Open AccessLand use optimization through bridging multiobjective optimization and multicriteria decision‐making models (case study: Tilabad Watershed, Golestan Province, Iran)
Author(s) -
Sheikh Vahedberdi,
Salmani Hossein,
Salman Mahiny Abdolrassoul,
Ownegh Majid,
Fathabadi Abolhasan
Publication year - 2021
Publication title -
natural resource modeling
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.28
H-Index - 32
eISSN - 1939-7445
pISSN - 0890-8575
DOI - 10.1111/nrm.12301
Subject(s) - watershed , multi objective optimization , multiple criteria decision analysis , surface runoff , land use , maximization , environmental science , environmental resource management , profit maximization , computer science , water resource management , profit (economics) , operations research , mathematical optimization , civil engineering , ecology , engineering , economics , mathematics , machine learning , biology , microeconomics
This study aims to present an efficient methodology for land use optimization based on minimization of runoff and sediment and maximization of economic benefits, occupational opportunities, and land use suitability in the Tilabad watershed in northeast of Iran. The land use map of the area was prepared using the Landsat satellite images and field surveys. The amounts of runoff and sediment were estimated via SWAT model. The TOPSIS multicriteria decision‐making (MCDM) approach was applied on the results of the multiobjective optimization (MOO) based on non‐dominated sorting genetic algorithm II (NSGA II) to choose the final optimal solution among the Pareto solutions front generated by MOO. The results indicated that the area of agriculture and rangelands should decrease, and the area of forests should increase to achieve the defined objectives. Overall, results indicated that integration of MOO and MCDM provides an efficient procedure for land use optimization in a complex watershed. Recommendations for Resource ManagersThe optimization of land use allocation across a complex watershed requires the combined application of several models and techniques to achieve a sustainable decision‐making process. By optimization of land use patterns according to the final solution, the surface runoff and sediment load of the watershed will decline, while the economic profit and land use suitability will improve. Despite using a maximization objective function, the land‐based job opportunities might decrease across a watershed by optimization of land use allocation, but this can be considered as an opportunity for provision of manpower to other socioeconomic sectors.