Fluvial Flood Events Research Articles

A Data-Driven Multi-Step Flood Inundation Forecast System

Inundation maps that show water depths that occur in the event of a flood are essential for protection. Especially information on timings is crucial. Creating a dynamic inundation map with depth data in temporal resolution is a major challenge and is not possible with physical models, as these are too slow for real-time predictions. To provide a dynamic inundation map in real-time, we developed a data-driven multi-step inundation forecast system for fluvial flood events. The forecast system is based on a convolutional neural network (CNN), feature-informed dense layers, and a recursive connection from the predicted inundation at timestep t as a new input for timestep t + 1. The forecast system takes a hydrograph as input, cuts it at desired timesteps (t), and outputs the respective inundation for each timestep, concluding in a dynamic inundation map with a temporal resolution (t). The prediction shows a Critical Success Index (CSI) of over 90%, an average Root Mean Square Error (RMSE) of 0.07, 0.12, and 0.15 for the next 6 h, 12 h, and 24 h, respectively, and an individual RMSE value below 0.3 m, for all test datasets when compared with the results from a physically based model.

Potential pollution risks of historic landfills in England: Further analysis of climate change impacts

AbstractFive years ago, an article in WIREs Water provided the first comprehensive analysis of historic (legacy) landfill sites vulnerable to coastal flooding and erosion at a national scale (England). This update expands upon that article by considering the potential impacts of climate change upon inland historic landfills. Globally, there are hundreds of thousands of landfills that predate modern environmental regulations, and where waste is not isolated from the surrounding environment, but climate change impacts on the pollution risk from historic landfills in freshwater environments has received little attention. Where climate change causes an increase in the frequency and magnitude of fluvial flood events, this will increase leachate generation and the probability of landfill erosion and solid waste release. Where there is increased drought the landfill capping materials may crack, opening up new pollutant pathways, and increasing the risk of solid waste release. Changes to groundwater movement resulting from climate change may open new leachate pathways, and in England alone, thousands of historic landfills are in (groundwater) Source Protection Zones where modern regulations to protect drinking water supplies would not permit their construction. This increased contaminant release from historic landfills in freshwater environments may impact surface and/or groundwater quality and ecological health, increase costs for drinking water monitoring/treatment, or make some abstraction sources unviable. This is especially of concern where receptors are subject to multiple pressures and may cause tipping points to be reached. Further research is warranted into contaminant behavior, receptor vulnerability, historic landfill risk prioritization, and mitigation/remediation methods.This article is categorized under: Engineering Water > Engineering Water Science of Water > Water Quality Science of Water > Water and Environmental Change Water and Life > Stresses and Pressures on Ecosystems

Contributed Indicators to Fluvial Flood Along River Basin in Urban Area of Indonesia

Flooding is the most common disaster in Indonesia, it is classified as a disaster if it affects humans causing physical and financial losses. Flood damage depends on the type of flood, flow velocity, and duration. The increase in population will cause an increase in infrastructure that will affect the environment, including the carrying capacity of rivers and catchment areas, while flooding in urban areas will also have an impact on infrastructure and assets, increasing flood damage. This study discusses the factors that cause flooding (rainfall, topography, soil type, land slope, distance from rivers, river waste, population density, etc.), as well as various types of floods that occur. The method used in this research was based on the qualitative analysis of the information from the government and literature over the last five years obtained from online databases and search engines. The results of this study can provide a reference for the theory regarding disaster risk assessment and flood hazard prediction in watersheds. This research was conducted in the Ciliwung Watershed (DAS), where the factors and the dominant type of flooding were determined. Knowing the contributing factors can be beneficial for flood risk management. This research focuses on identifying factors that contribute to fluvial flood events and understanding their influence so that a more integrated flood risk management that takes into account the upstream, middle, and downstream parts of the watershed can be arranged in other areas based on the example of measures implemented by the local government in the Ciliwung watershed. This conceptual effort provides a much-needed foundation for developing better mitigation efforts in watersheds.

A Multi‐Hazard Risk Framework to Stress‐Test Water Supply Systems to Climate‐Related Disruptions

AbstractWater utilities' supply systems are vulnerable to several climate‐related hazards, including droughts, floods and cyclones. Here we propose a generally applicable framework for conducting multi‐hazard risk assessments of water supply systems and use it to quantify the impact of present and future climate extremes on the national water supply network in Jamaica. The proposed framework involves stress‐testing a model of the system with a large set of spatially coherent drought, cyclone and pluvial and fluvial flood events to calculate the number of water users whose supplies would be disrupted during an event, that is, the Customer disruption days (CDD). We estimate the total multi‐hazard annual expected disruption to be approximately 5 days per year per utility customer under present conditions. This is increased by a factor of between 2 and 2.5 when end‐of‐century climate scenarios are propagated through the model. Our analysis shows that more high probability drought events lead to greater CDD compared with asset damage events. However, extreme asset damage events, despite manifesting over shorter timescales (days) compared to drought events (months), can lead to more widespread CDD. This quantified risk framework would allow utility managers to compare the risk of both asset damage‐ and water shortage‐induced disruptions via a common, decision‐relevant metric. However, applications to other utilities would require tailored hazard modeling approaches. The proposed risk assessment is intended to inform prioritization of infrastructure investments, ranging from asset protection to drought mitigation projects, with the goal of enhancing water supply resilience in the face of a changing climate.

An integrated approach to streamflow estimation and flood inundation mapping using VIC, RAPID and LISFLOOD-FP

Controlling the damaging effects of fluvial flood events has been a major challenge for mankind. Integrated hydrologic-hydrodynamic models are often employed to estimate the flow and vital flood inundation information for mitigating such damages. The most important criterion for their implementation is that they should offer large-scale applicability with a finer resolution to have local relevance and practicability. This study presented an integrated modeling framework, VIC-RAPID-LISFP that couples a hydrological model (VIC), a river routing model (RAPID) and a hydrodynamic model (LISFLOOD-FP) for fast generation of high-resolution flow and flood inundation extent. The utility of the model is tested and demonstrated for a case study in the Upper Krishna River basin in India. The results showed that the simulated hourly streamflows from the calibrated model match reasonably well with the observations in terms of various efficiency measures. Also, the generated flood inundation maps from the model can reliably capture more than 80% of the satellite-derived flood inundation extent during both the low and high flow events. The proposed modeling framework is based on readily available open-source hydrographic data, and minimum meteorological information, so it has global applicability for supporting a flood management system with local relevance, especially for the data-scarce regions.

Barrier Island Sediments Reveal Storm Surge and Fluvial Flood Events in the Past Centuries at Thua Thien Hue, Central Vietnam

Sedimentary evidence of storms and fluvial floods (FFs) is crucial for a better understanding of such events in coastal zones. In this study, we analyzed the sedimentary characteristics of the coastal storm and FF deposits at the Hoa Duan barrier, Thua Thien Hue, central Vietnam. Analyses of the sedimentary structures and properties (grain size distribution, composition, roundness, and sphericity) and loss on ignition revealed that the storm sediments were comprised of coarser grains with a low organic and carbonated content, and with sedimentary structures, including parallel and inclined landward lamination, multiple sets of normal and reverse grading, mud rip-up clasts, and sharp and erosional contacts (both top and bottom) with finer-grain layers. Conversely, the FF sediments had only fine to very fine grains, with dominant high organic and carbonate contents, and only exhibited sedimentary structures of sharp erosional top and bottom contacts with coarser-grained layers. The clearest differentiation to distinguish coastal storm layers from inland FF layers was obtained by plotting the mean grain size against the sorting. The results of optically stimulated luminescence dating suggested that two storm layers and one FF layer were deposited during the last 130 ± 10 years. Moreover, two layers were deposited by storms and one by a FF prior to that (>130 ± 10 years). The identification of the sedimentary diagnostic key of these two hazards can help to improve the understanding of the geomorphological evolution of the studied site and the other parts of this coastal region in order to remind the coastal community to prepare for future coastal hazards well.

A probabilistic approach to estimating residential losses from different flood types

Residential assets, comprising buildings and household contents, are a major source of direct flood losses. Existing damage models are mostly deterministic and limited to particular countries or flood types. Here, we compile building-level losses from Germany, Italy and the Netherlands covering a wide range of fluvial and pluvial flood events. Utilizing a Bayesian network (BN) for continuous variables, we find that relative losses (i.e. loss relative to exposure) to building structure and its contents could be estimated with five variables: water depth, flow velocity, event return period, building usable floor space area and regional disposable income per capita. The model’s ability to predict flood losses is validated for the 11 flood events contained in the sample. Predictions for the German and Italian fluvial floods were better than for pluvial floods or the 1993 Meuse river flood. Further, a case study of a 2010 coastal flood in France is used to test the BN model’s performance for a type of flood not included in the survey dataset. Overall, the BN model achieved better results than any of 10 alternative damage models for reproducing average losses for the 2010 flood. An additional case study of a 2013 fluvial flood has also shown good performance of the model. The study shows that data from many flood events can be combined to derive most important factors driving flood losses across regions and time, and that resulting damage models could be applied in an open data framework.

Nature Based Solutions for Climate Adaptation - Paying Farmers for Flood Control

Climate change is expected to lead to more frequent and severe fluvial flood events in Northern Europe. Nature Based Solutions are increasingly recognised as a natural insurance against flood risks in vulnerable areas. This requires collaboration at landscape scale between providers and beneficiaries of flood control. In particular, mechanisms to incentivise owners of land could potentially offer cost-effective ways to reduce damage to urban infrastructure. We conduct a choice experiment among farmers located in the vicinity of a river to assess their willingness to accept a contract that would allow a local Danish municipality to periodically flood farmland to reduce urban flood risks. Results indicate that farmers on average are hesitant about entering into abatement contracts, especially if they have prior experience of crop losses due to extreme weather events. If they were to agree on a contract they would prefer a separate compensation for lost crops; a collective negotiation and higher rather than lower yearly payments. Surprisingly, data did not show a significant preference for or against a requirement to grow flood resistant crops. The results suggest that a contract with a separate damage compensation and based on individual negotiation would on average require an annual payment of 290Euro/ha for farmers with no prior experience of crop losses and 469Euro/ha for farmers who have experienced crop losses. The paper discusses the potentials and limitations of landscape scale Nature Based Solutions for climate adaptation.

Linking weather patterns to regional extreme precipitation for highlighting potential flood events in medium‐ to long‐range forecasts

AbstractMedium‐ to long‐range precipitation forecasts are a crucial component in mitigating the impacts of fluvial flood events. Although precipitation is difficult to predict at these lead times, the forecast skill of atmospheric circulation tends to be greater. The study explores using weather patterns (WPs) as a preliminary step in producing forecasts of upper‐tail precipitation threshold exceedance probabilities for the UK. The WPs are predefined, discrete states representing daily mean sea‐level pressure (MSLP) over a European–North Atlantic domain. The WPs most likely to be associated with flooding are highlighted by calculating upper‐tail exceedance probabilities derived from the conditional distributions of regional precipitation given each WP. WPs associated with higher probabilities of extreme precipitation are shown to have occurred during two well‐known flood events: the 2014 Somerset Levels floods in southwest England; and Storm Desmond over the northern UK in December 2015. To illustrate the potential of this WP‐based prediction framework, a forecast guidance tool called Fluvial Decider is introduced. It is intended for use by hydro‐meteorologists in the England and Wales Flood Forecasting Centre (FFC). Forecasts of the MSLP from ensemble prediction systems (EPSs) are assigned to the closest‐matching WP, providing daily probabilistic forecasts of WPs out to the chosen lead time. Combining these probabilities with observed precipitation threshold exceedance probabilities provides a parsimonious tool for highlighting potential periods with increased risk of flooding. Model forecasts using the European Centre for Medium‐range Weather Forecasts (ECMWF) EPS highlighted both flood events as being at a higher than average risk of heavy extreme precipitation at lead times of over five days.

Implementing resilience in flood risk management

Implementing resilience in flood risk management

Multi-coverage optimal location model for emergency medical service (EMS) facilities under various disaster scenarios: a case study of urban fluvial floods in the Minhang district of Shanghai, China

Abstract. Emergency medical service (EMS) response is extremely critical for pre-hospital lifesaving when disaster events occur. However, disasters increase the difficulty of rescue and may significantly increase the total travel time between dispatch and arrival, thereby increasing the pressure on emergency facilities. Hence, facility location decisions play a crucial role in improving the efficiency of rescue and service capacity. In order to avoid the failure of EMS facilities during disasters and meet the multiple requirements of demand points, we propose a multi-coverage optimal location model for EMS facilities based on the results of disaster impact simulation and prediction. To verify this model, we explicitly simulated the impacts of fluvial flooding events using the 1-D–2-D coupled flood inundation model FloodMap. The simulation results suggested that even low-magnitude fluvial flood events resulted in a decrease in the EMS response area. The integration of the model results with a geographical-information-system (GIS) analysis indicated that the optimization of the EMS locations reduced the delay in emergency responses caused by disasters and significantly increased the number of rescued people and the coverage of demand points.

Pluvial, Fluvial, and Groundwater Flooding: The Case of Cologne

We compare property price effects from pluvial, fluvial, and groundwater flooding in the urban area of Cologne, Germany. We focus on pluvial flooding as it is becoming increasingly important to urban areas and research on its impact on housing prices is scarce. Using a spatial Durbin model and a spatial Durbin error model, we control for different types of spatial spillovers and find that pluvial flooding is not part of the property pricing process. Fluvial flooding from the Rhine River is more important to property pricing, at least for condominiums, resulting in direct price discounts in higher hazard zones. Groundwater flooding, which occurs with a temporal lag after fluvial flood events, shows only a partial strengthening effect. Our results point to the importance of adequate flood precautions and risk communication, and to an adjustment in flood insurance as property price effects are an important damage category in the flood risk management plans of communities.

Systematic analysis of uncertainty in 2D flood inundation models

Assessing uncertainty is a critical part of understanding and developing flood inundation models for use in risk assessment. Typically, uncertainties are investigated by comparing the effects of an ensemble of key model inputs, such as friction values and hydrographic uncertainties, on model outputs. In this study, an approach is adopted that also consider the uncertainty associated with the computational models. Using the LISFLOOD-FP code, which contains multiple methods for solving floodplain flow, two test cases with different hydraulic characteristics are used in a systematic uncertainty analysis. An ensemble of inputs including cell size, hydrological uncertainty, and representation of buildings are assessed for impact on modelling results. Results show the numerical complexity is a significant source of uncertainty in complex flow regimes, but this reduces in typical fluvial flood events. The method of assessing the modelling output is also found to be important in determining the overall influence of parameters.

Evaluating the impact of model complexity on flood wave propagation and inundation extent with a hydrologic–hydrodynamic model coupling framework

Abstract. Fluvial flood events are a major threat to people and infrastructure. Typically, flood hazard is driven by hydrologic or river routing and floodplain flow processes. Since they are often simulated by different models, coupling these models may be a viable way to increase the integration of different physical drivers of simulated inundation estimates. To facilitate coupling different models and integrating across flood hazard processes, we here present GLOFRIM 2.0, a globally applicable framework for integrated hydrologic–hydrodynamic modelling. We then tested the hypothesis that smart model coupling can advance inundation modelling in the Amazon and Ganges basins. By means of GLOFRIM, we coupled the global hydrologic model PCR-GLOBWB with the hydrodynamic models CaMa-Flood and LISFLOOD-FP. Results show that replacing the kinematic wave approximation of the hydrologic model with the local inertia equation of CaMa-Flood greatly enhances accuracy of peak discharge simulations as expressed by an increase in the Nash–Sutcliffe efficiency (NSE) from 0.48 to 0.71. Flood maps obtained with LISFLOOD-FP improved representation of observed flood extent (critical success index C=0.46), compared to downscaled products of PCR-GLOBWB and CaMa-Flood (C=0.30 and C=0.25, respectively). Results confirm that model coupling can indeed be a viable way forward towards more integrated flood simulations. However, results also suggest that the accuracy of coupled models still largely depends on the model forcing. Hence, further efforts must be undertaken to improve the magnitude and timing of simulated runoff. In addition, flood risk is, particularly in delta areas, driven by coastal processes. A more holistic representation of flood processes in delta areas, for example by incorporating a tide and surge model, must therefore be a next development step of GLOFRIM, making even more physically robust estimates possible for adequate flood risk management practices.

A full-scale fluvial flood modelling framework based on a high-performance integrated hydrodynamic modelling system (HiPIMS)

Full-scale fluvial flood modelling over large catchments has traditionally been carried out using coupled hydrological and hydraulic/hydrodynamic models. Such a traditional modelling approach is not well suited for the simulation of extreme floods induced by intense rainfall, which is usually featured with highly transient and dynamic rainfall-runoff and flooding process. This work aims to develop and demonstrate a modelling framework to predict the full-scale process of fluvial flooding from the source (rainfall) to impact (inundation) over a large catchment using a single high-performance hydrodynamic model driven by rainfall inputs. The modelling framework is applied to reproduce the flood event caused by the 2015 Storm Desmond in the 2500 km2 Eden Catchment at 5 m resolution. Without intensive model calibration, the predicted results compare well with field observations in terms of inundation extent and gauged water levels across the catchment. Sensitivity tests reveal that high-resolution grid is essential for accurate simulation of fluvial flood events using a 2D hydrodynamic model. Accelerated by multiple modern GPUs, the simulation is more than 2.5 times faster than real time although it involves 100 million computational cells inside the computational domain. This work provides a novel and promising approach to assess and forecast at real time the risk of extreme fluvial floods from intense rainfall.

Trigger characteristics of torrential flows from high to low alpine regions in Austria

Torrential processes like fluvial flows (flash floods with or without intensive sediment transport) and debris flows can represent a threat to people and infrastructure in alpine domains. Up to now the hydro-meteorological trigger conditions and their connection with geomorphic watershed characteristics that favor the initiation of either process are largely unknown. Based on modeled wetness states we determined the trigger types (long-lasting rainfall (LLR), short-duration storm (SDS) and intense snow melt (SM)) of 360 observed debris flow and fluvial flood events in six climatically and geomorphologically contrasting watersheds in Austria. Results show that the watershed wetness states play very distinct roles for triggering torrential events across the study regions. Hydro-meteorological variables have little power to explain the occurrence of fluvial flows and debris flows in these regions. Nevertheless, trigger type separation highlighted some geomorphic influences. For example, intense SM triggered more events in sub-watersheds (torrential watersheds in the study region) that are characterized by significantly higher Melton ruggedness numbers than LLR does. In addition, the data show that events triggered by LLRs occur in sub-watersheds of similar exposures (aspects) other than SDS. The results suggest that the consideration of different trigger types provides valuable information for engineering risk assessment.

Beyond ‘flood hotspots’: Modelling emergency service accessibility during flooding in York, UK

This paper describes the development of a method that couples flood modelling with network analysis to evaluate the accessibility of city districts by emergency responders during flood events. We integrate numerical modelling of flood inundation with geographical analysis of service areas for the Ambulance Service and the Fire & Rescue Service. The method was demonstrated for two flood events in the City of York, UK to assess the vulnerability of care homes and sheltered accommodation. We determine the feasibility of emergency services gaining access within the statutory 8- and 10-min targets for high-priority, life-threatening incidents 75% of the time, during flood episodes. A hydrodynamic flood inundation model (FloodMap) simulates the 2014 pluvial and 2015 fluvial flood events. Predicted floods (with depth >25cm and areas >100m2) were overlain on the road network to identify sites with potentially restricted access. Accessibility of the city to emergency responders during flooding was quantified and mapped using; (i) spatial coverage from individual emergency nodes within the legislated timeframes, and; (ii) response times from individual emergency service nodes to vulnerable care homes and sheltered accommodation under flood and non-flood conditions. Results show that, during the 2015 fluvial flood, the area covered by two of the three Fire & Rescue Service stations reduced by 14% and 39% respectively, while the remaining station needed to increase its coverage by 39%. This amounts to an overall reduction of 6% and 20% for modelled and observed floods respectively. During the 2014 surface water flood, 7 out of 22 care homes (32%) and 15 out of 43 sheltered accommodation nodes (35%) had modelled response times above the 8-min threshold from any Ambulance station. Overall, modelled surface water flooding has a larger spatial footprint than fluvial flood events. Hence, accessibility of emergency services may be impacted differently depending on flood mechanism. Moreover, we expect emergency services to face greater challenges under a changing climate with a growing, more vulnerable population. The methodology developed in this study could be applied to other cities, as well as for scenario-based evaluation of emergency preparedness to support strategic decision making, and in real-time forecasting to guide operational decisions where heavy rainfall lead-time and spatial resolution are sufficient.

City-scale accessibility of emergency responders operating during flood events

Abstract. Emergency responders often have to operate and respond to emergency situations during dynamic weather conditions, including floods. This paper demonstrates a novel method using existing tools and datasets to evaluate emergency responder accessibility during flood events within the city of Leicester, UK. Accessibility was quantified using the 8 and 10 min legislative targets for emergency provision for the ambulance and fire and rescue services respectively under "normal" no-flood conditions, as well as flood scenarios of various magnitudes (1 in 20-year, 1 in 100-year and 1 in 1000-year recurrence intervals), with both surface water and fluvial flood conditions considered. Flood restrictions were processed based on previous hydrodynamic inundation modelling undertaken and inputted into a Network Analysis framework as restrictions for surface water and fluvial flood events. Surface water flooding was shown to cause more disruption to emergency responders operating within the city due to its widespread and spatially distributed footprint when compared to fluvial flood events of comparable magnitude. Fire and rescue 10 min accessibility was shown to decrease from 100, 66.5, 39.8 and 26.2 % under the no-flood, 1 in 20-year, 1 in 100-year and 1 in 1000-year surface water flood scenarios respectively. Furthermore, total inaccessibility was shown to increase with flood magnitude from 6.0 % under the 1 in 20-year scenario to 31.0 % under the 1 in 100-year flood scenario. Additionally, the evolution of emergency service accessibility throughout a surface water flood event is outlined, demonstrating the rapid impact on emergency service accessibility within the first 15 min of the surface water flood event, with a reduction in service coverage and overlap being observed for the ambulance service during a 1 in 100-year flood event. The study provides evidence to guide strategic planning for decision makers prior to and during emergency response to flood events at the city scale. It also provides a readily transferable method for exploring the impacts of natural hazards or disruptions in other cities or regions based on historic, scenario-based events or real-time forecasting, if such data are available.

Combined fluvial and pluvial urban flood hazard analysis: concept development and application to Can Tho city, Mekong Delta, Vietnam

Abstract. Many urban areas experience both fluvial and pluvial floods, because locations next to rivers are preferred settlement areas and the predominantly sealed urban surface prevents infiltration and facilitates surface inundation. The latter problem is enhanced in cities with insufficient or non-existent sewer systems. While there are a number of approaches to analyse either a fluvial or pluvial flood hazard, studies of a combined fluvial and pluvial flood hazard are hardly available. Thus this study aims to analyse a fluvial and a pluvial flood hazard individually, but also to develop a method for the analysis of a combined pluvial and fluvial flood hazard. This combined fluvial–pluvial flood hazard analysis is performed taking Can Tho city, the largest city in the Vietnamese part of the Mekong Delta, as an example. In this tropical environment the annual monsoon triggered floods of the Mekong River, which can coincide with heavy local convective precipitation events, causing both fluvial and pluvial flooding at the same time. The fluvial flood hazard was estimated with a copula-based bivariate extreme value statistic for the gauge Kratie at the upper boundary of the Mekong Delta and a large-scale hydrodynamic model of the Mekong Delta. This provided the boundaries for 2-dimensional hydrodynamic inundation simulation for Can Tho city. The pluvial hazard was estimated by a peak-over-threshold frequency estimation based on local rain gauge data and a stochastic rainstorm generator. Inundation for all flood scenarios was simulated by a 2-dimensional hydrodynamic model implemented on a Graphics Processing Unit (GPU) for time-efficient flood propagation modelling. The combined fluvial–pluvial flood scenarios were derived by adding rainstorms to the fluvial flood events during the highest fluvial water levels. The probabilities of occurrence of the combined events were determined assuming independence of the two flood types and taking the seasonality and probability of coincidence into account. All hazards – fluvial, pluvial and combined – were accompanied by an uncertainty estimation taking into account the natural variability of the flood events. This resulted in probabilistic flood hazard maps showing the maximum inundation depths for a selected set of probabilities of occurrence, with maps showing the expectation (median) and the uncertainty by percentile maps. The results are critically discussed and their usage in flood risk management are outlined.

The winter storms of 2013/2014 in the UK: hydrological responses and impacts

This paper outlines the hydrological aspects of the 2013/2014 winter flooding in the UK, as well as the impacts. The episode is considered in a long-term historical context and wider issues raised by the flood events are discussed briefly.