Non-Euclidean Water Distance Based Interpolation for Increased Mapping of Coastal Water Clarity

Abstract

)Coastal regions are increasingly experiencing degraded water quality, affecting recreation, commerce, and human health. Water clarity in particular can have cascading impacts, from the function of the ecosystem itself (i.e., sea grass and phytoplankton growth) and either encouraging or deterring recreation. Here, we have applied a technique to expand the coverage of observations of water clarity by using non-Euclidean water distance-based kriging. Through many iterations and test configurations, the interpolation expands the spatial coverage of clarity estimates by multiple orders of magnitude with relatively high accuracy. Hold out data for validation of daily estimates of the diffuse attenuation coefficient, K d , had an R² =0.55 and a bias of 4%, while for Secchi depth R²=0.71 and bias was 4%. These new data products allow for the potential assimilation with models that utilize K d as a variable, integration with machine learning by gap filling in time and space, and providing labeled data for model calibration and validation.