Modeled daily salinity derived from multiple machine learning methodologies and Generalized Additive models for three salinity monitoring sites in Mobile Bay, northern Gulf of Mexico, 1980–2021

Results from Generalized Additive models (GAM), Random Forest models (RFM), and Cubist models (CUB) for three Dauphin Island Sealab (DIS) operated salinity sites in Mobile Bay are reported in this data release. These sites included Meaher Park (DIS:MHPA1), Middle Bay Lighthouse (DIS:MBLA1), and Dauphin Island (DIS:DPIA1). The constructed models predicted a 40-year daily salinity record from 1980 to 2021 at each site based on incomplete imputed salinity records and several explanatory variables. Explanatory variables included: daily streamflow from 8 United States Geological Survey (USGS) streamgages, daily minimum and maximum temperature, precipitation, vapor pressure, wind speed, wind direction, horizontal and...

Categories: Data; Types: Map Service, OGC WFS Layer, OGC WMS Layer, OGC WMS Service; Tags: Cubist model, Dauphin Island Sea Labs, Dauphin Island Sea Labs, Generalized Additive model, Gulf of Mexico, All tags... Gulf of Mexico, Hydrology, Mobile Bay, Modeling, Random Forest machine learning model, Salinity, USGS Science Data Catalog (SDC), Fewer tags