Datasets

subject: Soil Moisture

Total is 7 Results
Monitored soil moisture and temperature in Indiana crop rotated field

10.4231/7NSM-JJ67

Keith A Cherkauer ORCID logo , Laura C Bowling ORCID logo , Stuart D Smith

12/18/2019

Soil moisture and temperature data were collected at five different depths from October 2017 to September 2019 in a crop rotated field.

Agricultural and Biological Engineering Agriculture Environment Hydrology Indiana Soil Moisture Soil Temperature Time Series Climate Data

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

Multi-Year Study Maize Agrivoltaics Soil Moisture Data

10.4231/M2Z8-NT18

Geoffrey Alistair Sanchez ORCID logo , Peter Bermel ORCID logo

03/07/2024

Volumetric water content (m^3/m^3) data for agrivoltaic experimental setup. Here will also be the data which was inputed based off a k-fold Bayesian Regularization Neural Network.

agrivoltaics Bayesian Regularization Neural Network Maize Soil Moisture

A Hybrid Physics-Guided Deep Learning Modeling Framework for Predicting Surface Soil Moisture

10.4231/NR0B-EJ07

Qianlai Zhuang ORCID logo , Xinyu Liu , Xuan Xi ORCID logo

05/24/2024

This dataset contains the main materials for predicting site-level surface soil moisture based on a developed hybrid physics-guided deep learning modeling framework.

EAPS Long short-term memory (LSTM) Physics-Guided Deep Learning Soil Moisture Terrestrial Ecosystem Model (TEM)

A Hybrid Physics-Guided Deep Learning Modeling Framework for Predicting Surface Soil Moisture

10.4231/SBB0-V865

Qianlai Zhuang ORCID logo , Xinyu Liu , Xuan Xi ORCID logo

08/21/2024

This dataset contains the main materials for predicting site-level surface soil moisture based on a developed hybrid physics-guided deep learning modeling framework.

EAPS Long short-term memory (LSTM) Physics-Guided Deep Learning Soil Moisture Terrestrial Ecosystem Model (TEM)

Evaluating the variability of surface soil moisture simulated within CMIP5 using SMAP data

10.4231/A0QC-7E03

Pierre Gentine , Qianlai Zhuang ORCID logo , Seungbum Kim , Xuan Xi ORCID logo

12/01/2021

This dataset includes the comparison results of 17 land surface models from the Coupled Model Intercomparison Project Phase 5 (CMIP5) globally using the Soil Moisture Active Passive (SMAP) products and codes for analysis.

EAPS Fourier Analysis Land Surface Model Matlab SMAP Soil Moisture

Evaluating the effects of precipitation and evapotranspiration on soil moisture variability

10.4231/WHJ3-KN14

Pierre Gentine , Qianlai Zhuang ORCID logo , Seungbum Kim , Xuan Xi

04/22/2022

This dataset includes the comparison results of models from the Coupled Model Intercomparison Project Phase 5 (CMIP5) with Soil Moisture Active Passive (SMAP) and ECMWF Reanalysis v5 (ERA5) products and the corresponding codes for analysis.

CMIP5 EAPS Fourier Analysis Matlab software SMAP Soil Moisture

Display #

Results 1 - 7 of 7