Davood Mokhtari; Aliakbar Rasouli; Monire Moosabeigi
Abstract
Introduction: One of the most influential factors in the occurence of a flood in the spillway basins is proposed to be the unsuitable or exorbitanceuse use of lands. One of the flood management solutions is to optimize the land use allocation by considering multiple objectives and parameters. In this ...
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Introduction: One of the most influential factors in the occurence of a flood in the spillway basins is proposed to be the unsuitable or exorbitanceuse use of lands. One of the flood management solutions is to optimize the land use allocation by considering multiple objectives and parameters. In this regard, GIS capabilities could be applied as one of the novel scientific and technical methods along with taking the advantage of Artifcial intelligence capabilities, such as multi-objective genetic algorithm. This research aimed to model the land use allocation in GIS platform using NSGA-II algorithm to monitor flood crisis. Material and methods: In the designed model, using the interruptive method, land’s ecological capability was extracted and then using NSGA-II algorithm capabilities, optimal applications were obtained for various parts of the area in order to decrease the flood height as well as to increase the economic profit with the least difficult change of utilities. In the designed model, the curve number parameter (CN) was used to investigate the role of land use on the flood. Results and discussion: The results of the designed model are represented in several optimal patterns that have the same applicable value. Based on the present conditions of the studied region and the expert’s opinion, the optimal model could be executed. To evaluate the capability of the designed model, the Taleghan basin was selected which is located in Alborz Province; CN range of the study area was 83 in the searching space, while in designed output models, the lowest amount of CN, with 11% decrease compared to the current situation, was about 74.5%. Also, the economic profit growth was 52.19% in this land synthetic pattern. Conclusion: The results and achievements of this study include proposing a land use optimization model based on a multi-objective genetic algorithm for flood reduction, integrated river basin management, as well as programming in an expansive form to use in future studies.
