On Connecting Hydrosocial Parameters to Vegetation Greenness Differences in an Evolving Groundwater-Dependent Ecosystem
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Published:2024-07-10
Issue:14
Volume:16
Page:2536
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ISSN:2072-4292
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Container-title:Remote Sensing
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language:en
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Short-container-title:Remote Sensing
Author:
Lurtz Matthew R.12ORCID, Morrison Ryan R.3ORCID, Nagler Pamela L.4ORCID
Affiliation:
1. Department of Geosciences, Colorado State University, Fort Collins, CO 80523, USA 2. Cooperative Institute for Research in Environmental Sciences, University of Colorado, Boulder, CO 80309, USA 3. Department of Civil and Environmental Engineering, Colorado State University, Fort Collins, CO 80523, USA 4. U. S. Geological Survey, Southwest Biological Science Center, University of Arizona, Tucson, AZ 85719, USA
Abstract
Understanding groundwater-dependent ecosystems (i.e., areas with a relatively shallow water table that plays a major role in supporting vegetation health) is key to sustaining water resources in the western United States. Groundwater-dependent ecosystems (GDEs) in Colorado have non-pristine temporal and spatial patterns, compared to agro-ecosystems, which make it difficult to quantify how these ecosystems are impacted by changes in water availability. The goal of this study is to examine how key hydrosocial parameters perturb GDE water use in time and in space. The temporal approach tests for the additive impacts of precipitation, surface water discharge, surface water mass balance as a surrogate for surface–groundwater exchange, and groundwater depth on the monthly Landsat normalized difference vegetation index (NDVI). The spatial approach tests for the additive impacts of river confluences, canal augmentation, development, perennial tributary confluences, and farmland modification on temporally integrated NDVI. Model results show a temporal trend (monthly, 1984–2019) is identifiable along segments of the Arkansas River at resolutions finer than 10 km. The temporal impacts of river discharge correlate with riparian water use sooner in time compared to precipitation, but this result is spatially variable and dependent on the covariates tested. Spatially, areal segments of the Arkansas River that have confluences with perennial streams have increased cumulative vegetation density. Quantifying temporal and spatial dependencies between the sources and effects of GDEs could aid in preventing the loss of a vulnerable ecosystem to increased water demand, changing climate, and evolving irrigation methodologies.
Funder
Colorado Agricultural Experiment Station Graduate Teaching Fellowship in the Department of Civil Engineering at Colorado State University
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