Flash floods cause severe natural disasters over the world generating property and infrastructures damages, poverty and loss of human life, among others. Mediterranean coastal watersheds are specially sensible to flash floods effects due to their typical drainage basin features (steep slopes, short concentration times, complex orography, etc.) and the high rainfall intensity typical of convective systems. In the present study, the temporal evolution of the hydrological answer in five Mediterranean (SE Spain) ravine basins with sizes from 10.2 km to 200.9 km were analysed. A sub-daily SWAT model was used at watershed scale to capture the complex hydrological dynamics. Five land use scenarios corresponding to no-urbanization (baseline), 1990, 2000, 2006 and 2012 were evaluated using GIS-based tools. Additionally, statistical significant differences among the studied scenarios were checked employing the Kruskal-Wallis and post-hoc tests based on Mann-Whitney test with BH correction. Our results show that flash flood risks have increased in the studied catchments due to changes in land uses, particularly affected by a large urban growth. Observed changes in soil uses have been important since the sixties of the last century, because of a high demographic and touristic pressure and specially the urban area has enhanced considerably during the last 22 years. Currently, some of these catchments present around 70% of their surface occupied by urban land uses with high population density producing curve number surpasses 85 and 90 levels. The hydrological response of the studied basins changed to higher flow rate peaks and shorter concentration times. Some discharges increased significantly from the baseline land use scenario (≈50 m/s, 190 m/s, 380 m/s) to the most urbanised scenario (≈235 m/s, 385 m/s, 940 m/s), respectively. These findings provide to urban planning policy makers very useful information in the face of flash flood effects, which have cost even human lifes in the studied ravine basins during last years.
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http://dx.doi.org/10.1016/j.scitotenv.2018.12.034 | DOI Listing |
Heliyon
January 2025
Amrita School for Sustainable Futures, Amrita Vishwa Vidyapeetham, Amritapuri Campus, Kerala State, India.
The State of Uttarakhand, located in the Himalayan region of North India, suffered one of the worst flash floods on June 16, 2013 where 5700 were presumed dead or missing. Since then, the region has suffered two other major flooding events in 2021 and 2023. Although numerous national government agencies recommend keeping disaster preparedness kits ready, the saliency and effectiveness of a household disaster preparedness kit in helping survivors, has not been empirically tested in the region.
View Article and Find Full Text PDFSci Data
January 2025
University of Southern California, Viterbi School of Engineering, 3737 Watt Way, Powell Hall of Engineering, Los Angeles, CA, 90089, USA.
Soil erosion in North Africa modulates agricultural and urban developments as well as the impacts of flash floods. Existing investigations and associated datasets are mainly performed in localized urban areas, often representing a limited part of a watershed. The above compromises the implementation of mitigation measures for this vast area under accentuating extremes and continuous hydroclimatic fluctuations.
View Article and Find Full Text PDFSci Rep
January 2025
Key Laboratory of Water Cycle and Related Land Surface Processes, Institute of Geographic Sciences and Natural Resources Research (IGSNRR), Chinese Academy of Sciences (CAS), Beijing, 100101, China.
Flash flood susceptibility mapping is essential for identifying areas prone to flooding events and aiding decision-makers in formulating effective prevention measures. This study aims to evaluate the flash flood susceptibility in the Yarlung Tsangpo River Basin (YTRB) using multiple machine learning (ML) models facilitated by the H2O automated ML platform. The best-performing model was used to generate a flash flood susceptibility map, and its interpretability was analyzed using the Shapley Additive Explanations (SHAP) tree interpretation method.
View Article and Find Full Text PDFMar Pollut Bull
December 2024
Aix Marseille University, Université de Toulon, CNRS, IRD, MIO UM110, 13288 Marseille, France; Department Water-Environment-Oceanography, University of Science and Technology of Hanoi (USTH), Vietnamese Academy of Science and Technology (VAST), 18 Hoang Quoc Viet, Hanoi 100000, Viet Nam; IRD, Chulalongkorn University, 254 Henri Dunant Road, Pathumwan, 10330 Bangkok, Thailand.
Environ Monit Assess
December 2024
Wadia Institute of Himalayan Geology, Dehradun, India, 248001.
The Himalayas experiences several cloudburst events due to its varied physiographical, geomorphological, and geological conditions and high rainfall. Uttarakhand is one of the Indian states circumscribed by the Himalayan ranges and has experienced a rise in the number of cloudburst catastrophes in the last few decades. These events cause substantial loss of life and property; however, very few studies have characterized these unpredictable cloudburst-induced flash floods in different regions of Uttarakhand.
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