Modeling of land use/land cover change impact on urban ecological flood resilience: a case study of Rasht city
Document Type : Research Paper
Authors
1 Department of Landscape Architecture, Faculty of Agriculture, University of Tabriz, Tabriz, Iran.
2 Department of Physical Geography, Faculty of Geography, University of Tehran, Tehran, Iran.
10.22059/jne.2024.382160.2710
Abstract
The changes in land use and land cover (LULC) driven by increasing human activities have resulted in a multitude of environmental challenges, including an elevated risk of flooding in densely populated urban areas. To achieve sustainable development goals, it is imperative to employ spatial-temporal modeling of urban runoff and floods and to assess urban ecological resilience to this challenge. In this study, Landsat satellite data was employed within the Google Earth Engine web-based platform to generate LULC maps for the city of Rasht, which is undergoing rapid urbanization, for the years 1990, 2005, and 2020. A CA-Markov model was employed to predict the LULC map for 2035. Subsequently, the InVEST-UFRM model was employed to assess the generation of runoff and the resilience of urban areas against potential flood hazards during these years. The findings indicated that the study area experienced a high rate of urbanization between 1990 and 2020. This trend is anticipated to persist, accompanied by a notable expansion of built-up areas and a considerable reduction in green infrastructure in the future. The InVEST-UFRM model yielded results indicating that the area with a high potential for flooding constituted 7.5%, 12.6%, and 21% of the total area in 1990, 2005, and 2020, respectively. The model predicts that this area will reach 28.2% by 2035. In conclusion, the findings of this study demonstrate that LULC changes have significantly impacted the reduction in Rasht city's ecological resilience against flood hazards. This research, which combines remote sensing data with new technologies, provides insights into assessing urban flood resilience under the influence of land use changes, particularly in data-limited areas. The results of this study can be used as a strategic tool for urban managers to make informed decisions for effective urban flood management in areas with similar characteristics.
Keywords
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