Enhancing Farmers’ Resilience in Participatory Water Resources Management under Water Scarcity Conditions in the Lake Urmia Basin Using Agent-Based Modeling | ||
| تحقیقات مهندسی سازه های آبیاری و زهکشی | ||
| Volume 26, Summer - Serial Number 99, July 2025, Pages 74-55 PDF (909.29 K) | ||
| Document Type: Original Article | ||
| DOI: 10.22092/idser.2025.369484.1619 | ||
| Authors | ||
| Somayeh Emami* 1; Hossein Dehghanisanij2; Hojjat Emami3 | ||
| 1PhD in Hydraulic Structures, Department of Water Science and Engineering, University of Tabriz, Tabriz, Iran | ||
| 2Professor, Agricultural Research, Education and Extension Organization, Agricultural Engineering Research Institute, Karaj, Alborz, Iran. | ||
| 3Associate Professor, Department of Computer Engineering, Faculty of Engineering and Technology, University of Bonab, Bonab, Iran | ||
| Abstract | ||
| Introduction In arid and semi-arid regions, pressures from climate change, including increasing temperatures, decreasing precipitation, and severe seasonal fluctuations, along with institutional constraints and weaknesses in resource management, have created fundamental challenges for farmers and hindered the realization of sustainable agriculture. The Lake Urmia basin, one of the most sensitive aquatic ecosystems in the country, provides a prime example of such critical conditions due to the significant decrease in water levels, increased salinity, and decline in the quality of water resources, which have resulted in widespread economic, social, and environmental consequences for local communities. Water scarcity not only reflects physical resource limitations but also generates complex interactions among economic, social, institutional, and environmental factors, directly influencing farmers' decision-making, irrigation technology choices, and the effectiveness of water resource management policies. In this context, socio-institutional resilience is a multidimensional and decisive factor, encompassing household economic capacities, flexibility and adaptability of agricultural technologies, active and stable social networks, and organizational and institutional skills, all of which can enhance the sustainability of agricultural systems in the face of environmental pressures and economic instabilities. However, previous studies have mostly analyzed economic, individual, or social indicators separately and have not comprehensively examined the complex interactions among individual, social, technological, and environmental factors. As a result, the ability to predict the agricultural system's response to various policies and climate shocks has been limited. Moreover, an integrated framework for optimal water resource management and for enhancing farmers' resilience has not yet been provided. Methodology This study was conducted using a mixed qualitative and quantitative approach combined with agent-based modeling (ABM) to accurately represent the complex interactions between farmers, social-institutional networks, and environmental pressures in the Miandoab Plain, south of Lake Urmia. The study population included 50 farmers, 10 agricultural Jihad experts, and 10 representatives of the regional water organization. Data were collected through structured questionnaires, semi-structured interviews, and secondary sources. Six key indicators were defined in the model: economic resilience (ERI), technological flexibility (FTI), knowledge network strength (KNRI), innovation motivation in practice (MPI), environmental pressure (EPI), and irrigation technology level (IL). Farmers, as the main agents, interacted continuously with local knowledge networks and product markets, and their decision-making rules were shaped by individual motivations, environmental pressures, and the observed behavior of others. To examine the system's response under different conditions, four simulation scenarios were designed: fluctuations in agricultural product prices, introduction of new irrigation technologies at varying adoption rates, changes in the density of knowledge networks, and the occurrence of climate shocks and successive droughts. Quantitative data were analyzed using SPSS, and qualitative data were processed using open and axial coding in MAXQDA. Model validation was conducted by comparing outputs with historical data, consulting local experts, and performing sensitivity analyses to ensure the model accurately represents farmers' behavior and socio-institutional dynamics under various environmental pressures. Results and Discussion Simulation results showed that farmers' adoption of new technologies and changes in irrigation patterns are influenced by a combination of economic, individual, technological, social, and environmental factors. Farmers with higher economic resilience and denser social networks adopted new technologies faster, resulting in increased water productivity. Environmental pressures, particularly drought and water scarcity, were strong drivers for adoption, but their effects were sustainable only when combined with strong individual motivation and active knowledge networks. The technological flexibility index and innovation motivation were decisive in determining the speed and extent of technology adoption. Social networks and knowledge network strength enhanced collective learning and experience sharing, thereby creating synergistic effects with other indicators. The combination of low economic capacity and high environmental pressure highlighted the need for targeted support and guidance to help farmers adapt to new technologies. Analysis also showed that one-dimensional policies, such as simply providing subsidies or unsupervised training, have limited effectiveness and may even be counterproductive. In contrast, multidimensional policy packages, including targeted and continuous education, performance-based subsidies, strengthening local networks, and transparency in water allocation, create synergistic and sustainable impacts. International experiences indicate that farm schools, participatory local networks, and subsidy reforms can significantly increase farmer engagement and water productivity. Agent-based modeling also allows predicting farmers' responses to policies, testing different scenarios, and optimizing resource allocation before implementation. Conclusions The adoption of new irrigation technologies and sustainable water management results from complex interactions among economic, social, institutional, and environmental factors. Successful participatory policies require maintaining a minimum level of water resource sustainability, implementing multidimensional policy packages, strengthening social and institutional networks, and using agent-based modeling tools to assess policy effectiveness. This study demonstrated that the combination of economic indicators, innovation motivation, social networks, and environmental pressures can significantly determine the success or failure of policies. The proposed framework provides a practical and scientific roadmap for sustainable water management in areas affected by water crises. | ||
| Keywords | ||
| Water Resources Management; Participatory Modeling; Supportive Policies; Social Simulation | ||
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