Flash flood simulation for Tabuk City catchment, Saudi Arabia

2016 ◽  
Vol 9 (3) ◽  
Author(s):  
Eyad Abushandi
Keyword(s):  
Saudi Arabia ◽  
Flash Flood ◽  
Flood Simulation

scholarly journals Volumetric Quantification of Flash Flood Using Microwave Data on a Watershed Scale in Arid Environments, Saudi Arabia

2021 ◽  
Vol 13 (8) ◽  
pp. 4115
Author(s):  
Jaka Budiman ◽  
Jarbou Bahrawi ◽  
Asep Hidayatulloh ◽  
Mansour Almazroui ◽  
Mohamed Elhag
Keyword(s):  
Saudi Arabia ◽  
Flash Flood ◽  
Remote Sensing Data ◽  
Surface Elevation ◽  
Flood Mapping ◽  
Depth Information ◽  
Arid Environments ◽  
Volume Calculation ◽  
Flood Depth ◽  
Flood Volume

Actual flood mapping and quantification in an area provide valuable information for the stakeholder to prevent future losses. This study presents the actual flash flood quantification in Al-Lith Watershed, Saudi Arabia. The study is divided into two steps: first is actual flood mapping using remote sensing data, and the second is the flood volume calculation. Two Sentinel-1 images are processed to map the actual flood, i.e., image from 25 May 2018 (dry condition), and 24 November 2018 (peak flood condition). SNAP software is used for the flood mapping step. During SNAP processing, selecting the backscatter data representing the actual flood in an arid region is challenging. The dB range value from 7.23–14.22 is believed to represent the flood. In GIS software, the flood map result is converted into polygon to define the flood boundary. The flood boundary that is overlaid with Digital Elevation Map (DEM) is filled with the same elevation value. The Focal Statistics neighborhood method with three iterations is used to generate the flood surface elevation inside the flood boundary. The raster contains depth information is derived by subtraction of the flood surface elevation with DEM. Several steps are carried out to minimize the overcalculation outside the flood boundary. The flood volume can be derived by the multiplication of flood depth points with each cell size area. The flash flood volume in Al-Lith Watershed on 24 November 2018 is 155,507,439 m3. Validity checks are performed by comparing it with other studies, and the result shows that the number is reliable.

scholarly journals Designating Appropriate Areas for Determining Potential Rainwater Harvesting in Arid Region Using a GIS-based Multi-criteria Decision Analysis ‏

2021 ◽  
Author(s):  
Mohamed Abd-el-Kader ◽  
Ahmed Elfeky ◽  
Mohamed Saber ◽  
Maged AlHarbi ◽  
abed Alataway
Keyword(s):  
Water Management ◽  
Saudi Arabia ◽  
Decision Analysis ◽  
Rainwater Harvesting ◽  
Flash Flood ◽  
Flood Hazard ◽  
Flash Floods ◽  
Flood Mitigation ◽  
Water Harvesting ◽  
Multi Criteria Decision Analysis

Abstract Flash floods are highly devastating, however there is no effective management for their water in Saudi Arabia, therefore, it is crucial to adopt Rainfall Water Harvesting (RWH) techniques to mitigate the flash floods and manage the available water resources from the infrequent and rare rainfall storms. The goal of this study is to create a potential flood hazard map and a map of suitable locations for RWH in Wadi Nisah, Saudi Arabia for future water management and flood prevention plans and to identify potential areas for rainwater harvesting and dam construction for both a flood mitigation and water harvesting. This research was carried out using a spatiotemporal distributed model based on multi-criteria decision analysis by combining Geographic Information System (GIS), Remote Sensing (RS), and Multi-Criteria Decision-Making tools (MCDM). The flood hazard mapping criteria were elevation, drainage density, slope, direct runoff depth at 50 years return period, Topographic witness index, and Curve Number, according to the Multi-criteria decision analysis, while the criteria for RWH were Slope, Land cover, Stream order, Lineaments density, and Average of annual max-24hr Rainfall. The weight of each criteria was estimated based on Analytical Hierarchy Process (AHP). In multi-criteria decision analysis, 21.55 % of the total area for Wadi Nisah was classified as extremely dangerous and dangerous; 65.29 % of the total area was classified as moderate; and 13.15 % of the total area was classified as safe and very safe in flash flood hazard classes. Only 15% of Wadi Nisah has a very high potentiality for RWH and 27.7%, 57.31% of the basin has a moderate and a low or extremely low potentiality of RWH, respectively. According to the developed RWH potentiality map, two possible dam sites were proposed. The maximum height of the proposed dams, which corresponded to the cross section of dam locations, ranged from 6.2 to 9 meters; the maximum width of dams ranged from 573.48 to 725 meters; the maximum storage capacity of reservoirs, which corresponded to the distribution of topographic conditions in the surrounding area, ranged from 3976104.499 m3 to 4328509.123 m3; and the maximum surface area of reservoirs ranged from 1268372.625 m2 to 1505825.676.14 m2. These results are highly important for the decision makers for not only flash flood mitigation but also water management in the study area.

Impact of the models structure uncertainty in flood simulations: Simbach case study

2020 ◽  
Author(s):  
Qing Lin ◽  
Jorge Leandro ◽  
Markus Disse ◽  
Daniel Sturm
Keyword(s):  
Flash Flood ◽  
Drainage System ◽  
Model Structure ◽  
Flood Simulation ◽  
Hydraulic Models ◽  
Uncertainty Factor ◽  
Model Component ◽  
Model Structure Uncertainty ◽  
Flood Simulations ◽  
Model Structures

<p>The quantification of model structure uncertainty on hydraulic models is very important for flash flood simulations. The choice of an appropriate model structure complexity and assessment of the impacts due to infrastructure failure can have a huge impact on the simulation results. To assess the risk of flash floods, coupled hydraulic models, including 1D-sewer drainage and 2D-surface run-off models are required for urban areas because they include the bidirectional water exchange, which occurs between sewer and overland flow in a city [1]. By including various model components, we create different model structures. For example, modelling the inflow to the city with the 2D surface-runoff or with the delineated 1D model; including the sewer system or use a surrogate as an alternative; modifying the connectivity of manholes and pumps; or representing the drainage system failures during flood events. As the coupling pattern becomes complex, quantifying the model structure uncertainty is essential for the model structure evaluation. If one model component leads to higher model uncertainty, it is reasonable to conclude that the new component has a large impact in our model and therefore needs to be accounted for; if one component has a less impact in the overall uncertainty, then the model structure can be simplified, by removing that model component.</p> <p>In this study, we set up seven different model structures [2] for the German city of Simbach. By comparison with two inflow calculation types (1D-delineated inflow or 2D-catchment), the existence of drainage system and infrastructure failures, the Model Uncertainty Factor (MUF) is calculated to quantify the model structure uncertainties and further trade-off values with Parameter Uncertainty Factor (PUF) [3]. Finally, we can obtain a more efficient hydraulic model with the essential model structure for urban flash flood simulation.</p> <p> </p> <ol>1. Leandro, J., Chen, A. S., Djordjevic, S., and Dragan, S. (2009). "A comparison of 1D/1D and 1D/2D coupled hydraulic models for urban flood simulation." Journal of Hydraulic Engineering-ASCE, 6(1):495-504.</ol> <ol>2. Leandro, J., Schumann, A., and Pfister, A. (2016). A step towards considering the spatial heterogeneity of urban, key features in urban hydrology flood modelling. J. Hydrol., Elsevier, 535 (4), 356-365.</ol> <ol>3. Van Zelm, R., Huijbregts, M.A.J. (2013). Quantifying the trade-off between parameter and model structure uncertainty in life cycle impact assessment, Environ. Sci. Technol., 47(16), pp. 9274-9280.</ol> <p> </p>

scholarly journals Using unmanned aerial vehicle and volunteered geographic information to sophisticate urban flood modelling

2020 ◽  
Author(s):  
Yuan-Fong Su ◽  
Yan-Ting Lin ◽  
Jiun-Huei Jang ◽  
Jen-Yu Han
Keyword(s):  
Unmanned Aerial Vehicle ◽  
Urban Areas ◽  
Flash Flood ◽  
Volunteered Geographic Information ◽  
Geographic Information ◽  
Model Verification ◽  
Loss Assessment ◽  
Flood Simulation ◽  
Urban Flood ◽  
Aerial Vehicle

Abstract. Sophisticated flood simulation in urban areas is a challenging task due to the difficulties in data acquisition and model verification. This study incorporates three rapid-growing technologies, i.e. volunteered geographic information (VGI), unmanned aerial vehicle (UAV), and computational flood simulation (CFS) to reconstruct the flash flood event occurred in 14 June 2015, GongGuan, Taipei. The high-resolution digital elevation model (DEM) generated by a UAV and the real-time VGI photos acquired from social network are served to establish and validate the CFS model, respectively. The DEM data are resampled based on two grid sizes to evaluate the influence of terrain resolution on flood simulations. The results show that flood scenario can be more accurately modelled as DEM resolution increases with better agreement between simulation and observation in terms of flood occurrence time and water depth. The incorporation of UAV and VGI lower the barrier of sophisticated CFS and shows great potential in flood impact and loss assessment in urban areas.

Flash flood simulation using unit hydrograph and hydrodynamic models (case study of Western Caucasus, Russia)

2020 ◽  
Author(s):  
Pelagiya Belyakova ◽  
Ekaterina Vasil'eva ◽  
Andrey Aleksyuk ◽  
Vitaly Belikov ◽  
Boris Gartsman ◽  
...  
Keyword(s):  
Shallow Water ◽  
Monitoring System ◽  
Input Data ◽  
Flash Flood ◽  
Rainfall Runoff ◽  
Western Caucasus ◽  
Unit Hydrograph ◽  
Runoff Simulation ◽  
Flood Simulation ◽  
Flood Monitoring

<p>In the Russian part of Western Caucasus heavy rainfall episodes frequently occur, leading to flash floods that often cause fatalities and severe damage. As soon as climate change is expected to increase the risk of flash floods it is necessary to improve flood forecasting and flood risk mapping as well as other precautionary measures. For this scope the better knowledge of catchment response on heavy precipitation is needed using rainfall-runoff simulation and further hydrodynamic modelling of inundation of urbanized areas.</p><p>There is a number of models used for flash flood simulation. In this study we used an available unit hydrograph model KW-GIUH [1] and a hydrodynamic model STREAM 2D CUDA [2]. KW-GIUH model only schematically describes overland flow over the catchment, nonlinear character of response is introduced via kinematic-wave approximation of the travel time. STREAM 2D CUDA is based on numerical solution of shallow water equations in a two-dimensional formulation according to the original algorithm using the exact solution of the Riemann problem [2], due to which the calculation is performed for the entire catchment without special allocation of the channel network. Models were tested on several flash flood events on the river Adagum (6-7 July 2012, catastrophic flood in the Krymsk town) and the Zapadny Dagomys river (25 June 2015, 24-25 October 2018, Sochi).</p><p>Comparison of simulation results was done as the same input data set was used. Input data included DEM HydroSHEDS, measured hourly precipitation and runoff volumes observed on gauges and estimated after high-water marks. Also 10-min water levels from a regional automated flood monitoring system of the Krasnodar Territory were applied. Simulated runoff volumes and peak timing were analyzed. For the Zapadny Dagomys river a forecasting calculation was done using precipitation forecast from COSMO-Ru. For the Adagum river STREAM 2D CUDA allowed to conduct an experiment to assess possible effect from potential reservoir-traps in the tributaries. The results of the rainfall-runoff simulation by the KW-GIUH model can be used as inflow to the boundary of the area for hydrodynamic modeling using STREAM 2D CUDA, also for operational use. Scenario calculations with changing hydraulic conditions at the catchment can be simulated using the STREAM 2D CUDA model itself.</p><p>The flood simulation was supported by the Russian Science Foundation under grant №17-77-30006. Data processing from an automated flood monitoring system in the Krasnodar Territory is funded by Russian Foundation for Basic Research and the Krasnodar Territory, grant № 19-45-233007.</p><p>References:</p><ol><li>Lee K.T., Cheng N.K., Gartsman B.I., Bugayets A.N. (2009): A current version of the model of a unit hydrograph and its use in Taiwan and Russia, Geography and Natural Resources, Volume 30, issue 1, pp. 79–85. https://doi.org/10.1016/j.gnr.2009.03.015</li> <li>Aleksyuk A.I., Belikov V.V. (2017): Simulation of shallow water flows with shoaling areas and bottom discontinuities, Computational Mathematics and Mathematical Physics, Volume 57, issue 2, pp. 318–339. https://doi.org/10.1134/S0965542517020026</li> </ol>

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