Journal of Flood Risk Management最新文献

The Bangkok Metropolitan Region (BMR), located in the Chao Phraya River basin delta, is particularly vulnerable to floods, with susceptibility heightened by geographical aspects and rapid urbanization. This study aimed to assess spatiotemporal flood exposure and allow proper flood-risk recognition among all stakeholders through a three-phase flood exposure assessment. First, land use and land cover (LULC) changes were identified based on a 30-year Landsat time series. Second, built-up areas that overlapped with past flood inundation maps were designated as flood exposure areas. Third, a rainfall-runoff inundation (RRI) model simulated the 2011 Thailand Flood, the largest on record, by analyzing inundation depth implications across three decades. The findings revealed a dramatic increase in the use of built-up areas and the associated flood exposure. In 1992, built-up areas accounted for approximately 20% of the total area, sharply increasing to nearly 45% by 2022, according to the LULC classification. The flood exposure increased from 648.83 km² in 1992 to 1681.26 km² by 2022, demonstrating a linear trend. Notably, the catastrophic 2011 flood did not inhibit urbanization in flood-prone areas, highlighting the need for robust policies, such as the segmentation of flood-risk zones, to mitigate future exposure in the region.

Flash floods can carry substantial sediment, posing significant sedimentation hazards in hilly cities. The sedimentation hazard map can reproduce the sediment thickness and extent of an extreme events scenario, playing an important role in sediment risk management. However, current research primarily focuses on modeling the inundation area and depth of floods, while studying sedimentation hazard caused by flash floods in urban areas remains insufficient. This paper aims to address this gap by utilizing a numerical model that simulates hyperconcentrated flow in hilly urban areas using the two-dimensional hydro-sediment-morphological model to compile the cumulative sedimentation hazard map. The model, built upon the open-source TELEMAC-MASCARET framework, incorporates Zhang Hongwu's formula to simulate sediment-carrying capacity, particularly suitable for hyper-sediment concentration near the riverbed. This paper uses the data of extreme flash flood events in the Wuding River basin in 2017 to simulate and compile the cumulative sedimentation hazard map. The hazard map delineates the sedimentation hazard extent and level attributable to overbank floodplain sedimentation. Notably, the sediment thickness is highest in areas near the levees on both sides of the Dali River. Moreover, the map illustrates the extent of channel erosion resulting from hyperconcentrated floods, which could jeopardize bank stability.

The development of a basin-specific comprehensive flood record using publicly available data for the James River Basin, Virginia. Using mixed surface analysis maps (NOAA, NWS), historical hurricane records (IBTrACS, HURDAT2), and flood and river gauge records (NWS, USGS), a database is created for analysis. Related to creating this database, a novel classification of six unique weather systems (non-tropical and tropical) responsible for flooding is presented. The analysis includes Two-Way tables with observed marginal and joint probabilities in various potential flood, storm, and regional combinations. Results show 233 tropical systems passed within the 500-km study area, with 12.4%, or 29 systems of those systems causing flooding within the basin. An additional 713 events were non-tropical, composing the majority of flood sources in the basin. Non-tropical systems are responsible for 84% of the worst floods recorded, leading to an increased frequency of 6% yearly since 1941 and nearly 770% between 2014 and 2018. The findings of this study will be the basis for assessing land use and population patterns in the area, along with a future compound flooding model for the lower James River Basin.

This investigation explores the interactions of different shaped debris with an array of obstacles under subcritical flow conditions, representative of a flood associated with a storm surge or tsunami. Panels, blocks and cylinders were used in a flow channel, as analogues for house panels, cars/containers and trees respectively, whilst some tests used a mix of debris. The backwater effect due to the blockage caused by the obstacles was most (least) significant for panels (cylinders). There was some evidence that smaller key log types and higher flow rates led to smaller dams. It was also evident that key logs formed at different depths depending on debris shape; debris shape also determined the vertical shape of the dam. Capture efficiency had a broadly negative (positive) correlation with the Froude number (permeability). Also, from video footage there were examples of the debris moving more quickly through partial dams. Finally, the drag force, deduced from only the water depths and the flow discharge, showed a clear relationship between drag force and Froude number, and a dependency of drag force on debris shape. There are some implications for the layout of building footprints in the inundation zones and the use of large, break-away panels.

This study proposes a model-based methodology to estimate design precipitation for long durations during the winter and spring seasons (October to June) through its application to the drainage areas of two dams in the Columbia River Basin, United States. For basins with large reservoir storage or snowpack, design precipitation and floods need to be estimated based on long-duration processes rather than focusing only on flood peaks or single storm durations. This study used the advanced research version of weather research and forecasting (WRF) model to maximize the target precipitation over the drainage areas by means of the Atmospheric Boundary Condition Shifting and Relative Humidity Perturbation with relaxed moisture flux thresholds. The greatest cumulative basin-average precipitation depths during Oct–Jun were estimated to be 1220.5 and 1595.4 mm for the drainage areas of Bonneville and Libby Dams, respectively. The 95% confidence interval (CI) of the exceedance probabilities of the estimated design precipitation depths were found to range from 10⁻³ to 10⁻⁵ at Bonneville Dam's drainage area. Those orders were found to be comparable with the documented exceedance probabilities of PMP/PMF in the US. The estimated design precipitation and corresponding atmospheric/land-surface fields together will drive a physical model to estimate the design flood.

Hawassa is a rapidly developing city in Lake Hawassa watershed of Ethiopia. Analyzing the effect of land cover dynamics on surface runoff remains imperative to adaptive urban stormwater management. This study quantified spatial variation of land cover and sensitivity of stormwater management response. Historical 30 years of daily annual rainfall, three satellite imageries, DEM, and hydrological soil group data were analyzed. A statistical-based combined approach of geospatial techniques and Soil Conservation Service-Curve Number (SCS-CN) model was employed. CN and surface runoff depth for the delineated urban watersheds were determined. The result revealed that the built-up area increased by 30.9 km², where the rate varies spatially. The variation of impervious land cover explains 58.6% of change in CN with coefficient of 0.352. While CN is inversely correlated with agricultural and vegetation land cover variations. The finding suggests CN explains 96.78% of the change in surface runoff with a significant correlation coefficient of 3.91. The proposed integrated model approach justifies the potential to reorganize the relationship between the spatial effect of land cover variation on surface runoff at the urban watersheds. Thus, suitable local-specific solutions can be devised for effective management of flood risk and optimize the drainage system of urban areas.

Levees aim to provide protection during floods, however, these structures can breach, causing significant damage. Flood maps that include levee breaching are often limited to deterministic methods. Where probabilistic breaching is done, it often requires computationally expensive Monte Carlo simulations and an understanding of the geotechnical levee properties that are often limited. In this paper, we combine existing fragility curves and empirical breaching equations with a framework for automating levee breaching in catchments with limited geotechnical information. This method can be adapted and applied to existing 2D flood models to determine the probability of inundation, given that a breach occurs. This ultimately allows for greater emergency responses and land use planning to reduce the flood risk faced by our communities. The method was applied to four case study catchments. The results showed that including levee breaching in one catchment led to an average increase in the inundated area by 48.2% and a tripling in the potentially exposed area. However, breaching in some locations reduced the inundation extent by 12%, illustrating the potential for fuse plug levees and floodways as a flood mitigation strategy. This strategy has seen successful usage internationally. Further investigation is recommended to consider whether these mitigation strategies should be enacted.

Effective management of flood risks requires the prioritization of appropriate flood control solutions. This study aims to prioritize structural flood control options using multi-criteria decision-making (MCDM) methods. Four MCDM methods, namely analytic hierarchy process, technique for order preference by similarity to ideal solution, multi-criteria optimization and compromise solution, and Fuzzy-VIKOR are employed to assess and rank the flood control options based on multiple criteria. Field surveys, interviews with local authorities and experts, and on-site assessments of existing flood control structures constituted the primary data collection methods. The findings demonstrate the effectiveness of reservoir dams, retention basins, and levees as viable solutions. Conversely, flood control gates and the no-project options were assigned lower priorities. The findings highlight the importance of considering multiple MCDM methods to account for variations in rankings. The study provides valuable insights into the decision-making process for prioritizing flood control options in the study area. These findings can assist policymakers and stakeholders in effectively allocating resources and implementing appropriate structural flood control measures to mitigate flood risks.

Extremely rapid rates of rise in level and discharge in a subset of flash floods (‘abrupt wave front floods’, AWF) are separate hazards from peak level. Such flood events are investigated for Pennine catchments in northern England using both gauged and historical information. Gauged level and flow digital records at 15-min intervals provide recent data. Historical information for 122 AWF events is extracted from a chronology of flash floods for Britain. Historical AWF events are mapped and found to occur on every major Pennine catchment; catchment descriptors are derived as a basis for assessing catchment vulnerability. We discuss the disputed origin of AWF. Using gauged data, we contrast the rising limb of AWF and ‘normal’ floods. We investigate time series of historical AWF, noting a puzzling peak in the late 19th century. Current rainfall and river monitoring does not provide a reliable basis for understanding AWF processes or for operational response and we suggest improvements. Similarly, current models for design flood estimation and forecasting do not generate the observed rapid increase in level in AWF floods.

Built environment flood resilience is a critical challenge facing communities worldwide. Amongst various efforts to resilience, the conception towards data utilization becomes popular with enormous technological advancements. Built environment creates varieties of data at larger volumes throughout their life cycle signifying that the importance of these data in the context of flood resilience cannot be ignored. However, despite the power of data, the greatest opportunities that exist for flood resilience enhancement have been mired by numerous and complex unidentified challenges. Thus, identifying these challenges with timely relevant strategies is a significant need. One of the best ways to tackle these challenges is by viewing them through the lens of data life cycle stages. This study, therefore, aimed to identify these challenges in each stage of the data life cycle with strategies to overcome them. Semi-structured interviews conducted with 12 experts revealed the significant challenges allied with built environment data with potential future strategies. The qualitative content analysis was conducted to analyse the findings. The use of advanced sensing technologies, cloud-based storage solutions, data governance policies and the development of predictive models are some of the consequential strategies outlined in this study. These findings provide valuable insights and guidance to facilitate built environment data utilization for flood resilience.