REGRESSION ANALYSIS OF RAINFALL AND RUNOFF PROCESS OF A TYPICAL WATERSHED

The integration strategy for a watershed can be carried out by various procedures. However a first step is usually a resource survey or inventory. This attempts to answer the question of the supply and demand for resources both natural and human resources. Depending upon the area involved, a survey may include socio-economic characteristics, soil characteristics, land capacity/suitability classifications, hydrological assessment including climate characteristics, water use and other parameters as needed. Runoff is one of the important integral part of the integrated watershed management, so for this estimation of runoff is required. The rainfall-runoff process in a catchment is a complex and complicated phenomenon governed by large number of known and unknown physiographic factors that vary both in space and time. Application of mathematical modeling techniques to the constituent processes involved in the physical processes of runoff generation has led to better understanding of the processes and their interaction. Conventional hydrological models for the prediction of runoff particularly over a basin require considerable hydrological and meteorological data. Collection of these data is expensive, time consuming and difficult process. Remote Sensing technology and Geographical Information Systems (GIS) can augment the conventional methods to a great extent in rainfall runoff studies. Remote Sensing technology and Geographical Information Systems (GIS) can augment the conventional methods to a great extent in rainfall runoff studies. In the present study a small agricultural watershed rainfall-runoff model was chosen. The advantage of formulating this regression analysis for the watershed is that it enables to generate the runoff. Once the regression analysis is formulated the same can be applied to any watershed to estimate the runoff, even if the sub catchment is ungauged. Keeping these points in view, the rainfall-runoff model, regression nalysis has been formulated and developed. It contains three modules namely Time of Concentration, Rainfall and Soil Moisture module for the estimation of daily runoff. Pamena – I Watershed, Chevella Mandal, Rangareddy District, Andhra Pradesh, India has been considered for the study. It is concluded that the regression analysis developed is a fairly good model and it is comparable with the standard models considered in the present study viz., SCS-CN and TR-55 Models.