of Science and Technology, Jeppiaar Nagar, Rajiv Gandhi Salai, Chennai ABSTRACT Rainfall runoff is one of the important hydrological variables in determining land and water resources application. Curve Number method is widely used and efficient method to estimate the infiltration characteristic of the watershed in accordance with the land use/land cover property and soil property. In this study to estimate the rainfall runoff modeling in this study area with an area of sq km using Soil Conservation Service Curve Number (SCS-CN) method and GIS. The estimated amount average annual rainfall mm from 1999 to 2013.The runoff varied from 285 mm 4053mm, which is corresponds to 61.6% of annual average rainfall of Thiruvalur district. These details are used for better watershed management and conservation purpose. Keywords: Rainfall, Runoff, Watershed, Curve number, Soil Conservation Service, GIS. Cite this Article: S.Nandhakumar, S.Arsheya and V.K.Kirthika Sri, Estimation of Rainfall Runoff using Scs-Cn and Gis Approach in Puzhal Watershed, International Journal of Civil Engineering and Technology, 10(1), 2019, pp

2 S.Nandhakumar, S.Arsheya and V.K.Kirthika Sri 1. INTRODUCTION The word watershed means an area of land which contains a common set of rivers and streams that all drain into a single body of water, such as a lake, a large river or an ocean. The rainfall and runoff modeling can be done in the simplest way using the Soil Conservation Service - Curve Number (SCS-CN) method which was developed by United States Department of Agriculture (USDA),since this method is accepted worldwide[ashish bansode & Patil 2014]. The SCS-CN method has been proved to be rapid, precise estimator of runoff and land use/ land cover classes and are combined with the soil group. There are four soil groups and they are as follows: A, B, C and D [Satheeshkumar 2017]. The Group A soil group have high in-filtration rates, group B and group C soil groups have moderate infiltration rates and group D soil group have low infiltration rates. The SCS-CN method is commonly used for calculating direct runoff volume for any given rainfall event. This method is also suitable for red hill slope areas as per observations examined by the USDA. The Geographical Information System (GIS) is used in this study. Numerous researchers utilize the GIS and curve number that has proved to be quick, accurate estimator of runoff. The Geographic Information Systems (GIS) has been applied extensively in hydrologic modeling in new studies. The runoff estimated when compared with that of GIS tool indicated that the GIS method is providing agreeable results and also as a substitute to the manual method of computation. Based on SCS-CN method and using GIS data as inputs and median of ordering data for all the three antecedent moisture conditions (AMC I, AMC II and AMC III) is used. The Sahu model (2007) and Michel model (2005), generally on the basis of the SCS CN methods, with slight modifications are used [Sundara kumar et al. 2016].Watershed management for conservation has required the runoff information for better understanding and results. Three-dimensional data have made it possible to precisely predict the runoff which has led to significant increases in its use in hydrological applications. The SCS CN is a flexible and widely used for runoff estimation. This method is an important property of the watershed, specifically soil permeability, land use and antecedent soil water conditions [Jaimin Patel et al. 2017]. There are the few estimated details for the better watershed management and conservation purposes and they are as follows: the amount average annual rainfall 1073mm from 1999 to 2013 and the runoff varied from 587mm to 1705mm. 2. DESCRIPTION OF THE STUDY AREA The study area, Puzhal watershed is located in Ponneri Taluk, Thiruvalur District, Tamil Nadu, India. It is one of the rain fed reservoirs from where the water is drawn for supply of water in Chennai city. It is situated at 13 10ʹ0ʺ N and 80 5ʹ0ʺE. It covers an area of sq. km shows the location map of study area. as shown in this Figure (1).The study area attains maximum elevation of 53m and minimum elevation of 6m. It has a tropical climate and the average annual temperature is 28.6 C editor@iaeme.com

3 Estimation of Rainfall Runoff using Scs-Cn and Gis Approach in Puzhal Watershed Figure 1 Study Area - Puzhal Watershed 3. METHODS AND DATA COLLECTION The methodology of the present study is shown in this Figure (2), were the flowchart for the model development of runoff is shown. There are various steps involved is deriving the model of development of the runoff and they are as follows: the major entity required is the study area in this case our study area is the Puzhal watershed. Firstly we need the Rainfall data of the study are and it is collected from the Indian metrological department in this case we have the rainfall data of Puzhal watershed from Secondly we need the land use/land cover of 2018 can be obtained from the satellite images LISS III and the toposheet map were collected from the survey of India and also the textures and soil types (black soil, red soil and clay,) are collected from Survey of India, Rainfall Data collected from Indian Metrological Department (IMD), Chennai. To find out curve number, the boundary of the watershed and catchment area is defined [Amutha & Porchel 2009]. After obtaining all the data required first the soil texture is tested and grouped, there are four groups in the hydrological soil group and they are as follows: A, B, C and D. The Group A soil group have high in-filtration rates, group B and group C soil groups have moderate infiltration rates and group D soil group have low infiltration rates. They study areas soil is group D which has low infiltration rates, high runoff potential when thoroughly wet, the movement of soil is restricted and the group D soil contains less than 50 percent sand, 40 percent clay and it has a clayey texture[ningaraju et al. 2016]. After studying the satellite images the LU/LC is determined is shown Figure (3) editor@iaeme.com

4 S.Nandhakumar, S.Arsheya and V.K.Kirthika Sri Figure 1 Flowchart of Methodology for Rainfall-Runoff Figure 2 Land use / Land cover of Puzhal Watershed 4. SCS-CN MODEL The United Sates Department of Agriculture (USDA) established a very simple method called Soil Conversion Service Curve Number (SCS-CN) in the year 1954 [USDA 1986]. The Soil Conversion Services (SCS) is defined in the National Engineering Handbook (NEH- 4) in the Hydrology Section. The SCS-CN method is based on the two fundamental theories and water balance calculation. The first theory states that the amount of early abstraction is a fraction of the probable maximum retention and the second theory states that the ratio of the editor@iaeme.com

5 Estimation of Rainfall Runoff using Scs-Cn and Gis Approach in Puzhal Watershed real quantity of direct runoff to the maximum possible runoff is equal to the ratio of the amount of real infiltration to the quantity of the potential maximum retention. To estimate the direct runoff from the watershed in the study area, the SCS-CN method is used very frequently. The infiltration losses are combined with surface storage by the relation of [USDA 1974], Q = (P Ia)2 (1) P Ia+S Where, Q is the gathered runoff in mm, P is the rainfall depth in mm, Ia is the initial abstraction in mm and surface storage, interception, and infiltration prior to runoff in the watershed. The empirical relationship is given by [USDA 1974], Ia = 0.2S (2) For Indian condition the form S in the potential maximum retention and it is given by, S = (3) CN Where, CN is known as the curve number which can be taken from SCS handbook of Hydrology (NEH-4), section 4. Now the equation can be written as, Q = (P 0.2S)2 (4) P+0.8S Significant the value of CN, the runoff from the watershed was calculated from Eqs. 3 and 4. The SCS-CN is a purpose of the ability of soils to allow infiltration of water with respect to land use/land cover (LU/LC) and Antecedent Soil Moisture Condition (AMC) [Amutha & Porchel 2009]. 5. ANTECEDENT MOISTURE CONDITION (AMC) The Antecedent Moisture Condition (AMC) refers to the amount of water content present in the soil at a given time. It is determined by total rainfall in 5-day period preceding a rainfall event (SCS, 1986) [Vinithra & Yeshodha 2014].There are three different AMC they are as follows: AMC I, AMC II and AMC III, these are based on different soil conditions shown in Table (1). Using runoff Curve Numbers (CN) from LU/LC and soil type taken for the dry conditions (AMC I), average conditions (AMC II) and wet conditions (AMC III), we can calculate the Curve Numbers (CN). Table 1 Group of Antecedent Moisture Condition (AMC) Classes AMC Group Soil Characteristics Five day antecedent rainfall in mm I Wet Condition <13 II Average Condition III Heavy Condition >28 To calculate CN(I), CN(II) and CN(III) [Chow et al.1988], editor@iaeme.com

6 S.Nandhakumar, S.Arsheya and V.K.Kirthika Sri CN(II) = CN(III) = CN(I) = ΣA.CN ΣA 4.2CN(II) CN(II) 23CN(II) CN(II) (5) (6) (7) 6. HYDROLOGIC SOIL GROUP The soils are classified by the natural resource conservation service into four hydrologic soil groups based on the soils,the groups are A, B, C and D shown in Table (2). Details of this classification can be found in Urban Hydrology for Small Watersheds published by the engineering division of the natural resource conservation service, USDA, TR-55[Chow et al.1988]. The hydrologic soil groups classify soil texture, runoff potentials, water transmission and final infiltration. All the subjects mentioned above will be tabulated below for a better understanding is shown in Table (1). The Group A soil indicates low runoff potential and high infiltration rate, the Group B soil indicates moderate infiltration rate and moderately well drained to well drained, the Group C soil indicates moderately fine to moderately rough textures and moderate rate of water transmission and the Group D soil indicates slow infiltration and possible high runoff. The study area, Puzhal watershed belongs to Group D soil,is shown in Figure (3). Hydrologic Soil Group (HSG) Group A Group B Group C Group D Table 2 Soil Conversion Service Classification (USDA 1974) [USDA 1974] Soil Texture Deep, well drained sands and gravels. Moderately deep, well drained with Moderate. Clay loams, shallow sandy loan with moderate to fine texture. Clay soils that swell significantly when wet. Runoff Potential Water Transmission Final Infiltration Low High Rate >7.5 Moderate Moderate Rate Moderate Moderate Rate High Low Rate < editor@iaeme.com

7 Estimation of Rainfall Runoff using Scs-Cn and Gis Approach in Puzhal Watershed Figure 3 Puzhal Watershed - Soil Map Puzhal watershed comes under gentle to steep slope class shown in Table (3). (Medium to high runoff) thus improving chance of improving infiltration and recharge in the study area shown in Figure ( 5). Table 3 Slope Classes of Puzhal watershed [IMSD 1995] Sl. No. %Slope Area in Km 2 Implication of Potential 1 Nearly Level Km 2 Low surface runoff 2 Gentle Km 2 Low surface runoff 3 Moderate Km 2 Medium surface runoff 4 Steep Km 2 High surface runoff 5 Very Steep Km 2 High surface runoff editor@iaeme.com

8 S.Nandhakumar, S.Arsheya and V.K.Kirthika Sri Figure 4 Puzhal Watershed - Slope Map 6. RESULTS AND DISCUSSIONS The calculated curve numbers (CN) for normal, average and wet conditions are 77.93, and in Figure (7). The rainfall varies from 630 mm 2396 mm ( ) as shown in Figure (6). The runoff varies from 285 mm 4053 mm ( ) as shown in Figure (7).The average annual runoff calculated come to be mm Table (4) and average runoff volume for fourteen years is 164,107,796,924 m 2. The rainfall runoff relationship is shown in Figure (8) for Puzhal watershed. The rainfall and runoff are strongly correlated with a correlation coefficient (r) value being Figure (9). For this study area, the relation was found to be strongest linear editor@iaeme.com

9 Estimation of Rainfall Runoff using Scs-Cn and Gis Approach in Puzhal Watershed Table 4 Annual average runoff depth and volume Year Rainfall (mm) Runoff (mm) Figure 5 Rainfall varies in Puzhal watershed editor@iaeme.com

10 S.Nandhakumar, S.Arsheya and V.K.Kirthika Sri Figure 6 Runoff varies in Puzhal watershed Figure 7 Chart between rainfall and runoff Figure 9 Scatter plot between rainfall and calculated Runoff 7. CONCLUSION The Soil Conversion service (SCS) and Curve Number (CN) method is used in the present work with the help of land use and soil maps described in Arc GIS, as input. The amount of editor@iaeme.com

11 Estimation of Rainfall Runoff using Scs-Cn and Gis Approach in Puzhal Watershed runoff represented is 61.6% of the total annual rainfall. Maximum rainfall and runoff occurred in the year 2005 and Minimum in the year The monthly rainfall-runoff simulation found good in the watershed. In SCN-CN method Antecedent Moisture Condition (AMC) of the soil plays a very significant role because the CN number differs according to the soil and that is considered while estimating runoff depth. For a given study area that is puzhal watershed CN number is calculated equals to for AMC - I, AMC-II and for AMC-III. In conclusion, Soil Conversations Service Curve Number (SCS-CN) methodology is efficiently proven as a better method, which consumes a smaller amount of time and facility to handle wide-ranging data set and a larger environmental area to find site selection of artificial recharge structures. REFERENCE [1] Satheeshkumar, S., Venkateswaran, R., & Kannan, R. (2017), Rainfall runoff estimation using SCS CN and GIS approach in the Pappiredipatti watershed of the Vaniyar sub basin, South India. DOI: /s [2] Ashish Bansode, K., & Patil, A. (2014), Estimation of Runoff by using SCS Curve Number Method and Arc GIS, International Journal of Scientific & Engineering Research, Volume 5, Issue 7, July [3] Sundara Kumar, P., Praveen, T.V., Prasad, M.A., (2016), Rainfall-Runoff Modeling using Modified NRCS-CN,RS and GIS -A Case Study, Int. Journal of Engineering Research and Applications, Vol. 6, Issue 3, (Part - 1) March [4] Jaimin Patel, N., Singh, P.,Indra Prakash, P., Khalid Mehmood, (2017), Surface Runoff Estimation Using SCSCN method- A Case Study on Bhadar Watershed, Gujarat, India, Imperial Journal of Interdisciplinary Research (IJIR) Vol-3, Issue-5, [5] Vinithra, R., l. Yeshodha, I., (2014), Rainfall- Runoff Modeling Using SCS-CN Method: A Case Study of Krishnagiri District, Tamil Nadu, International Journal of Science and Research (IJSR). [6] Ningaraju, H. J., Ganesh kumar,s. B., Surendra, H. J., (2016), Estimation of Runoff Using SCS-CN and GIS method in ungauged watershed: A case study of Kharadya mill watershed, India, International Journal of Advanced Engineering Research and Science (IJAERS), Vol-3, Issue-5, May [7] Dipesh, B., Chavda, Jaydip, j. Makwana, J., Hitesh, V., Parmar, Arvind, N., kunapara and Girish V., Prajapati, (2016), Estimation of Runoff for Ozat Catchment using RS and GIS based SCS-CN method, Current World Environment, Vol. 11(1), (2016). [8] Chow, V. T., Maidment, D. R., and l. w. Mays, I.W., (1988). Applied Hydrology. McGraw-Hill, New York city, New York, USA. [9] USDA (1986) urban hydrology for small Watersheds, TR-55, United States Department of Agriculture, 210-VI-TR-55, 2nd edn June [10] USDA (1972) Soil Conservation Service, National Engineering Handbook. Hydrology Section 4. Chapters Washington, D.C: USDA. [11] USDA-SCS (1974) Soil survey of Travis County, Texas. College Station, Tex.: Texas Agricultural Experiment Station, and Washington, D.C.USDA Soil Conservation Service. [12] [Taha, M., Taher, (2014) Integration of GIS Database and SCS-CN Method to Estimate Runoff Volume of Wadis of Intermittent Flow, DOI /s [13] r. viji, p. rajesh prasanna, r. ilangovan, Gis Based SCS - CN Method For Estimating Runoff In Kundahpalam Watershed, Nilgries District, Tamilnadu, (2015), Earth Sci. Res. J. Vol. 19, No. 1 (June, 2015): editor@iaeme.com

12 S.Nandhakumar, S.Arsheya and V.K.Kirthika Sri [14] G. p. bharathi, k. balasubramani, Rainfall - Runoff Modeling using Soil Conservation Service Curve Number (SCS-CN) Method A Case Study of Ungauged Andipatti Watershed, Tamil Nadu, India, (2015). [15] IMSD (1995) Technical guidelines, integrated mission for sustainable development, national remote sensing center (NRSC) Department of Space, Government of India. [16] amutha r, porchelvan P (2009) Estimation of surface runoff in Malattar sub-watershed using Himanshu Bavishi and Bhagat N.K, Rainfall Runoff CoRelationship Using Empirical Methods for Lower Mahi Basin, India. International Journal of Civil Engineering and Technology, 8(3), 2017, pp SCS-CN method. J Soc RemoteSens 37(2): [17] Eshanthini P, P. Vijayalakshmi, P.K. Raji, Rainfall Runoff Estimation Using SCS Model and Arc Gis for Micro Watershed in Cuddalore District. International Journal of Civil Engineering and Technology, 9(9), 2018, pp [18] H.L. Tiwari, Ankit Balvanshi and Deepak Chouhan, Simulation of Rainfall Runoff of Shipra River Basin. International Journal of Civil Engineering and Technology, 7(6), 2016, pp editor@iaeme.com