2020
DOI: 10.1016/j.jhydrol.2020.125313
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Exploring spatial heterogeneity and temporal dynamics of human-hydrological interactions in large river basins with intensive agriculture: A tightly coupled, fully integrated modeling approach

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Cited by 35 publications
(27 citation statements)
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“…However, similar to those in other studies (e.g., Mulligan et al., 2014), the ABM in Du et al. (2020) was limited to the case in which a basin‐level centralized manager applies uniform policies to the entire river basin. In this study, we improve the ABM of Du et al.…”
Section: Introductionmentioning
confidence: 66%
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“…However, similar to those in other studies (e.g., Mulligan et al., 2014), the ABM in Du et al. (2020) was limited to the case in which a basin‐level centralized manager applies uniform policies to the entire river basin. In this study, we improve the ABM of Du et al.…”
Section: Introductionmentioning
confidence: 66%
“…In this study, we improve the ABM of Du et al. (2020) by incorporating a distributed policy design scheme that includes multiple decentralized water management agents in the system. Each local water manager can adopt time‐varying policies in their administrative area.…”
Section: Introductionmentioning
confidence: 99%
“…Integrating monitoring, modeling and data manipulation and collaborating with multiple research teams, a fully integrated water-ecosystem-economy model and a spatially explicit decision-support system (DSS) have been put in place to identify, simulate and predict land management scenarios to define the water operation policies (Step 2). An agent-based model (ABM) was developed to simulate farmers' decisionmaking on conjunctive use of groundwater and surface water under the influence of policy portfolio with collective water management policies (Du et al, 2020). Such management scenarios include recommendation of modification of crop pattern in the middle reach oasis area, water exchange through market mechanisms among water users in the middle reach area to promotes efficient and beneficial water uses, approval of a proposed water allocation plan in the HRB to deliver 0.95 billion m 3 of water downstream annually for ecosystem rehabilitation by the State Council of China to address the downstream water shortages (Cheng et al, 2014;Li et al, 2018;Song, 2019;He et al, 2020).…”
Section: Application Of Watershed Sciencementioning
confidence: 99%
“…Of the 16 ABM-based studies that simulated noncooperative water use, 10 are based on optimizing agents [13,17,26,62,63,[65][66][67][68][69]. Three ABM studies, Schlueter and Pahl-Wostl [16], Khan et al [64], and Du et al [61], used heuristics while Becu et al [55] combined optimization with heuristics for decisions on rice planting and off-farm labor participation. The optimization approaches are theoretically strong but accused of seeing the human decision makers as rational optimizers with perfect foresight based on classical microeconomic theory.…”
Section: Decision Rules and Solution Algorithmsmentioning
confidence: 99%
“…Overall, the ABM-based studies put more focus on the biophysical processes where physically based distributed hydrological models are linked to simplified economic model. The agents in ABM studies are often defined as rule-based agents, meaning that water-related economic decisions draw on predefined heuristics [61,64]. This is mainly due to model tractability and computation time, especially with large numbers of agents.…”
Section: Agents' Behaviors Interactions Uncertainties and Spatio-tempmentioning
confidence: 99%