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Advancing diagnostic model evaluation to better understand water shortage mechanisms in institutionally complex river basins
  • Antonia Hadjimichael,
  • Julianne Quinn,
  • Patrick Reed
Antonia Hadjimichael
Cornell University

Corresponding Author:ah986@cornell.edu

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Julianne Quinn
University of Virginia
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Patrick Reed
Cornell University
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Water resources systems models enable valuable inferences on consequential system stressors by representing both the geophysical processes determining the movement of water, and the human elements distributing it to its various competing uses. This study contributes a diagnostic evaluation framework that pairs exploratory modeling with global sensitivity analysis to enhance our ability to make inferences on water scarcity vulnerabilities in institutionally complex river basins. Diagnostic evaluation of models representing institutionally complex river basins with many stakeholders poses significant challenges. First, it needs to exploit a large and diverse suite of simulations to capture important human-natural system interactions as well as institutionally-aware behavioral mechanisms. Second, it needs to have performance metrics that are consequential and draw on decision-relevant model outputs that adequately capture the multi-sector concerns that emerge from diverse basin stakeholders. We demonstrate the proposed model diagnostic framework by evaluating how potential interactions between changing hydrologic conditions and human demands influence the frequencies and durations of water shortages of varying magnitudes experienced by hundreds of users in a sub-basin of the Colorado river. We show that the dominant factors shaping these effects vary both across users and, for an individual user, across percentiles of shortage magnitude. These differences hold even for users sharing diversion locations, demand levels or water right seniority. Our findings underline the importance of detailed institutional representation for such basins, as institutions strongly shape how dominant factors of stakeholder vulnerabilities propagate through the complex network of users.
Oct 2020Published in Water Resources Research volume 56 issue 10. 10.1029/2020WR028079