Estimation of surface runoff in nallur amanikere watershed using scs cn method

IJRET: International Journal of Research in Engineering and Technology eISSN: 2319-1163 | pISSN: 2321-7308
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IC-RICE Conference Issue | Nov-2013, Available @ http://www.ijret.org 404
ESTIMATION OF SURFACE RUNOFF IN NALLUR AMANIKERE
WATERSHED USING SCS-CN METHOD
Sindhu D1
, B L Shivakumar2
, A. S Ravikumar3
1, 2
Department of Civil Engineering, R. V. College of Engineering, Bangalore-560059
3
Department of Civil Engineering, UVCE, Bangalore University, Jnanabharathi, Bangalore-560056
sindhud@rvce.edu.in, shivakumarbl@rvce.edu.in, as_ravik@yahoo.com
Abstract
The development of watershed aims at productive utilization of all the available natural resources in the entire area extending from
ridge line to stream outlet. The per capita availability of land for cultivation has been decreasing over the years. Therefore, water and
the related land resources must be developed, utilized and managed in an integrated and comprehensive manner. Remote sensing and
GIS techniques are being increasingly used for planning, management and development of natural resources. The study area, Nallur
Amanikere watershed geographically lies between 110
38’ and 110
52’ N latitude and 760
30’ and 760
50’ E longitude with an area of
415.68 Sq. km. The thematic layers such as land use/land cover and soil maps were derived from remotely sensed data and overlayed
through ArcGIS software to assign the curve number on polygon wise. The daily rainfall data of six rain gauge stations in and around
the watershed (2001-2011) was used to estimate the daily runoff from the watershed using Soil Conservation Service - Curve Number
(SCS-CN) method. The runoff estimated from the SCS-CN model was then used to know the variation of runoff potential with different
land use/land cover and with different soil conditions.
Keywords: Watershed, Nallur watershed, Surface runoff, Rainfall-Runoff, SCS-CN, Remote Sensing, GIS.
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1. INTRODUCTION
A watershed is the area covering all the land contributes
runoff water to a common point. It is a natural physiographic
or ecological unit composed of interrelated parts and function.
Each watershed has definite characteristics such as size, shape,
slope, drainage, vegetation, geology, soil, geomorphology,
climate and land use. Watershed management implies the
proper use of all land and water resources of a watershed for
optimum production with minimum hazard to natural
resources. Runoff is one of the important hydrologic variables
used in the water resources applications and management
planning. Estimation of surface runoff is essential for the
assessment of water yield potential of the watershed, planning
of water conservation measures, recharging the ground water
zones and reducing the sedimentation and flooding hazards
downstream. Also, it is an important and essential prerequisite
of Integrated Watershed Management [7]. Remote Sensing
and GIS techniques are being increasingly used for planning,
development and management of natural resources. GIS in
particular help in integrating various data sets and perform
spatial analysis for decision making. GIS and remote sensing
are presently being used for solving environmental problems
like degradation of land by water logging, soil erosion,
deforestation, changes in ecological parameters and many
more. Jasrotia et al., [4] used a mathematical model to
estimate rainfall, runoff in conjunction with remote sensing
data and GIS using SCS CN method and runoff potential map.
Ashish Pandey et al., [1] estimated the runoff from SCS curve
number model modified for Indian condition by conventional
data base and GIS for Dikrong river basin. Amutha et al., [2]
showed that estimation of runoff by SCS-CN method
integrated with GIS can be used in watershed management
effectively. Somashekar et al.,[6] estimated surface runoff of
Hesaraghatta watershed. The analysis was carried using IRS-
ID LISS III satellite images in the form of FCC using SCS
curve number method and found that the runoff estimated by
SCS method shown reasonable good result.
2. STUDY AREA
The study area, Nallur Amanikere watershed is located in
Chamarajnagar district and geographically lies between 110
38'
and 110
52'
N latitude and 760
30'
and 760
50'
E longitude
covering an area of 415.68 Sq.km as delineated from Survey
of India (SOI) toposheet numbers 58A/9, 58A/10, 58A/13 and
58A/14 on 1:50000 scale. Maximum length and width of
watershed are 34.97 km and 21.91km respectively. Fig.1
shows the location map of the study area. The study area is
characterized by an undulating landscape and mountain ranges
covered with vast forests. The highest relief in the watershed
is found to be 1451 m and the lowest relief is 762 m above the
mean sea level. The overall relief of the watershed is found to
be 0.689 km. The area comprises of the land derived from
granite gneisses and charnockite. The soils in the watershed
are loamy skeletal, clayey skeletal, fine and fine loamy and

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isohyperthermic. Rainfall in the study area is highly erratic.
The average annual rainfall for 11 years (2001-2011) found to
be 839.7mm. Since the study area chosen is an ungauged
watershed an attempt was made to estimate runoff by SCS-CN
model, obtaining model parameters by integrating the thematic
maps prepared using SOI topomaps and remotely sensed data
on 1: 50,000 scale and analysing the thematic maps through
GIS software.
Fig.1 Location map of study area
3. METHODOLOGY
SOI toposheet numbers 58A/9, 58A/10, 58A/13 and 58A/14
on 1:50000 scale were used for delineating the watershed
boundary and preparation of base map, drainage map. In order
to know the different natural resources, terrain conditions, etc.
in the study area, toposheets along with the satellite data was
used to prepare different thematic maps, updation of drainage,
land use/ land cover, soil map. Fig. 2 shows the methodology
followed to estimate runoff using SCS Curve Number model.
Figs. 3(a), 3(b), 3(c) shows the drainage map, land use/ land
cover map, soil map of Nallur Amanikere watershed. Daily
rainfall data of six rain gauge stations in and around the
watershed for a period of 2001 to 2011 was used for
estimation of runoff. Runoff was estimated with the aid of
hydrological model using USDA (United States Department
for Agriculture) methodology for estimation of surface runoff
using SCS (Soil Conservation Service) Curve Number model.
3.1 SCS Curve Number Model
The curve number method (Soil Conservation Services, SCS,
1972) also known as the hydrologic soil cover complex
method, is a versatile and widely used procedure for runoff
estimation. This method includes several important properties
of the watershed namely soil permeability, land use and
antecedent soil water conditions which are taken into
consideration. To estimate the curve number, depth of runoff
the land use/land cover and hydrological soil group map
showing hydrologic soil groups prepared from IRS satellite
data were integrated.
Fig. 2 Methodology to estimate surface runoff by SCS CN
model

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Fig. 3 (a) Drainage map; (b) Land use/ land cover map;
(c) Soil map; (d) Hydrological Soil Group map of Nallur Amanikere watershed
3.2 Runoff Volume
Surface runoff is mainly controlled by the amount of rainfall,
initial abstraction and moisture retention of the soil. The SCS
curve number method is based on the water balance equation
and two fundamental hypotheses which are stated as, ratio of
the actual direct runoff to the potential runoff is equal to the
ratio of the actual infiltration to the potential infiltration, and
the amount of initial abstraction is some fraction of the
potential infiltration.
1
2
Substituting eq. (2) in eq. (1) and by solving;
3
a b
c d

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where, Q = actual runoff (mm), P = rainfall (mm), Ia = initial
abstraction, which represents all the losses before the runoff
begins and is given by the empirical equation
= 0.2 (4)
Substituting eq. (4) in eq. (3); the eq. (3) becomes
=
( − 0.2 )
( + 0.8 )
(5)
S = the potential infiltration after the runoff begins given by
following equation
=
25400
− 254 (6)
Where CN is Curve Number and estimated using antecedent
moisture condition and hydrological soil group.
3.3 Antecedent Moisture Condition (AMC)
Antecedent Moisture Condition (AMC) refers to the water
content present in the soil at a given time. It is determined by
total rainfall in 5 day period preceding a storm. The AMC
value is intended to reflect the effect of infiltration on both the
volume and rate of runoff according to the infiltration curve.
An increase in index means an increase in the runoff potential.
SCS developed three antecedent soil-moisture conditions and
labeled them as I, II, III, according to soil conditions and
rainfall limits for dormant and growing seasons. Classification
of Antecedent Moisture Condition is shown in Table 1.
Table 1 Classification of Antecedent Moisture Conditions (AMC)
3.4 Hydrological Soil Group (HSG) Classification
SCS developed soil classification system that consists of four
groups, which are identified as A, B, C, and D according to
their minimum infiltration rate. Table 2 shows the
hydrological soil group classification. CN values were
determined from hydrological soil group and antecedent
moisture conditions of the watershed. The Curve Number
values for AMC-I and AMC-II were obtained from AMC-II
(Chow et al. 1988) [3] by the method of conservation. Runoff
curve numbers (AMC II) for hydrologic soil cover complex
are shown in Table 3. Fig. 3(d) shows the Hydrological Soil
Group map of Nallur Amanikere watershed.
Table 2 Hydrological Soil Group Classification (Mc. Cuen, 1982) [5]
Soil
Group
Description
Minimum Infiltration
rate (mm/hr)
A
Soils in this group have a low runoff potential (high-infiltration rates) even
when thoroughly wetted. They consist of deep, well to excessively well-
drained sands or gravels. These soils have a high rate of water transmission.
7.62 - 11.43
B
Soils in this group have moderate infiltration rates when thoroughly wetted
and consists chiefly of moderately deep to deep, well-drained to moderately
well-drained soils with moderately fine to moderately coarse textures. These
soils have a moderate rate of water transmission.
3.81 - 7.62
C
Soils have slow infiltration rates when thoroughly wetted and consist chiefly
of soils with a layer that impedes the downward movement of water, or soils
with moderately fine-to fine texture. These soils have a slow rate of water
transmission.
1.27 - 3.81
AMC
Class
Description of soil condition
Total five day antecedent rainfall (mm)
Dormant season Growing season
I
Soils are dry but not to the wilting point; satisfactory
cultivation has taken place.
< 12.7 mm < 35.56 mm
II Average conditions. 12.7 - 27.94 mm 35.56 - 53.34 mm
III
Heavy rainfall or light rainfall and low temperatures
have occurred within last 5 days; Saturated soils.
> 27.94 mm 53.34 mm

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D
Soils have a high runoff potential (very slow infiltration rates) when
thoroughly wetted. These soils consist chiefly of clay soils with high swelling
potential, soils with a permanent high-water table, soils with a clay layer near
the surface, and shallow soils over nearly impervious material. These soils
have a very slow rate of water transmission.
0 - 1.27
Table 3 Runoff curve numbers (AMC II) for hydrologic soil cover complex
(Source: Chow et al, 1988)[3]
4. RESULTS AND DISCUSSION
The study area constitutes different land use/ land cover, about
4.56% of the area is occupied by agricultural plantation , 17.26
% of area is covered by forest , 67.94 % of area by crop land,
0.77% of area by fallow land and remaining 9.47% of the area
is occupied by others such as, water body, settlement, land
with scrub and tanks. In general, among the different land
cover types the crop land plays the major role for the direct
surface runoff. According to Drought monitoring cell (DMC)
Bangalore, the mean annual rainfall of the study area for the
period between 2001 and 2011 is 5018.50 mm with a
maximum rainfall of 7419.40 mm in 2005 and a minimum of
2455.20 mm in 2003. From SCS Curve number, the maximum
runoff for the watershed was estimated to be 1869.57 mm in
the year 2005 and minimum runoff of 263.68 mm in the year
2003. Table 4 shows the annual rainfall and runoff for Nallur
Amanikere watershed for the period 2001 to 2011. Fig. 4
shows the rainfall runoff relationship for Nallur Amanikere
watershed. The rainfall and runoff are strongly correlated with
correlation coefficient (r) value being 0.85.
Sl No. Land use
Hydrologic Soil Group
A B C D
1 Agricultural land without conservation (Kharif) 72 81 88 91
2 Double crop 62 71 88 91
3 Agriculture Plantation 45 53 67 72
4 Land with scrub 36 60 73 79
5 Land without scrub (Stony waste/ rock out crops) 45 66 77 83
6 Forest (degraded) 45 66 77 83
7 Forest Plantation 25 55 70 77
8 Grass land/pasture 39 61 74 80
9 Settlement 57 72 81 86
10 Road / railway line 98 98 98 98
11 River / stream 97 97 97 97
12 Tanks without water 96 96 96 96
13 Tank with water 100 100 100 100

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CONCLUSIONS
The estimation of runoff using GIS based SCS curve number
method can be used in watershed management effectively. All
the factors in SCS model are geographic in character. Due to
the geographic nature of these factors, SCS runoff model can
be easily molded into GIS. The study demonstrates the
importance of remotely sensed data in conjunction with GIS to
derive the model parameter to estimate surface runoff from the
ungauged watershed. Results obtained clearly shows the
variation in runoff potential with different land use/land cover
and with different soil conditions. Based on the digital
database creation, conservation techniques such as percolation
pond, check dam etc., can be recommended for better
management of land and water resources for sustainable
development of the watershed.
REFERENCES
[1] Ashish Pandey and Dabral. P.P. (2004), “Estimation of
Runoff for Hilly Catchment Using Satellite Data”,
Journal of Indian Society of Remote Sensing, Vol. 32,
No. 2, pp. 236-240.
[2] Amutha R, Porchelvan P (2009), “Estimation of
Surface Runoff in Malattar Sub-Watershed using SCS-
CN method”, Journal of Indian Society of Remote
Sensing, Vol. 37, pp.291-304.
[3] Chow, V. T., Maidment, D. R., and Mayse, W. (1988).
“Applied Hydrology”, New York:Mc Graw Hill.
[4] Jasrotia A. S., Dhiman S. D., and Aggarwal S. P.
(2002). “Rainfall-runoff and soil erosion modeling
using remote sensing and GIS technique – A case study
on tons watershed”, Journal of Indian Society of
Remote Sensing, Vol.30(3), pp. 167–180.
[5] Mc. Cuen, R. H. (1982). “A guide to hydrologic
analysis using SCS methods”, Englewood Cliffs:
Prentice Hall Inc.
[6] Somashekar R. K., Ravikumar P., Sowmya S. V.,
Mubhashir Aziz Dar, Ravikumar A. S., (2011) “Runoff
estimation and morphometric analysis for Hesaraghatta
watershed using IRS-ID LISS III FCC satellite data”,
Journal of Indian Society of Remote Sensing, Vol.
39,pp. 95-106.
[7] Subramanya K. (2008), “Engineering Hydrology”,
Publisher Tata McGraw Hill, 3rd edition, pp.139-195.
[8] USDA-SCS-CN Method (1972), “A Method for
Estimating Volume and Rate of Runoff in Small
watersheds”; SCS-TP-149, U.S. Department of
Agriculture, Soil Conservation Service, Washington,
DC.

Estimation of surface runoff in nallur amanikere watershed using scs cn method

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