Event-based rainfall–run-off modeling and uncertainty analysis for lower Tapi Basin, India

Abstract

Today, it is essential to use a hydrological model to assess and predict the water availability of river basins due to climate change. Event-based rainfall–run-off modeling is carried out using HEC-HMS. In the present study, linear imaging self-scanning sensor (LISS-III) satellite images are used to delineate the river basin using ArcGIS. Penman–Montieth model is used for the estimation of evapotranspiration loss. SCS-CN method and Snyder’s method are compared for the predictive capability. From the study, it is found that SCS-CN method is much suitable for the study area. Uncertainty analysis was carried out on SCS-CN parameters. In the present study, five events are considered for the period 2011–2014. Three events are used for the model development. Model is validated for the independent two events. The objective of the present study is to develop the rainfall–run-off model for the lower Tapi basin and carry out the uncertainty analysis. For the uncertainty analysis, Monte Carlo method adopted. Nash–Sutcliffe coefficient is used as an objective function, which is to be maximized. Results shows that curve number 85–90, initial abstraction 5–10 mm, and percentage impervious of about 5–10% are optimized parameter range values for study area under consideration.