Comprehensive Overview of Flood Modeling Approaches: A Review of Recent Advances

Hydrology, Journal Year: 2023, Volume and Issue: 10(7), P. 141 - 141

Published: June 30, 2023

As one of nature’s most destructive calamities, floods cause fatalities, property destruction, and infrastructure damage, affecting millions people worldwide. Due to its ability accurately anticipate successfully mitigate the effects floods, flood modeling is an important approach in control. This study provides a thorough summary modeling’s current condition, problems, probable future directions. The includes models based on hydrologic, hydraulic, numerical, rainfall–runoff, remote sensing GIS, artificial intelligence machine learning, multiple-criteria decision analysis. Additionally, it covers heuristic metaheuristic techniques employed evaluation examines advantages disadvantages various models, evaluates how well they are able predict course impacts floods. constraints data, unpredictable nature model, complexity model some difficulties that must overcome. In study’s conclusion, prospects for development advancement field discussed, including use advanced technologies integrated models. To improve risk management lessen society, report emphasizes necessity ongoing research modeling.

Language: Английский

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Toward Street‐Level Nowcasting of Flash Floods Impacts Based on HPC Hydrodynamic Modeling at the Watershed Scale and High‐Resolution Weather Radar Data

Water Resources Research, Journal Year: 2023, Volume and Issue: 59(10)

Published: Oct. 1, 2023

Abstract In our era, the rapid increase of parallel programming coupled with high‐performance computing (HPC) facilities allows for use two‐dimensional shallow water equation (2D‐SWE) algorithms simulating floods at “hydrological” catchment scale, rather than just “hydraulic” fluvial scale. This approach paves way development new operational systems focused on impact‐based flash‐floods nowcasting, wherein hydrodynamic simulations directly model spatial and temporal variability measured or predicted rainfall impacts even a street Specifically, main goal this research is to make step move toward implementation an effective flash flood nowcasting system in which timely accurate impact warnings are provided by including weather radar products HPC 2D‐SWEs modelling framework able integrate watershed hydrology, flow hydrodynamics, river urban flooding one model. The timing, location, intensity street‐level evolution some key elements risk (people, vehicles, infrastructures) also discussed considering both calibration issues role played resolution. All these analyzed having as starting point event hit Mandra town (Athens, Greece) 15 November 2017, highlighting feasibility accuracy overall providing insights field.

Language: Английский

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Evaluation of 2D hydrodynamic-based rainfall/runoff modelling for soil erosion assessment at a seasonal scale

Journal of Hydrology, Journal Year: 2024, Volume and Issue: 632, P. 130778 - 130778

Published: Jan. 26, 2024

Badlands are often the source of a significant fraction sediment reaching river network due to exposure bare soil impact rain drops and bed shear stress generated by surface runoff. Hence, correct understanding erosion transport processes inside badlands can help better characterisation suspended production at catchment scale. In this work we study suitability two-dimensional (2D) physically-based event-scale model as tool represent in seasonal The solves 2D shallow water equations, including infiltration rainfall, order compute generation routing runoff within badland. Coupled hydrodynamic equation with terms that account for rainfall- runoff-driven deposition. Based on model, an overall procedure was developed tested considering, case study, badland located El Soto (central Pyrenees, Iberian Peninsula). For analysed badland, several high-resolution topography surveys were available, which allowed estimation loss spatial distribution patterns periods 3-4 months over two years. These data sets used calibrate validate proposed modelling approach, analyse its capabilities limitations assessment

Language: Английский

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Unravelling spatial heterogeneity of inundation pattern domains for 2D analysis of fluvial landscapes and drainage networks

Journal of Hydrology, Journal Year: 2024, Volume and Issue: 632, P. 130728 - 130728

Published: Jan. 24, 2024

Fluvial landscape analysis represents an essential component in geomorphology, hydrology, ecology and cartography. It is traditionally focused on the transition between hillslopes channel domain, which network drainage represented by static flow lines. However, natural fluctuations of processes occurring watershed induce lateral longitudinal expansions contractions patterns variations stream surface area. These can be better understood introducing a two-dimensional (2D) view catchment hydrography, river width floodplain are included analysis. The novelty introduced this work development hydrodynamic hierarchical framework (HHF) to analyse transitions among geomorphic hydrographic features fluvial landscape, distinguishing hillslope, unchanneled valleys, floodplains, single/multithreads channels. HHF based estimation nested inundation pattern domains (IPDs) from digital elevation models 2D modeling. IPDs defined scaling laws that characterize log–log relations density unit discharge thresholds extracted direct rainfall method (DRM) approach under steady state solutions. physical significance analysed within context both physiographic rates employed as input for modeling approach. Initially, spatial heterogeneity initially used derive metrics function rate. Then, index, representative IPDs' heterogeneity, measure susceptibility area expand/contract. Finally, consistency results assessed comparison another hydrodynamic-based recently proposed literature. using challenging mountain low-relief environments, characterized multithread channels, meander cut-offs, oxbow lakes, extreme landscapes feature glacial outwash, permafrost, peatlands.

Language: Английский

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A complete methodology to assess hydraulic risk in small ungauged catchments based on HEC-RAS 2D Rain-On-Grid simulations

Natural Hazards, Journal Year: 2024, Volume and Issue: 120(8), P. 7381 - 7409

Published: March 13, 2024

Abstract This paper explores the use of rain-on-grid (or direct rainfall) method for flood risk assessment at a basin scale. The is particularly useful rural catchments with small vertical variations and complex interactions man-made obstacles structures, which may be oversimplified by traditional hydrologically based estimations. hydrodynamic model solving mass momentum conservation equations allows simulation runoff over watershed As drawback, more detailed spatially distributed data are needed, computational time extended. On other hand, smaller number parameters needed compared to hydrological model. Roughness rainfall loss coefficients need calibrated only. methodology was here implemented within two-dimensional HEC-RAS low-land rural, ungauged, Terdoppio River, Northern Italy. resulting hydrographs closing section were synthetic design evaluated through pure modelling, showing agreement on peak discharge values low-probability scenarios, but not total volumes. results in terms water depth flow velocity maps used create hazard using Australian Institute Disaster Resilience methodology. Index Proportional Risk then adopted generate basin-scale map, combining maps, damage functions different building-use classes, value reconstruction content per unit area.

Language: Английский

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Geospatial modelling of floods: a literature review

Stochastic Environmental Research and Risk Assessment, Journal Year: 2023, Volume and Issue: 37(11), P. 4109 - 4128

Published: July 10, 2023

Language: Английский

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Flood Forecasting Using Hybrid LSTM and GRU Models with Lag Time Preprocessing

Water, Journal Year: 2023, Volume and Issue: 15(22), P. 3982 - 3982

Published: Nov. 16, 2023

Climate change and urbanization have increased the frequency of floods worldwide, resulting in substantial casualties property loss. Accurate flood forecasting can offer governments early warnings about impending disasters, giving them a chance to evacuate save lives. Deep learning is used improve timeliness accuracy water level predictions. While various deep models similar Long Short-Term Memory (LSTM) achieved notable results, they complex structures with low computational efficiency, often lack generalizability stability. This study applies spatiotemporal Attention Gated Recurrent Unit (STA-GRU) model for prediction increase models’ computing efficiency. Another salient feature our methodology incorporation lag time during data preprocessing before training model. Notably, 12-h forecasting, STA-GRU model’s R-squared (R2) value from 0.8125 0.9215. Concurrently, manifested reduced root mean squared error (RMSE) absolute (MAE) metrics. For more extended 24-h R2 improved 0.6181 0.7283, accompanied by diminishing RMSE MAE values. Seven typical models—the LSTM, Convolutional Neural Networks LSTM (CNNLSTM), (ConvLSTM), (STA-LSTM), GRU, GRU (CNNGRU), STA-GRU—are compared prediction. Comparative analysis delineated that use application pre-processing method significantly reliability forecasting.

Language: Английский

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Effects of DEM Depression Filling on River Drainage Patterns and Surface Runoff Generated by 2D Rain-on-Grid Scenarios

Water, Journal Year: 2022, Volume and Issue: 14(7), P. 997 - 997

Published: March 22, 2022

Topographic depressions in Digital Elevation Models (DEMs) have been traditionally seen as a feature to be removed no outward flow direction is available route and accumulate flows. Therefore, simplify hydrologic analysis for practical purposes, the common approach treated all DEMs artefacts completely them DEMs’ data preprocessing prior modelling. However, effects of depression filling on both geomorphic structure river network surface runoff still not clear. The use two-dimensional (2D) hydrodynamic modeling track inundation patterns has potential provide novel point views this issue. Specifically, there need remove topographic from DEM, performed traditional methods automatic extraction networks, so that their can directly taken into account simulated drainage associated response. novelty introduced work evaluation DEM net-points characterizing networks response watersheds simplified rainfall scenarios. results highlight how important these might applications, providing new insights field watershed-scale modeling.

Language: Английский

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A GPU-accelerated and LTS-based 2D hydrodynamic model for the simulation of rainfall-runoff processes

Journal of Hydrology, Journal Year: 2023, Volume and Issue: 623, P. 129735 - 129735

Published: May 30, 2023

Language: Английский

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Effect of intense rainfall and high riverine water level on compound flood hazards in a river-valley city: A case study of Yingde, China

Journal of Hydrology, Journal Year: 2023, Volume and Issue: 625, P. 130044 - 130044

Published: Aug. 24, 2023

Language: Английский

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