10.4231/R7NK3C03
Liuying Du , Nikhil Sangwan , Venkatesh Mohan Merwade
07/22/2016
This dataset provides a shapefile showing the natural floodplain for Washington. These floodplain polygons for the entire state are extracted from the gSSURGO soil data from the Natural Resources Conservation Service (NRCS).
biota Environment floodplain maps Forestry and Natural Resources Geographic Information Systems (GIS) geoscientific gSSURGO soil Data Hydrology inland water shapefile Washington
10.4231/R7D21VKD
Liuying Du , Nikhil Sangwan , Venkatesh Mohan Merwade
07/22/2016
This dataset provides a shapefile showing the natural floodplain for Wisconsin. These floodplain polygons for the entire state are extracted from the gSSURGO soil data from the Natural Resources Conservation Service (NRCS).
biota Environment floodplain maps Forestry and Natural Resources Geographic Information Systems (GIS) geoscientific gSSURGO soil Data Hydrology inland water shapefile Wisconsin
10.4231/R7HT2M8C
Liuying Du , Nikhil Sangwan , Venkatesh Mohan Merwade
07/22/2016
This dataset provides a shapefile showing the natural floodplain for West Virginia. These floodplain polygons for the entire state are extracted from the gSSURGO soil data from the Natural Resources Conservation Service (NRCS).
biota Environment floodplain maps Forestry and Natural Resources Geographic Information Systems (GIS) geoscientific gSSURGO soil Data Hydrology inland water shapefile West Virginia
10.4231/R78C9T7D
Liuying Du , Nikhil Sangwan , Venkatesh Mohan Merwade
07/22/2016
This dataset provides a shapefile showing the natural floodplain for Wyoming. These floodplain polygons for the entire state are extracted from the gSSURGO soil data from the Natural Resources Conservation Service (NRCS).
biota Environment floodplain maps Forestry and Natural Resources Geographic Information Systems (GIS) geoscientific gSSURGO soil Data Hydrology inland water shapefile Wyoming
10.4231/FM0P-AJ03
Keith A Cherkauer , Laura C Bowling , Stuart D Smith
11/23/2020
Soil moisture and temperature data were collected at five different depths from October 2017 to September 2020 in a crop rotated field.
Agricultural and Biological Engineering Agriculture Environment Hydrology Indiana Soil Moisture Soil Temperature Time Series Climate Data
10.4231/0PG5-KC30
Pin-ching Li , Sayan Dey , Venkatesh Mohan Merwade
01/23/2023
This resource contains the data used in the study "Analyzing the Effect of Data Splitting and Covariate Shift on Machine Leaning Based Streamflow Prediction in Ungauged Basins" published in Water Resources Research (doi: 10.1029/2023WR034464)
Artificial Neural Network (ANN) covariate shift Hydrology Machine Learning prediction in ungauged basin Random Forest streamflow prediction
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