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Inadequate drainage capacity often fails to offer the desired response in urban flooding. This aim of this study was to develop a flood hazard map through a field survey and numerical modelling. The field survey comprises cross-sectional data for tertiary drains; these are then transferred for setting up the numerical model. To feature flooding conditions, both hydrological and hydraulic model studies were carried out using the Hydrologic Engineering Center–hydrologic modelling system (HEC-HMS) developed by the US Army Corps of Engineers, and the personal computer storm water management model (PCSWMM). The use of HEC-HMS generated the runoff; the PCSWMM model simulation was carried out for 760 conduits and 693 junctions in the city that was studied. Three major outlets were considered for model calibration for 2014, the model simulated runoff showed a reasonable match with field records – that is, R2 = 0.782, R2 = 0.719 and R2 = 0.768 for the reaches Chaktai Khal, Rajakhali Khal and Mahesh Khal, respectively. Thus, the validated model was used for flood hazard mapping. It is envisaged that development authority and city planners would benefit from this coupled model.

Coastal flood risk is expected to increase as a result of climate change effects, such as sea level rise, and socioeconomic growth. To support policymakers in making adaptation decisions, accurate flood risk assessments that account for the influence of complex adaptation processes on the developments of risks are essential. In this study, we integrate the dynamic adaptive behavior of homeowners within a flood risk modeling framework. Focusing on building-level adaptation and flood insurance, the agent-based model (DYNAMO) is benchmarked with empirical data for New York City, USA. The model simulates the National Flood Insurance Program (NFIP) and frequently proposed reforms to evaluate their effectiveness. The model is applied to a case study of Jamaica Bay, NY. Our results indicate that risk-based premiums can improve insurance penetration rates and the affordability of insurance compared to the baseline NFIP market structure. While a premium discount for disaster risk reduction incentivizes more homeowners to invest in dry-floodproofing measures, it does not significantly improve affordability. A low interest rate loan for financing risk-mitigation investments improves the uptake and affordability of dry-floodproofing measures. The benchmark and sensitivity analyses demonstrate how the behavioral component of our model matches empirical data and provides insights into the underlying theories and choices that autonomous agents make.

The incidence of flooding events and the threat they pose in urban areas is a growing global issue, but it is particularly acute in developing countries like India, where the hazard is typically underrecognized and understudied. With current estimates indicating that future scenarios would become more severe, it is necessary to adopt integrated flood risk management solutions that involve flood modelling. This study is part of a bigger effort to quantify and simulate urban flood dangers. It emphasizes cutting-edge research and concepts in the area of urban flood risk management. It reviews the literature on current flood modelling approaches and provides a comprehensive overview of the different approaches, including their advantages and disadvantages. Indeed, flood modelling research has been extensive throughout the years, leading in the development of a diverse array of models, databases, and methodologies for simulating flood hydrodynamics. However, the actual potential of these developments in terms of flood risk management has yet to be shown. There is currently no perfect model or generic approach that can adequately capture all aspects of flood hydrodynamics over a broad variety of study locations. As a consequence, extensive calibration of state-of-the-art flood models is crucial for resolving current challenges in flood modelling. Additionally, the prospect of developing unique flood models based on fundamental mathematical formulations that are simple to parameterize by using global, open source, and publicly accessible data should pique academics' attention.

The multi-layer safety approach was introduced in 2009 in the Netherlands as a result of the shift from flood prevention to flood risk management. It aims at reducing flood risks by integrating defensive measures against floods (layer 1), resilient spatial planning measures (layer 2), and effective disaster management measures (layer 3). But how are these measures integrated? This contribution explores that question with a qualitative case study in Zwolle. In particular, policy and territorial integration among the multiple stakeholders are analysed. The analysis shows that the defensive approach (layer 1) still prevails, but that flood risk management is integrated into spatial planning (layer 2) in terms of policy integration and territorial integration. That is not the case for disaster management (layer 3), which remains detached from the other two layers. This contributes to the debate on integration in water management with other sectors through an in-depth analysis.

In design and periodic safety reviews of flood-detention reservoirs one of the key issues, in terms of sustainability, affordability and safety, is the need for a positive cutoff through foundation strata to prevent internal erosion. Such strata often involve alluvial or terrace deposits, which are of variable composition and lithology. The authors will describe the considerations that affect the decision as to when a positive cutoff such as sheet piles, or a bentonite cutoff wall is required, and conversely when it can be omitted, with the potential consequences of such an omission. The latter is likely to include additional requirements for surveillance and monitoring. The paper will describe the investigations that are necessary to inform that decision, including desk study, understanding geological context, site-specific intrusive investigations and arrangements for inspections and so on during construction. The paper will conclude with key issues to be evaluated in deciding when a positive cutoff is necessary.

Scouring around piers is recognised as one of the main causes of bridge failure. Local scour refers to the localised erosion of soil at piers and abutments caused by flow-induced vortices around their base. This paper studies experimentally the response of a bridge pier, supported on a cylindrical embedded foundation, subjected to flood-induced scour. A hybrid two-step methodology is developed to study the hydraulic and the mechanical part of the problem. In the first step, the hydraulic problem of local scour around a pier is experimentally modelled in 1g using a recently developed miniaturised tidal generator. The experimentally generated scour hole is then three-dimensionally scanned to produce a three-dimensional (3D)-printed mould. The latter is used in the second step to reproduce the scour hole in an Ng model, subsequently tested in a drum centrifuge to study the mechanical part of the problem under proper stress scaling. Foundation performance before and after local scour is studied through vertical, lateral monotonic and slow cyclic pushover tests. The effects of general (uniform) scour are also investigated by removing a soil layer of constant thickness. Local scour is shown to have a minor effect on vertical bearing capacity. In stark contrast, the lateral performance is significantly affected, with the foundation moment capacity Mult being reduced by up to 38%. The effect of general scour is even more pronounced, leading to 48% reduction of Mult. The rate of cyclic settlement accumulation is also much more severely affected by general scour as compared to local scour. Overall, the effects of local scour on foundation performance differ substantially to those of general scour, bringing into question the common simplification of ignoring the geometry of the scour hole, making no distinction between local and general scour.

The aim of this study is to lay a framework for evaluating flood vulnerabilities. Specifically, it applies the proposed methodology to evaluate flood vulnerability index (FVI) across 21 districts comprising a significantly large part (drainage area of 85 859 km2) of Narmada River basin in the central Indian state of Madhya Pradesh. The study assesses sensitivity, adaptive capacity indices, and the exposure risk over a chosen set of 22 climatic, demographic, social and economic parameters, and applies principal component analysis to evolve a composite FVI. The results rank various districts for their vulnerabilities to floods. The analysis indicates that, in the study area, around a third of the vulnerability is accounted by two factors: a lack of adaptive capacity of the community and heightened sensitivity to floods. There exists significant scope to modify these two factors by appropriate policy interventions at the social and economic levels. It is expected that the framework would be of use to stakeholders such as planners, policymakers, flood management authorities, field engineers, district administration and local non-governmental organisations who strive to make the community less vulnerable to floods.

Immunization is widely recognized as one of the most successful and cost-effective health interventions, preventing two to three million deaths from vaccine-preventable diseases each year. Although progress has been made in recent years, substantial operational challenges persist in resource-limited settings with frequent stock-outs contributing to sub-optimal immunization coverage and inequality in vaccine access. In this paper, we investigate the role of rainy season induced supply chain disruptions on vaccination coverage and inequalities. We develop a modeling framework combining spatial modeling—to predict flood disruptions in road networks—and a discrete-event simulation of a multi-tiered vaccine supply chain (VSC). Our models are fitted using data from the Malagasy VSC network and validated to the best extent possible with scarce data. Our baseline simulation predicts the national vaccination coverage with good accuracy and suggests that 67% of regions with low reported immunization coverage are affected by rainy season disruptions or operational inefficiencies, causing significant geographical inequalities in vaccine access. We investigate various mitigation strategies to increase the resiliency of VSCs and find that, by strategically placing buffer inventory at targeted facilities prior to the rainy season, the proportion of children receiving all basic vaccines in these areas is increased by 8% and the geographical inequality in vaccination coverage between areas affected and not affected by the rainy season is reduced by 11%. By also increasing the replenishment frequency from every third month to every month, the national vaccination coverage improves by 41%. Our results contribute to achieving the UN Sustainable Development Goals (SDGs) by providing actionable insights for improving vaccination coverage (SDG 3) and investigating the resiliency of the VSC to increased flooding due to climate change (SDG 13).

Flooding causes serious impacts on the old town of Venice, its residents, and its cultural heritage. Despite this existence-defining condition, limited scientific knowledge on flood risk of the old town of Venice is available to support decisions to mitigate existing and future flood impacts. Therefore, this study proposes a risk assessment framework to provide a methodical and flexible instrument for decision-making for flood risk management in Venice. We first use a state-of-the-art hydrodynamic urban model to identify the hazard characteristics inside the city of Venice. Exposure, vulnerability, and corresponding damage are then modeled by a multi-parametric, micro-scale damage model which is adapted to the specific context of Venice with its dense urban structure and high risk awareness. Furthermore, a set of individual protection scenarios are implemented to account for possible variability in flood preparedness of the residents. This developed risk assessment framework was tested for the flood event of 12 November 2019 and proved able to reproduce flood characteristics and resulting damage well. A scenario analysis based on a meteorological event like 12 November 2019 was conducted to derive flood damage estimates for the year 2060 for a set of sea level rise scenarios in combination with a (partially) functioning storm surge barrier, the Modulo Sperimentale Elettromeccanico (MOSE). The analysis suggests that a functioning MOSE barrier could prevent flood damage for the considered storm event and sea level scenarios almost entirely. A partially closed MOSE barrier (open Lido inlet) could reduce the damage by up to 34 % for optimistic sea level rise prognoses. However, damage could be 10 % to 600 % higher in 2060 compared to 2019 for a partial closure of the storm surge barrier, depending on different levels of individual protection.

In contrast with classic centralized risk sharing, a novel peer-to-peer risk sharing framework is proposed. The presented framework aims to devise a risk allocation mechanism that is structurally decentralized, Pareto optimal, and mathematically fair. An explicit form for the pool allocation ratio matrix is derived, and convex programming techniques are applied to determine the optimal pooling mechanism in a constrained variance reduction setting. A tiered hierarchical generalization is also constructed to improve computational efficiency. As an illustration, these techniques are applied to a flood risk pooling example. It is shown that peer-to-peer risk sharing techniques provide an economically viable alternative to traditional flood policies.

Relief demand forecasting is vital to the success of disaster relief operations, but it is associated with challenges including insufficient training samples, incomplete and imprecise inputs, and inaccurate demands. This paper presents a co-evolutionary fuzzy deep transfer learning (CoFDTL) method for relief demand forecasting where different types of disasters (e.g., earthquake, typhoon, and flood) are considered as different tasks. CoFDTL consists of three stages. First, a deep fuzzy learning model is used to learn latent representation of the shared inputs of all tasks. Second, a co-evolutionary algorithm is used to simultaneously learn task-specific features and the shared regressor. Third, the shared regressor is re-trained based on the best solutions obtained for different tasks in the second stage. Experiments demonstrate that CoFDTL exhibits significant performance improvements over the selected popular fuzzy learning, deep learning, and transfer learning models. This paper also reports the application of CoFDTL to two real-world disasters in China, 2018. The proposed CoFDTL that integrates fuzzy deep learning, transfer learning, and co-evolutionary learning can be used for many other complex multi-task transfer learning problems with insufficient samples and uncertain information.

The Hertfordshire and North London Area of the Environment Agency has 18 flood storage reservoirs (FSRs) which come within the remit of the Reservoirs Act 1975. Many have fixed flow control orifices, which cannot be changed when the reservoir is in operation. A review was carried out to determine the ability of the flow control systems to provide drawdown at these reservoirs, considering both the latest guidance on drawdown rates and the ability of the reservoirs to empty quickly to accommodate subsequent floods. The ratio of full storage volume to maximum allowable outflow was used to rank the 18 reservoirs, in order to identify whether investigations into additional drawdown facilities were needed. Three reservoirs were found to require alterations to their outflow controls so that they could provide adequate emergency drawdown. The works required at these three FSRs are described, all of which involve penstocks with differing methods of operation – two being remotely operated.

Investigations of the formation mechanisms of flood peaks in small catchments facilitate flood prediction and disaster prevention under extreme rainstorms. However, there have been few studies on the responses of flood peaks to land use landscape patterns using field surveys during extreme rainstorm events. Based on field data from 17 small catchments near the rainstorm center of Typhoon Lekima, 7 landscape indices were chosen. The flood peak and its sensitivity to the land use landscape were investigated by combining remote sensing interpretation and related analysis. The conclusions are as follows: (1) The peak discharge of the small catchment was 2.36–56.50 m3/s, the peak modulus was 8.00–48.89 m3/(s·km2), and the flood index K ranged from 3.61 to 4.55. (2) Under similar rainfall conditions, the flood peak modulus, K and the proportion of sloping cropland had significantly positive correlations (p

Improving the resilience of complex engineered and engineering systems (CES) includes planning for complex resilience situations, in which there may be multiple threats, interactions, and disruptions. One challenge in the modeling of CES is the identification of how interactions in a complex situation occur and their combined influence on CES resilience. This article presents a resilience holon that can be used to analyze complex resilience situations. It is made up of 24 elements (defining types of resilience, threats, interactions, and disruptions), which have varying importance to specific situations. Holons can be linked together hierarchically or in a network. An application of the resilience holon to a documented real-world resilience situation, widespread flooding in a city, illustrates its use. Pathways taken by threats and disruptions, as the flood effects cascaded through the city, are shown as connections between holons. The resilience holon could be used to decompose diverse resilience situations involving CES, to identify where critical vulnerability points are and how the whole resilience situation could be improved. The visual nature of the resilience holon could be used in an interactive way, allowing stakeholders to better understand the full resilience picture of CES that they use or operate.

Housing constitutes a basic need for all living beings. Unfortunately, natural hazards, including floods, pose a severe threat to housing infrastructure systems. In turn, this paper develops a framework to quantify the resilience of housing infrastructure systems against flood hazards. The parameters for this resilience are based on the literature and knowledge from experts. This paper gauges the significance of each resilience parameter by using the analytic hierarchy process (AHP) and the fuzzy AHP. The evaluated values are then compared to observe the effectiveness of fuzzy AHP over AHP. The evaluated importance of each parameter will help stakeholders focus on the most important parameters and, in turn, boost the flood resilience of infrastructure. This paper then implements the developed framework in a study area to quantify local flood resilience. This resilience value will help stakeholders in the considered area to understand the resilience of local housing infrastructure.

Our study focuses on the hydrologic implications of resolving and modeling atmospheric processes at different spatial scales. Here we use heavy precipitation events from an atmospheric model that was run at different horizontal grid spacings (i.e., 250 m, 500 m, 1 km, 2 km 4 km, and 12 km) and able to resolve different processes. Within an idealized simulation framework, these rainfall events are used as input to an operational distributed hydrologic model to evaluate the sensitivity of the hydrologic response to different forcing grid spacings. We consider the finest scale (i.e., 250 m) as reference, and compute event peak flows and volumes across a wide range of basin sizes. We find that the use of increasingly-coarser inputs leads to changes in the distribution of event peak flows and volumes, with the strongest sensitivity at the smallest catchment sizes. Overall, we find that 4-km rainfall simulations represent a good compromise between computational costs and hydrologic performance, providing basic information for future endeavors geared towards regional downscaling.

With climate change, hydro-climatic hazards, i.e., floods in the Himalayas regions, are expected to worsen, thus, likely to affect humans and socio-economic growth. Precisely, the Koshi River basin (KRB) is often impacted by flooding over the year. However, studies on estimating and predicting floods still lack in this basin. This study aims at developing flood probability map using machine learning algorithms (MLAs): gaussian process regression (GPR) and support vector machine (SVM) with multiple kernel functions including Pearson VII function kernel (PUK), polynomial, normalized poly kernel, and radial basis kernel function (RBF). Historical flood locations with available topography, hydrogeology, and environmental datasets were further considered to build flood model. Two datasets were carefully chosen to measure the feasibility and robustness of MLAs: training dataset (location of floods between 2010 and 2019) and testing dataset (flood locations of 2020) with thirteen flood influencing factors. The validation of the MLAs was evaluated using a validation dataset and statistical indices such as the coefficient of determination (r2: 0.546~0.995), mean absolute error (MAE: 0.009~0.373), root mean square error (RMSE: 0.051~0.466), relative absolute error (RAE: 1.81~88.55%), and root-relative square error (RRSE: 10.19~91.00%). Results showed that the SVM-Pearson VII kernel (PUK) yielded better prediction than other algorithms. The resultant map from SVM-PUK revealed that 27.99% area with low, 39.91% area with medium, 31.00% with high, and 1.10% area with very high probabilities of flooding in the study area. The final flood probability map could add a greatt value to the effort of flood risk mitigation and planning processes in KRB.

Flood events are the most frequent cause of damage to infrastructure compared to any other natural hazard, and global changes (climate, socioeconomic, technological) are likely to increase this damage. Transportation infrastructure systems are responsible for moving people, goods and services, and ensuring connection within and among urban areas. A failed link in these systems can impact the community by threatening evacuation capability, recovery operations and the overall economy. Bridges are critical links in the wider urban system since they are associated with little redundancy and a high (re)construction cost. Riverine bridges are particularly prone to failure during flood events; in fact, the risks to bridges from high river flows and erosion have been recognized as crucial at global level. The interaction of flow, structure and network is complex, and not fully understood. This study aims to establish a rigorous, multiphysics modeling approach for the assessment of the hydrodynamic forces impacting inundated bridges, and the subsequent structural response, while understanding the consequences of such impact on the surrounding network. The objectives of this study are to model hydrodynamic forces as demand on the bridge structure, to advance a performance evaluation of the structure under the modeled loading, and to assess the overall impact at systemic level. The flood-prone city of Carlisle (UK) is used as a case study and a proof of concept. Implications of the hydrodynamic impact on the performance and functionality of the surrounding transport network are discussed. This research will help to fill the gap between current guidance for design and assessment of bridges within the overall transport system.

Kuahuqiao site, famous for its early rice cultivation, is taken to be a typical case of how agriculture emerged in a littoral environment in the early Holocene. However, the lack of fire history and local climatic reconstruction has hindered the detailed picture of agricultural origins and development. Here we report new records of TOC, BC, δ 13CTOC, δ 13CBC, and C/N, alongside published pollen and charcoal data. Our δ 13CTOC and C/N confirm the previously-proposed formation of wetlands, which offered favorable landscapes for rice paddy agriculture, prior to the appearance of the Kuahuqiao culture. Based on BC, δ 13CTOC, and δ 13CBC records we suggest a hotter but drier climate that would have benefited rice agriculture by augmenting the distribution of wild rice and C4 herbs. In addition, δ 13CTOC shows a decreased C3/C4 ratio as a signal of human occupation with manipulation of forest for hunting-gathering or/and land clearance for agriculture. Combined δ 13CBC and BC records oppose the proposal of intense fire use in early agriculture and suggest that fire use was constrained to domestic purposes. Flood events which seem to have terminated the Kuahuqiao culture left impressions in TOC, BC, δ 13CTOC, δ 13CBC.

Commercial microwave links (CMLs) can be used as opportunistic and unconventional rainfall sensors by converting the received signal level into path-averaged rainfall intensity. As the reliable reconstruction of the spatial distribution of rainfall is still a challenging issue in meteorology and hydrology, there is a widespread interest in integrating the precipitation estimates gathered by the ubiquitous CMLs with the conventional rainfall sensors, i.e. rain gauges (RGs) and weather radars. Here, we investigate the potential of a dense CML network for the estimation of river discharges via a semi-distributed hydrological model. The analysis is conducted in a peri-urban catchment, Lambro, located in northern Italy and covered by 50 links. A two-level comparison is made between CML- and RG-based outcomes, relying on 12 storm/flood events. First, rainfall data are spatially interpolated and assessed in a set of significant points of the catchment area. Rainfall depth values obtained from CMLs are definitively comparable with direct RG measurements, except for the spells of persistent light rain, probably due to the limited sensitivity of CMLs caused by the coarse quantization step of raw power data. Moreover, it is shown that, when changing the type of rainfall input, a new calibration of model parameters is required. In fact, after the recalibration of model parameters, CML-driven model performance is comparable with RG-driven performance, confirming that the exploitation of a CML network may be a great support to hydrological modelling in areas lacking a well-designed and dense traditional monitoring system.

A compound perspective on hydrological extreme events is of paramount significance as it may lead to damages with larger losses. In this study, an integrated framework, based on downscaled climate variables and hydrological model, i.e. the Soil and Water Assessment Tool, was applied to generate extreme precipitation (Rx1day) and extreme streamflow (Sx1day) series under historical and future climate conditions. Then the potential impacts of climate change for univariate and bivariate joint frequency of extreme precipitation and flood in Xitiaoxi River Basin (XRB), a representative watershed of the Yangtze River Delta, is detected. The compound risk of extreme precipitation and flood under different levels of joint return period for historical and projected periods are estimated by copula‐based two-dimensional approaches. Major findings can be summarized: (1) The Rx1day and Sx1day under future scenarios increased by -0.4 ~ 11.7% and 0.7 ~ 20.4%, respectively, compared to historical period based on univariate frequency analysis, indicating the increasing magnitude of the flood in the future. (2) Climate change with different emission scenarios all have a driving effect on the rising coactivity of extreme precipitation and flood under compound flooding frequency analysis. In addition, the enhancement of climate change to extreme events is more apparent for extremes with higher return period and under the periods of 2080s. (3) Moreover, the flood frequency designs are deduced by bivariate joint distribution are safer than that by univariate distribution. This study may provide actionable insights to formulate the planning scheme of flood control and disaster reduction under the changing environment.

Floods are hydrological disasters that can alter the physical, socioeconomic, and environmental settings of a region. The objective of the present study is to develop an efficient and reliable methodology to prepare a flood risk map for Assam, the North-eastern region (NER) of India, by the integration of hazard and vulnerability components. Three indices, namely flood hazard index (FHI), flood vulnerability index (FVI), and flood risk index (FRI), are developed using multi-criteria decision analysis (MCDA) – Analytical hierarchy process (AHP) approach in GIS environment for the regional and administrative level of Assam. The selected hazard and vulnerability indicators define the topographical, geological, meteorological, drainage characteristics, land use land cover, and demographical features of Assam. The results show that more than 70% of the total area lies in the moderate to very high FHI class, 57.37% have moderate to high FVI, and more than 50% have moderate to very high FRI class.

This study aimed at mapping the Kota Tinggi flood event in 2006/07 that had caused massive damages to properties and the environment. The flood was associated with unusually high intensity and continuous rainfall. Therefore, a reliable technique of floodplain mapping is crucial for the improvement of flood control strategies and for preparing an evacuation plan. The main objective of this study is to compare the effect of tide on flood modeling analysis. The inundated areas were mapped for various annual recurrent intervals using peak flow data from 1965 to 2010. The study used Light Detection and Ranging (LiDAR) data for flood modeling. HEC-HMS, HEC-RAS, and HEC-GeoRAS were used to develop the flood model. The results reaffirm that the GEV model is the best for fitting the annual flood. The HEC-HMS hydrologic model was calibrated and validated using observed hydrographs in Sep 2002 and Jan 2003, respectively. Upon successful calibration and validation, the model was used to simulate flood hydrograph in Jan 2007. The modeling took into account the tidal effect. When the tidal effect was not considered, the simulated flood depth was 43 % lower than the observed flood. However, the inclusion of the tidal effect has reduced the simulation error with an average similarity of 91.4%. The simulation results show that the river flow starts to over bank for ARIs exceeded 25 years.

Natural disasters, such as floods, may damage power system assets and lead to widespread and long outages. The impact of flood can be alleviated by preventive actions such as installing tiger dams around power substations before the flood. In this regard, it is imperative that critical substations are identified in terms of the connected load and imposed costs to the system. This paper presents a stochastic resource allocation approach for protecting power substations against flood events a day ahead of the event. Flood probability distribution functions are used to generate several flood scenarios at each substation. Using flood scenarios and substations' fragility, damage, and repair time curves obtained from historical data, the failure probability, damage percentage, damage cost, and repair time of substations are estimated. A day-ahead risk-aware stochastic scheduling model is proposed to identify the critical substations whose protection by tiger dams maximizes grid resilience. The risk-aware approach prevents high cost and low resilience if a particular scenario with a low probability is realized. A scenario reduction method is developed to generate representative substation failure scenarios and reduce the computational cost of the optimization problem. The simulation results on a realistic 30-substation system show the effectiveness of the proposed model.

There are currently around four new flood-detention reservoirs (FDRs) built each year in the UK, which although only being modest structures with a median height of 4 m and reservoir capacity of 300 000 m3, can pose a significant risk to the community as they are located immediately upstream of the community they are protecting. These communities range from around five to several thousand households. The authors have designed and supervised over 30 new FDRs in the UK in the last 20 years, together with inspections of a similar number designed by others. This paper describes the emerging issues regarding risk of failure of these dams. Examples of measures to manage risk are described, with discussion of when selection of the options to increase resilience against a particular failure mode should be mandatory, and when it may be more appropriate to consider it on a case-by-case risk-based approach. The paper also discusses more strategic issues of design standards for design of spillways at FDRs, comparing the hazard introduced by construction of the reservoirs with the annual benefits of flood risk reduction.

As an important soil and water conservation engineering measure, more than 100,000 check dams are constructed across the Loess Plateau; these dams play a vital role in reducing floods and sediment in the region. However, the effects of check dams on hydrologic process are still unclear, particularly when they are deployed as a system for watershed soil and water management. This study examined the watershed hydrologic process modulated by the check dam system in a typical Loess Plateau catchment. By simulating scenarios with various numbers of check dams using a distributed physically-based hydrological model, the effects of the number of check dams on runoff generation and concentration were analyzed for the study catchment. The results showed that the presence of check dams reduced the peak discharge and the flood volume and extended the flood duration; the reduction effect on peak discharge was most significant among the three factors. The system of check dams substantially decreased the runoff coefficient, and the runoff coefficient reduction rate was greater for rainstorms with shorter return periods than for rainstorms with longer return periods. The check dams increased the capacity of the catchment regulating and storing floods and extended the average runoff concentration time in the catchment that flattened the instantaneous unit hydrograph. This study reveals the influencing mechanism of check dam system on the watershed hydrological process under heavy rainstorm conditions and provides a theoretical basis for evaluating the effects of numerous check dams on regional hydrology and water resources on the Loess Plateau.

Operational global-scale hydrological forecasting systems are widely used to help manage hydrological extremes such as floods and droughts. The vast amounts of raw data that underpin forecast systems and the ability to generate information on forecast skill have, until now, not been publicly available. As part of the Global Flood Awareness System (GloFAS; https://www.globalfloods.eu/) service evolution, in this paper daily ensemble river discharge reforecasts and real-time forecast datasets are made free and openly available through the Copernicus Climate Change Service (C3S) Climate Data Store (CDS). They include real-time forecast data starting on 1 January 2020 updated operationally every day and a 20-year set of reforecasts and associated metadata, available through the dedicated GloFAS FTP service. This paper describes the model components and configuration used to generate the real-time river discharge forecasts and the reforecasts. An evaluation of ensemble forecast skill using the Continuous Ranked Probability Skill Score (CRPSS) was also undertaken for river points around the globe. Results show that GloFAS is skilful in over 93thinsp;% of catchments in the short- (1- to 3-days) and medium-range (5- to 15-days) against a persistence benchmark forecast, and skilful in over 80 % of catchments out to the extended-range (16- to 30-days) against a climatological benchmark forecast. However, the strength of skill varies considerably by location with GloFAS found to have no or negative skill at longer lead times in broad hydroclimatic regions in tropical Africa, western coast of South America, and catchments dominated by snow and ice in high northern latitudes. Forecast skill is summarised as a new headline skill score to be added as a layer on the GloFAS forecast Web Map Viewer at the next GloFAS cycle release, expected Autumn 2020, to aid user’s interpretation and understanding of forecast quality.

MDFRC item.Hypoxic blackwater events are characterised by high levels of dissolved organic carbon in the water column,the metabolism of which depletes dissolved oxygen, which can cause fish and crustacean mortality. Understanding the drivers of and controls on hypoxic blackwater events is important in order to reduce the potential for detrimental water quality impacts from both managed and natural flows. After a decadelong drought in south-eastern Australia, a series of spring and summer flood events in 2010-2011 resulted in a large-scale hypoxic blackwater event in the southern Murray-Darling Basin that affected over 2000 km of river channels and persisted for 6 months. We examined the biogeochemistry and hydrology underpinning this extreme event and found that multiple drivers contributed to the development and persistence of hypoxic blackwater. Inundation of both forested and agricultural floodplains that had not been flooded for over a decade mobilised large stores of reactive carbon. Altered flow seasonality, due to a combination of climatic effects and river regulation, not only increased the risk of hypoxic blackwater generation but also shifted the proportion of bioavailable carbon that was returned to the river channels. Hypolimnetic weir discharge also contributed to hypoxia at some sites. These findings highlight the need for a whole-of-system perspective for the management of regulated river systems - especially in the face of a changing climate.

La Trobe University Faculty of Science, Technology and Engineering Murray Darling Freshwater Research CentreMDFRC item.Knowledge of the biology of native fishes of the Murray-Darling Basin is based largely on studies conducted under hatchery conditions and on a limited number of recreationally important species. From observations that increases in water level in aquaculture ponds initiate spawning in some species, and from limited studies of wild fishes and studies in overseas floodplain river systems, a perception has emerged of the importance of flooding and the flood plain in the life cycles of Murray-Darling fishes in general. However, there is little confirmatory evidence of the use of temporary floodplain habitats by larvae, juveniles or adults. The significance of in-channel habitats, especially for rearing, has received little attention. Murray-Darling fish species can be placed into three life history modes, based mainly on spawning style and time and developmental intervals of larvae at first feeding. Fish in each group may be able to take advantage of floods if the timing is right and prey are plentiful, however, the larvae of some species are able to recruit under non-flood conditions within the main river channel. This forms the basis of the low flow recruitment hypothesis, which attempts to explain why some species spawn during the warmest months and lowest flows and how they are able to recruit under these conditions. This hypothesis is then placed in the context of the current state of knowledge of the relationships between flow and the biology of Murray-Darling fishes, specifically cues for spawning, movement and recruitment. The lack of widespread evidence for floodplain use by any life history interval of fish may be due to a paucity of study, however, there are some fundamental factors, such as the predictability of timing and duration of high flow events as well as the lack of coincidence of high flows and high temperatures in some regions of the Basin, which may be important in determining the use of floodplain habitats by fish.

Shoreline erosion and storm tide inundation increasingly threaten coastal populations, infrastructure and economies. Hard infrastructure, known as gray infrastructure (e.g. concrete seawalls), has commonly been used to protect coastal communities but is expensive to build, maintain, and deteriorates coastal vegetation. Green infrastructure (e.g. restored or conserved mangrove and marsh ecosystems) delivers nature-based coastal protection but in comparatively lower density coastal areas. Nowadays a more popularized approach to coastal protection is hybrid eco-engineering. In this study, we discuss lessons-learnt on how the hybridization of engineered structures and wetland restoration practices compared with traditional gray and green approaches. We contrast hybrid applications in mangrove and tidal marsh areas in the UK and south-east Asia. The majority (70%) of successful hybrid infrastructure cases were underpinned by understanding of ecological and hydrological changes in response to infrastructure and involved a wide range of stakeholders. In terms of construction and maintenance cost, limited data suggested that hybrid infrastructure may be more cost effective than gray infrastructure, but more expensive than green; however, data were very limited and therefore we suggest the need for further cost-benefit analyses to inform a robust comparison. Development of new technologies should see growing efficacy of future hybrid infrastructure in mitigating coastal flood risks.

MDFRC item.Common carp Cyprinus carpio are a declared pest fish throughout the Murray-Darling Basin. Successful management of this highly-invasive species aimed at mitigating its detrimental effects on aquatic ecosystems is therefore a priority issue for wetland restoration and rehabilitation programmes for the benefit of native fish communities. As part of a large-scale, field-based experiment on carp impacts, a population of carp was extensively sampled from 2009 to 2011 at Brenda Park wetland (lower River Murray, South australia) under both drought and flooding conditions. A consistent young-of-year (YoY) cohort was present in the 2009–10 breeding season, indicating successful spawning within the wetland. However, the same cohort appeared not to leave the wetland later in the season, possibly as a result of drought-induced low-flow conditions. Conversely, there was no evidence for within-wetland spawning in 2010–11 and 2011–12. Following a major flood event in Summer/autumn 2011, a consistent stock-size (210–440 mm tL) component was present in the carp population. Despite one successful spawning event out of the three breeding seasons of sampling, it cannot be ruled out that Brenda Park can act as a recruitment hot-spot for carp, especially in light of the large-scale population dynamics of this species. Measures for wetland rehabilitation should account for this and rely on a combination of flow regulation practices, enhancement of native fish passage and integrated carp management/control measures involving use of selective traps or exclusion screens, removal programmes and, whenever feasible, water draw-downs.

La Trobe University Faculty of Science, Technology and Engineering Murray Darling Freshwater Research CentreMDFRC item.In many long-term, intensive experimental and field studies there often arises a need to trade off taxonomic resolutionfor ecological answers. Compounding this problem is a taxonomic impediment, the lack of experiencedtaxonomists capable of processing large numbers of samples to species resolution, especially in groups such as theRotifera. This paper has two aims: (1) To investigate the level of taxonomic resolution required to determine theimpact of a disturbance, in the form of a flood event; (2) to compare the impact of different taxonomic resolutionsin assessing biodiversity. Results suggest both family and generic resolution can be used to determine the impactof a flood event and that these levels have some applicability to biodiversity studies. Relatively inexperiencedtaxonomists who can identify the common rotifers to generic level, can be relied upon to detect disturbance tocommunity structure but their data become unreliable when assessing biodiversity.

La Trobe University Faculty of Science, Technology and Engineering Murray Darling Freshwater Research CentreMDFRC item.Floodplain inundation in rivers is thought to enhance fish recruitment by providing a suitable spawning environment and abundant food and habitat for larvae. Although this model has not previously been tested in Australian rivers, it is often extrapolated to fishes of the Murray-Darling Basin. Fortnightly sampling of larvae and juveniles was conducted in the unregulated Ovens River floodplain during spring–summer of 1999 (non-flood year) and 2000 (flood year). The only species that increased in larval abundance during or shortly after flooding was an introduced species, common carp (Cyprinus carpio). Additionally, the peak abundance of larvae on the floodplain occurred during a rapidly declining hydrograph under low flow conditions in isolated billabongs and anabranches. The low use of the inundated floodplain for recruitment contradicts previous models. We propose a model of the optimum environmental conditions required for use of the inundated floodplain for fish recruitment. The model suggests that the notion of the flood pulse alone controlling fish recruitment is too simplistic to describe all strategies within a system. Rather, the life history adaptations in the fauna of the system and aspects of the hydrological regime such as duration and timing of inundation will control the response of a river's fish fauna to flooding.

Objective: This case study documents Harris County hospitals’ flood preparedness and mitigation efforts before Hurricane Harvey, their collective response experience during Hurricane Harvey, and their lessons learned in the storm’s aftermath. Methods: The case study was constructed using a survey of hospital emergency managers, semi-structured interviews with local agencies involved in public health, emergency management, and health care, and an analysis of news reports and other documents from a variety of government agencies, local organizations, and hospitals themselves. Results: Harris County hospitals learned their most valuable lessons through their direct and repeated experience with flooding over the years, leading to improved preparedness before Hurricane Harvey. Hospital emergency response successes included infrastructure improvements, staff resilience, advanced planning, and pre-established collaboration. However, hospitals still experienced challenges with staff burnout, roadway flooding, and patient evacuation. Conclusions: Although the current state of hospital flood preparedness and mitigation is rather advanced and mature, it is advisable that Harris County takes steps to strengthen emergency management efforts in hospitals with fewer financial and staffing resources and less direct flood experience.

Understanding household disaster risk perception is crucial to formulate and apply disaster risk reduction strategies. Using survey data from 300 households from three highly disaster-prone areas of the lower Teesta River basin in Bangladesh, this study explores households’ risk perception of drought, earthquake, and flood at the local-level. The ordered probit regression model was applied to identify the factors influencing household disaster risk perception. Most of the respondents perceived the likelihood of occurring drought, earthquake, and flood hazards on large-scale in the selected areas which cause negative impacts on their quality of life and financial losses. They lacked knowledge on mitigation actions which makes them unable to control the devastating impacts of disasters. Econometric results show that households’ age, gender, education, and income-generating sources had significantly influenced the respondent's drought, earthquake, and flood risk perception (p

Intensive stratigraphic work on a horizontally extensive but shallow sample of early Holocene archaeology at Ntloana Tsoana rockshelter in western Lesotho has revealed a complex social history of waxing and waning occupation sandwiched between, and overlapping with, two distinct flood events. Bayesian models of radiocarbon and OSL ages are critical, enabling robust temporal ranges to be assigned to stratigraphic phases despite considerable challenges. This, in turn, means that site-specific happenings can be linked to broader ecological and cultural processes, including early Holocene warming and the emergence of southern Africa's small scraper tradition. By emphasising the duration of human activity, these results also show how specific hide working practices were repeated there by successive generations. Questions arise about the separation of scales that has characterised explanation in Later Stone Age archaeology and the largely overlooked role of persistent places in hunter-gatherer history. It is argued that repeatedly occupied rockshelters and their enduring sedimentary, bone and lithic residues would have been active entities in the past, anchoring people in time and space and may have led to an ontological merging of practice and place. Related ways of thinking about our own practice reveals that archaeologists can also benefit from thinking about sedimentary deposits as active and enduring as well as sequential.

Since the major flood event in 2007, RPS has been deeply involved in investigating, understanding and reducing flood risk across the Hull and Haltemprice catchment. RPS has developed and refined a complex integrated catchment model by combining Yorkshire Water's model of below-ground assets with data for the watercourses and overland flow paths obtained from the Environment Agency, East Riding of Yorkshire Council and Hull City Council. RPS used the model to identify major schemes, leading to the design of flood alleviation schemes at Willerby and Derringham, Anlaby and East Ella, and Cottingham and Orchard Park. With further enhancements, the model has been used to better understanding of the complex interactions between the various water systems and solutions are being identified for a long-term plan. Hull has many unique features, driven by its topography, geology and the historical developments of its sewerage network and waterways. These specific challenges require bespoke solutions and there is a clear desire among the partner organisations to work together to drive contemporary blue–green solutions. This requires multi-agency working and progressive thinking to deliver effective flood risk management. This paper reviews the challenges in understanding and resolving these issues.

Increasing studies have highlighted that the remarkable inherent uncertainty in design flood hydrograph (DFH) can potentially undermine flood management decisions. In order to quantitatively trace the propagation of DFH uncertainty in reservoir flood control system, we propose a novel methodological framework including three corn parts. First, a copula-based DFH estimation model integrating Bayes’ theorem is presented to estimate DFH under model parameter uncertainty. Second, we perform an optimal reservoir operation model for flood control (OROMFC) with uncertain DFH as input variable to derive reservoir flood control operations (i.e. output variable). Third, an information theory-based model is designed to trace the DFH uncertainty propagation in reservoir flood control system. A reservoir flood control system in the Han River basin in China is selected as case study. Related results indicate that uncertainty in reservoir flood control operations reduces in comparison with the remarkable uncertainty in DFH due to the performance of the OROMFC. Specifically, uncertainty in reservoir flood control operations in periods close to peak flow is much smaller compared with that in other periods. The phenomenon further highlights the importance of reservoir flood control operations during periods prior to peak flow. Additionally, we find that uncertainty in flood peak of DFH is the dominant factor affecting reservoir flood control operations compared with that in flood volume of DFH. Moreover, we explore the impact of reservoir flood control capacity on reservoir flood operations in the context of DFH uncertainty. An interesting linear expression is found and fitted for identifying design flood events inducing reservoir overtopping under specific reservoir flood control capacity.

Combatting the global threats to climate and biodiversity require further efforts in conserving earth's key ecosystems such as tropical forests. Today, worldwide conservation strategies have largely focused on protecting old-growth forests. Yet logged forests are more widespread than old-growth forests and harbour huge amounts of biodiversity and carbon stores, providing many ecosystem services and functions. In Borneo, logged forests support the livelihood of half a million indigenous people. Empowering these communities to manage logged forests can result in ecological, social and economic benefits. This study took place in Sabah, Malaysian Borneo, and focused on logged forests. We investigated how community members value ecosystem services (ES) in terms of importance for their lives, and explored factors influencing their valuation. We combined a qualitative analysis of semi-structured interviews with a statistical analysis of respondents’ preferences for ES. We present three key findings: 1. Clean water, clean air, regulation of temperature, flood and erosion are the ES ranked as the most important by all community members regardless of their spatial and socio-demographic backgrounds, 2. Prioritization for other ES varied according to members’ age, gender, ethnicity, dependence on forest resources and distance to forest, 3. Community members’ priorities for ES align with the ecological literature that these services are retained by logged forest. Our results emphasize the need to promote people-centred approaches to design sustainable conservation policies of logged forests in Sabah., Environmental Science & Policy, 128, ISSN:1462-9011, ISSN:1873-6416

The combined effect of global sea level rise and local subsidence phenomena poses a major threat to coastal settlements. Flooding events are expected to grow in frequency and magnitude, increasing the potential economic losses and costs of adaptation. In Italy, a large share of the population and economic activities are located along the coast of the peninsula, although risk of inundation is not uniformly distributed. The low-lying coastal plain of Northeast Italy is the most sensitive to relative sea level changes. Over the last half a century, the entire north-eastern Italian coast has experienced a significant rise in relative sea level, the main component of which was land subsidence. In the forthcoming decades, sea level rise is expected to become the first driver of coastal inundation hazard. We propose an assessment of flood hazard and risk linked with extreme sea level scenarios, both under historical conditions and sea level rise projections at 2050 and 2100. We run a hydrodynamic inundation model on two pilot sites located in the North Adriatic Sea along the Emilia-Romagna coast: Rimini and Cesenatico. Here, we compare alternative risk scenarios accounting for the effect of planned and hypothetical seaside renovation projects against the historical baseline. We apply a flood damage model developed for Italy to estimate the potential economic damage linked to flood scenarios and we calculate the change in expected annual damage according to changes in the relative sea level. Finally, damage reduction benefits are evaluated by means of cost-benefit analysis. Results suggest an overall profitability of the investigated projects over time, with increasing benefits due to increased probability of intense flooding in the next future.

A short span of abnormal precipitation in the year 2018 has ravaged the southwestern state of Kerala. It has resulted in widespread flooding and landslides with more than 400 casualties. The present study has implemented the SAR (Synthetic Aperture Radar)-based Sentinel 1C band satellite data. The researchers have analyzed the remotely sensed data to examine the severely affected areas. The study area included Alappuzha, Kottayam, Thrissur, and Pathanamthitta districts. The daily and monthly precipitation data is acquired from the Indian Meteorological Department (IMD) and Tropical Rainfall Measuring Mission (TRMM). During 2018, Kerala has experienced a severe escalation in the volume of rainfall from June onwards till September. The current study has analyzed the spatial and temporal variation in the extent of severe flooding in Kerala during the monsoon months of 2018. The south-central parts of Kerala are most severely impacted by flooding. The districts of Alappuzha and Kottayam were severely affected, followed by Thrissur and Pathanamthitta, moderate to low. The outcomes of this assessment would be helpful for risk-informed planning in the pre-disaster context and help in decision-making for response planning and early recovery.

Methods of rainstorm disaster risk monitoring based on retrieved satellite rainfall data are studied. Due to significant regional differences in global rainstorm disasters, they are not only affected by geographical location, topography, and rivers, but also by climate events. It is necessary to study disaster-causing factors, hazard-formative environments, and hazard-affected incidents of rainstorm disasters based on the climate distribution characteristics of precipitation and rainstorm disasters worldwide. According to a global flood disaster data-set from the last 20 years, the top four flood disaster causes (accounting for 96.8% in total) related to precipitation, from most to least influential, are heavy rain (accounting for 61.6%), brief torrential rain (16.7%), monsoonal rain (9.4%), and tropical cyclone/storm rain (9.1%). The dynamic global rainstorm disaster threshold is established using global climate data on 3319 rainstorm-induced floods and rainfall retrieved by satellites in the last 20 years. Taking the 7-day accumulated rainfall, 3-hour and 12-hour maximum rainfall, 24-hour rainfall, rainstorm threshold, and others as the main parameters, a rainstorm intensity index is established. The calculation method and global map of hazard-formative environmental factor and hazard-affected body factor of rainstorm disasters are formed based on the terrain, river datasets, the population, and economic datasets. Finally, a satellite remote sensing rainstorm disaster risk monitoring model is established including these three factors (rainstorm intensity index, hazard-formative environment factor, and hazard-affected body factor). The results show that the model can well describe the rainstorm disasters that happened in the middle and lower reaches of the Yangtze River in China and in South Asia in 2020.

Indo Gangetic flood plains are subjected to recurring floods due to large low-lying land areas adjacent to major Himalayan Rivers. Recent floods in the Ganga River during the late withdrawal phase of Indian summer monsoon rains in 2019 had reportedly caused death of ∼200–500 people and damaged major infrastructures in different parts of Bihar state, India. This paper presents a detailed analysis of the spatial extent and temporal pattern of flood inundation areas in Patna district of Bihar using Sentinel-1 Synthetic Aperture Radar (SAR) data. The results obtained using K-means classification show that about 1268 km2 (20% of the studied portion) of the land area were inundated during the peak flooding conditions on 9th October 2019. The peak flooding lasts for more than 20 days, with a maximum water depth of 18 m in the main river. Owing to the continually changing nature of river morphology by recurring floods, we also analyzed the channel morphology and bar characteristics before, during, and after the floods. Geomorphic change assessment indicates that the total bar occupied area was decreased from 661 km2 for pre-flood time to 446 km2 in peak flood time, whereas it retains its original shape in post-flood images.

We combine a glacier outburst flood model with a glacier flow model to investigate decadal to centennial variations in outburst floods originating from ice-dammed marginal basins. Marginal basins can form due to the retreat and detachment of tributary glaciers, a process that often results in remnant ice being left behind. The remnant ice, which can act like an ice shelf or break apart into a pack of icebergs, limits a basin's water storage capacity but also exerts pressure on the underlying water and promotes drainage. We find that during glacier retreat there is a strong, nearly linear relationship between flood water volume and peak discharge for individual basins, despite large changes in glacier and remnant ice volumes that are expected to impact flood hydrographs. Consequently, peak discharge increases over time as long as there is remnant ice remaining in a basin, and peak discharge begins to decrease once a basin becomes ice-free. Thus, similar size outburst floods can occur at very different stages of glacier retreat. We also find that the temporal variability in outburst flood magnitude depends on how the floods initiate. Basins that connect to the subglacial hydrological system only after reaching flotation depth yield greater long-term variability in outburst floods than basins that are continuously connected to the subglacial hydrological system (and therefore release floods that initiate before reaching flotation depth). Our results highlight the importance of improving our understanding of both changes in basin geometry and outburst flood initiation mechanisms in order to better assess outburst flood hazards and their impacts on landscape and ecosystem evolution.

Purpose The government-led public healthcare services in Sri Lanka became a major strength in managing the COVID-19 comparatively well. However, natural hazards are a major threat to this healthcare system, as they cause severe damages, especially to curative healthcare infrastructures such as hospitals. Floods have been the major contributor to the economic loss of the Sri Lankan healthcare system. Therefore, the purpose of this study is to develop a proper flood risk assessment framework for Sri Lankan hospitals. Design/methodology/approach This research study has attempted to develop a flood vulnerability assessment tool for hospitals using the concept of Depth Damage Functions (DDFs). Flood vulnerability curves have been developed for identified critical units of hospitals considering the damage caused to building contents which are predominantly expensive medical equipment. The damage caused only by wetting was considered in generating vulnerability curves. Structured interviews were conducted with government officials in the healthcare sector to gather details on the cost and damages of medical equipment. Pilot studies were carried out in two hospitals identified as located in flood-prone areas and have previous experiences of flooding, to acquire data regarding building contents of the critical units. Findings The developed vulnerability curves indicate that no major damage would occur to building contents in critical units (other than the labor room) until the inundation depth reaches a value of 0.6–0.9 m (varies for each type of unit). It is also noteworthy that after a certain range in the inundation depth, the damage increases drastically, and building contents would incur total damage if the inundation depth passes a value of 1.2–1.5 m. Originality/value This study explains the initial phase of developing a flood vulnerability assessment framework for Sri Lankan hospitals. Not many studies had been carried out to assess the vulnerability of hospitals specifically for floods using vulnerability curves. The study recommends a zoning system with pre-defined vulnerability levels for critical units during a flood, which can be associated with evacuation planning as well. Further studies must be carried out to verify this system for hospitals in Sri Lanka.