USING GEOSTATISTICS TO SELECT GRID-CELL LAYOUTS FOR THE AGNPS MODEL

Abstract

Currently, little guidance is available for the design of accurate grid-cell layouts for spatially distributedmodels like the Agricultural Nonpoint Source Pollution (AGNPS) model. Inaccuracies in the grid-cell input could negatethe advantages provided by the spatially distributed approach to watershed (field) representation. The objective of thisstudy was to develop procedures for designing grid-cell layouts using geostatistical methods. Geostatistical spatialanalysis tools were used to select a base cell size and locate cell sub-divisions for use in AGNPS. The overall spatialcorrelation structure of SCS Curve Number data was used to select the base cell size. The specific criterion used to selectthe base cell size was the average squared residual of kriged estimates for randomly selected locations within the studyarea. The cell size with the minimum average squared residual was selected as the base cell size. Next, cells thatwarranted sub-divisions were identified using the squared residual of kriged estimates for each cell in the base cell layout.The grid-cell layout resulting from the application of the geostatistical methods and the squared residual criteria had anaverage squared residual less than the grid-cell representation without sub-divisions. Furthermore, the cells that weresub-divided fell within the most heterogeneous areas of the watershed. The geostatistical methods provided quantitativeinformation about the error associated with various grid-cell designs. This information was then used to design accurategrid-cell layouts that preserved the spatial heterogeneity of the original data. Further development and application of thegeostatistical methods used to design grid-cell layouts will lead to greater improvements in the simulation accuracy ofspatially distributed models including AGNPS.