Water-Distance-Based Kriging in Chesapeake Bay

Abstract

The complex shapes of estuaries need to be considered when developing spatial interpolation methods for water quality analyses. In this study, a statistical interpolation method (kriging) is used to interpolate water quality data in Chesapeake Bay, and the issue of shape is addressed by incorporating “water distance” into the method (i.e., the shortest path over water between any two points). Results show that water-distance-based kriging performed just as well as, and in most cases better than, a kriging method based on Euclidean distance. Benefits of the water-distance-based method with kriging include improved estimates in regions with complex geometry and lower uncertainty in the kriging predictions.