158
R. Murmu and S. Murmu
indirect manner. For estimation of quantity and rate of the surface runoff accurately
from land surface into streams and rivers is difficult and time consuming. The estimated runoff can be used further to assess the likelihood and aspects of flooding. The
manner in which different variables affecting runoff interacts with time and space
makes the direct determination of runoff very difficult. Therefore, we estimate runoff
using methods that reflect the combine effect of the variables on an individual catchment. The conventional methods of predicting runoff can be augmented by incorporation of satellite imaging technology in the field of hydrology. Remote sensing technology is the most reliable and potent technique to derive spatial information on land
use, soil, vegetation, drainage, etc., from satellite data which can be used to interpret
runoff. These data can be incorporated with the conventionally measured topographic
and climatic parameters like precipitation and temperature to contribute the rainfallrunoff models as inputs. Additionally, Geographical Information System (GIS) is a
powerful tool for input of remotely sensed data into database, further processing and
retrieval of selected information which can analyze/manipulate the data to generate
useful spatial information on specific format. Thus, the emergences and advances
of remote sensing and GIS in a combined manner can provide a new perspective to
rainfall-runoff studies. This paper aims to simulate runoff for Subarnarekha catchment using Soil and Water Assessment Tool (SWAT) Model. This model is capable
of forecasting the possible impacts of climate change, and the effects that cause
changes on water resources due to human activities, in form of both quantity and
quality [1]. GIS-based ArcSWAT model has been used for simulation of runoff with
the required weather parameters of 30 years with a good correlation coefficient result
[2]. Development of watershed simulation models with reliable accuracy including
calibration and validation of the results is a challenging task [3]. Accurately validated
SWAT Models can be useful for decision making problems for watershed planning
[4]. This model can also help in predicting hydrologic variables like coefficient of
runoff, baseflow and evapotranspiration as well as comparative analysis with the
observed data can be done after successful outcome [5]. Performances of SWAT and
Xinanjiang (XAJ) models have been compared using ten year daily runoff data from
four different gauging stations, which shows reasonably good runoff simulation from
both the models [6].
2 Materials and Methods
2.1 Area Under Study
The present study has been conducted for the upper part of Subarnarekha river basin
which is a part of the Chotanagpur River system, a plateau in the eastern part of
India. The river Subarnarekha originates near Nagri village in the Ranchi district and
flows over the states of Jharkhand, West Bengal and Odisha before joining the Bay
of Bengal. The river is having a total catchment area of 18,951 km
2 surrounded by
R. Murmu and S. Murmu
indirect manner. For estimation of quantity and rate of the surface runoff accurately
from land surface into streams and rivers is difficult and time consuming. The estimated runoff can be used further to assess the likelihood and aspects of flooding. The
manner in which different variables affecting runoff interacts with time and space
makes the direct determination of runoff very difficult. Therefore, we estimate runoff
using methods that reflect the combine effect of the variables on an individual catchment. The conventional methods of predicting runoff can be augmented by incorporation of satellite imaging technology in the field of hydrology. Remote sensing technology is the most reliable and potent technique to derive spatial information on land
use, soil, vegetation, drainage, etc., from satellite data which can be used to interpret
runoff. These data can be incorporated with the conventionally measured topographic
and climatic parameters like precipitation and temperature to contribute the rainfallrunoff models as inputs. Additionally, Geographical Information System (GIS) is a
powerful tool for input of remotely sensed data into database, further processing and
retrieval of selected information which can analyze/manipulate the data to generate
useful spatial information on specific format. Thus, the emergences and advances
of remote sensing and GIS in a combined manner can provide a new perspective to
rainfall-runoff studies. This paper aims to simulate runoff for Subarnarekha catchment using Soil and Water Assessment Tool (SWAT) Model. This model is capable
of forecasting the possible impacts of climate change, and the effects that cause
changes on water resources due to human activities, in form of both quantity and
quality [1]. GIS-based ArcSWAT model has been used for simulation of runoff with
the required weather parameters of 30 years with a good correlation coefficient result
[2]. Development of watershed simulation models with reliable accuracy including
calibration and validation of the results is a challenging task [3]. Accurately validated
SWAT Models can be useful for decision making problems for watershed planning
[4]. This model can also help in predicting hydrologic variables like coefficient of
runoff, baseflow and evapotranspiration as well as comparative analysis with the
observed data can be done after successful outcome [5]. Performances of SWAT and
Xinanjiang (XAJ) models have been compared using ten year daily runoff data from
four different gauging stations, which shows reasonably good runoff simulation from
both the models [6].
2 Materials and Methods
2.1 Area Under Study
The present study has been conducted for the upper part of Subarnarekha river basin
which is a part of the Chotanagpur River system, a plateau in the eastern part of
India. The river Subarnarekha originates near Nagri village in the Ranchi district and
flows over the states of Jharkhand, West Bengal and Odisha before joining the Bay
of Bengal. The river is having a total catchment area of 18,951 km
2 surrounded by