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Agent-based socio-hydrological modeling for restoration of Urmia Lake: Application of theory of planned behavior

Pouladi, P ; Sharif University of Technology | 2019

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  1. Type of Document: Article
  2. DOI: 10.1016/j.jhydrol.2019.06.080
  3. Publisher: Elsevier B.V , 2019
  4. Abstract:
  5. This study proposes a novel socio-hydrological modeling framework for assessing the performance of complex water resources systems. It employs and integrates agent-based modeling (ABM) and the theory of planned behavior (TPB) into the socio-hydrological modeling framework to account for agents’ behaviors. Due to farmers’ major role in anthropogenic droughts, this paper mainly focuses on farmers’ behavior. The TPB framework and the agents’ behavioral rules in ABM are structured based on the data obtained from field questionnaires and interviews by the farmers in the Zarrineh River Basin as the main river feeding the Urmia Lake. The proposed modeling framework, including the TPB and ABM structures and rules, are validated by comparing the results of the proposed socio-hydrological simulation model with the actual data on the simulation period. To assess the ability of the proposed framework, root mean square error (RMSE) and the determination coefficient (DC) were computed. The results show the acceptable performance of the proposed model by RMSE = 0.18 and DC = 0.92. Analysis of the results indicates that financial conditions, farmland size, farmers’ age, and farmers’ education are among the major factors in farmers’ decision-making process, respectively. © 2019
  6. Keywords:
  7. Agent-based model (ABM) ; Decision-making process ; Socio-hydrology ; Theory of planned behavior (TPB) ; Urmia Lake ; Autonomous agents ; Computational methods ; Decision making ; Decision theory ; Hydrology ; Lakes ; Mean square error ; Simulation platform ; Surveys ; Acceptable performance ; Agent-based model ; Decision making process ; Determination coefficients ; Hydrological simulations ; Root mean square errors ; Theory of Planned Behavior ; Water resources systems ; Agriculture ; Artificial neural network ; Habitat restoration ; Hydrological modeling ; Questionnaire survey ; River basin ; Simulation ; Water resource ; Iran ; Lake Urmia ; Zarrineh River
  8. Source: Journal of Hydrology ; Volume 576 , 2019 , Pages 736-748 ; 00221694 (ISSN)
  9. URL: https://www.sciencedirect.com/science/article/abs/pii/S0022169419306286