Search

On November 23, 2018, cascading rainfall events that occurred in the upstream section of wadi Al-Lith, which is located in the western part of the Kingdom of Saudi Arabia, caused a failure in the Al-Lith earthen dam. This event was followed by a large-scale devastating flood that inundated the area downstream of the dam, damaging infrastructure and property. The main scope of this work was to identify the causes of catastrophic flooding and ways to prevent and mitigate the potential consequences of a future flood occurrence in the study area. For this purpose, remote sensing images, DEM, field observations, and rainfall data were used. A geospatial integrated approach using a GIS, remote sensing, hydromorphological analysis, and rainfall-runoff modeling was utilized to provide a better understanding of the hydrology of the wadi Al-Lith catchment. Various methods were used for rainfall frequency analyses; supervised classification was applied on Landsat (OLI), in which land-use types were classified to identify the curve number values. Rainfall-runoff modeling was conducted using the catchment characteristics and rainfall analysis to calculate flood volumes and peak discharges. Peak discharge results at the flood event on November 23, 2018, and at 5-and 100-year return periods were used for the prediction of flood extent using the 2D HEC-RAS model. Water inundated depth and velocity were mapped. The result of the 5-year return period simulated model showed a good correlation with the flood extent of the event on November 23, 2018 that extracted from the sentinel-2 image. This model was validated using field observation data and remote sensing interpretation at the real flood event of November 2018. The flood model indicated that a dam failure with the substantial release of an enormous amount of water in a short period created exacerbates the problem. Also, the simulated model of the 100-year return period showed high-risk of the whole floodplain area of Wadi Al-Lith and the urbanized zone, where utterly devastation could be occurred. Finally, the results showed that a new dam proposal is urgently required to prevent the area from future flood events to replace the failed dam with a 45 m high dam. In this case, the reservoir capacity is estimated to be ~147.4 million m3, which is above the runoff volume for a 200-year return period. © 2021 Gebr. Borntraeger Verlagsbuchhandlung, Stuttgart, Germany.

Multi-hazard assessment modeling comprises an essential tool in any plan that aims to mitigate the impact of future natural disasters. For a particular area they can be generated by combining assessment maps for different types of natural hazards. In the present study, the analytical hierarchy process (AHP) supported by a Geographical Information System (GIS) was utilized to initially produce assessment maps on hazards from landslides, floods and earthquakes and subsequently to combine them into a single multi-hazard map. Evaluation of the reliability of the proposed model predictions was performed through uncertainty analysis of the variables that we used for producing the final model. The drainage basin of Peneus (Pinios) River (Western Peloponnesus, Greece), an area that is prone to landslides, floods and seismic events, was selected for the implementation of the aforementioned approach. Our findings revealed that the high hazard zones are mainly distributed in the western and north-eastern part of the region under investigation. The calculated multi-hazard map, which corresponds to the potential urban development suitability map of the study area, was classified into five classes, namely of very low, low, moderate, high and very high suitability. The most suitable areas for urban development are distributed mostly in the eastern part, in agreement with the low and very low hazard level for the three considered natural hazards. In addition, by performing uncertainty analysis we showed that the spatial distribution of the suitability zones does not change significantly. Ultimately, the final map was verified using the actual inventory of landslides and floods that affected the study area. In this context, we showed that 80% of the landslide occurrences and all the recorded flood events fall within the boundaries of the moderate, low and very low suitability zones. Consequently, the predictive capacity of the applied method is quite good. Finally, the spatial distribution of the urban areas and the road network were compared with the derived suitability map and the results revealed that approximately 50% of both of them are located within areas susceptible to natural hazards. The proposed approach can be useful for engineers, planners and local authorities in spatial planning and natural hazard management. © 2019, Springer-Verlag GmbH Germany, part of Springer Nature.