Stakeholder-Informed Hydroclimate Scenario Modeling in the Lower Santa Cruz River Basin for Water Resource Management
Affiliation
Arizona Institute for Resilience, University of ArizonaCenter for Climate Adaptation Science and Solutions, University of Arizona
Department of Hydrology and Atmospheric Sciences, University of Arizona
Issue Date
2023-05-16Keywords
climate changehydroclimate modeling
riparian health
Santa Cruz River
stakeholder-informed modeling
Tucson
water resource management
weather generator
Metadata
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MDPICitation
Gupta, N.; Bearup, L.; Jacobs, K.; Halper, E.; Castro, C.; Chang, H.-I.; Fonseca, J. Stakeholder-Informed Hydroclimate Scenario Modeling in the Lower Santa Cruz River Basin for Water Resource Management. Water 2023, 15, 1884. https://doi.org/10.3390/w15101884Journal
Water (Switzerland)Rights
© 2023 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution license.Collection Information
This item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at repository@u.library.arizona.edu.Abstract
The Lower Santa Cruz River Basin Study (LSCRB Study) is a collaborative effort of regional and statewide water management stakeholders working with the US Bureau of Reclamation under the auspices of the 2009 SECURE Water Act. The impacts of climate change, land use, and population growth on projected water supply in the LSCRB were evaluated to (1) identify projected water supply and demand imbalances and (2) develop adaptation strategies to proactively respond over the next 40 years. A multi-step hydroclimate modeling and risk assessment process was conducted to assess a range of futures in terms of temperature, precipitation, runoff, soil moisture, and evapotranspiration, with a particular focus on implications for ecosystem health. Key hydroclimate modeling process decisions were informed by ongoing multi-stakeholder engagement. To incorporate the region’s highly variable precipitation pattern, the study used a numerical “weather generator” to develop ensembles of precipitation and temperature time series for input to surface hydrology modeling efforts. Hydroclimate modeling outcomes consistently included increasing temperatures, and generated information related to precipitation responses (season length and timing, precipitation amount) considered useful for evaluating potential ecosystem impacts. A range of risks was identified using the hydroclimate modeling outputs that allowed for development of potential adaptation strategies. © 2023 by the authors.Note
Open access journalISSN
2073-4441Version
Final Published Versionae974a485f413a2113503eed53cd6c53
10.3390/w15101884
Scopus Count
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Except where otherwise noted, this item's license is described as © 2023 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution license.