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ARS Home » Southeast Area » Florence, South Carolina » Coastal Plain Soil, Water and Plant Conservation Research » Research » Publications at this Location » Publication #380016
Research Project: Managing Water Availability and Quality for Sustainable Agricultural Production and Conservation of Natural Resources in Humid Regions

Location: Coastal Plain Soil, Water and Plant Conservation Research

Title: Data from: Climate-driven prediction of land water storage anomalies: an outlook for water resources monitoring across the conterminous United States

Author
item Sohoulande, Clement
item Martin, Jerry
item Szogi, Ariel
item Stone, Kenneth - Ken

Submitted to: Dryad Digital Repository
Publication Type: Database / Dataset
Publication Acceptance Date: 11/13/2020
Publication Date: 1/18/2021
Citation: Sohoulande Djebou, D.C., Martin, J.H., Szogi, A.A., Stone, K.C. 2021. Data from: Climate-driven prediction of land water storage anomalies: an outlook for water resources monitoring across the conterminous United States. Dryad Digital Repository. https://doi.org/10.5061/dryad.qnk98sfdz.
DOI: https://doi.org/10.5061/dryad.qnk98sfdz

Interpretive Summary:

Technical Abstract: These data are associated with the manuscript entitled “Climate-driven prediction of land water storage anomalies: An outlook for water resources monitoring across the conterminous United States” (https://doi.org/10.1016/j.jhydrol.2020.125053). The study focused on the conterminous United States (CONUS) which extends over a region of contrasting climates with an uneven distribution of freshwater resources. Under climate change, an exacerbation of the contrast between dry and wet regions is expected across the CONUS and could drastically affect local ecosystems, agriculture practices, and communities. Hence, efforts to better understand long-term spatial and temporal patterns of freshwater resources are needed to plan and anticipate responses. Since 2002, the Gravity Recovery and Climate Experiment (GRACE) and GRACE Follow-On (GRACE-FO) satellite observations provide estimates of large-scale land water storage changes with an unprecedented accuracy. However, the limited lifetime and observation gaps of the GRACE mission have sparked research interest for GRACE-like data reconstruction. This study developed a predictive modeling approach to quantify monthly land liquid water equivalence thickness anomaly (LWE) using climate variables including total precipitation (PRE), number of wet day (WET), air temperature (TMP), and potential evapotranspiration (PET). The approach builds on the achievements of the GRACE mission by determining LWE footprints using a multivariate regression on principal components model with lag signals. The performance evaluation of the model with a lag signals consideration shows 0.5 = R2 = 0.8 for 41.2% of the CONUS. However, the model’s predictive power is unevenly distributed. The model could be useful for predicting and monitoring freshwater resources anomalies for the locations with high model performances. The processed data used in the study are here provided.