|Author:||Erin M.K. Haacker, Vaishali Sharda, Amanda M. Cano, R. Aaron Hrozencik, Agustín Núñez, Zachary Zambreski, Soheil Nozari, Garvey Engulu B. Smith, Lacey Moore, Sumit Sharma, Prasanna Gowda, Chittaranjan Ray, Meagan Schipanski, and Reagan Waskom|
|Book Group Author:|
Agricultural water management (AWM) is an interdisciplinary concern, cutting across traditional domains such as agronomy, climatology, geology, economics, and sociology. Each of these disciplines has developed numerous process‐based and empirical models for AWM. However, models that simulate all major hydrologic, water quality, and crop growth processes in agricultural systems are still lacking. As computers become more powerful, more researchers are choosing to integrate existing models to account for these major processes rather than building new cross‐disciplinary models. Model integration carries the hope that, as in a real system, the sum of the model will be greater than the parts. However, models based upon simplified and unrealistic assumptions of physical or empirical processes can generate misleading results which are not useful for informing policy. In this article, we use literature and case studies from the High Plains Aquifer and Southeastern United States regions to elucidate the challenges and opportunities associated with integrated modeling for AWM and recommend conditions in which to use integrated models. Additionally, we examine the potential contributions of integrated modeling to AWM — the actual practice of conserving water while maximizing productivity.
|Journal:||Journal of the American Water Resources Association (JAWRA)|
Groundwater; irrigation; water scarcity economics; decision support systems; soil health; water conservation