IJREAS VOLUME 5, ISSUE 6 (June, 2015) (ISSN 2249-3905) International Journal of Research in Engineering and Applied Sciences (IMPACT FACTOR – 5.981) PRIORITIZATION OF WATERSHED THROUGH SURFACE RUNOFF IN PAMBAR RIVER BASIN USING SCS - CN METHOD IN THE PAMBAR RIVER BASIN,

Baidyanath Kumar Research Scholar, Department of Geography B.R.A Bihar University, Muzaffarpur, Bihar

Abstract

A watershed is an area that drains water and other substances to a common outlet as concentrated drainage. Nowadays watershed management plays a vital role in water resources management. Watershed based on water resources management is necessary to plan and conserve the available resources. Remote Sensing (RS) and Geographic Information System (GIS) techniques can be effectively used to manage spatial and non spatial database that represent the hydrologic characteristics of the watershed use as realistically as possible. The present study has been conducted on Pambar River is one of the major river drains the eastern slopes of covering Anamalai – Cardamom hill ranges. The Pambar watershed basin receives the average annual rainfall of 43.7 inches mainly during June to September monsoon season (1961-2005). Sandy clay loam, Clay loam, silty clay loam, sandy clay, silty clay, or clay are the main soil group confined in this basin. Such a soil group obviously allows less water to infiltrate into it. The result runoff will be more. Due to high runoff potential and poor infiltration, drought like situation prevails in this area from December to June almost every year. So the conservation of watershed is very much essential to protect the environment. The watershed conservation priority number for the each watershed will be assigned according to the value generated from the runoff.

Keywords: SCS – CN; Rainfall; Pambar; GIS; Remote Sensing

1. Introduction

Watershed is defined as “ Natural hydrologic entity that cover a specific area expanse of land surface from which the rainfall runoff flows to a defined drain, channel, stream or river at any particular point” (K.V Seshagiri Rao, 2003). A watershed is made up of soil, vegetation and water along with the people and animals who are the integral part of the system (Sreedevi TK et al, 2004). Modeling of the event based rainfall runoff process has significant important in Hydrology (R K Sahu et.al, 2007 ) The CN is a hydrologic parameter used to describe the storm water runoff potential for drainage area. The CN is a function of land use, soil type, and soil moisture. (Jeffry Swingly Frans Sumarauw, 2012) The core focus of watershed management is controlling the flow of water and runoff material to the down slope areas, which is an applied and multidisciplinary subject based on geology, ecology, environmental economics and the social sciences (Food and Agriculture Organization of UN, 2006). A watershed is the area covering all the land contributes runoff water to a common point ( R. Amutha et al, 2009). Rainfall runoff is an important component contributing significantly to the hydrological cycle, design of hydrological structures and morphology of the drainage system. (Ratika Pradhan et al, 2010). Runoff refers to the flow of water from the land as both surface and subsurface discharge; the more restricted and common use, however, refers to runoff as surface discharge in the form of overland flow and channel flow. (William. Marsh et al, 2013). The relationship between rainfall runoff and annual spatial soil loss is determined using USDA Soil Conservation Service (SCS) method in conjunction with remote sensing and GIS technology (A S Jasrotia, 2002) The hydrological response of watershed is usually

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IJREAS VOLUME 5, ISSUE 6 (June, 2015) (ISSN 2249-3905) International Journal of Research in Engineering and Applied Sciences (IMPACT FACTOR – 5.981) altered due to revolution in the watershed development. Thus it is necessary to quantify the likely changes in the surface runoff in a watershed as an impact of the planned or unplanned changes made in the land use (Tejram Nayak, 2012) Watershed management implies proper usage of water to land and other natural resources in a watershed for estimation of runoff which is required for planning, developing and managing the water resources and irrigation scheduling. Runoff is one of the important hydrologic variables used in the water resources applications and management planning. For gauged watershed accuracy of estimation of runoff on land surface and rivers requires much time and effort. GIS is utilized as a tool to store analyse and integrate information pertaining to runoff, slope, drainage and fractures (D. Ramakrishnan et. Al Aug. 2009) In the present study SCS-CN technique was used to generate rainfall runoff model by incorporating spatial variation of the various physiographic characteristics of the study area such as geomorphology, geology, land use / land cover, soil and drainage pattern integrated with the help of Remote Sensing data and GIS techniques.

2. Study Area

The present study has been conducted in Pambar River Basin situated in Taluk, of . Among the three east flowing rivers in Kerala, Pambar River is one which drains the eastern slopes of Western Ghats covering Anamalai – Cardamom hill ranges. The study area stretched between the latitudes of 1008’ 0’’ to 100 12’ 0’’ N and longitudes of 7703’0’’ to 77016’0’’E covers an area of about 289 Sq.Km. Pambar river basin is a 6th order basin developed in a part of the Proterozoic, high-grade, Southern Granulite Terrain of the Peninsular India are carved out of a terrain dominantly made of granite- and hornblende-biotite gneisses (S. Suresh et al, 2014). The study area has been divided into different geomorphic units, such as escarpments, valley fill, Highly dissected denudational slopes, valleys, denudational slope etc. It covers , Kanthalloor and parts of marayoor and Kannan Devan Hills Villages. Pambar River is one of the main tributaries of flowing from west to east confluence near Chinnar chauki settlement. Map.1 Shows the Study are a location.

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Map 1: Study Area Location

3. Aims and Objectives

The aim and objective of the present study is

 To calculate season wise runoff in a watershed  To assign priority rank on the basis of runoff value

4. Data

The Survey of India topographic maps no 58F03 & 58F04 and Google terrain map were used for the demarcation of the watershed boundary. Geological Survey of India (1:2,50,000) for Idukki District is used for geological map. The rainfall data of Pambar watershed basin from 1961 to 2005 have been used in the study. The rainfall data is collected from UPASI Idukki District. The land use and land cover map was prepared using Google satellite imagery of Pambar basin for the year 2013. The soil information was collected from the soil map of Idukki District, published by the Soil Survey Organization and Agriculture Department. To compute the runoff SCS-CN formulated by United States department of agriculture, 1986 has employed

4. Methodology

All tributaries of different extents and patterns, Soil cover map, Geology map, Land use and land cover map were digitized from corresponding sources in ArcGIS 9.3 software platform. On the basis of rainfall availability, the rainfall data has divided into three categories. They are summer season (February – May), Monsoon season (June – September) and Winter season (October – January). Inorder to scrutinized the runoff in the Pambar river basin landuse – land cover and soil

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IJREAS VOLUME 5, ISSUE 6 (June, 2015) (ISSN 2249-3905) International Journal of Research in Engineering and Applied Sciences (IMPACT FACTOR – 5.981) layer have been merged together and the appropriate CN value was assign in the merged data as a separate field on the basis of soil and landuse and availability of rainfall in situ. Based on the runoff value the sub watershed basin has been arranged in hierarchy manner. Thus the final output has been evolved.

4.1 Curve Number (CN) Analysis The CN is estimated for a drainage basin using a combination of river basin, land use, soil (Jeffry Swingly Frans Sumarauw et.al, 2012). The CN generator requires three shape files the drainage basin boundaries for which CN will be calculated, the soil type, and the land use layer. The information needed to determine a CN is the hydrologic soil group (HSG), which indicates the amount of infiltration the soil will allow. There are four hydrologic soil groups (USDA, 1986). They are given below in Table-1. Table-2 presents the typical land use categories used for hydrologic analysis, along with corresponding curve numbers for each land use-soil group combination.

Effect of Hydrologic Soil Group on Runoff Volumes and Peak Rates.

HSG Soil Textures A Sand, loamy sand, or sandy loam B Silt loam or loam C Sandy clay loam D Clay loam, silty clay loam, sandy clay, silty clay, or clay Table 1: hydrologic soil groups

Group A soils have low runoff potential and high infiltration rates even when thoroughly wetted. They consist chiefly of deep, well to excessively drained sand or gravel and have a high rate of water transmission (greater than 0.30 in/hr)

Group B soils have moderate infiltration rates when thoroughly wetted and consist chiefly of moderately deep to deep, moderately well to well drained soils with moderately fine to moderately course textures. These soils have moderate rate of water transmission (0.15-0.30 in/hr)

Group C soils have low infiltration rates when thoroughly wetted and consist chiefly of soils with a layer that impedes downward movement of water and soils with moderately fine to fine textures. These soils have a low rate of water transmission (0.05-0.15 in/hr)

Group D soils have high runoff potential. They have very low infiltration rates when thoroughly wetted and consist chiefly of clay soils with a high swelling potential, soil with a permanent high water table, soils with a clay or clay layer at or near the surface, and shallow soils cover nearly impervious material. These soils have a very low rate of water transmission (0-0.05 in/hr)

Curve number by hydrologic soil Land use A B C D River and Waterbody 100 100 100 100 Rocky outcrop 81 86 91 93 Plantation 43 65 76 82 Forest 35 56 70 77 Grass land 49 69 79 84 Agriculture 67 78 85 89 Settlement 54 70 81 86 Table-2. Land use categories and associated CN.

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IJREAS VOLUME 5, ISSUE 6 (June, 2015) (ISSN 2249-3905) International Journal of Research in Engineering and Applied Sciences (IMPACT FACTOR – 5.981) 4.2 Computing Runoff The SCS Runoff Curve Number (CN) Method The SCS runoff equation is Q= (P-Ia)2 / (P-Ia)+S [Eq. 1] Where, Q = runoff (in) P = rainfall S = potential maximum retention after runoff begin (in), and Ia = Initial abstraction (in) Initial abstraction (Ia) is all losses before runoff begins. It includes water retained in surface depressions, water intercepted by vegetation, evaporation, and infiltration. Ia is highly variable but generally is correlated with soil and cover parameters. Through studies of many small agricultural watersheds, Ia was found to be approximated by the following empirical equation: Ia = 0.2S [Eq.2] By removing Ia as an independent parameter, this approximation allows use of a combination of S and P to produce a unique runoff amount. Substituting equation 2 into equation 1 gives Q = (P-0.2S)2 / (P+0.8S) [Eq.3] S is related to the soil and cover conditions of the watershed through the CN. Cn has a range of 0 to 100, and S is related to CN by S = (1000/CN)-10 [Eq.4]

5. Result and Discussion

5.1 Climate Climate in this area is mainly monsoon climate. For the study area 45 years climatic data has been taken into account (1961-2005). Due to high altitude almost 2500 mt above MSL heavy downpour and moderate temperature is experienced in these areas. The maximum temperature is 25.650C in March and minimum temperature is 19.010C in July. The average temperature is 22.380C. Likewise the rainfall also varied from season to season. Huge downpour was happened in monsoon season (June-September) and Occasional conventional rainfall recorded in summer season. According to the data maximum rainfall recorded in September 53.24 inches and minimum rainfall received in January o.55 inches. The average rainfall of this region is 18.24 inches. The climatic data for Pambar river basin is given in table 3

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IJREAS VOLUME 5, ISSUE 6 (June, 2015) (ISSN 2249-3905) International Journal of Research in Engineering and Applied Sciences (IMPACT FACTOR – 5.981)

Mean Rain fall (In) & Temperature in (oC) 1961 to 2005 Month Rainfall Total Temperature Total

January 0.55 23.74

February 0.78 24.72

March 1.60 25.65

April 16.01 24.81

May 8.40 23.46

June 36.05 20.04

July 49.00 19.01

August 36.44 19.19

September 53.24 20.79

October 10.17 22.06

November 5.06 22.44

December 1.63 22.73

Table-3 The climatic data for Pambar river basin

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CLIMATIC DIAGRAM

60

50

40

30

20

10

0

Rainfall Temperature

Fig.1 Climatic Diagram

5.2 Drainage Density The drainage density is an important indicator of the linear scale of landform elements in stream eroded topography. Low drainage density leads to coarse drainage texture while high drainage density leads to fine drainage texture (Strahler, 1964). The less permeable a rock is, the less the infiltration of rainfall, which conversely tends to be concentrated in surface runoff. Drainage density of the study area is calculated using spatial analysis-IDW technique tool in ArcGIS software. The study area has been grouped into five classes. These classes have been assigned to very good, good, moderate, poor, and very poor respectively. High drainage density is recorded in the central parts of the basin (Map.2). The suitability of groundwater potential zones is indirectly related to drainage density because of its relation with surface runoff and permeability.

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Map. 2:

Drainage Density

5.3 Geology Geology plays an important role in the distribution and occurrence of groundwater. In the present study geological mapping is done using Idukki District Geological Map (GSI) with scale 1:250,000. The study area is underlain by Hornblende-biotite gneiss, Granite gneiss, Anticline, syncline, strike and dip of foliation. The geological map of study area is shown in Map.3

Map. 3: Geological map of study area

5.4 Soil Soil types of the study area are largely depending on lithology characters. There are two main soil group of this area (Map.4). The first one is Hill soil (Chinnar Series) well drained with depth more than 150 cm developed from gneissic parent material, strongly acid. Soils dark

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IJREAS VOLUME 5, ISSUE 6 (June, 2015) (ISSN 2249-3905) International Journal of Research in Engineering and Applied Sciences (IMPACT FACTOR – 5.981) yellowish brown to red with clay loam to clay texture and the second one is Forest soil (Anaimudi Series) well drained with depth more than 150 cm. developed from gneissic parent material, very strongly acid and soils dark reddish brown to reddish yellow with silty loam to clay texture.

Map. 4: Soil Map of Pambar River Basin

5.5 Land Use / Land Cover

Land Use / Land Cover Map (Map. 5) was prepared by the analysis of Landsat ETM+ images of 2004 and Google Map images 2013. Based on the prepared map, 10% area is come under agricultural land followed by 39.18% forest land, 34.70% Grass land, 9.15% Plantation, 5.42% Rock outcrop, 1.05% settlement and 1% waterbody respectively. The land use/land cover map has been shown in fig.9 considering the areas under irrigation, they constitute about 10% of the study area indicating a strong reliance of the agricultural activities on irrigation which due to low precipitation in the region is supplied by groundwater resources.

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Map. 5: Land use and Land cover of Pambar River Basin

LAND USE / LAND COVER DETAIL Land Use Area in Sq.Km Area in % Pambar River Basin: Land Use Land Cover in % Agricultural Land 29.62 10 Forest 115.61 39.18 40 Grass Land 102.38 34.70 30 Plantation 27.60 9.15 20 Rock Outcrop 16.23 5.42 10 Settlement 3.12 1.05 0 River & Waterbody 1.54 0.33

Table. 4 Area of Land Use / Land Cover in Pambar River Basin

Fig.2 Land Use / Land Cover in %

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IJREAS VOLUME 5, ISSUE 6 (June, 2015) (ISSN 2249-3905) International Journal of Research in Engineering and Applied Sciences (IMPACT FACTOR – 5.981) 5.6 Runoff Estimation From the rainfall data collected for 45 years (1961 – 2005), almost sufficient rainfall received only during monsoon season that is June – September reveals that average rainfall received during this month is 43.7 inches. In contrast to that the rainfall data reckons reveals summer season (6.7 inches) and winter season (4.4 inches) received in that particular years. With the help of that rainfall data in associated with soil, land use data and also the SCS – CN the runoff has been predicted. The table.5 depicts the appropriate runoff value for Pambar watershed basin in season wise. The given maps also clearly indicate that the runoff (Q) for the river basin. In monsoon season itself the runoff volume was so high rather than the two seasons. In Pambar watershed basin almost all land use / land cover release more out flow of water especially rock outcrops, settlement and agricultural land release more runoff water. This is mainly because of poor water infiltration and high runoff potential hill soil and forest soil. The remaining two seasons only meager amount of rain was received so obviously the amount of runoff also low.

Mean Rain fall (Inches) 1961 to 2005 Summer season (Feb-May) Monsoon season (Jun – Sep) Winter season (Oct – Jan) Average rainfall= 6.7 inches Average rainfall= 43.7 inches Average rainfall= 4.4 inches CN Run CN Run CN Run CN Run CN Run CN Run SI. Land use value off value off value off value off value off value off No for (Q) for (Q) for (Q) for (Q) for (Q) for (Q) HSG HSG HSG HSG HSG HSG (C) (D) (C) (D) (C) (D) 1 River & Water 100 100 100 100 100 100 100 100 100 100 100 100 body 2 Rock 91 5.6 93 5.8 91 42.5 93 42.8 91 3.4 93 3.6 Outcrop 3 Plantation 76 4.0 82 4.6 76 40.1 82 41.2 76 2.0 82 2.5 4 Forest 70 3.4 77 4.1 70 38.9 77 40.3 70 1.6 77 2.1 5 Pasture Land 79 4.3 84 4.9 79 40.6 84 41.5 79 2.3 84 2.7 6 Agricultur 85 4.9 89 5.4 85 41.6 89 42.3 85 3.0 89 3.2 e Land 7 Settlement 81 4.6 86 5.1 81 41.1 86 41.8 81 2.5 86 2.9 Table. 5 Land Use / Land Cover and its Runoff in Pambar River Basin

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The given map.6 indicates the runoff of a Pambar watershed. From the map high runoff observed on western parts of hilly region, the eastern part of Madavari mala, Anavari mala and the Pambar River. The low amount of runoff identified on the northern and southern part of the basin. Table.6 portrays the actual classified runoff area in Sq.Km.

Runoff Area in Sq.Km

V. High 0.93

High 31.44 Medium 74.37

Low 146.59 V. Low 36.04

Table 6: Runoff Area in Sq. Km

Runoff Area in Sq.Km.

160 140 120 100 80 60 40 20 0

Map.6: Land Use / Land Cover and its Runoff in Fig.3 Runoff Area in Sq.Km. Pambar River Basin

5.7 Prioritization of Watershed Runoff analysis is an effective one for prioritization of sub-watershed. Soil erosion of a drainage basin is directly linked with runoff. According to the runoff value the watershed basin has been arranged hierarchically. The basin assigned the priority rank one indicates the high amount of runoff and less infiltration. In contrast to that high priority value of a basin reveals more infiltration than runoff. In this study area the watershed priority map indicates watershed sub basin no 5, 3 and 7 are the high priority on the other hand watershed no 1, 4, 2 are the lowest priority number. The given table.7 and map.7 show the watershed priority.

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PRIORITIZATION OF WATERSHED Watershed Very Low Low Medium High Very High Priority of No Runoff Runoff Runoff Runoff Runoff Watershed 1 0 15 1 0.3 0 10 2 0 15 3 0.1 0 8 3 0 7 25 2 0 2 4 0 12 2 .55 0 9 5 0.2 19 16 7 0.05 1 6 0.8 13 7 2 0 6 7 0.06 13 8 10 0 3 8 12 19 5 3 0.2 5 9 3 18 7 5 0.5 4 10 20 17 1 2 0.05 7

Table.7 Prioritization of Watershed in Pambar River Basin

Map.7 Prioritization of Watershed in Pambar River Basin

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IJREAS VOLUME 5, ISSUE 6 (June, 2015) (ISSN 2249-3905) International Journal of Research in Engineering and Applied Sciences (IMPACT FACTOR – 5.981) Conclusion

The incorporation of SCS-CN model and GIS facilitates runoff estimation and improves the accuracy of estimated data. The result indicates that different land uses with different CN remarkably influenced peak flow in Pambar River basin. The decreasing of CN caused the decreasing of peak flow. The amount of rainfall also decided the runoff. Maximum rainfall recorded in September 53.24 inches. Pambar river basin is surrounded by rocky terrain of western ghats especially Anaimudi and Gundala mountain. The slope also gentle to steep manner. Hill soil and forest soil both are contain clay texture result more runoff than infiltration.Grass land, forest and plantation are the major landcover of this basin reduce the runoff significantly. The conclusions that may be drawn are 1.The combination of remote sensing and SCS model makes the runoff estimate more accurate and fast;

2. Geographical information system arises as an efficient tool for the preparation of most of the input data required by the SCS curve number model;

3. The analysis can be extended further to assess the impact of landuse changes, after developments in the watershed, on the rainfall-runoff relationship.

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