B8, 2012
1 Image Date
| Sciences.
08). Vegetation
ion of Western
thematical and
Australian soil
RO Publishing.
ment: An Earth
arson Prentice
Evaluating the
1tcrop wetlands
t region: Stage
vironment and
)5). "Detecting
thern Germany
al for Nature
J. & Harris, D.
ver the State of
roceedings 9th
try Conference.
dione, J. A. &
om high-spatial
t Valley Fever
onment, 106(1):
sing and Image
ac.
Data Online."
| technique for
Landsat data."
197-2203.
yrphic approach
egetatio, (118):
it surface water
e composites."
)46.
Monitoring the
sets on multi-
nment, 115(9):
International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume XXXIX-B8, 2012
XXII ISPRS Congress, 25 August — 01 September 2012, Melbourne, Australia
Runoff simulation using distributed hydrological modeling approach, remote sensing and GIS
techniques: À case study from an Indian agricultural watershed.
V.M.Chowdary"", V.R.Desai?, Mukesh Gupta?, A Jeyaram!, Y.V.N.K.Murthy?
'Regional remote Sensing Centre (East), NRSC, ISRO Kolkata, India -700156
Department of Civil Engineering, IIT, Kharagpur, India- 721302
*DDRC, National remote Sensing Centre, Hyderabad, India
*Corresponding author (chowdary_isro@yahoo.com; muthayya.chowdary@gmail.com)
Working Group, Theme: VIII/4:Water
Keywords: Distributed hydrological model, GIS, Remote sensing, Curve number, Muskingum-Cunge technique
ABSTRACT:
Distributed hydrological modeling has the capability of simulating distributed watershed basin
processes, by dividing a heterogeneous and complex land surface divided into computational
elements such as Hydrologic Response Units (HRU), grid cell or sub watersheds. The present study
was taken up to simulate spatial hydrological processes from a case study area of Kansavati
watershed in Purulia district of West Bengal, India having diverse geographical features using
distributed hydrological modelling approach. In the present study, overland flow in terms of direct
runoff from storm rainfall was computed using USDA Soil Conservation Services (SCS) curve
number technique and subsequently it served as input to channel routing model. For channel flow
routing, Muskingum-Cunge flood routing technique was used, specifically to route surface runoff
from the different sub watershed outlet points to the outlet point of the watershed. Model
parameters were derived for each grid cell either from remote sensing data or conventional maps
under GIS environment. For distributed approach, validation show reasonable fit between the
simulated and measured data and CMR value in all the cases is negative and ranges from -0.1 to -
0.3. Further, this study investigates the effect of cell size on runoff simulation for different grid cell
sizes of 23, 46, 92, 184, 368, 736, 1472 m resolution. The difference between simulated and
observed runoff values increases with the increase of grid size beyond 184 m more prominently.
Further, this model can be used to evaluate futuristic water availability scenarios for an agricultural
watershed in eastern India.
1. INTRODUCTION
Hydrological behaviour of any watershed can be predicted
through modeling. Particularly, the conversion of excess rainfall
into surface runoff is traditionally analyzed by means of lumped
models and these models assume that excess rainfall and
physiographical conditions over a watershed are uniform. Thus
errors can be introduced while simulating rainfall-runoff
process using lumped models. Hence to overcome this
difficulty, distributed modelling approach was proposed (Diksi
et al., 1984). This approach has the capability of simulating the
heterogeneity of both rainfall spatial distribution and catchment
characteristics, may offer a better approach for runoff
hydrograph simulation. Recent developments in the remote
sensing technology and geographical information systems make
It possible to capture and manage a vast amount of data of
spatially distributed hydrological parameters and variables.
Linking GIS and the hydrological modeling is very essential to
achieve the desired objectives. As distributed models are more
widely use in practice, the need of scientific principal relating to
spatial variability, temporal and spatial resolution, information
content and calibration become more apparent.
One of the most widely used techniques for estimating direct
runoff depths from storm rainfall is the United States
Department of Agriculture (USDA) Curve Number (CN)
method (SCS 1972). Greene and Cruise (1995) and Ponce and
Hawkins (1996) identified the CN method as one of the most
popular tools for calculating runoff depths. The description of
the flow process in the numerous distributed rainfall-runoff
models may be classified into two basic kinds (Beven, 1985).
One is the kinematic wave approach for simulating the overland
and channel flow (Abbott et al., 1986; Morris, 1980). The other
is the conceptual storage approach (Diskin et al., 1984; Beven et
al, 1984). Yu (1990) has a detailed literature review of the
distributed rainfall runoff models. The conventional
