Ijciet 10 01_180

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International Journal of Civil Engineering and Technology (IJCIET)
Volume 10, Issue 01, January 2019, pp. 1978-1998, Article ID: IJCIET_10_01_180
Available online at http://www.iaeme.com/ijciet/issues.asp?JType=IJCIET&VType=10&IType=01
ISSN Print: 0976-6308 and ISSN Online: 0976-6316
© 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 600119
S.Arsheya
Department of Civil Engineering, Sathyabama Institute of Science and Technology,
Jeppiaar Nagar, Rajiv Gandhi Salai, Chennai 600119.
V.K.Kirthika Sri
Department of Civil Engineering, Sathyabama Institute of Science and Technology,
Jeppiaar Nagar, Rajiv Gandhi Salai, Chennai 600119
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 152.81 sq km using Soil
Conservation Service Curve Number (SCS-CN) method and GIS. The estimated
amount average annual rainfall 1322.29mm 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. 1978-1998
http://www.iaeme.com/IJCIET/issues.asp?JType=IJCIET&VType=10&IType=01

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 in-
filtration 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 151.82 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.

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 1999 – 2013. 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 1999–2013
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 in-
filtration 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).

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

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
𝑃−𝐼𝑎+𝑆
(1)
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 =
25400
𝐶𝑁
− 254 (3)
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
𝑃+0.8𝑆
(4)
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 13-28
III Heavy Condition >28
To calculate CN(I), CN(II) and CN(III) [Chow et al.1988],

𝐶𝑁(𝐼𝐼) =
4.2𝐶𝑁(𝐼𝐼)
10−0.058 𝐶𝑁(𝐼𝐼)
(5)
𝐶𝑁(𝐼𝐼𝐼) =
23𝐶𝑁(𝐼𝐼)
10+0.13 𝐶𝑁(𝐼𝐼)
(6)
𝐶𝑁(𝐼) =
Σ𝐴.𝐶𝑁
Σ𝐴
(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).
Table 2 Soil Conversion Service Classification (USDA 1974) [USDA 1974]
Hydrologic Soil
Group (HSG)
Soil Texture
Runoff
Potential
Water
Transmission
Final
Infiltration
Group A
Deep, well drained sands
and gravels.
Low High Rate >7.5
Group B
Moderately deep, well
drained with Moderate.
Moderate Moderate Rate 3.8-7.5
Group C
Clay loams, shallow
sandy loan with
moderate to fine texture.
Moderate Moderate Rate 1.3-3.8
Group D
Clay soils that swell
significantly when wet.
High Low Rate <1.3

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 Km2
Implication of Potential
1 Nearly Level 33.76 Km2
Low surface runoff
2 Gentle 31.76 Km2
Low surface runoff
3 Moderate 46.69 Km2
Medium surface runoff
4 Steep 38.22 Km2
High surface runoff
5 Very Steep 11.78 Km2
High surface runoff

Figure 4 Puzhal Watershed - Slope Map
6. RESULTS AND DISCUSSIONS
The calculated curve numbers (CN) for normal, average and wet conditions are 77.93, 89.37
and 95.08 in Figure (7). The rainfall varies from 630 mm – 2396 mm (1999 - 2013) as shown
in Figure (6). The runoff varies from 285 mm – 4053 mm (1999 - 2013) as shown in Figure
(7).The average annual runoff calculated come to be 1311.21 mm Table (4) and average
runoff volume for fourteen years is 164,107,796,924 m2
. 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 0.944 Figure (9). For this study area, the relation was
found to be strongest linear.

Table 4 Annual average runoff depth and volume
Year Rainfall (mm) Runoff (mm)
1999 1005.2 720.19
2000 1256 635.53
2001 1429.6 817.016
2002 1077 574.83
2003 671.8 279.86
2004 1169.4 654.31
2005 2397.5 1705
2006 1326 748.01
2007 1455.4 782.81
2008 1755 1109.14
2009 1277 781.89
2010 1469.6 827.36
2011 1486 925.02
2012 941.3 524.04
2013 1117.6 526.91
Figure 5 Rainfall varies in Puzhal watershed

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

runoff represented is 61.6% of the total annual rainfall. Maximum rainfall and runoff
occurred in the year 2005 and Minimum in the year 2003. 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 77.93 for AMC - I, 89.37 – AMC-II and
95.08 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.
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