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An Uncertainty Analysis Procedure For Spatially Joint Simulations Of Multiple Attributes, Shoufan Fang, Guangxing Wang, George Z. Gertner, Alan Anderson

Conference on Applied Statistics in Agriculture

In this study, an uncertainty analysis procedure for joint sequential simulation of multiple attributes of spatially explicit models was developed based on regression analysis. This procedure utilizes information obtained from joint sequential simulation to establish the relationship between model uncertainty and variation of model inputs. Using this procedure, model variance can be partitioned by model input parameters on a pixel by pixel basis. In the partitioning, the correlation of neighboring pixels is accounted for. With traditional uncertainty analysis methods, this is not possible. In a case study, spatial variation of soil erodibility from a joint sequential simulation of soil properties …