Role of Remotely Sensed Data
The land cover maps derived by remote sensing are the
basis of hydrologic response units for modelling units. For an understanding of
the hydrology of areas with little available data, a better insight into the
distribution of the physical characteristics of the catchments is provided by
image processing techniques. Some of the new measurement methods (photographic
systems, active radar systems etc.) could yield assessment of areal distribution
or atleast to some extent reliable areal totals or averages of hydrologic
variable such as precipitation, evapotranspiration and soil moisture. Some of
the main hydrological application field of remote sensing are:
- Spatial rainfall patterns
- Evaporation and soil moisture
- Snow cover extent
- Groundwater
- Topography
- Water Bodies
- Vegetation
GIS Applications
Since, GIS does not directly land itself to time varying studies, its features are utilised in hydrological studies by coupling it with hydrological models. Two types of approaches are possible for this purpose. In the model driven approach, a model or set of models is defined and thus the required spatial (GIS) input for the preparation of the input data and output maps. The other approach is the data driven approach. It limits the input spatial data to parameters which can be obtained from generally available maps, such as topographic maps, soil maps etc. The possibility of rapidly combining data of different types in a GIS has led to significant increase in its use in hydrological applications. It also provides the opportunities to combine a data from different sources and different types. One of the typical applications is use of a digital terrain model (DTM) for extraction of hydrologic catchment properties such as elevation matrix, flow direction matrix, ranked elevation matrix, and flow accumulation matrix.
Application of TOPMODEL
Calibration and validation of the TOPMODEL was carried out on Hemavati catchment situated in Western Ghats. Raster DEM input for the model is generated through ILWIS after digitization contour map from Survey of India toposheets. In all 5 years of data was available for simulation study. Available data series was broken in two parts and first part i.e. June 1975-December 1977 was used for model parameter calibration and remaining data series i.e. January 1978 to December 1980 was used for model validation. Simulation results are encouraging. Model efficienty was more than 0.84 both for model calibration and validation on independent data series.
The TOPMODEL has been applied to Malaprabha catchment in Karnataka to simulate the daily flows at Khanapur. River Malaprabha is a tributary of river Krishna. The catchment area of Malaprabha upto discharge measuring site Khanapur is 520 Sq. Km. The model uses topographic index for the formation of runoff. The topographic index for Malaprabha catchment was derived by developing a Digital Elevation Model (DEM) by interpolating the contours in the basin at 300 m grid size.The results indicate that the model can be used to simulate the flows in the catchment quite accurately (the efficiency of the model is 0.89 and 0.79 respectively in calibration and validation run).
Application of SHE model for sub-basins of river Narmada
The distributed and physically based nature of the SHE requires that in each application study a vast amount of data and parameters describing the physical characteristics of the catchments are available. This includes data for catchment geometry, land use and soil parameters, surface flow characteristics and input data of rainfall, evapotranspiration, stream flow etc. The data handling package of the SHE Model has therefore been organised on the lines of a typical GIS format. A brief processor package produces maps of spatially distributed data and enables an automatic setup of input data for the SHE at a desired grid square scale. Digitised data such as contour lines from toposheets are transformed to average elevation values compatible with the chosen grid square size. Also soil land-use maps are digitised and codes attached to each type are allocated to each grid square. The SHE model was applied to six sub-basins of river Narmada namely - Kolar, Barna, Sher, Ganjal, Hiren and Narmada upto Manot. The SHE model has been found to be successful for modelling the rainfall, runoff process in these sub-basins within data availability constraint. These studies have also provided useful guidelines for carrying out systematic field investigations for determination of various parameters for application of a physically based modelling approach.
Typical studies were also carried out for Kolar basin to consider the effect of changes in soil depth, soil properties, vegetation, surface roughness characteristics etc. on water yield from the catchment. Some simple studies for hypothetical irrigation systems were carried out for Barna basin. These clearly demonstrated capabilities of physically based distributed models using spatial information in typical GIS type framework.
Discussion
Until very recently,
GIS was a tool for managing and analysing spatial data and hydrologists were
collecting their own data and sharing it in a format specific to the model they
worked with. The integration of these two technologies began slowly as GIS was
used to perform overlays of basin characteristics for further analysis by
FORTRAN programme or a statistical package. However, now significant
developments have already taken place for the integration of GIS and
hydrological modelling. The basin characteristics for use in hydrological
modelling is now being readily derived from digital elevation models. GIS is a
valuable tool for use in parameterization for large scale physically based
distributed models and significant developments in this area are taking place.
These would result in corresponding increase in operational use of such models.
There is however, need for considerable efforts to obtain representative
hydrological data and information for use in such applications.