The present study is carried out using the NRCS- CN methodology. This model uses, antecedent moisture condition, land use and soil type as the major input. For the calculation of runoff, daily rainfall data for 15 rain gauge stations were collected from the Institute for Water Studies, Public Works Department, Government of Tamil Nadu, Chennai, Tamil Nadu. The soil data is derived from the National Bureau of Soil Survey and Land Use Planning. The Land use and Land cover is analysed by remote sensing data. Accordingly, the Runoff is given by
![](data:image/png;base64,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)
Which is expressed in unit depth spread over the watershed and where Q = runoff in mms, P is Depth of precipitation over the entire watershed, S = maximum potential retention, and Ia is the initial abstraction. The Ia is the lose of water before the runoff begins, and includes the water collected in the depressions and absorbed by vegetation, and lost through evaporation and infiltration. Ia varies with the type of terrain and soil characteristics. USDA (1956) has given out the relationship between Ia and S as
Ia= 0.2S
Rao et al., (2010) has revised this relationship to suit the Indian conditions and has expressed it as
Ia= 0.3S
Substituting this value in the equation, it can be revised as
![](data:image/png;base64,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)
Where S is related to CN, and is a function of HSG (Hydrological Soil Group) and AMC (Antecedent Moisture Condition). The Curve Number is a dimensionless feature and its value varies from 0 to 100. Patila et al., 2008 derived the value of S as
![](data:image/png;base64,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)
a. Hydrological Soil Group (HSG)
To understand the properties of infiltration, USDA (1986) has developed a classification system, where the soils are categorized into 4 groups namely A, B, C, and D. Soils were assigned different grouping based on measured rainfall, runoff and infiltrometer data (Musgrave,1955). The classes are based on intake and transmission of water under the conditions of maximum yearly wetness, soil not frozen, bare soil surface and maximum swelling of expensive clays. The following table explains the different soil groups.
Table I: Hydrological Soil Groups and its characteristics
Soil Groups
|
Soil Characteristics
|
A
|
Low runoff potential when thoroughly wet, water transmitted freely, < 10% clay &>90% sand or gravel. Texture: - sand, gravel, loamy sand, sandy loam, loam or silt loam. Saturated hydraulic conductivity exceeds 40.0 micrometers/second, depth to water permeable layer- >50cm, depth to water table > 60cm.
|
B
|
Moderately low runoff potential when thoroughly wet. Water transmission unimpeded. Clay between 10% & 20%. Sand between 50% & 90%. Texture: - loamy sand, sandy loam, sandy clay loam. Saturated hydraulic conductivity- between 10.0–40.0 micrometer/second.
|
C
|
Moderately high runoff potential when thoroughly wet. Clay between 20% & 40%. Sand < 50%. Texture: - loam, silt loam, sandy clay loam, clay loam and silt clay loam. Saturated hydraulic conductivity- between 1.0–10.0 micrometer/second.
|
D
|
High runoff potential when thoroughly wet, water movement restricted or very restricted. Clay > 40% and Sand- < 50%. Saturated hydraulic conductivity less than or equal to 1.0 micrometer / second.
|
Source : USDA, Hydrology National Engineering Handbook, 2007. |
b. Antecedent Moisture Conditions (AMC)
AMC refers to the moisture content present in the soil at a given period of time. It is determined by the amount of total rainfall in 5-day period preceding a rainfall event (McCuen, 1982). Three AMC conditions (AMC I, II & III) are identified by USDA (1986) based on different soil conditions and rainfall limits for dormant and growing seasons. Low, medium and high runoff potentials are respectively indicated by AMC I, II and III conditions.
Table II: Antecedent Moisture Conditions and its corresponding Soil Groups
AMC
|
Soil Characteristics
|
5-day total Rainfall (mm)
|
Dormant Season
|
Growing Season
|
I
|
Soils dry, but not to wilting point.
|
< 13
|
< 36
|
II
|
Average moisture condition.
|
13–28
|
36–53
|
III
|
Heavy or light rainfall and low temperature occurred within last 5 days, soil is saturated.
|
> 28
|
> 53
|
Source: Source: USDA, Hydrology National Engineering Handbook, 2007. |
Based on all these the CN value can be estimated for different AMC classes. As a standard rule, these values are first applied to AMC II and then it is extended to AMC I and III.
![](data:image/png;base64,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)
Accordingly, Rao et al.(2010) revised the form CN formula as follows:
![](data:image/png;base64,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)
Where, CNi is the curve number for LU-HSG class,
A is the area of each class and
N is the number of LU-HSG polygons.
Table III: Curve Number for corresponding LULC& HSG class of the watershed
LU/LC CLASS
|
HSG NUMBER
|
A
|
B
|
C
|
D
|
Settlement
|
48
|
66
|
78
|
83
|
River and stream
|
90
|
94
|
98
|
100
|
Barren/wasteland
|
64
|
75
|
83
|
85
|
Crop land
|
67
|
78
|
85
|
89
|
Degraded forest
|
-
|
72
|
80
|
87
|
Dense forest
|
-
|
67
|
77
|
83
|
Fallow land
|
76
|
86
|
90
|
93
|
Land with scrub
|
48
|
67
|
77
|
83
|
Open forest
|
|
79
|
86
|
89
|
Plantation
|
65
|
73
|
79
|
81
|
Land without scrub
|
-
|
66
|
77
|
-
|
Source: USDA, 1986 & Rao et al., 2010 |
Land use/ land cover and its changes were analysed for the year 2016. The image used for the LU/LC analysis was obtained from LANDSAT 8 (Operational Land Imager & Thermal Infrared Sensor). The date of the acquired image is 02.03.2016. The errors related to geometry and the brightness of the pixels values were rectified using image enhancement technique. Redistributing the pixel value is done by histogram equalisation, which is a non linear stretching method. This helps in flattening the histogram by increasing the contrast at the peaks and reducing at the tails (Rao et al., 1989). The next step is the classification of the image, by labelling a pixel based on its grey value and grouping them on the basis of their spectral signature. This present study is based on supervised classification done in ERDAS Imagine 2014. The LU/LC classes were derived based on NRSC level 2 classification, with slight modifications to suit the local environment. For the present study, 11 LULC classes have been identified in the watershed, based on the modified NRSC level two classification system. The major land use types found in Vannathangarai watershed are Built up, Dense forest, Degraded Forest and Open Forest, coming under Forest Class, water bodies, land with and without scrub and barren wasteland coming under Waste land class, Plantation, cropland and fallow land under agriculture.