{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,20]],"date-time":"2026-03-20T00:37:46Z","timestamp":1773967066326,"version":"3.50.1"},"reference-count":79,"publisher":"MDPI AG","issue":"14","license":[{"start":{"date-parts":[[2023,7,21]],"date-time":"2023-07-21T00:00:00Z","timestamp":1689897600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Miriam Watts-Wheeler research fund"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>The terrestrial water cycle intensity (WCI) is a widely used tool to quantify the impact of climate change on the distribution of global water resources. In this study, a satellite-based WCI was tested by comparing the parameter-elevation regressions on independent slopes model (PRISM) precipitation estimates with those of the Global Precipitation Measurement (GPM) satellite mission across the contiguous United States (CONUS), based on an existing K\u00f6ppen\u2013Geiger climate classification for the CONUS. Both precipitation products were not statistically different across all climate classes. Consequently, satellite-based WCI changes between two multiannual periods (2001 to 2009 and 2010 to 2019) were calculated at a 0.1-degree spatial resolution using the GPM and a validated global evapotranspiration dataset. This study showed that: (1) The water cycle is speeding up in many parts of the CONUS, particularly the West, driven by recent increases in both precipitation and evapotranspiration through much of the region. (2) The El Ni\u00f1o-Southern Oscillation (ENSO) may be influencing the WCI of the CONUS by driving precipitation in the west, southeast, and parts of the north, and dryness in the northeast regions. The hydrological impacts of these results cannot be generalized. However, flood and drought risks, water availability and quality issues remain key primary concerns.<\/jats:p>","DOI":"10.3390\/rs15143632","type":"journal-article","created":{"date-parts":[[2023,7,24]],"date-time":"2023-07-24T01:12:28Z","timestamp":1690161148000},"page":"3632","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":5,"title":["A Satellite-Based Approach for Quantifying Terrestrial Water Cycle Intensity"],"prefix":"10.3390","volume":"15","author":[{"given":"Fabian J.","family":"Zowam","sequence":"first","affiliation":[{"name":"Water Resources & Remote Sensing Laboratory (WRRS), Department of Geology, University of Georgia, 210 Field Street, 306 Geography-Geology Building, Athens, GA 30602, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0494-8002","authenticated-orcid":false,"given":"Adam M.","family":"Milewski","sequence":"additional","affiliation":[{"name":"Water Resources & Remote Sensing Laboratory (WRRS), Department of Geology, University of Georgia, 210 Field Street, 306 Geography-Geology Building, Athens, GA 30602, USA"}]},{"given":"David F.","family":"Richards IV","sequence":"additional","affiliation":[{"name":"Water Resources & Remote Sensing Laboratory (WRRS), Department of Geology, University of Georgia, 210 Field Street, 306 Geography-Geology Building, Athens, GA 30602, USA"}]}],"member":"1968","published-online":{"date-parts":[[2023,7,21]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"361","DOI":"10.1016\/j.jhydrol.2018.02.048","article-title":"A new indicator framework for quantifying the intensity of the terrestrial water cycle","volume":"559","author":"Huntington","year":"2018","journal-title":"J. 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