Runoff estimation from a small watershed using GIUH approach in a GIS environment
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Date
2005-07
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G.B. Pant University of Agriculture and Technology, Pantnagar - 263145 (Uttarakhand)
Abstract
The conventional techniques of derivation of unit hydrographs require historical rainfall- runoff data. In a developing country like India, the most of the small watersheds are still ungauged; hence adequate runoff data are not generally available. For such type of catchments tedious procedure of regionalization of model parameters are sought. The research in the field of fluvial geomorphology of the problems facing the hydrologist today, in this regard the concept of geomorphologic instantaneous unit hydrograph (GIUH) has been introduced. Wherein the characteristics of instantaneous unit hydrograph are related to the geomorphological and climatic characteristics of the watershed. The major advantage of this approach is that this linking of geomorphologic parameters with the hydrologic characteristics of the watershed can lead to a simple and useful procedure to simulate the hydrologic behavior of various catchments, particularly ungauged ones.
In the present study the geomorphologic characteristics of Kothuwatari watershed, a sub-watershed of upper Damodar Valley, Hazaribagh, Jharkhand, India have been estimated from the toposheets 72H/7 and 72H/8 by using the GIS software ILWIS 3.0. The GIUH based Clark and Nash models have been used for the simulation of nine storm events. The direct surface runoff (DSRO) hydrographs derived by both the models have been compared with the observed DSRO hydrographs. The performance of the models for the study area has been evaluated by employing performance indices viz., (i) absolute relative error, (ii) Absolute percentage deviation in peak flow rates, (iii) coefficient of efficiency, (iv) absolute average error, (v) root mean square error and (vi) average error in volume. The results of the study showed that both the developed models provide a reasonably good estimate of direct surface runoff based on these performance indices. However it was difficult to conclude that which model performs better for the study area as based on percentage absolute deviation in peak and average error in volume, the GIUH based Clark model was found better while based on rest of the indices the GIUH based Nash model was found better.
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