Jat, P., Serre, M. I., , , , , , , , . 2016. Bayesian Maximum Entropy Space/Time Estimation of Surface Water Chloride in Maryland Using River Distances: Environmental Pollution. Elsevier, Ltd., . 219, . 1148-1155

Analysis, Modeling, Rivers, Road salt, Streams, Water quality, Chloride, De-icing, Winter maintenance

This study presents a spatiotemporal, geostatistical estimation framework (called Bayesian Maximum Entropy, BME), which uses river distances to estimate surface water chloride concentrations. The framework is demonstrated using nearly 10 years of data in three subbasins in Maryland (U.S.). The results show that this framework increases the cross-validation R-squared value by over 20% when compared to the original, Euclidian framework.