A Data-Driven Framework for Efficient Water Quality Monitoring Using Spatiotemporal Autocorrelation and Value of Information
Seyed Abolfazl Ebrahimi1, Nicolas Fernandez2, Linus Schauer3, Aléxia Oliveira4, Harald Klammler5, Andreas Musolff3, Andrew A. Ali6, Arial J. Shogren6, James W Jawitz7 and Matthew J Cohen8, (1)University of Florida, Ft Walton Beach, FL, United States, (2)University of Florida, Department of Soil, Water, and Ecosystem Sciences, Ft Walton Beach, FL, United States, (3)Helmholtz Centre for Environmental Research UFZ Leipzig, Hydrogeology, Leipzig, Germany, (4)Federal University of Bahia, Salvador, Brazil, (5)Federal University of Bahia, Department of Geophysics, Salvador, Brazil, (6)University of Alabama, Department of Biological Sciences, Tuscaloosa, United States, (7)University of Florida, Department of Soil, Water, and Ecosystem Sciences, Gainesville, United States, (8)University of Florida, School of Forest, Fisheries, and Geomatics Sciences, Gainesville, United States