Iranian Journal of Soil and Water Research

Iranian Journal of Soil and Water Research

Identification and Prioritization of Sustainable Strategies for Water and Soil Resources Management in Agriculture: A Case Study of Guilan Province

Document Type : Research Paper

Authors
Mohammad Ali Ghahremani-Aghbolagh Rostam Khan 1
Hassan Ghasemi-Mobtaker 2
Majid Khanali 1
1 Department of Agricultural Machinery Engineering, Faculty of Agricultural Engineering and Technology, College of Agriculture and Natural Resources, University of Tehran, Karaj, Iran
2 Corresponding Author, Department of Agricultural Machinery Engineering, Faculty of Agricultural Engineering and Technology, College of Agriculture and Natural Resources, University of Tehran, Karaj, Iran
10.22059/ijswr.2026.408965.670079
Abstract
Sustainable water and soil resource management is a strategic cornerstone for ensuring food security and achieving sustainable agricultural development amidst climate change, erratic precipitation, and intensifying pressure on natural resources. Despite its humid climate and fertile soils, Guilan Province faces rising water demand, inefficient resource use, soil degradation, and environmental pollution, necessitating the development of prioritized, practical, and feasible strategies for effective management of basic resources. The present study aimed to employ the analytic hierarchy process (AHP) as a multi-criteria decision-making (MCDM) method to identify and rank effective management strategies for the optimal utilization of water and soil resources in the agricultural sector of Guilan Province. To this end, the study's criteria and sub-criteria were selected through a systematic review of scientific literature and subsequently refined via expert consultation. The required data were collected using pairwise comparison questionnaires and analyzed with Expert Choice software. The findings revealed that the criterion of water productivity held the highest priority with a relative weight of 0.367, followed by environmental sustainability (0.278) and soil resource productivity (0.160). At the sub-criteria level, irrigation efficiency and reduction of water loss, along with reducing agricultural operation pollution and optimal fertilizer use, were accorded greater significance. The prioritization of management strategies identified the implementation of modern pressurized irrigation systems as the most effective option, succeeded by the development of conservation agriculture and farmer education and extension programs. Finally, for a more comprehensive assessment, integrating MCDMs with spatial data and emphasizing stakeholder education and active participation is recommended.
Keywords
Agricultural economics
Analytical hierarchy process
Decision making
Environmental sustainability
Social acceptance
Subjects

Introduction

Water and soil resources are vital for agricultural production, food security, and sustainable development. Population growth and pressure on limited resources have intensified challenges such as climate change, water scarcity, and soil degradation. In Iran, water shortages, inefficient irrigation, and severe soil erosion threaten agricultural productivity. Thus, sustainable practices and effective risk management are essential. Previous studies show that agriculture is the largest consumer of water and that inefficient use and rainfall variability increase production risks. Multi-criteria decision-making (MCDM) approaches, especially the Analytic Hierarchy Process (AHP), are effective for evaluating management options. This study applies AHP to prioritize sustainable water and soil management strategies in Guilan Province to enhance resilience and support sustainable decision-making.

Material and Methods

This study was conducted in Guilan Province, located between 36–38° N latitude and 48–50° E longitude, a region characterized by a humid climate, high annual rainfall (about 1506 mm), and fertile clay–loam soils. Required data were first collected through a systematic review of recent scientific literature from databases such as Scopus and Google Scholar to identify relevant criteria and sub-criteria for sustainable water and soil management. The extracted indicators were refined through expert judgment. Experts were selected using snowball sampling and included university faculty members and PhD students specializing in water, soil, environmental sciences, and agricultural economics. A pairwise comparison questionnaire based on the AHP was designed using Saaty’s 9-point scale. Pairwise comparisons were analyzed in Expert Choice 11 software to calculate relative weights and priorities. Consistency ratios were evaluated to ensure reliability of expert judgments.

Results and Discussion

The results of the AHP analysis revealed priorities among criteria, sub-criteria, and management alternatives for sustainable water and soil management in Guilan Province. Among the main criteria, water productivity ranked first with a weight of 0.367, indicating that water is perceived as the primary limiting factor for agricultural production. This priority reflects increasing irrigation demand, rainfall variability, and declining irrigation efficiency. Environmental sustainability (0.278) and soil resource productivity (0.160) followed, highlighting expert concern for long-term ecological impacts and soil quality preservation alongside short-term production goals. Economic efficiency, social acceptance, and institutional feasibility received lower weights, suggesting that environmental considerations dominate sustainability-oriented decision making. At the sub-criteria level, irrigation efficiency and reduction of surface and groundwater losses were the most influential factors within water productivity, emphasizing demand-side management rather than water supply expansion. For soil productivity, optimal fertilizer application and crop rotation were prioritized, confirming the critical role of soil conservation in reducing erosion and maintaining fertility. Within environmental sustainability, reducing agricultural pollution and protecting local ecosystems received the highest weights, consistent with concerns regarding greenhouse gas emissions and biodiversity loss. Economic analysis showed that net profitability and cost reduction strongly affect adoption potential, while farmer acceptance and education were decisive social drivers. Regarding management alternatives, implementation of modern pressurized irrigation systems ranked first across all criteria, followed by conservation agriculture and farmer education programs. Sensitivity analysis demonstrated that these rankings remained stable under weight changes, confirming model robustness. These results support integrated and sustainability-oriented agricultural policy decisions.

Conclusions

This study applied the AHP method based on expert judgment to identify and prioritize sustainable water and soil management strategies in Guilan Province agriculture. Results showed that water productivity ranked first with a weight of 0.367, confirming water as the main limiting factor under increasing demand, rainfall variability, and low irrigation efficiency. Environmental sustainability (0.278) and soil resource productivity (0.160) followed, indicating strong concern for long-term ecosystem protection and soil conservation beyond short-term productivity. At the sub-criteria level, irrigation efficiency, reduction of water losses, optimal fertilizer use, crop rotation, and mitigation of agricultural pollution were prioritized. Among management alternatives, modern pressurized irrigation systems ranked first (0.510), followed by conservation agriculture and farmer education programs. This study recommends prioritizing modern irrigation systems with institutional support, conservation agriculture, and participatory extension programs to enhance agricultural resilience.

Funding

This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.

Authorship contribution

All authors contributed equally to the conceptualization of the article and writing of the original and subsequent drafts. All authors have read and agreed to the published version of the manuscript.

Declaration of Generative AI and AI-assisted technologies in the writing process

During the preparation of this work the author(s) used ChatGPT in order to assist with translation and language refinement. After using this tool, the author(s) reviewed and edited the content as needed and take(s) full responsibility for the content of the publication.

Data availability statement

The data that support the findings of this study will be available from the corresponding author on reasonable requests.

Acknowledgements

The authors gratefully acknowledge the support provided by the University of Tehran, which contributed significantly to the completion of this study.

Ethical considerations

The authors avoided data fabrication, falsification, and plagiarism, and misconduct.

Conflict of interest

The authors declare no conflict of interest.

Abbas, A., Waseem, M., Ahmad, R., khan, K. A., Zhao, C., & Zhu, J. (2022). Sensitivity analysis of greenhouse gas emissions at farm level: case study of grain and cash crops. Environmental Science and Pollution Research, 29(54), 82559–82573. https://doi.org/10.1007/s11356-022-21560-9
Abd-Elaty, I., Fathy, I., Kuriqi, A., John, A. P., Straface, S., & Ramadan, E. M. (2023). Impact of Modern Irrigation Methods on Groundwater Storage and Land Subsidence in High-water Stress Regions. Water Resources Management, 37(4), 1827–1840. https://doi.org/10.1007/s11269-023-03457-5
Adabi, S., & Noorivandi, A. N. (2022). Application of Fuzzy AHP to Identify and Prioritize the Challenges of Resistive Economics in Iran’s Agricultural Sector. International Journal of Agricultural Management and Development, 12(1), 63-78. https://doi.org/10.22004/AG.ECON.335185
Agarwal, R., & Garg, P. K. (2016). Remote Sensing and GIS Based Groundwater Potential & Recharge Zones Mapping Using Multi-Criteria Decision Making Technique. Water Resources Management, 30(1), 243–260. https://doi.org/10.1007/s11269-015-1159-8
Aguarón, J., Escobar, M. T., Moreno-Jiménez, J. M., & Turón, A. (2019). AHP-Group Decision Making Based on Consistency. Mathematics, 7(3), 242. https://doi.org/10.3390/math7030242
Amiri, A. A., Wahid, M. N., Al-Buraiki, A. S., & Al-Sharafi, A. (2024). A strategic multi-criteria decision-making framework for renewable energy source selection in Saudi Arabia using AHP-TOPSIS. Renewable Energy, 236, 121523. https://doi.org/10.1016/j.renene.2024.121523
Bagheri, M., Zaiton Ibrahim, Z., Mansor, S., Abd Manaf, L., Akhir, M. F., Talaat, W. I. A. W., & Beiranvand Pour, A. (2021). Application of Multi-Criteria Decision-Making Model and Expert Choice Software for Coastal City Vulnerability Evaluation. Urban Science, 5(4), 84. https://doi.org/10.3390/urbansci5040084
Bartzas, G., & Komnitsas, K. (2020). An integrated multi-criteria analysis for assessing sustainability of agricultural production at regional level. Information Processing in Agriculture, 7(2), 223–232. https://doi.org/10.1016/j.inpa.2019.09.005
Bera, A., Mukhopadhyay, B. P., & Das, D. (2019). Landslide hazard zonation mapping using multi-criteria analysis with the help of GIS techniques: a case study from Eastern Himalayas, Namchi, South Sikkim. Natural Hazards, 96(2), 935–959. https://doi.org/10.1007/s11069-019-03580-w
Bera, D., & Dutta, D. (2024). A Comprehensive Evaluation of Agricultural Drought Vulnerability Using Fuzzy‐AHP‐Based Composite Index Integrating Sensitivity and Adaptive Capacity. Hydrological Processes, 38(11). https://doi.org/10.1002/hyp.15331
Biswas, T., Majumder, A., Dey, S., Mandal, A., Ray, S., Kapoor, P., Emam, W., Kanthal, S., ISHIZAKA, A., & Matuka, A. (2024). Evaluation of management practices in rice–wheat cropping system using multicriteria decision-making methods in conservation agriculture. Scientific Reports, 14(1), 8600. https://doi.org/10.1038/s41598-024-58022-w
Bousalah, H. (2025). Strengthening environmental communication for sustainable rural development: A Case Study of Maala Municipality, Algeria. Comunicar: Revista Científica de Comunicación y Educación, 83, 89–102.
Bozorg-Haddad, O., Zolghadr-Asli, B., Sarzaeim, P., Aboutalebi, M., Chu, X., & Loáiciga, H. A. (2020). Evaluation of water shortage crisis in the Middle East and possible remedies. Journal of Water Supply: Research and Technology-Aqua, 69(1), 85–98. https://doi.org/10.2166/aqua.2019.049
Caicedo Solano, N. E., García Llinás, G. A., & Montoya-Torres, J. R. (2022). Operational model for minimizing costs in agricultural production systems. Computers and Electronics in Agriculture, 197, 106932. https://doi.org/10.1016/j.compag.2022.106932
Caldera, U., Sadiqa, A., Gulagi, A., & Breyer, C. (2021). Irrigation efficiency and renewable energy powered desalination as key components of Pakistan’s water management strategy. Smart Energy, 4, 100052. https://doi.org/10.1016/j.segy.2021.100052
Cao, J., & Solangi, Y. A. (2023). Analyzing and Prioritizing the Barriers and Solutions of Sustainable Agriculture for Promoting Sustainable Development Goals in China. Sustainability, 15(10), 8317. https://doi.org/10.3390/su15108317
Coffey, L., & Claudio, D. (2021). In defense of group fuzzy AHP: A comparison of group fuzzy AHP and group AHP with confidence intervals. Expert Systems with Applications, 178, 114970. https://doi.org/10.1016/j.eswa.2021.114970
De Olde, E. M., Oudshoorn, F. W., Sørensen, C. A. G., Bokkers, E. A. M., & de Boer, I. J. M. (2016). Assessing sustainability at farm-level: Lessons learned from a comparison of tools in practice. Ecological Indicators, 66, 391–404. https://doi.org/10.1016/j.ecolind.2016.01.047
Dibbern, T., Romani, L. A. S., & Massruhá, S. M. F. S. (2024). Main drivers and barriers to the adoption of Digital Agriculture technologies. Smart Agricultural Technology, 8, 100459. https://doi.org/10.1016/j.atech.2024.100459
Dixit, A., Suvadarshini, P., & Pagare, D. V. (2024). Analysis of barriers to organic farming adoption in developing countries: a grey-DEMATEL and ISM approach. Journal of Agribusiness in Developing and Emerging Economies, 14(3), 470–495. https://doi.org/10.1108/JADEE-06-2022-0111
El-Beltagi, H. S., Basit, A., Mohamed, H. I., Ali, I., Ullah, S., Kamel, E. A. R., Shalaby, T. A., Ramadan, K. M. A., Alkhateeb, A. A., & Ghazzawy, H. S. (2022). Mulching as a Sustainable Water and Soil Saving Practice in Agriculture: A Review. Agronomy, 12(8), 1881. https://doi.org/10.3390/agronomy12081881
Eslami, A. (2021). Impacts of climate change on agricultural production and food security. Journal of Water and Sustainable Development, 7(4), 83-87.(In Persian).
Erjavec, E., Volk, T., Rednak, M., Ciaian, P., & Lazdinis, M. (2021). Agricultural policies and European Union accession processes in the Western Balkans: aspirations versus reality. Eurasian Geography and Economics, 62(1), 46–75. https://doi.org/10.1080/15387216.2020.1756886
Fazeli, H., Allahyari, M. S., Firouzi, S., Ben Hassen, T., Surujlal, J., Nejadrezaei, N., & Sadeghzadeh, M. (2023). Knowledge, Attitude, and Perception of Students Regarding Renewable Energies in Agriculture in Guilan, Iran. Agriculture, 13(8), 1624. https://doi.org/10.3390/agriculture13081624
Ghaznavi, S., Yazdani, S., Rafiee, H., Saleh, I., Jalilian, A., Kaab, A., & Nabavi-Pelesaraei, A. (2025). Sustainable synergies of rice–fish–duck symbiosis: A life cycle assessment in Guilan Province of Iran. Results in Engineering, 28, 107226. https://doi.org/10.1016/j.rineng.2025.107226
Goodarzi, M. (2022). Prioritization of Arable Crops Using Multiple Criteria and Analytical Hierarchy Process (AHP) Method, Case Study: Markazi Province - Farahan Plain. Iranian Journal of Irrigation & Drainage, 16(3), 485-498. (In Persian).
Hadadin, N., Qaqish, M., Akawwi, E., & Bdour, A. (2010). Water shortage in Jordan — Sustainable solutions. Desalination, 250(1), 197–202. https://doi.org/10.1016/j.desal.2009.01.026
Hamidah, M., Mohd Hasmadi, I., Chua, L. S. L., Yong, W. S. Y., Lau, K. H., Faridah-Hanum, I., & Pakhriazad, H. Z. (2022). Development of a protocol for Malaysian Important Plant Areas criterion weights using Multi-criteria Decision Making - Analytical Hierarchy Process (MCDM-AHP). Global Ecology and Conservation, 34, e02033. https://doi.org/10.1016/j.gecco.2022.e02033
Hartmann, M., & Six, J. (2022). Soil structure and microbiome functions in agroecosystems. Nature Reviews Earth & Environment, 4(1), 4–18. https://doi.org/10.1038/s43017-022-00366-w
Hasily, M. A., Golabi, M., & Nasab, S. B. (2020). Study and evaluation of irrigation and drainage networks using analytic hierarchy process in Khuzestan Province: A virtual water approach. Agricultural Water Management, 241, 106305. https://doi.org/https://doi.org/10.1016/j.agwat.2020.106305
Hemmati, S., Yaghmaeian, N., Farhangi, M. B., & Sabouri, A. (2022). Soil quality assessment of paddy fields (in Northern Iran) with different productivities: establishing the critical limits of minimum data set indicators. Environmental Science and Pollution Research, 30(4), 10286–10296. https://doi.org/10.1007/s11356-022-22846-8
Horňáková, N., Jurík, L., Hrablik Chovanová, H., Cagáňová, D., & Babčanová, D. (2021). AHP method application in selection of appropriate material handling equipment in selected industrial enterprise. Wireless Networks, 27(3), 1683–1691. https://doi.org/10.1007/s11276-019-02050-2
Hutchinson, J. W., Alba, J. W., & Eisenstein, E. M. (2010). Heuristics and Biases in Data-Based Decision Making: Effects of Experience, Training, and Graphical Data Displays. Journal of Marketing Research, 47(4), 627–642. https://doi.org/10.1509/jmkr.47.4.627
Ishizaka, A., & Labib, A. (2009). Analytic hierarchy process and expert choice: Benefits and limitations. OR Insight, 22(4), 201–220.
Jia, L., Xin, J., Wu, H., Gong, S., Wu, H., & Zhang, Z. (2023). Enhancing nitrate attenuation in groundwater via selectively applying surface agricultural practices: A novel and sustainable strategy for non-point source pollution mitigation. Water Research, 239, 120052. https://doi.org/10.1016/j.watres.2023.120052
Jiang, Y., Zhang, J., Manuel, D.-B., Op de Beeck, M., Shahbaz, M., Chen, Y., Deng, X., Xu, Z., Li, J., & Liu, Z. (2022). Rotation cropping and organic fertilizer jointly promote soil health and crop production. Journal of Environmental Management, 315, 115190. https://doi.org/10.1016/j.jenvman.2022.115190
Joy, T. M., Aneesh, K. S., & Sreekumar, V. (2023). Analysis of a decision support system for supplier selection in glove industry. Materials Today: Proceedings, 72, 3186–3192. https://doi.org/10.1016/j.matpr.2022.11.344
Karimi, M., Tabiee, M., Karami, S., Karimi, V., & Karamidehkordi, E. (2024). Climate change and water scarcity impacts on sustainability in semi-arid areas: Lessons from the South of Iran. Groundwater for Sustainable Development, 24, 101075. https://doi.org/10.1016/j.gsd.2023.101075
Khalfaoui, R., Goodell, J. W., Mefteh-Wali, S., Chishti, M. Z., & Gozgor, G. (2024). Impact of climate risk shocks on global food and agricultural markets: A multiscale and tail connectedness analysis. International Review of Financial Analysis, 93, 103206. https://doi.org/10.1016/j.irfa.2024.103206
Khan, F. U., Nouman, M., Negrut, L., Abban, J., Cismas, L. M., & Siddiqi, M. F. (2024). Constraints to agricultural finance in underdeveloped and developing countries: a systematic literature review. International Journal of Agricultural Sustainability, 22(1). https://doi.org/10.1080/14735903.2024.2329388
Khan, Md. R., Alam, M. J., Tabassum, N., & Khan, N. A. (2022). A Systematic Review of the Delphi–AHP Method in Analyzing Challenges to Public-Sector Project Procurement and the Supply Chain: A Developing Country’s Perspective. Sustainability, 14(21), 14215. https://doi.org/10.3390/su142114215
Khatri, P., Kumar, P., Shakya, K. S., Kirlas, M. C., & Tiwari, K. K. (2023). Understanding the intertwined nature of rising multiple risks in modern agriculture and food system. Environment, Development and Sustainability, 26(9), 24107–24150. https://doi.org/10.1007/s10668-023-03638-7
Khosravi, K., Rezaie, F., Cooper, J. R., Kalantari, Z., Abolfathi, S., & Hatamiafkoueieh, J. (2023). Soil water erosion susceptibility assessment using deep learning algorithms. Journal of Hydrology, 618, 129229. https://doi.org/10.1016/j.jhydrol.2023.129229
Levis, C., Flores, B. M., Campos-Silva, J. V., Peroni, N., Staal, A., Padgurschi, M. C. G., Dorshow, W., Moraes, B., Schmidt, M., Kuikuro, T. W., Kuikuro, H., Wauja, K., Kuikuro, K., Kuikuro, A., Fausto, C., Franchetto, B., Watling, J., Lima, H., Heckenberger, M., & Clement, C. R. (2024). Contributions of human cultures to biodiversity and ecosystem conservation. Nature Ecology & Evolution, 8(5), 866–879. https://doi.org/10.1038/s41559-024-02356-1
Li, C., Sha, Z., Sun, X., & Jiao, Y. (2022). The Effectiveness Assessment of Agricultural Subsidy Policies on Food Security: Evidence from China’s Poverty-Stricken Villages. International Journal of Environmental Research and Public Health, 19(21), 13797. https://doi.org/10.3390/ijerph192113797
Madani, K. (2014). Water management in Iran: what is causing the looming crisis? Journal of Environmental Studies and Sciences, 4(4), 315–328. https://doi.org/10.1007/s13412-014-0182-z
Mbukanma, I., Sithole, V. L., & Hosu, Y. S. (2025). Exploring the Factors Enhancing Marketability of Coastal Agricultural Products in Rural South Africa. Economies, 13(5), 141. https://doi.org/10.3390/economies13050141
Mohammadrezaei, M., Meredith, D., McNamara, J., Kinsella, J., & Flannery, S. (2023). Do social influences, awareness, or experience matter? Toward a better understanding of Farm-related Injury Risk Perception among agricultural science college students in Ireland. Frontiers in Public Health, 11. https://doi.org/10.3389/fpubh.2023.1076332
Molavi-Arabshahi, M., & Eskandari, S. (2025). Analyzing the cyclical impact of sunspot activity and ENSO on precipitation patterns in Gilan province: a wavelet-based approach. Scientific Reports, 15(1), 22184. https://doi.org/10.1038/s41598-025-05797-1
Motamed, M. K., Javadi Baghi, S., Ghorbani Piralidehi, F., & Esfanjari Kenari, R. (2025). Identification and prioritization of strategies for achieving sustainable agriculture in rice production (Case study: Guilan Province, northwest Iran). Caspian Journal of Environmental Sciences, 23(3), 757–769. https://doi.org/10.22124/cjes.2025.8954
Naeem, M., Farid, H. U., Madni, M. A., Albano, R., Inam, M. A., Shoaib, M., Shoaib, M., Rashid, T., Dilshad, A., & Ahmad, A. (2024). GIS-Based Analytical Hierarchy Process for Identifying Groundwater Potential Zones in Punjab, Pakistan. ISPRS International Journal of Geo-Information, 13(9), 317. https://doi.org/10.3390/ijgi13090317
Naqvi, H. R., Mallick, J., Devi, L. M., & Siddiqui, M. A. (2013). Multi-temporal annual soil loss risk mapping employing Revised Universal Soil Loss Equation (RUSLE) model in Nun Nadi Watershed, Uttrakhand (India). Arabian Journal of Geosciences, 6(10), 4045–4056. https://doi.org/10.1007/s12517-012-0661-z
Niles, M. T., Lubell, M., & Brown, M. (2015). How limiting factors drive agricultural adaptation to climate change. Agriculture, Ecosystems & Environment, 200, 178–185. https://doi.org/10.1016/j.agee.2014.11.010
Nugroho, A. D., Bhagat, P. R., Magda, R., & Lakner, Z. (2021). The impacts of economic globalization on agricultural value added in developing countries. PLOS ONE, 16(11), e0260043. https://doi.org/10.1371/journal.pone.0260043
Nwer, B. A., Ben Mahmoud, K. R., Zurqani, H. A., & Elaalem, M. M. (2021). Major limiting factors affecting agricultural use and production. In The Soils of Libya (pp. 65-75). https://doi.org/10.1007/978-3-030-66368-1_5
Oruma, S. O., Misra, S., & Fernandez-Sanz, L. (2021). Agriculture 4.0: An Implementation Framework for Food Security Attainment in Nigeria’s Post-Covid-19 Era. IEEE Access, 9, 83592–83627. https://doi.org/10.1109/ACCESS.2021.3086453
Ostad-Ali-Askari, K., & Shayannejad, M. (2021). Quantity and quality modelling of groundwater to manage water resources in Isfahan-Borkhar Aquifer. Environment, Development and Sustainability, 23(11), 15943–15959. https://doi.org/10.1007/s10668-021-01323-1
Pradeep, G. S., Krishnan, M. V. N., & Vijith, H. (2015). Identification of critical soil erosion prone areas and annual average soil loss in an upland agricultural watershed of Western Ghats, using analytical hierarchy process (AHP) and RUSLE techniques. Arabian Journal of Geosciences, 8(6), 3697–3711. https://doi.org/10.1007/s12517-014-1460-5
Rahmani, S., Yazdani, S., Mahmoudi, A., Shokat Fadaei, M., & Souri, A. (2017). An Investigation into the Economic Benefits and Savings Resulting From the Pressurized Irrigation System Development in Ardabil Province. Journal of Hydrosciences and Environment, 1(2), 1–11. https://doi.org/10.22111/jhe.2017.3353
Rahmati, K., Ashofteh, P.-S., & Loáiciga, H. A. (2021). Application of the Grasshopper Optimization Algorithm (GOA) to the Optimal Operation of Hydropower Reservoir Systems Under Climate Change. Water Resources Management, 35(13), 4325–4348. https://doi.org/10.1007/s11269-021-02950-z
Rajbonshi, M. P., Gupta, D., & Mitra, S. (2026). Seasonal comparison of the impacts of climate-smart agrotechnologies on greenhouse gas mitigation in flooded rice fields: Application of multi-criteria decision making (MCDM) technique. Agricultural Systems, 231, 104550. https://doi.org/10.1016/j.agsy.2025.104550
Rezaee, L., Moosavi, A. A., Davatgar, N., & Sepaskhah, A. R. (2020). Soil quality indices of paddy soils in Guilan province of northern Iran: Spatial variability and their influential parameters. Ecological Indicators, 117, 106566. https://doi.org/10.1016/j.ecolind.2020.106566
Rodrigues de Oliveira, B., & Duarte, M. A. Q. (2024). Automatic and Semi-automatic Analytic Hierarchy Process (AHP). Trends in Agricultural and Environmental Sciences, e240009. https://doi.org/10.46420/TAES.e240009
Rozos, D., Skilodimou, H. D., Loupasakis, C., & Bathrellos, G. D. (2013). Application of the revised universal soil loss equation model on landslide prevention. An example from N. Euboea (Evia) Island, Greece. Environmental Earth Sciences, 70(7), 3255–3266. https://doi.org/10.1007/s12665-013-2390-3
Saaty, T. L. (2008). Decision making with the analytic hierarchy process. International Journal of Services Sciences, 1(1), 83-98. https://doi.org/10.1504/IJSSCI.2008.017590
Saaty, T. L. (1990). How to make a decision: The analytic hierarchy process. European Journal of Operational Research, 48(1), 9–26. https://doi.org/10.1016/0377-2217(90)90057-I
Sapbamrer, R., & Thammachai, A. (2021). A Systematic Review of Factors Influencing Farmers’ Adoption of Organic Farming. Sustainability, 13(7), 3842. https://doi.org/10.3390/su13073842
Schöning, J., Wachter, P., & Trautz, D. (2023). Crop rotation and management tools for every farmer? Smart Agricultural Technology, 3, 100086. https://doi.org/10.1016/j.atech.2022.100086
Senapati, U., & Das, T. K. (2024). Delineation of potential alternative agriculture region using RS and AHP-based GIS techniques in the drought prone upper Dwarakeswer river basin, West Bengal, India. Ecological Modelling, 490, 110650. https://doi.org/10.1016/j.ecolmodel.2024.110650
Shin, E., Shin, Y., Lee, S.-W., & An, K. (2024). Evaluating the Environmental Factors of Organic Farming Areas Using the Analytic Hierarchy Process. Sustainability, 16(6), 2395. https://doi.org/10.3390/su16062395
Shojaei‐Miandoragh, M., Bijani, M., & Abbasi, E. (2020). Farmers’ resilience behaviour in the face of water scarcity in the eastern part of Lake Urmia, Iran: an environmental psychological analysis. Water and Environment Journal, 34(4), 611–622. https://doi.org/10.1111/wej.12489
Song, Q., Ma, M., Liu, Y., Wang, Z., Wu, W., Xu, Z., & Xue, J. (2025). Identifying groundwater potential zones in a typical irrigation district using the geospatial technique and analytic hierarchy process. Geocarto International, 40(1). https://doi.org/10.1080/10106049.2025.2453025
Špendl, R., Bohanec, M., & Rajkovič, V. (2003). Comparative analysis of AHP and DEX decision making methods. Program and Abstracts of the International Conference on Methodology and Statistics; Mrvar, A., Ferligoj, A., Eds, 65–66.
Taherzadeh-Shalmaei, N., Rafiee, M., Kaab, A., Khanali, M., Vaziri Rad, M. A., & Kasaeian, A. (2023). Energy audit and management of environmental GHG emissions based on multi-objective genetic algorithm and data envelopment analysis: An agriculture case. Energy Reports, 10, 1507–1520. https://doi.org/10.1016/j.egyr.2023.08.020
Tashayo, B., Honarbakhsh, A., Azma, A., & Akbari, M. (2020). Combined Fuzzy AHP–GIS for Agricultural Land Suitability Modeling for a Watershed in Southern Iran. Environmental Management, 66(3), 364–376. https://doi.org/10.1007/s00267-020-01310-8
Terefe, T. T., Legese, B. B., Abebaw, S., Bojer, A. K., & Nadarajah, S. (2025). Evaluating irrigation suitability for wheat in East Shewa, Ethiopia using remote sensing and AHP. Agricultural Water Management, 319, 109777. https://doi.org/10.1016/j.agwat.2025.109777
Veisi, H., Deihimfard, R., Shahmohammadi, A., & Hydarzadeh, Y. (2022). Application of the analytic hierarchy process (AHP) in a multi-criteria selection of agricultural irrigation systems. Agricultural Water Management, 267, 107619. https://doi.org/10.1016/j.agwat.2022.107619
Veisi, H., Liaghati, H., & Alipour, A. (2016). Developing an ethics-based approach to indicators of sustainable agriculture using analytic hierarchy process (AHP). Ecological Indicators, 60, 644–654. https://doi.org/10.1016/j.ecolind.2015.08.012
Wadumestrige Dona, C. G., Mohan, G., & Fukushi, K. (2021). Promoting Urban Agriculture and Its Opportunities and Challenges—A Global Review. Sustainability, 13(17), 9609. https://doi.org/10.3390/su13179609
Wang, Z., Wang, J., Zhang, G., & Wang, Z. (2021). Evaluation of Agricultural Extension Service for Sustainable Agricultural Development Using a Hybrid Entropy and TOPSIS Method. Sustainability, 13(1), 347. https://doi.org/10.3390/su13010347
Yang, Z., & Solangi, Y. A. (2024). Analyzing the relationship between natural resource management, environmental protection, and agricultural economics for sustainable development in China. Journal of Cleaner Production, 450, 141862. https://doi.org/10.1016/j.jclepro.2024.141862
Yousefi, R. (2025). Suitable plants as a second crop after Rice in the Paddy Fields of Guilan Province. Journal of Environmental Science Studies, 10(3), 10631-10643. doi: 10.22034/jess.2025.540405.2393. (In Persian).
Zeng, J., Li, H., Tang, Y., & Qing, P. (2022). Does Adoption of Biofortification Increase Return on Investment? Evidence from Wheat Farmers in China. Agronomy, 12(9), 2019. https://doi.org/10.3390/agronomy12092019
Ziadi, K., Barakat, A., Elaloui, A., Ouayah, M., & Namous, M. (2025). Prioritization of the Tassaoute Watershed (Morocco) for soil erosion using analytical hierarchy process (AHP) and geospatial techniques. Geosystems and Geoenvironment, 4(2), 100389. https://doi.org/10.1016/j.geogeo.2025.100389
Zhang, S., Liu, J., Li, C., Yu, F., Jing, L., & Chen, W. (2023). Evaluation of Water Resources Utilization Efficiency Based on DEA and AHP under Climate Change. Water, 15(4), 718. https://doi.org/10.3390/w15040718
Zumara, R., & Nasher, N. M. R. (2024). Soil erodibility mapping of hilly watershed using analytical hierarchy process and geographical information system: A case of Chittagong hill tract, Bangladesh. Heliyon, 10(5), e26728. https://doi.org/10.1016/j.heliyon.2024.e26728
Iranian Journal of Soil and Water Research
Volume 57, Issue 7
September 2026
Pages 1513-1536