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Parameter Uncertainty Analysis of Rainfall Runoff Model Using Monte-Carlo Method

Author(s): Praveen Rathod; V. L. Manekar

Linked Author(s): Praveen Rathod

Keywords: HEC-HMS; Monte-Carlo method; Sensitivity analysis; Rainfall runoff model

Abstract: In this study Monte-Carlo method of uncertainty analysis is used to perform uncertainty analysis of rainfall runoff model. HEC-HMS is used to simulate rainfall runoff process for the Panam catchment of Mahi River. Green-Ampt model is used to account for the infiltration loss. Penman-Montieth model is used to account for evaporation loss. Snyder method is used to account actual surface runoff. LISS III images are used in ArcG IS to delineate the catchment. Detailed process for basin delineation and forming river stream networks is explained using Arc GIS. Sensitivity analysis is being carried out on the model parameters and most sensitive parameters are being used for the uncertainty analysis. Mainly Green-Ampt parameters namely initial moisture content, saturated moisture content, suction head, conductivity and lag time are considered for the uncertainty analysis. Detail algorithm is developed for the Monte-Carlo method of uncertainty analysis and applied on the developed rainfall runoff model. For the Monte-Carlo method, Nash-Sutcliffe model efficiency coefficient is used as the objective function and it is maximized to increase predictive capability of the model. Total 1875model simulations are being carried. Out of 1875 model simulations, representative 12 model results by random selection are shown in this paper. By using Monte-Carlo methodology the model efficiency is increased from 75%to 90%and above. Application of Monte-Carlo method of uncertainty analysis for the study area shows the recommendation of the methodology in similar kind of problems.


Year: 2016

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