Datasets

Subject
Creator
Type
Date

subject: Hydrology type: dataset

Total is 55 Results
gSSURGO-based Floodplain Maps of Wisconsin

10.4231/R7D21VKD

Liuying Du , Nikhil Sangwan , Venkatesh Mohan Merwade ORCID logo

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

gSSURGO-based Floodplain Maps of West Virginia

10.4231/R7HT2M8C

Liuying Du , Nikhil Sangwan , Venkatesh Mohan Merwade ORCID logo

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

gSSURGO-based Floodplain Maps of Wyoming

10.4231/R78C9T7D

Liuying Du , Nikhil Sangwan , Venkatesh Mohan Merwade ORCID logo

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

Monitored soil moisture and temperature in Indiana crop rotated field

10.4231/FM0P-AJ03

Keith A Cherkauer ORCID logo , Laura C Bowling ORCID logo , 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

Data for Analyzing the Effect of Data Splitting and Covariate Shift on Machine Leaning Based Streamflow Prediction in Ungauged Basins

10.4231/0PG5-KC30

Pin-ching Li , Sayan Dey ORCID logo , Venkatesh Mohan Merwade ORCID logo

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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