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Metadata for: Climate-driven prediction of land water storage anomalies: An outlook for water resources monitoring across the conterminous United States

Data reported in the csv files are gridded monthly time-series used in the article “Sohoulande, C.D., Martin, J., Szogi, A. and Stone, K., 2020. Climate-Driven Prediction of Land Water Storage Anomalies: An Outlook for Water Resources Monitoring Across the Conterminous United States. Journal of Hydrology, p.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. The 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. Methods are described in the manuscript https://doi.org/10.1016/j.jhydrol.2020.125053. Descriptions corresponding to each figure and table in the manuscript are placed in the Read Me.docx file that is included as part of the Dryad dataset.

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FieldValue
Tags
Climate
GRACE satellite
Multivariate model
lag signals
land water resources
NP211
Modified
2022-09-29
Release Date
2020-11-17
Frequency
Monthly
Identifier
2c7a0610-bbc3-4e61-b6e8-05032d4a39ad
Spatial / Geographical Coverage Area
POLYGON ((-67.0166015625 44.24126379834, -67.1923828125 45.240085610903, -67.8955078125 46.645665192585, -68.4228515625 47.305309510776, -70.0927734375 46.343135602602, -72.2021484375 44.991997953824, -76.0693359375 44.555249259711, -79.1455078125 43.671844983222, -79.7607421875 42.516650753611, -82.3974609375 41.603120764512, -83.0126953125 42.516650753611, -82.3095703125 44.429857265397, -83.3642578125 45.671643852265, -84.6826171875 46.585293905836, -88.330078125 48.158757304569, -93.251953125 48.509326449766, -95.712890625 49.088257784725, -123.134765625 49.088257784725, -123.55224609375 48.325212956177, -124.34326171875 48.4127955811, -125.13427734375 48.52933815688, -124.34326171875 45.750276864304, -124.78271484375 43.082931450354, -124.38720703125 41.126952506008, -120.76171875 34.143634820313, -117.9931640625 33.390172864722, -116.4990234375 32.579220642876, -114.2138671875 32.208153325473, -111.0498046875 31.386468269542, -108.3251953125 31.311408386202, -106.2158203125 31.76086695138, -105.0732421875 30.708781226254, -104.2822265625 29.568679425235, -103.5791015625 29.339086927341, -102.7001953125 29.645094649861, -102.2607421875 30.178373310708, -101.2939453125 29.797751134173, -100.1513671875 28.492833128965, -99.2724609375 26.779943479945, -98.3056640625 26.386948928734, -97.2509765625 26.150507192329, -96.8994140625 27.249746156837, -95.4931640625 28.724313406473, -93.8232421875 29.262440796699, -92.1533203125 29.415675471218, -90.7470703125 28.955282292975, -89.5166015625 28.955282292975, -88.8134765625 29.492206334849, -87.6708984375 30.178373310708, -86.3525390625 30.026299582224, -85.3857421875 29.568679425235, -84.0673828125 29.797751134173, -83.1884765625 29.032157826223, -82.3974609375 26.465655637838, -82.2216796875 25.83450534734, -81.9580078125 25.596948323286, -81.463623046875 24.855288259359, -82.320556640625 24.615808859044, -82.100830078125 24.235694754669, -81.156005859375 24.355854429729, -80.321044921875 24.795461666933, -79.947509765625 25.392419908212, -79.727783203125 26.85225423018, -80.496826171875 28.564019358848, -80.782470703125 29.256450395257, -79.78271484375 32.674060852092, -78.50830078125 33.410809551114, -76.48681640625 34.359308974794, -75.25634765625 35.655064568954, -75.673828125 37.501010429493, -73.037109375 40.638967343817, -70.224609375 43.253204949088, -67.516479492188 44.154129786288, -67.197875976563 44.280112529946, -67.197875976563 44.280112529946))
Publisher
Dryad
Spatial / Geographical Coverage Location
Conterminous United States; 0.5 degree spatial resolution
Temporal Coverage
January 1, 2002 to July 1, 2017
License
U.S. Public Domain
Contact Name
Sohoulande, Clement
Contact Email
clement.sohoulande@usda.gov
Public Access Level
Public
Program Code
005:040 - Department of Agriculture - National Research
Bureau Code
005:18 - Agricultural Research Service
Extended Metadata: 
FieldValue
Authors
Sohoulande, Clement (ORCID)
Peer Reviewed
No
Funding Sources
Agricultural Research Service
6082-13000-010-00D
Primary Article

Sohoulande, C. D., Martin, J., Szogi, A., & Stone, K. (2020). Climate-driven prediction of land water storage anomalies: An outlook for water resources monitoring across the conterminous United States. Journal of Hydrology, 588, 125053. https://doi.org/10.1016/j.jhydrol.2020.125053

AgID: 6948710
Method Citation

Sohoulande, C. D., Martin, J., Szogi, A., & Stone, K. (2020). Climate-driven prediction of land water storage anomalies: An outlook for water resources monitoring across the conterminous United States. Journal of Hydrology, 588, 125053. https://doi.org/10.1016/j.jhydrol.2020.125053

AgID: 6948710
Dataset DOI (digital object identifier)
10.5061/dryad.qnk98sfdz
Product Type
Dataset
FieldValue
ISO Topic(s)
climatologyMeteorologyAtmosphere
environment
inlandWaters
planningCadastre
State or Territory
United States Of America
National Agricultural Library Thesaurus Term
time series analysis
prediction
water storage
water resources
monitoring
United States
evapotranspiration
air temperature
geographic information systems
data collection
freshwater
climate change
ecosystems
satellites
models
climatic factors
hydrology
atmospheric precipitation
meteorological data
Ag Data Commons Keywords
  • Agroecosystems & Environment
  • Water
  • Hydrology
  • Agroecosystems & Environment
  • Water
  • Evapotranspiration
  • Agroecosystems & Environment
  • Weather and Climate
  • Agroecosystems & Environment
  • Management
  • Agroecosystems & Environment
  • Water
  • Agroecosystems & Environment

Suggested Citations:

(original article) Sohoulande, C. D., Martin, J., Szogi, A., & Stone, K. (2020). Climate-driven prediction of land water storage anomalies: An outlook for water resources monitoring across the conterminous United States. Journal of Hydrology, 588, 125053. https://doi.org/10.1016/j.jhydrol.2020.125053

(dataset) Sohoulande, Clement (2020). Metadata for: Climate-driven prediction of land water storage anomalies: An outlook for water resources monitoring across the conterminous United States. Dryad. https://doi.org/10.5061/dryad.qnk98sfdz. Accessed 2023-09-29.