LONG TERM HYDROLOGIC SIMULATION USING SCS-CN METHOD

Abstract

A model capable of' simulating runoff response of the catchrncnt resulting from long term rainfall data could be used as an essential tool for the study of quantitative and qualitative assessment of stream flow and water resource management. In the present study. a new simplified continuous long term hydrologic simulation (L'I'l-IS) model is developed based on the SCS-CN method to simulate the daily stream flow of the catchment. The proposed model incorporates different modules for surface and sub-surface flow components such as surface runoff, evapotranspiration. sub-surface drainage and base flow. It operates on daily time step with daily rainfall as the only input data and computes the total stream flow of the catchment as the sum of surface runoff and base flow. To test the applicability of the proposed L'I'HS model, it is applied to the daily rainfall and runoff' data of seven different catchments lying under different agro-clirnatic zones of India and its performance was quantitatively evaluated using the different statistical evaluation criteria such as Nash-Sutcliffe coefficient of efficiency (NSF), relative crroi' (RE) and standard error (SE). Based on the analysis of results obtained from the study, it is found that the proposed model gives satisfactory efficiency for all the study catchments except for the dry I lirchalla catchment. for which NSF is very poor. It is also observed that the model performed best on wet 1-lemavati catchment with a high value of NSF for both the calibration and validation period. Also, when compared to the existing Ll'l-IS ASMA model (Durbude et al. 201 1). the proposed model yields overall improved NSE and lower SE values for all the study catchments, thus indicating the better performance of the proposed model. The results of the proposed model is also farther analyses to identify the dominant/dormant process involved in catchment runoff generating mechanism and for which it is observed that the surface runoff and base flow are the most dominant process for all the study catchment expect for dry liridaynagar and Ilirehalla catchment in which evapotranspiration is the most pre-dorninant process. l'he sensitivity analysis carried out to identify the sensitivity of parameters to model output also shows that the model parameters such as field capacity (Oi) and coefficient of evapotranspiration (P) are the most highly sensitive among all the parameters and slight change in their value results in large changes in the computed runoff'. The next highly sensitive parameters are the initial curve number (CN(j). wilting point (0) and subsurface drainage coefficient (P2) with the parameters storage coefficient (K) and coefficient of antecedent moisture () among the least sensitive. And the remaining other parameters like a, 'I't To and Eg are less sensitive in most of the study catchments and thus it does not contribute much significant errors in runoff estimation.