flood simulation
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Satellite remote sensing precipitation is useful for many hydrological and meteorological applications such as rainfall-runoff forecasting. However, most studies have focused on the use of satellite precipitation on daily, monthly, or larger time scales. This study focused on flash flood simulation using satellite precipitation products (IMERG) on an hourly scale in a poorly gauged mountainous catchment in southwestern China. Deep learning (long short-term memory, LSTM) was used, merging satellite precipitation and gauge observations, and the merged precipitation data were used as inputs for flood simulation based on the HEC-HMS model, compared with the gauged precipitation data and original IMERG data. The results showed that the application of original IMERG data used directly in the HEC-HMS hydrological model had much lower accuracy than that of gauged data and merged data. The simulation using the merged precipitation in HEC-HMS exhibited much better performances than gauged data. The mean NSE improved from 0.84 to 0.87 for calibration and 0.80 to 0.84 for verification, while the lower NSE improved from 0.81 to 0.84 for calibration and 0.73 to 0.86 for verification, which showed that accuracy and robustness were both significantly improved. Results of this study indicate the advances of remote sensing precipitation with deep learning for flash flood forecasting in mountainous regions. It is likely that more significant improvements can be made in flash flood forecasting by employing multi-source remote sensing products and deep learning merging methods considering the impact of complex terrain.

Abstract. The French Riviera is very often threatened by flash floods. These hydro-meteorological events, which are fast and violent, have catastrophic consequences on life and property. The development of forecasting tools may help to limit the impacts of these extreme events. Our purpose here is to demonstrate the possibility of using b-flood (a subset of the Basilisk library http://basilisk.fr/, last access: 8 November 2021), which is a 2D tool based on the shallow-water equations and adaptive mesh refinement. The code is first validated using analytical test cases describing different flow regimes. It is then applied to the Toce river valley physical model produced by ENEL-HYDRO in the framework of the CADAM project and on a flash-flood case over the urbanized Toce area produced during the IMPACT project. Finally, b-flood is applied to the flash flood of October 2015 in Cannes in south-eastern France, which demonstrates the feasibility of using software based on the shallow-water equations and mesh refinement for flash-flood simulation in small watersheds (less than 100 km2) and on a predictive computational timescale.

AbstractDigital Elevation Models (DEMs) play a critical role in hydrologic and hydraulic modeling. Flood inundation mapping is highly dependent on the accuracy of DEMs. Various vertical differences exist among open access DEMs as they use various observation satellites and algorithms. The problem is particularly acute in small, flat coastal cities. Thus, it is necessary to assess the differences of the input of DEMs in flood simulation and to reduce anomalous errors of DEMs. In this study, we first conducted urban flood simulation in the Huangpu River Basin in Shanghai by using the LISFLOOD-FP hydrodynamic model and six open-access DEMs (SRTM, MERIT, CoastalDEM, GDEM, NASADEM, and AW3D30), and analyzed the differences in the results of the flood inundation simulations. Then, we processed the DEMs by using two statistically based methods and compared the results with those using the original DEMs. The results show that: (1) the flood inundation mappings using the six original DEMs are significantly different under the same simulation conditions—this indicates that only using a single DEM dataset may lead to bias of flood mapping and is not adequate for high confidence analysis of exposure and flood management; and (2) the accuracy of a DEM corrected by the Dixon criterion for predicting inundation extent is improved, in addition to reducing errors in extreme water depths—this indicates that the corrected datasets have some performance improvement in the accuracy of flood simulation. A freely available, accurate, high-resolution DEM is needed to support robust flood mapping. Flood-related researchers, practitioners, and other stakeholders should pay attention to the uncertainty caused by DEM quality.

River flood events have recently been increased due to many reasons such as climate change and excessive land usage. Thus, one of the greatest challenges is to control the flooding in urban areas. River flooding has become a phenomenon worldwide in general and in Iraq specifically. This is associated with the rapid increase of urbanization as well as mismanagement of land utilization; especially those located near the river banks, in addition to lack of consideration in terms of the design and implementation of drainage networks. In Iraq and especially in Al-Anbar governorate, studies in the field of flood simulation control have been rare. This study aims to suggest a fast and accurate methodology for local authorities, by providing a proposed solution and prediction of flooding area in the case study of the Fallujah barrage. Global Mapper software has been used to produce simulation photos on flooding area. Earth Explorer USGS website has been used to download water body data; and Global Digital Surface website has been used to extract and download the surface elevation data. The result of the simulation photos has predicted valuable information about the flooding area and proposed a general vision on the areas that are under threat of flooding. Four main areas were exposed to flooding, area 1, area 2, area 3, and area 4; A total flooding area of 11.89 km2. The total maximum operational level for the barrage was designed to be 44.79 m above sea level. Also, the recommended maximum operation level for the barrage was 43 m ASL. Doi: 10.28991/cej-2021-03091754 Full Text: PDF

Abstract—MAPATÓN 2021 was organized by CONIDA (Peruvian Space Agency) as part of the celebrations for the bicentennial of Peru's independence. MAPATÓN was oriented to disaster management. This work aims to transmit the experience of participation in MAPATON and communicate the results achieved. The authors participated in developing flood simulation models and analyzing SENTINEL-1 satellite images to identify areas affected by floods that occurred in 2017, 2019 and 2020. The results obtained, shown in a story map, show the great utility of this type of analysis for risk management and disaster management. Keywords—MAPATON 2021; natural disasters; Peru; disaster management; Sentinel; satellite images

A digital elevation model (DEM) is a quantitative representation of terrain and an important tool for Earth science and hydrological applications. A high-resolution DEM provides accurate basic Geodata and plays a crucial role in related scientific research and practical applications. However, in reality, high-resolution DEMs are often difficult to obtain. Due to the self-similarity present within terrains, we proposed a method using the original DEM itself as a sample to expand the DEM using sliding windows method (SWM) and generate a higher resolution DEM. The main processes of SWM include downsampling the original DEM and constructing mapping sets, searching for the optimal matching, window replacement. Then, we repeat these processes with the small-scale expansion factor. In this paper, the grid resolution of the Taitou Basin was expanded from 30 to 10 m. Overall, the superresolution reconstruction results showed that the method could achieve better outcomes than other commonly used techniques and exhibited a slight deviation (root mean square error (RMSE) = 3.38) from the realistic DEM. The generated high-resolution DEM prove to be significant in the application of flood simulation modeling.

Abstract The larval stage of the European fire salamander (Salamandra salamandra) inhabits both lentic and lotic habitats. In the latter, they are constantly exposed to unidirectional water flow, which has been shown to cause downstream drift in a variety of taxa. In this study, an artificial stream was used to examine the individual movement patterns of marked larval fire salamanders exposed to unidirectional flow with simulated flood events. Movements were tracked by marking the larvae with VIAlpha tags individually and by using downstream and upstream traps. Most individuals showed stationarity, while downstream drift dominated the overall movement pattern. Upstream movements were rare and occurred only on small distances of about 30 cm; downstream drift distances exceeded 10 m (until next downstream trap). The simulated flood events increased drift rates significantly, even days after the flood simulation experiments. Drift probability increased with decreasing body size and decreasing nutritional status.