Daily rainfall-runoff modeling for Gundlakamma basin of Andhra Pradesh – A research report by National Institute of Hydrology

The study applies a simple five-parameter model to simulate the daily runoff over a nine-year period of 1989-1997 at Tamavaram in Prakasham district of Andhra Pradesh on the Gundlakamma river.
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The study applies a simple five-parameter model based on the concept of probability distributed method as proposed by Moore (1985) to simulate the daily runoff over a nine-year period of 1989-1997 at Tamavaram in Prakasham district of Andhra Pradesh on the Gundlakamma river.

Modeling of catchment response using monthly data does not serve the needs of most applications. At the same time, use of sufficiently fine data interval to catch the complete temporal variations of observed flows is impractical.

Conceptual modeling is a way of undertaking hydrological modeling wherein mathematical representation of physical processes is employed with specific inputs to derive the output. The process is simplified by utilizing the concepts of physics to describe the land phase of hydrological cycle in space and time. Conceptual models with a few parameters are being preferred for quick and effective modeling.

The model is based on Moore’s probability distributed technique and has a soil moisture store with a capacity varying across the basin and a groundwater store. It consists of a number of stores with model parameters controlling the store sizes and rate of outflow. It uses the conceptualization of flow processes with inputs of daily rainfall and pan evaporation to generate runoff.

New techniques are being applied since 1990s in solving analytical problems of rainfall-runoff modeling on the readily accessible personal computers. In this study a program in Fortran 77 has been developed to undertake automatic optimization of the model to simulate the observed flows using a proper objective function.

Through the calibration and validation of the study, it is found that the model, through a five-parameter representation, could respond properly to the rainfall and resulted in a reasonable efficiency of 72.14 % in calibration and 68.25 % in validation. 

Download the report here:

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