Modelling runoff using modified SCS CN method for middle South Saurashtra region Gujarat India

Abstract

The runoff generation process is highly complex, nonlinear, dynamic in nature, and affected by many interrelated physical factors. Further, the temporal and spatial variability of these factors causes more uncertainty in the parameterization of the model. Therefore, modelling the runoff becomes more challenging task. However, with present technological capabilities, computing techniques and software tools, it is possible to identify, assess and understand the response of the dominant processes rather accurately. Accurate runoff estimation is prerequisite for effective management and development of water resources. Many methods are being used to estimate runoff in literature; however, the SCS-CN method still remains the most popular, fruitful and frequently used method. The major reasons for this popularity may be attributed to ease of use, less number of input parameters, robustness of model results, and acceptability among both researcher and practitioner community.Runoff curve number (CN) is a key factor of the SCS-CN method and it is a function of land use/land cover (LULC), soil type, and antecedent soil moisture. The attractive feature of the SCS-CN method is that it integrates the complexity of runoff generation into single parameter, i. e. CN. However, lumped conceptual approach and simplicity of a single parameter introduces great uncertainty to estimate runoff in practical applications. The CN is usually selected from available standard tables in the National Engineering Handbook, Section-4 (NEH-4) as well available curves; but, this procedure is very tedious, laborious, and time consuming. It was further observed that large errors can be expected in surface runoff estimation where, the validity of the hand book tables for the CN was not verified. The SCS-CN method does not adequately model all of the important physical processes of runoff generation viz. impact of land use changes, accumulation of moisture, morphometric parameters, and long term evapotranspiration loss.