Abstract
BackgroundUrban flood susceptibility evaluation (FSE) can utilize empirical and rational procedures to focus on the urban flood evaluation using physical coefficients and land-use change ratios. The main aim of the present paper was to evaluate a flood susceptibility model in the southern watersheds of Mashhad city, in Iran, for 2010, 2020, and 2030. The construction of the model depended on the utilization of some global datasets to estimate the runoff coefficients of the watersheds, peak flood discharges, and flood susceptibility evaluations.Results and conclusionsBased on the climatic precipitation and urban sprawl variation, our results revealed the mean values of the runoff coefficient (Cr) from 0.50 (2010) to 0.65 (2030), where the highest values of Cr (> 0.70) belonged to the watersheds with real estate cover, soil unit of the Mollisols, and the slope ranges over 5–15%. The averagely cumulative flood discharges were estimated from 2.04 m3/s (2010) to 5.76 m3/s (2030), revealing an increase of the flood susceptibility equal 3.2 times with at least requirement of an outlet cross-section by > 46 m2 in 2030. The ROC curves for the model validity explained AUC values averagely over 0.8, exposing the very good performance of the model and excellent sensitivity.
Highlights
Recent scientific publications support the fact that the occurrences of climate-related disasters have significantly increased under the abrupt changes through the hydro-meteorological conditions (Huang et al 2017; Ahmadi and Moradkhani 2019; Mihu-Pintilie et al 2019)
The runoff coefficient is a fraction of rainfall volume retained by the land, soil, and vegetation characteristics, i.e., it relates to the transformation of the total rainfall in net rainfall influenced by infiltration, canopy interception, and surface detention (Del Giudice et al 2014)
We evaluated a flood susceptibility model in the southern watersheds of Mashhad city, in Iran, during three temporal windows of 2010, 2020, and 2030
Summary
Recent scientific publications support the fact that the occurrences of climate-related disasters (e.g., flash floods and severe storms) have significantly increased under the abrupt changes through the hydro-meteorological conditions (Huang et al 2017; Ahmadi and Moradkhani 2019; Mihu-Pintilie et al 2019). Urban growth can be responsible for over 50% of the increase in flood risk, and urban areas face global challenges of flood susceptibility due to climate change and the development of residential areas and urban sprawl (Berndtsson et al 2019). In this regard, urbanization impacts on runoff measures and flood damages are important fields of research (Isidoro et al 2012), especially in the non-western. The construction of the model depended on the utilization of some global datasets to estimate the runoff coefficients of the watersheds, peak flood discharges, and flood susceptibility evaluations
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