Validation, uncertainty and sensitivity analysis of crop growth simulation model for Barind in Bangladesh

Abstract

A combined weather generator and crop growth model has been built (Rahman, 1998). This is based on the EPIC model (Sharpley and Williams, 1990). Crop growth simulation model have become very complex. The behavior of some of these models may only be explored by uncertainty and sensitivity analysis, because the structural complexity of the model are coupled with a high degree of uncertainty in estimating the values of the input parameters. Uncertainty analysis may be used to assess the variability in the outcome variable that is due to the uncertainty in estimating the input values. A sensitivity analysis can extend an uncertainty analysis by identifying which parameters are important in contributing to the variability. In this paper an uncertainty and a sensitivity analysis are describeu and applied; both analysis are based upon the Latin Hypercube Sampling (LHS) techniques, which is extremely efficient sampling design proposed by McKay, Conover and Beckman (1979). The utility of the LHS uncertainty and the LHS/PRC (Latin Hypercube Sampling/Partial Rank Correlation) sensitivity analysis techniques are illustrated by analysis a complex crop growth simulation model. The model have been validated by comparing simulated and measured yield of transplanted Aman rice for,Barind region.