TY - JOUR
T1 - A satellite-driven hydro-economic model to support agricultural water resources management
AU - Maneta, M. P.
AU - Cobourn, K.
AU - Kimball, J. S.
AU - He, M.
AU - Silverman, N. L.
AU - Chaffin, B. C.
AU - Ewing, S.
AU - Ji, X.
AU - Maxwell, B.
N1 - Publisher Copyright:
© 2020 Elsevier Ltd
PY - 2020/12
Y1 - 2020/12
N2 - The management of water resources among competing uses presents a complex technical and policy challenge. Integrated hydro-economic models capable of simulating the hydrologic system in irrigated and non-irrigated regions including the response of farmers to hydrologic constraints and economic and policy incentives, provide a framework to understand biophysical and socioeconomic implications of changing water availability. We present a transformative hydro-economic model of agricultural production driven by multi-sensor satellite observations, outputs from regional climate models, and socioeconomic data. Our approach overcomes the limitations of current decision support systems for agricultural water management and provides policymakers and natural resource managers with satellite data-driven, state-wide, operational models capable of anticipating how farmers allocate water, land, and other resources when confronted with new climate patterns, policy rules, or market signals. The model can also quantify how farming decisions affect agricultural water supplies. We demonstrate the model through an application in the state of Montana.
AB - The management of water resources among competing uses presents a complex technical and policy challenge. Integrated hydro-economic models capable of simulating the hydrologic system in irrigated and non-irrigated regions including the response of farmers to hydrologic constraints and economic and policy incentives, provide a framework to understand biophysical and socioeconomic implications of changing water availability. We present a transformative hydro-economic model of agricultural production driven by multi-sensor satellite observations, outputs from regional climate models, and socioeconomic data. Our approach overcomes the limitations of current decision support systems for agricultural water management and provides policymakers and natural resource managers with satellite data-driven, state-wide, operational models capable of anticipating how farmers allocate water, land, and other resources when confronted with new climate patterns, policy rules, or market signals. The model can also quantify how farming decisions affect agricultural water supplies. We demonstrate the model through an application in the state of Montana.
KW - Data assimilation
KW - Decision support systems
KW - Hydro-economic models
KW - Positive mathematical programming
UR - http://www.scopus.com/inward/record.url?scp=85092140251&partnerID=8YFLogxK
U2 - 10.1016/j.envsoft.2020.104836
DO - 10.1016/j.envsoft.2020.104836
M3 - Article
AN - SCOPUS:85092140251
SN - 1364-8152
VL - 134
JO - Environmental Modelling and Software
JF - Environmental Modelling and Software
M1 - 104836
ER -