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Research Papers

GIUH based Clark and Nash models for runoff estimation for an ungauged basin and their uncertainty analysis

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Pages 281-290 | Received 14 Dec 2004, Accepted 14 Dec 2004, Published online: 23 Aug 2010
 

Abstract

Runoff estimation is an important aspect of river basin planning, development and management. Geomorphological instantaneous unit hydrograph (GIUH) approach holds a great potential for estimation of runoff from ungauged basins because of its direct application to ungauged basins, without going for cumbersome procedure of regionalization. In this study, GIUH is derived from the geomorphological characteristics of a basin and it is related to the parameters of the Clark instantaneous unit hydrograph (IUH) model as well as Nash IUH model for deriving its complete shape. The developed GIUH based Clark and Nash models are applied for simulation of the direct surface runoff (DSRO) hydrographs for ten rainfall‐runoff events of the Ajay basin upto Sarath gauging site of eastern India. The geomorphological characteristics of the Ajay basin are evaluated using the GIS package, Integrated Land and Water Information System (ILWIS). A comparison of the performances of the GIUH based Clark and Nash models in simulating the DSRO hydrographs by employing some of the commonly used error functions reveals that the DSRO hydrographs are computed with reasonable accuracy by both the models, which simulate the DSRO hydrographs of the basin considering it to be ungauged. The relative sensitivity and the degree of uncertainty associated with each of the input parameters of the GIUH based Clark and Nash models have been quantified. The uncertainty analysis reveals that apart from the velocity (V) parameter, the length of the highest order stream (LO) is the only geomorphological parameter which results in higher degree of uncertainty in derivation of unit hydrograph using the GIUH based Clark and Nash models, and hence, it is to be evaluated with greater precision for accurate runoff estimation from ungauged basins.

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