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Optimizing Land Use and Land Cover Allocation for Flood Mitigation Using Land Use Change and Hydrological Models with Goal Programming, Chaiyaphum, Thailand

Author

Listed:
  • Athiwat Phinyoyang

    (School of Geoinformatics, Institute of Science, Suranaree University of Technology, Nakhon Ratchasima 30000, Thailand)

  • Suwit Ongsomwang

    (School of Geoinformatics, Institute of Science, Suranaree University of Technology, Nakhon Ratchasima 30000, Thailand)

Abstract

Floods represent one of the most severe natural disasters threatening the development of human society worldwide, including in Thailand. In recent decades, Chaiyaphum province has experienced a problem with flooding almost every year. In particular, the flood in 2010 caused property damage of 495 million Baht, more than 322,000 persons were affected, and approximately 1046.4 km 2 of productive agricultural area was affected. Therefore, this study examined how to optimize land use and land cover allocation for flood mitigation using land use change and hydrological models with optimization methods. This research aimed to allocate land use and land cover (LULC) to minimize the surface for flood mitigation in Mueang Chaiyaphum district, Chaiyaphum province, Thailand. The research methodology consisted of six stages: data collection and preparation, LULC classification, LULC prediction, surface runoff estimation, the optimization of LULC allocation for flood mitigation and mapping, and economic and ecosystem service value evaluation and change. According to the results of the optimization and mapping of suitable LULC allocation to minimize surface runoff for flood mitigation in dry, normal, and wet years using goal programming and the CLUE-S model, the suitable LULC allocation for flood mitigation in 2049 under a normal year could provide the highest future economic value and gain. In the meantime, the suitable LULC allocation for flood mitigation in 2049 under a drought year could provide the highest ecosystem service value and gain. Nevertheless, considering future economic and ecosystem service values and changes with surface runoff reduction, the most suitable LULC allocation for flood mitigation is a normal year. Consequently, it can be concluded that the derived results of this study can be used as primary information for flood mitigation project implementation. Additionally, the presented conceptual framework and research workflows can be used as a guideline for government agencies to examine other flood-prone areas for flood mitigation in Thailand.

Suggested Citation

  • Athiwat Phinyoyang & Suwit Ongsomwang, 2021. "Optimizing Land Use and Land Cover Allocation for Flood Mitigation Using Land Use Change and Hydrological Models with Goal Programming, Chaiyaphum, Thailand," Land, MDPI, vol. 10(12), pages 1-41, November.
    • Handle: RePEc:gam:jlands:v:10:y:2021:i:12:p:1317-:d:691684
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    References listed on IDEAS

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    Cited by:

    1. Hui Xu & Junlong Gao & Xinchun Yu & Qianqian Qin & Shiqiang Du & Jiahong Wen, 2024. "Assessment of Rainstorm Waterlogging Disaster Risk in Rapidly Urbanizing Areas Based on Land Use Scenario Simulation: A Case Study of Jiangqiao Town in Shanghai, China," Land, MDPI, vol. 13(7), pages 1-18, July.
    2. Kyu-Won Seo & Seung Beom Seo & Kyeung-Min Kim & Chan Park & Park Hyemin & Jonghyun Yoo, 2024. "Genetic algorithm-based allocation of LID practices to mitigate urban flooding," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 120(1), pages 447-462, January.

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