Fluvial Flood Research Articles

Service Accessibility Risk (SAR) Assessment for Pluvial and Fluvial Floods in an Urban Context

The development of strategies to adapt to and mitigate the potential adverse consequences of natural hazards requires support from risk assessment studies that quantify the impacts of hazardous events on our society. A comprehensive analysis of risk commonly evaluates the elements exposed to the hazard probabilistic scenarios and their vulnerabilities. However, while significant advances have been made in the assessment of direct losses, indirect impacts are less frequently examined. This work assesses the indirect consequences of two hydrologic hazards, i.e., pluvial and fluvial floods, in an urban context from a system perspective. It presents a methodology to estimate the services accessibility risk (SAR) that considers the accessibility of roads and the connection between providers and users of services in a city. The feasibility of the proposed approach is illustrated by an application to a pilot study in Monza city (northern Italy) considering pluvial and fluvial flood hazard with different return periods. The results in terms of the social and economic impacts are analyzed considering features of age, disability, and the different economic sectors.

Integrated flood vulnerability assessment of villages in the Waimanu River Catchment in the South Pacific: the case of Viti Levu, Fiji

This paper uses a holistic approach within a catchment scale, through the application of both climatic and non-climatic parameters, to analyze the impacts of river floods on the human security needs of rural riverine communities in the Waimanu Catchment situated in Nausori, Fiji. Consideration of both climatic and non-climatic factors is required since non-climatic factors could be controlled to build resilience against floods. The indicator-based flood vulnerability index methodology is applicable worldwide, but the indicators used in this study were specifically related to the Pacific Island context. In the context of fluvial flood vulnerability, effects of land management and climate change are not mutually exclusive of each other. Consequently, vulnerability assessments should consider the connection between people’s actions and ecosystems for the entire catchment area since upstream land use practices influence flood vulnerabilities downstream. In our research, a community-based flood vulnerability index system in conjunction with rainfall variability and land use assessments was used to quantitatively and qualitatively analyze the flood vulnerability, and it was found that increased rainfall, poor agricultural practices, gravel extraction, and improper waste management predominantly increased the exposure and sensitivity of midstream and downstream communities to river floods by modifying river morphology. Midstream communities in the Waimanu Catchment were most vulnerable to river floods due to their very low adaptive capacity in terms of poor ecosystem health and lack of natural resources to cope with the subsequent impacts of floods, being most sensitive to changes in land use and land cover.

Coastal inconsistencies: Living with and anticipating coastal flood risks in southern France

As coastal floods will grow stronger due to climate change, coastal communities' capacity to perceive, understand and adapt to an evolving environment must be assessed. This study explores how inhabitants of two Mediterranean French cities, Fréjus and Port-Saint-Louis-du-Rhône (PSLR), understand and prepare for coastal flood risk. A constructivist approach was adopted combining elements of the Theory of Social Representations and the Social Amplification of Risk Framework. Semistructured interviews were conducted with 41 inhabitants of these two localities. Local dwellers of the two cities base their knowledge of coastal flood risk on previous fluvial flood experiences. Affective attachment to the coast is expressed differently between localities – PSLR inhabitants describe an environmental history that is part of their personal history; whereas Fréjus inhabitants have elected this place to live. Risk attenuation argumentative strategies are identified: social comparison, risk comparison and fatalism. A shared understanding that ‘something must happen’ before coastal floods are taken seriously was also identified. This is discussed as an example of how the objectification process of social representations contributes to raising the societal awareness of new risks, or to their social amplification.

Connecting research and practice

Connecting research and practice

Evaluation of artificial intelligence models for flood and drought forecasting in arid and tropical regions

With the advancement of computer science, Artificial Intelligence (AI) is being incorporated into many fields to increase prediction performance. Disaster management is one of the main fields embracing the techniques of AI. It is essential to forecast the occurrence of disasters in advance to take the necessary mitigation steps and reduce damage to life and property. Therefore, many types of research are conducted to predict such events due to climate change in advance using hydrological, mathematical, and AI-based approaches. This paper presents a comparison of three major accepted AI-based approaches in flood and drought forecasting. In this study, fluvial floods are measured by the runoff change in rivers whereas meteorological droughts are measured using the Standard Precipitation Index (SPI). The performance of the Convolutional Neural Network (CNN), Long-Short Term Memory network (LSTM), and Wavelet decomposition functions combined with the Adaptive Neuro-Fuzzy Inference System (WANFIS) are compared in flood and drought forecasting, with five statistical performance criteria and accepted flood and drought indicators used for comparison, extending to two climatic regions: arid and tropical. The results suggest that the CNN performs best in flood forecasting with WANFIS for meteorological drought forecasting, regardless of the climate of the region under study. Besides, the results demonstrate the increased accuracy of the CNN in applications with multiple features in the input.

Hindcast of pluvial, fluvial, and coastal flood damage in Houston, Texas during Hurricane Harvey (2017) using SFINCS

Hindcast of pluvial, fluvial, and coastal flood damage in Houston, Texas during Hurricane Harvey (2017) using SFINCS

Trends and Frequencies of Extreme Rainfall Events in the Urban Catchments of Dar es Salaam, Tanzania

Understanding the characteristics of extreme rainfall events is necessary for proper planning and management of urban flooding impacts. In this paper, daily rainfall data from four key weather stations for the period 1967-2017 were used to investigate temporal variability in annual, seasonal, and extreme rainfall in the urban catchments of Dar es Salaam, Tanzania. The MannKendall trend analysis and Sen’s slope estimator were used to quantify the magnitudes and significance of long-term trends in rainfall. The frequencies of extreme rainfall events were modelled using the Generalized Pareto model. Results of trend analysis provided evidence of a decrease in total annual rainfall, with the highest decrement being 6.59mm per year. The statistical significance of the decrease in total annual rainfall was inconclusive. Observations of increase in both annual and seasonal maximum rainfall were also made; with the highest increments being 1.01mm and 0.79mm per event, for annual and seasonal maximum rainfall, respectively. The statistical significance of the increase in annual maximum rainfall was certain at 3 out of 4 stations. Frequencies of extreme rainfall events investigated using the R6 threshold provided reasonable results based on actual experience in the study area. Results indicated that most of the pluvial and fluvial flooding are from rainfall events with a 2 to 10-year return period. This is indicative of issues with the drainage systems in the area; either in their designed capacity or the reduction of their water carrying capacity due to anthropogenic factors.

Anthropogenic climate change has changed frequency of past flood during 2010-2013

The ongoing increases in anthropogenic radiative forcing have changed the global water cycle and are expected to lead to more intense precipitation extremes and associated floods. However, given the limitations of observations and model simulations, evidence of the impact of anthropogenic climate change on past extreme river discharge is scarce. Here, a large ensemble numerical simulation revealed that 64% (14 of 22 events) of floods analyzed during 2010-2013 were affected by anthropogenic climate change. Four flood events in Asia, Europe, and South America were enhanced within the 90% likelihood range. Of eight snow-induced floods analyzed, three were enhanced and four events were suppressed, indicating that the effects of climate change are more likely to be seen in the snow-induced floods. A global-scale analysis of flood frequency revealed that anthropogenic climate change enhanced the occurrence of floods during 2010-2013 in wide area of northern Eurasia, part of northwestern India, and central Africa, while suppressing the occurrence of floods in part of northeastern Eurasia, southern Africa, central to eastern North America and South America. Since the changes in the occurrence of flooding are the results of several hydrological processes, such as snow melt and changes in seasonal and extreme precipitation, and because a climate change signal is often not detectable from limited observation records, large ensemble discharge simulation provides insights into anthropogenic effects on past fluvial floods.

Urban Population Flood Impact Applied to a Warsaw Scenario

The provision of detailed information on the impact of potential fluvial floods on urban population health, quantifying the impact magnitude and supplying the location of areas of the highest risk to human health, is an important step towards (a) improvement of sustainable measures to minimise the impact of floods, e.g., by including flood risk as a design parameter for urban planning, and (b) increase public awareness of flood risks. The three new measures of the impact of floods on the urban population have been proposed, considering both deterministic and stochastic aspects. The impact was determined in relation to the building’s function, the number of residents, the probability of flood occurrence and the likely floodwater inundation level. The building capacity concept was introduced to model population data at the building level. Its proposed estimation method, an offshoot of the volumetric method, has proved to be successful in the challenging study area, characterised by a high diversity of buildings in terms of their function, size and density. The results show that 2.35% of buildings and over 122,000 people may be affected by 500-year flooding. However, the foreseen magnitude of flood impact on human health is moderate, i.e., on average ten persons per residential building over the 80% of flood risk zones. Such results are attributed to the low inundation depth, i.e., below 1 m.

LISFLOOD-FP 8.0: the new discontinuous Galerkin shallow-water solver for multi-core CPUs and GPUs

Abstract. LISFLOOD-FP 8.0 includes second-order discontinuous Galerkin (DG2) and first-order finite-volume (FV1) solvers of the two-dimensional shallow-water equations for modelling a wide range of flows, including rapidly propagating, supercritical flows, shock waves or flows over very smooth surfaces. The solvers are parallelised on multi-core CPU and Nvidia GPU architectures and run existing LISFLOOD-FP modelling scenarios without modification. These new, fully two-dimensional solvers are available alongside the existing local inertia solver (called ACC), which is optimised for multi-core CPUs and integrates with the LISFLOOD-FP sub-grid channel model. The predictive capabilities and computational scalability of the new DG2 and FV1 solvers are studied for two Environment Agency benchmark tests and a real-world fluvial flood simulation driven by rainfall across a 2500 km2 catchment. DG2's second-order-accurate, piecewise-planar representation of topography and flow variables enables predictions on coarse grids that are competitive with FV1 and ACC predictions on 2–4 times finer grids, particularly where river channels are wider than half the grid spacing. Despite the simplified formulation of the local inertia solver, ACC is shown to be spatially second-order-accurate and yields predictions that are close to DG2. The DG2-CPU and FV1-CPU solvers achieve near-optimal scalability up to 16 CPU cores and achieve greater efficiency on grids with fewer than 0.1 million elements. The DG2-GPU and FV1-GPU solvers are most efficient on grids with more than 1 million elements, where the GPU solvers are 2.5–4 times faster than the corresponding 16-core CPU solvers. LISFLOOD-FP 8.0 therefore marks a new step towards operational DG2 flood inundation modelling at the catchment scale. LISFLOOD-FP 8.0 is freely available under the GPL v3 license, with additional documentation and case studies at https://www.seamlesswave.com/LISFLOOD8.0 (last access: 2 June 2021).

Pre-Operational Application of a WRF-Hydro-Based Fluvial Flood Forecasting System in the Southeast Mediterranean

The Southeast Mediterranean (SEM) is characterized by increased vulnerability to river/stream flooding. However, impact-oriented, operational fluvial flood forecasting is far away from maturity in the region. The current paper presents the first attempt at introducing an operational impact-based warning system in the area, which is founded on the coupling of a state-of-the-art numerical weather prediction model with an advanced spatially-explicit hydrological model. The system’s modeling methodology and forecasting scheme are presented, as well as prototype results, which were derived under a pre-operational mode. Future developments and challenges needed to be addressed in terms of validating the system and increasing its efficiency are also discussed. This communication highlights that standard approaches used in operational weather forecasting in the SEM for providing flood-related information and alerts can, and should, be replaced by advanced coupled hydrometeorological systems, which can be implemented without a significant cost on the operational character of the provided services. This is of great importance in establishing effective early warning services for fluvial flooding in the region.

Spatially compounded surge events: an example from hurricanes Matthew and Florence

Abstract. The simultaneous rise of tropical-cyclone-induced flood waters across a large hazard management domain can stretch rescue and recovery efforts. Here we present a means to quantify the connectedness of maximum surge during a storm with geospatial statistics. Tide gauges throughout the extensive estuaries and barrier islands of North Carolina deployed and operating during hurricanes Matthew (n=82) and Florence (n=123) are used to compare the spatial compounding of surge for these two disasters. Moran's I showed the occurrence of maximum storm tide was more clustered for Matthew compared to Florence, and a semivariogram analysis produced a spatial range of similarly timed storm tide that was 4 times as large for Matthew than Florence. A more limited data set of fluvial flooding and precipitation in eastern North Carolina showed a consistent result – multivariate flood sources associated with Matthew were more concentrated in time as compared to Florence. Although Matthew and Florence were equally intense, they had very different tracks and speeds which influenced the timing of surge along the coast.

Assessing the economic impacts of future fluvial flooding in six countries under climate change and socio-economic development

Floods are among the most frequent and costliest natural hazards. Fluvial flood losses are expected to increase in the future, driven by population and economic growth in flood-prone areas, and exacerbated in many regions by effects of climate change on the hydrological cycle. Yet, studies assessing direct and indirect economic impacts of fluvial flooding in combination with climate change and socio-economic projections at a country level are rare. This study presents an integrated flood risk analysis framework to calculate total (direct and indirect) economic damages, with and without socio-economic development, under a range of warming levels from < 1.5 to 4 °C in Brazil, China, India, Egypt, Ethiopia, and Ghana. Direct damages are estimated by linking spatially explicit daily flood hazard data from the Catchment-based Macro-scale Floodplain (CaMa-Flood) model with country- and sector-specific depth-damage functions. These values input into an economic Input-Output model for the estimation of indirect losses. The study highlights that total fluvial flood losses are largest in China and India when expressed in absolute terms. When expressed as a share of national GDP, Egypt faces the largest total losses under both the climate change and climate change plus socio-economic development experiments. The magnitude of indirect losses also increased significantly when socio-economic development was modelled. The study highlights the importance of including socio-economic development when estimating direct and indirect flood losses, as well as the role of recovery dynamics, essential to provide a more comprehensive picture of potential losses that will be important for decision makers.

2 °C vs. High Warming: Transitions to Flood-Generating Mechanisms across Canada

Fluvial flooding in Canada is often snowmelt-driven, thus occurs mostly in spring, and has caused billions of dollars in damage in the past decade alone. In a warmer climate, increasing rainfall and changing snowmelt rates could lead to significant shifts in flood-generating mechanisms. Here, projected changes to flood-generating mechanisms in terms of the relative contribution of snowmelt and rainfall are assessed across Canada, based on an ensemble of transient climate change simulations performed using a state-of-the-art regional climate model. Changes to flood-generating mechanisms are assessed for both a late 21st century, high warming (i.e., Representative Concentration Pathway 8.5) scenario, and in a 2 °C global warming context. Under 2 °C of global warming, the relative contribution of snowmelt and rainfall to streamflow peaks is projected to remain close to that of the current climate, despite slightly increased rainfall contribution. In contrast, a high warming scenario leads to widespread increases in rainfall contribution and the emergence of hotspots of change in currently snowmelt-dominated regions across Canada. In addition, several regions in southern Canada would be projected to become rainfall dominated. These contrasting projections highlight the importance of climate change mitigation, as remaining below the 2 °C global warming threshold can avoid large changes over most regions, implying a low likelihood that expensive flood adaptation measures would be necessary.

Microplastic pollution of Calicut beach - Contributing factors and possible impacts

Annual monitoring was carried out in the shoreline sediments of the Calicut beach, from 2016 to 2019 to understand the distribution and abundance of microplastics and its environmental implications. Further, the impact of the severe fluvial floods of Kerala during the August months of 2018 and 2019, on the microplastic pollution of the Calicut beach was also determined. Microplastic concentrations ranged between 80.56 items/kg of dry sand to 467.13 items/kg of dry sand during the sampling period. Polyethylene type was consistently higher in all the samples. There was a surge in microplastics concentration during both the floods with a higher proportion of low-retention-period microplastics. Among the different oceanographic parameters, it was found that significant wave height and surface wind speed are positively correlated to the number of the microplastics in Calicut beach.

Impacts of fluvial flood on physical and biogeochemical environments in estuary–shelf continuum in the East China Sea

Land-ocean interaction plays an essential role in the transport fate of terrestrial matters in the coastal and shelf regions. Flood discharge from a mega river, containing massive water, sediment, and nutrient loads, could result in substantial and complex impacts on the physical and biogeochemical dynamics of coastal systems. In this study, field campaigns were conducted in a region from the Changjiang River Estuary to the East China Sea (ECS) before and after a significant flood. The impacts of the flood on physical and biogeochemical environments were assessed. The results revealed that the fluvial flood enhanced the offshore expansion of the low-salinity river plume and associated sediment/nutrient fronts. However, the area of elevated chlorophyll-a at the river mouth did not expand noticeably. A numerical model was applied to quantify the contribution of the Three Gorges Dam (TGD) to the spatial intensity and temporal duration of fluvial flood effects on estuary–shelf continuum. The results predicted a maximum of 2° latitudinal offshore displacement of the shelf water. Salinity and nitrate exhibited conservative expansions, with a longer relaxation time (~2 months) than chlorophyll-a and phosphate. After the TGD-regulated flow event ceased, salinity and nitrate effects persisted, but phosphate and chlorophyll-a recovered rapidly. The flood decreased the dissolved oxygen (DO) concentration around the river mouth and the offshore region, but not in the nearshore transient area. In contrast, the non-TGD regulation increased the regional DO concentration, which reduced the hypoxia risk. The TGD has become a crucial anthropogenic driver of environmental changes in the Changjiang Estuary-ECS continuum.

Targeting property flood resilience in flood risk management

AbstractIn this article, we evaluate property flood resilience (PFR) to manage pluvial and combined tidal/ fluvial flood risks. We achieve this by evaluating flood risk and intervention targeting strategies across a case study in Bristol (UK) using data types generally available for preliminary option assessment. We investigate opportunities for mitigating flood damages within catchments using PFR and evaluate two targeting strategies: Installing PFR across strategic areas of a catchment and targeting interventions at specific high‐risk properties. We find that individually targeting PFR is more effective than focusing resources on specific high‐risk areas. Targeting pluvial flood measures at individual properties across our case study provides an average annual benefit per property of approximately £750 more than applying zonal targeting, supporting use of high‐resolution modelling in surface water management, and highlighting the applicability of PFR to manage damages at specific high‐risk properties which may not fall under the protection of community level defences. A similar approach provides the best outcomes for fluvial targeting; however, the hazard is more concentrated and so a zonal targeting approach may be more acceptable. Overall, we find resistance based PFR an effective intervention to mitigate damages, however complementary strategies are required when managing extreme flooding.

A deep learning technique based flood propagation experiment

AbstractThis work presents an experiment involving detailed fluvial flood propagation process. Comparing to the existing flood experiments which collect hydrodynamical data just at gauges, flood evolution process in river channel and flood plain is measured and temporal–spatial data are provided. In the experiment, three inflow patterns are considered to reflect the different severity of the floods. The flood propagation and inundation are captured by using an array of surveillance cameras. The images are pre‐processed by applying camera calibration method to correct the barrel distortion. A deep learning technique is introduced to automatically identify inundated area. The inundation process is therefore obtained by identifying image series. In addition to the spatial data, the water level evolutions at three gauges are also monitored to supply detailed hydrodynamic information at gauges. The repeatability of the experiments and reliability of the deep learning technique are verified. The experimental data including spatial and point hydrodynamic features for flood events can be used to systematically validate numerical model and calibrate parameters.

The 2019/2020 floods in the UK: a hydrological appraisal

The 2019/2020 floods in the <scp>UK</scp>: a hydrological appraisal

Key factors influencing the severity of fluvial flood hazard from tropical cyclones

AbstractKnowledge of the key drivers of the severity of river flooding from tropical cyclones (TCs) is vital for emergency preparedness and disaster risk reduction activities. This global study examines landfalling TCs in the decade from 2010 to 2019, to identify those characteristics that influence whether a storm has an increased flood hazard. The highest positive correlations are found between flood severity and the total precipitation associated with the TC. Significant negative correlations are found between flood severity and the translation speed of the TC, indicating that slower moving storms, that rain over an area for longer, tend to have higher flood severity. Larger and more intense TCs increase the likelihood of having a larger area affected by severe flooding but not its duration or magnitude, and it is found that the fluvial flood hazard can be severe in all intensity categories of TC, including those of tropical storm strength. Catchment characteristics such as antecedent soil moisture and slope also play a role in modulating flood severity, and severe flooding is more likely in cases where multiple drivers are present. The improved knowledge of the key drivers of fluvial flooding in TCs can help to inform research priorities to help with flood early warning, such as increasing the focus on translation speed in model evaluation and impact-based forecasting.