Management of socio-ecological wetland systems using mulino decision support system and analytic network process

• Published in: International journal of environmental science and technology (Tehran) Vol. 19; no. 4; pp. 2559 - 2572
• Main Authors: Zare, G., Malekmohammadi, B., Jafari, H., Yavari, A. R., Nohegar, A.
• Format: Journal Article
• Language: English
• Published: Berlin/Heidelberg Springer Berlin Heidelberg 01.04.2022
• Subjects: Aquatic Pollution; Earth and Environmental Science; Ecotoxicology; Environment; Environmental Chemistry; Environmental Science and Engineering; Original Paper; Soil Science & Conservation; Waste Water Technology; Water Management; Water Pollution Control; Decision-making; Driving forces-pressures-state-impacts-responses; Iran; Geographic information system; Parishan wetland
• ISSN: 1735-1472; 1735-2630
• DOI: 10.1007/s13762-021-03368-1

Wetlands play an important role in the life of the planet. In order to preserve and revive the wetlands, decision-makers need to employ appropriate approaches and tools to identify the main driving forces and this could be an important step toward adopting effective strategies and making critical decisions. The current study used the combined analytic network process with driving forces-pressures-state-impacts-responses framework in mulino decision support system. The Parishan wetland, located in Iran, has been selected as the case study. After an initial study of the conditions of Parishan wetland and identifying the stakeholders, the opinions of experts and local residents were gathered to identify the most important parameters influencing the conditions of the wetland. The analytic network process model was used to improve and reduce the number of input parameters to mulino decision support system. Then, the most important and the best responses associated with the management of Parishan wetland were identified through questionnaires and imported into mulino decision support system along with other components. Finally, the mulino decision support system decision algorithm was run. The findings revealed that reduced precipitation, land-use change, competition of farmers in the wetland to use water resources, and increased temperature were the main driving forces. Moreover, water transfer from the Nargesi Dam was chosen as the most effective response. The results suggest that the driving forces-pressures-state-impacts-responses framework in mulino decision support system algorithm combined with analytic network process model can be used as an integrated tool to study and manage wetland socio-ecological ecosystems.