Optimal land-use allocation using MCDM and SWAT for the Hablehroud Watershed, Iran

• Published in: Land use policy 2021-01, Vol.100, p.104930, Article 104930
• Main Authors: Arjomandi, Amin, Mortazavi, Seyed Abolghasem, Khalilian, Sadegh, Garizi, Arash Zare
• Format: Article
• Language: English
• Subjects: Agricultural production; Agricultural watersheds; Allocation; Criteria; Decision making; Decision-making methods; Economic problems; Economics; Goal programming; Hablehroud watershed; Hydrologic simulation; Land; Land use; Land-use allocation; Multiple criterion; Optimization; Watershed management; Watersheds
• ISSN: 0264-8377; 1873-5754
• DOI: 10.1016/j.landusepol.2020.104930

•Several multi-criterion decision-making methods were used for land use optimization.•Weighted goal programming model provides better solutions than the other methods.•Land use optimization could reduce harmful environmental impacts up to 74 percent.•Improvement of economic criteria raises socio-economic and environmental conditions. The watershed, a dynamic and integrated social, economic, and biological system, plays an important role in the growth and development of the economy. Watersheds as a basis to support natural life and human activities have been heavily damaged over the past few centuries. One of the major causes of which is the inappropriate land-use allocation. Studies on land-use allocation mostly investigate optimization methods apart from each other but combining different approaches and comparing outcomes of different methods seems to be more helpful, especially for the decision-makers in a watershed. Hablehroud watershed as an important agricultural production region in Iran has been facing different ecological and economic problems during recent decades. Therefore, the current study aimed to determine the optimal land-use allocation according to the economic, social, and environmental criteria in the Hablehroud watershed using multi-criteria decision-making (MCDM) method. The optimal land-use solutions were obtained using the weighted goal programming (WGP), lexicographic goal programming (LGP), and compromise programming (CP) methods. The results indicated that after the optimization, in all the scenarios (economic, neutral and environmental), the average values of the environmental criteria decreased 66 % in WGP, 65 % in LGP and 66.6 % in CP and the social criterion increased 62 % in WGP, 82 % in LGP, and 46.3 % in CP. The values of the economic criteria (profit) increased 2% in WGP, 21 % in LGP and 6% (on average) in CP, only in the economic scenario. However, the economic scenarios showed a better results in all of the methods, based on which the recommendations were made to improve watershed management policies based on the optimal land-use patterns.