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<p>The present research investigates the influential factors on flood susceptibility and the occurrence of future floods in the Zarrinehroud watershed, located in West Azerbaijan Province, one of the sub-basins of Lake Urmia. Considering population growth, social and economic development, and climate changes resulting from global warming, flood damages in this region have increased. This research aims to identify the main factors influencing flood susceptibility and predict the likelihood of future floods. To achieve this goal, monitoring and assessing land use changes in the past seven years were initially conducted utilizing Sentinel-2 images through the object-based method and image classification with the SVM algorithm. Additionally, to simulate future land use changes, the CA-MARKOV algorithm was employed. Ultimately, runoff simulation was performed using the InVEST model, incorporating variables such as precipitation (operating the LARS-WG software, derived from the ACCESS-CM2 climate model under the SSP2-4.5 and SSP5-8.5 scenarios), land use, soil hydrological group, and the curve number specific to the study watershed. The final results indicate high runoff potential for 2016, 2023, and 2030 in the southern and eastern parts of the Zarrinehroud watershed. This is while the potential for runoff production is low in the northwest. According to the prediction results for the year 2030, the potential for runoff production was estimated to be at maximum and minimum values of 111 and 0 m3, respectively. Therefore, runoff is expected to increase in most parts of the Zarrineh-Roud watershed.</p>

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Assessing flood potential prediction under joint LULC and climate change in a mountainous watershed, Northwest Iran

  • 期刊论文

  • 发表日期：

    2025年11月5日

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  • Tayebeh Irani,
  • Hirad Abghari,
  • Ali Akbar Rasouli

摘要

The present research investigates the influential factors on flood susceptibility and the occurrence of future floods in the Zarrinehroud watershed, located in West Azerbaijan Province, one of the sub-basins of Lake Urmia. Considering population growth, social and economic development, and climate changes resulting from global warming, flood damages in this region have increased. This research aims to identify the main factors influencing flood susceptibility and predict the likelihood of future floods. To achieve this goal, monitoring and assessing land use changes in the past seven years were initially conducted utilizing Sentinel-2 images through the object-based method and image classification with the SVM algorithm. Additionally, to simulate future land use changes, the CA-MARKOV algorithm was employed. Ultimately, runoff simulation was performed using the InVEST model, incorporating variables such as precipitation (operating the LARS-WG software, derived from the ACCESS-CM2 climate model under the SSP2-4.5 and SSP5-8.5 scenarios), land use, soil hydrological group, and the curve number specific to the study watershed. The final results indicate high runoff potential for 2016, 2023, and 2030 in the southern and eastern parts of the Zarrinehroud watershed. This is while the potential for runoff production is low in the northwest. According to the prediction results for the year 2030, the potential for runoff production was estimated to be at maximum and minimum values of 111 and 0 m3, respectively. Therefore, runoff is expected to increase in most parts of the Zarrineh-Roud watershed.