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Assessing the impacts of climate change on agriculture and water systems via coupled human-hydrological modeling

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  • Javansalehi, Maryam
  • Shourian, Mojtaba

Abstract

Understanding the intricate relationship between farmers’ water usage and its hydrological effects is crucial for developing adaptable water policies. However, conducting such an analysis proves challenging due to the lack of appropriate modeling tools that comprehensively integrate water policies, water utilization, and hydrological processes. To address this challenge, this study introduces an innovative socio-hydrological framework to investigate the interplay between farmer actions and water resources. This framework integrates an agent-based model, which is based on the Value-Belief-Norm (VBN) theory, linked with a distributed hydrological model (SWAT-MODFLOW) to capture farmer behaviors. The modeling framework is applied to the Mahabad River Basin to assess water use and hydrological impacts. To assess the framework's ability, Nash–Sutcliffe (NS) efficiency and the coefficient of determination (R2) are computed for simulating runoff, while Mean Absolute Residual Error (MAE) and Root Mean Square Error (RMSE) are computed for simulating groundwater head. Results demonstrate the acceptable performance of the proposed model, with NS = 0.61, R2 = 0.69, MAE = 1.16, and RMSE = 1.92. Moreover, this study integrates climate change data from the 6th IPCC report to evaluate the model's responsiveness to altering climate conditions. Findings suggest that farmers facing economic challenges tend to opt for high-profit crops to ameliorate their financial situation. So, without policy changes, climate change will reduce crop yield, farmer income, and water storage. Furthermore, the study evaluates enhancing irrigation efficiency and groundwater extraction restrictions to mitigate climate change effects. Enhancing irrigation efficiency annually conserves 38.39 MCM, boosts crop yields by 6 %, elevates farmer incomes, and encourages a shift toward low-water-consuming crops, contributing to regional groundwater sustainability. Overall, the results of this study can enhance our comprehension of the impact of human activities on hydrological cycles, offering valuable insights for water managers.

Suggested Citation

  • Javansalehi, Maryam & Shourian, Mojtaba, 2024. "Assessing the impacts of climate change on agriculture and water systems via coupled human-hydrological modeling," Agricultural Water Management, Elsevier, vol. 300(C).
  • Handle: RePEc:eee:agiwat:v:300:y:2024:i:c:s0378377424002543
    DOI: 10.1016/j.agwat.2024.108919
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    References listed on IDEAS

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    1. Masih Akhbari & Neil Grigg, 2013. "A Framework for an Agent-Based Model to Manage Water Resources Conflicts," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 27(11), pages 4039-4052, September.
    2. Amadou, Mahamadou L. & Villamor, Grace B. & Kyei-Baffour, Nicholas, 2018. "Simulating agricultural land-use adaptation decisions to climate change: An empirical agent-based modelling in northern Ghana," Agricultural Systems, Elsevier, vol. 166(C), pages 196-209.
    3. Stefania Bandini & Sara Manzoni & Giuseppe Vizzari, 2009. "Agent Based Modeling and Simulation: An Informatics Perspective," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 12(4), pages 1-4.
    4. Fernandez-Mena, Hugo & Gaudou, Benoit & Pellerin, Sylvain & MacDonald, Graham K. & Nesme, Thomas, 2020. "Flows in Agro-food Networks (FAN): An agent-based model to simulate local agricultural material flows," Agricultural Systems, Elsevier, vol. 180(C).
    5. Huber, Robert & Bakker, Martha & Balmann, Alfons & Berger, Thomas & Bithell, Mike & Brown, Calum & Grêt-Regamey, Adrienne & Xiong, Hang & Le, Quang Bao & Mack, Gabriele & Meyfroidt, Patrick & Millingt, 2018. "Representation of decision-making in European agricultural agent-based models," Agricultural Systems, Elsevier, vol. 167(C), pages 143-160.
    6. G. Tsakiris & D. Pangalou & H. Vangelis, 2007. "Regional Drought Assessment Based on the Reconnaissance Drought Index (RDI)," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 21(5), pages 821-833, May.
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    1. Ru, Wenchao & Zhang, Liangliang & Liu, Dong & Sun, Nan & Li, Mo & Faiz, Muhammad Abrar & Li, Tianxiao & Cui, Song & Khan, Muhammad Imran, 2024. "New approach for regional water-energy-food nexus security assessment: Enhancing the random forest model with the aquila optimizer algorithm," Agricultural Water Management, Elsevier, vol. 301(C).

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