Hydrology and Earth System Sciences (Jul 2017)

Coupling biophysical processes and water rights to simulate spatially distributed water use in an intensively managed hydrologic system

  • B. Han,
  • B. Han,
  • S. G. Benner,
  • J. P. Bolte,
  • K. B. Vache,
  • A. N. Flores

DOI
https://doi.org/10.5194/hess-21-3671-2017
Journal volume & issue
Vol. 21
pp. 3671 – 3685

Abstract

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Humans have significantly altered the redistribution of water in intensively managed hydrologic systems, shifting the spatiotemporal patterns of surface water. Evaluating water availability requires integration of hydrologic processes and associated human influences. In this study, we summarize the development and evaluation of an extensible hydrologic model that explicitly integrates water rights to spatially distribute irrigation waters in a semi-arid agricultural region in the western US, using the Envision integrated modeling platform. The model captures both human and biophysical systems, particularly the diversion of water from the Boise River, which is the main water source that supports irrigated agriculture in this region. In agricultural areas, water demand is estimated as a function of crop type and local environmental conditions. Surface water to meet crop demand is diverted from the stream reaches, constrained by the amount of water available in the stream, the water-rights-appropriated amount, and the priority dates associated with particular places of use. Results, measured by flow rates at gaged stream and canal locations within the study area, suggest that the impacts of irrigation activities on the magnitude and timing of flows through this intensively managed system are well captured. The multi-year averaged diverted water from the Boise River matches observations well, reflecting the appropriation of water according to the water rights database. Because of the spatially explicit implementation of surface water diversion, the model can help diagnose places and times where water resources are likely insufficient to meet agricultural water demands, and inform future water management decisions.