Fluvial Flood Research Articles

Recommendations to improve the interpretation of global flood forecasts to support international humanitarian operations for tropical cyclones

AbstractInternational humanitarian organisations increasingly turn to forecast teams to support the coordination of efforts to respond to disasters caused by hazards such as tropical cyclones and large‐scale fluvial floods. Such disasters often occur where there is limited local capacity or information available to support decision making and so global forecasting capacity is utilised to provide impact‐based flood forecast bulletins. A multidisciplinary team joined together to provide forecast bulletins and expertise for such events through the UK Foreign and Commonwealth Development Office (FCDO). This paper captures the successes and challenges from two cyclones: Hurricane Iota in Central America (November 2020) and Cyclone Eloise in Mozambique (January 2021). Recommendations to improve global forecasting systems are made which will benefit the international community of researchers and practitioners involved in disaster prediction, anticipatory action and response. These include the need for additional data and expertise to support the interpretation of global models, clear documentation to support decision makers faced with multiple sources of information, and the development of user relevant metrics to assess the skill of global models. We discuss the value of effective partnerships and improving synergies between global models and local contexts, highlighting how global forecasting can help build local forecasting capability.

A cross-scale modeling framework for simulating typhoon-induced compound floods and assessing the emergency response in urban regions

The cities within the Pearl River Delta (PRD), known as the Greater Bay Area (GBA), are flood-prone areas that faced frequent threats from typhoon-induced storm surges and rainfall in recent decades. To assess the potential consequences of a typical typhoon event, fine-scale simulations of inundation induced by both pluvial and fluvial flooding (known as compound flooding) are crucial for policymakers and concerned stakeholders to develop proper measures. In this study, we develop a cross-scale framework for modeling city inundation arising from typhoon-induced surges and torrential rainfall–runoff by coupling a three-dimensional ocean model (FVCOM) and a one-dimensional and two-dimensional coupling river analysis system (HEC-RAS). The ocean model is applied to capture the mesoscale behavior of surge and tide propagation from the deep sea to shallow offshore areas near the PRD. The river analysis system can simulate storm wave propagation along rivers, overtopping banks on floodplains and rainfall–runoff-induced flooding in urban regions at gradually refined scales. Second, the framework integrates GIS components (network analysis) with these hydraulic models. Through this framework, the urban emergency service coverage can be assessed under various potential flood scenarios during typhoon landfalls. Super Typhoon Mangkhut in 2018, the most devastating typhoon in the last decade in the PRD, is used as a case study in simulating and studying the flooding process. The simulated results show that in this typhoon event, pluvial and fluvial flooding play different roles in hindering the accessibility of emergency resources. Moreover, the interaction between pluvial and fluvial flooding significantly affects some urban regions.

Apply MIKE models to study the impacts of climate change on flooding and design adaptation measures in Can Tho City in the Vietnamese Mekong Delta.

Can Tho City in the Mekong Delta usually has pluvial and fluvial floods every year. The situation will get worst in the future under climate change. This study aims (i) to apply the MIKE 11, MIKE 21, and MIKE FLOOD model to simulate the impact of climate change scenarios on flooding in Can Tho city (ii) to suggest climate change adaptation measures for sustainable social-economic activities of the city. We considered the combined effect of sea-level rise including RCP 2.6, RCP 4.5, and RCP 8.5, and changes in climate factor (i.e., precipitation) for the years 2025, 2030, and 2050. The results show that the flood model is appropriate to simulate the flood. The flooded areas of the city under the scenarios of RCP 2.6 and RCP 8.5 will be increased from 2025 to 2050, and RCP 4.5 will be increased progressively from the year 2025 to 2030 and reduced to 2050. In the scenario of RCP 8.5, the flooded area of the city will be gradually increased in 2025, 2030, and 2050 at 3,559 ha, 3,719 ha, and 4,476 ha, respectively. Fifteen adaptation measures to climate change from 2021 to 2050 are suggested.

EXTREME RAINFALL-RUNOFF MODELING DURING REMNANTS OF IDA IN NEW YORK

While the effects of wind and pressure on coastal waters can generate large storm surges that lead to coastal flooding, storm surge represents only one driver of flooding. In reality, flooding is often driven by the combined action of several geophysical drivers (Couasnon et al., 2020; Zscheischler et al., 2018). Formally compound flooding is defined as the combined action of meteorological forces, tidal forces,, fluvial, and pluvial discharge (Zscheischler et al., 2018). Recent events such as the extreme rainfall associated with the remnants of Hurricane Ida in the Northeast United States have demonstrated the need to model the rainfall-runoff impact (i.e., pluvial flooding) and its downstream impact (i.e., fluvial flooding). In extreme rainfall cases in which large quantities of precipitation fall in short periods, urban environments often flood, and wastewater collection systems often exceed their design limit. In severe scenarios, surcharged sewer systems can significantly exacerbate urban flooding. While several existing flood risk methods consider storm surge in them approach, it remains active research topic concerning how and when rainfall-runoff processes should be incorporated in flooding models to assess site-specific flood risk. Often an approach is pursued that involves loosely coupling multiple numerical models each modeling a particular flood driver; however, this approach can become cumbersome. Instead in this work we pursue a different approach in which compound flooding can be resolved in a single numerical model (herein termed a monolithic approach).

Assessing the impact of climate change on fluvial flood losses in urban areas: a case study of Pamplona (Spain)

ABSTRACT Climate change is expected to increase the frequency and magnitude of flooding. Furthermore, in recent years, there has been an increase in city extent and population densities. This study considers the metropolitan area of Pamplona (Spain) as a case study. The delta changes in precipitation quantiles in the Arga River catchment, obtained from 12 climate models, have been transformed into peak flow delta changes using the Real-time Interactive Basin Simulator (RIBS) model. Also, three percentiles of flood quantile delta changes are selected. Water depths and flood extents expected in future flood events have been obtained using the two-dimensional Iber hydrodynamic model. The Safer_DAMAGE algorithm has been used to assess flood losses in urban areas at the building scale. The results show that flood losses are expected to be smaller for low return periods and greater for high return periods.

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

River-valley cities are susceptible to compound floods induced by intense rainfall and high riverine water level, especially where design standard of levees is low and overtopping-induced fluvial flood are very likely to run into urban area. However, the holistic impact of high riverine water level and intense rainfall on a river-valley city still needs to be assessed within a quantitative analyzing framework. In this study, a typical river-valley city named Yingde in Guangdong Province of China is selected as the study area. A framework combining multivariate statistical analysis and numerical hydrodynamic modeling is proposed to quantitatively assess the compound flood hazard in river valley cities. To be specific, a compound flood numerical model that can integrate rainfall and overtopping flow processes is first developed and validated based on historical observations. Then, the joint probability distribution of rainfall and riverine water level is established based on the copula function. After that, the compound flood scenarios corresponding to different joint return periods are simulated and compared. Considering only one factor may underestimate the probability of flooding occurrence. The compound flood severity in terms of both inundation area and depth for the study area is majorly dominated by intense rainfall, but the extra contribution from upstream water level cannot be ignored. An inundation amplification factor can be used to assess the amplification effect of high upstream water level on the flood hazard of the riparian area. For a site that is quite near the river, the inundation amplification factor can be drastically decreased as the levee crest elevation is heightened. Without the contribution from the fluvial floods, the rainfall-induced inundation could be several times smaller than the compound floods.

Challenges for Flood Risk Reduction in Poland’s Changing Climate

Floods are the main natural disaster in Poland, and the risk of both fluvial and pluvial floods is serious in the country. Pluvial floods are on the rise in the changing climate, particularly in increasingly sealed urbanized areas. In this paper, we examine the changes in flood risk in Poland, discussing the mechanisms, observations, projections and variability. Next, we discuss flood risk management in the country, including specific issues related to urban and rural areas and the synergies between flood and drought risk reduction measures. We identify and assess the weaknesses of the existing flood risk management plans in Poland for the first planning period 2016–2021 and for the second planning period 2022–2027. We find the level of implementation of plans in the former period to be very low. Many planned measures do not have much to do with flood risk reduction but are often linked to other objectives, such as inland navigation. The plans contain numerous small measures, which come across as inapt and economically ineffective solutions. We specify policy-relevant recommendations for necessary and urgent actions, which, if undertaken, could considerably reduce flood risk. We also sketch the way ahead for flood risk management in Poland within the timeframe of the implementation of plans for 2022–2027 and the next regular update of plans for 2028–2033.

Sea Level Rise-Induced Transition from Rare Fluvial Extremes to Chronic and Compound Floods

Flooding is becoming more frequent along U.S. coastlines due to the rising impacts of fluvial and coastal flood sources, as well as their compound effects. However, we have a limited understanding of mechanisms whereby sea level rise (SLR) changes flood drivers and contributes to flood compounding. Additionally, flood mitigation studies for fluvial floodplains near tidal water bodies often overlook the potential future contribution of coastal water levels. This study investigates the role of SLR in inducing high-tide flooding (HTF) and compound flooding in a neighborhood that lies on a fluvial floodplain. Eastwick, Philadelphia, is a flood-prone neighborhood that lies on the confluence of two flashy, small tributaries of the tidal Delaware River. We develop a combined 1D-2D HEC-RAS fluvial-coastal flood model and demonstrate the model’s accuracy for low-discharge tidal conditions and the extreme discharge conditions of tropical Cyclone (TC) Isaias (2020) (e.g., Root Mean Square Error 0.08 and 0.13 m, respectively). Simulations show that Eastwick may experience SLR-induced HTF as soon as the 2060s, and the flood extent (34.4%) could become as bad as present-day extreme event flooding (30.7% during TC Isaias) as soon as the 2080s (based on 95th percentile SLR projections). Simulations of Isaias flooding with SLR also indicate a trend toward compounding of extreme fluvial flooding. In both cases the coastal flood water enters Eastwick through a different pathway, over a land area not presently included in some fluvial flood models. Our results show that SLR will become an important contributor to future flooding even in fluvial floodplains near tidal water bodies and may require development of compound flood models that can capture new flood pathways.

Coastal and River Embankment Performance at Cengkareng Drain Estuary Under Compound Hazards Conditions Using HEC-RAS 2D

Jakarta is prone to pluvial, fluvial, and coastal flooding due to its geographical location and topography. In response to this problem, the Indonesian government has implemented several master plans, including the National Capital Integrated Coastal Development (NCICD). This ongoing program encompasses the construction of coastal and river embankment that stretch all over the coast of Jakarta. Since many coastal areas in Jakarta are residential or industrial, evaluating this performance of embankment has become crucial for effective flood management. The findings of this research can also support the development of other locations where NCICD embankment plan and enhance coastal resilience. Therefore, this research assessed the effectiveness of coastal and river embankment at Cengkareng Drain, a vital floodway in Jakarta, during extreme events that occur simultaneously. To simulate flooding events, two-dimensional HEC-RAS features were used to numerically calculate the area and depth of inundation. The simulation required geometry, terrain, land cover, and unsteady flow data. For the flow boundary conditions, a 100-year design rainfall, HHWL (Highest High Water Level), and 100-year design wave were considered to represent estuary conditions accurately. The simulation result showed that the maximum water level influenced by these factors was +3.145 mMSL, while the planned embankment top elevation was +3.40 mMSL. Furthermore, without the NCICD embankment, the simulation showed an inundation area of 1212.37 ha, which was reduced to 1111.22 ha after their implementation, leading to a decrease of 101.15 ha. This reduction significantly decreases potential damage to property and infrastructure, particularly in densely populated areas. The simulation also showed a reduction of 86.49 hectares or 66.22% in the inundation area with a depth exceeding 1 meter. These findings demonstrate the effectiveness of embankment in reducing the inundation area without any overtopping incidents.

Fusing morphometric characteristics with extreme precipitation indices for identifying the most vulnerable sub-basin at risk of flooding

Fluvial floods are commonly studied as an occurrence at the level of a specific basin and are speculated to be closely related to the basin's morphometry. It is possible to identify and rank sub-basins based on how susceptible they are to fluvial flooding events using morphometric criteria. However, one of the key causes that triggers fluvial flooding is the increase in precipitation extremes and changes to their patterns. In this study, influence of morphometric factors and extreme precipitation events on the hydrological responses of the Brahmani River, India as well as their sensitivity to fluvial flooding, are investigated to identify the most vulnerable sub-basin in a catchment. The morphometric parameters were calculated from a digital elevation model (DEM), and the change in trend of extreme precipitation indices was detected using precipitation data of period 1991 to 2021. Furthermore, the Standardized Precipitation Index (SPI) was used to determine the frequency of wet cycles on time scale of 1, 3, 12, and 24 months, as well as their link to fluvial flooding. The two sub-basins of the catchment that are most vulnerable to river flooding are recognised as Noamundi and Gomlai based on morphometric criteria. However, analysis of SPI and extreme precipitation indices showed that the Jenapur sub-basin is the most vulnerable to flooding. It is also corroborated with analytic hierarchy process (AHP) based weighted overlay analysis and historical flood records. The outcomes will assist researchers in better understanding the mechanisms causing flooding in the Brahamni River Basin and in developing flood mitigation practices for the most vulnerable Jenapur sub-basin.

Sampling‐Based Methods for Uncertainty Propagation in Flood Modeling Under Multiple Uncertain Inputs: Finding Out the Most Efficient Choice

AbstractIn probabilistic flood modeling, uncertainty manifests in frequency of occurrence, or histograms, for quantities of interest, including the Flood Extent and hazard rating (HR). Such modeling at the field‐scale requires the identification of a more efficient alternative to the Standard Monte Carlo (SMC) method that can reproduce comparable output probability distributions with a relatively reduced sample size, including detailed histograms of quantities of interest. Latin hypercube sampling (LHS) is the most evaluated alternative for fluvial floods but yields no considerable sample size reduction. Potentially better alternatives include adaptive stratified sampling (ASS), Quasi Monte Carlo (QMC) and Haar‐wavelet expansion (HWE), which are yet unevaluated for probabilistic flood modeling. To fulfill this gap, LHS, ASS, QMC, and HWE are compared to quantify sample size reduction to reproduce output detailed histograms—for Flood Extent, and average and maximum HR—while keeping the difference below 10% to the reference SMC prediction. The comparison is done for two test cases with two (i.e., inflow discharge and Manning's coefficient) and three (i.e., further including the ground elevation) input random variables, and a real case with five input random variables. With two input random variables, all four alternatives yield sample size reductions, with QMC and HWE considerably outperforming the others; with three and more input random variables, HWE becomes inflexible and LHS underperforms. Still, QMC is a better choice than ASS to boost sample size reduction for the real case and shall be preferred in probabilistic flood modeling. Accompanying research codes are openly available online.

Modeling compound flood risk and risk reduction using a globally applicable framework: a pilot in the Sofala province of Mozambique

Abstract. In low-lying coastal areas floods occur from (combinations of) fluvial, pluvial, and coastal drivers. If these flood drivers are statistically dependent, their joint probability might be misrepresented if dependence is not accounted for. However, few studies have examined flood risk and risk reduction measures while accounting for so-called compound flooding. We present a globally applicable framework for compound flood risk assessments using combined hydrodynamic, impact, and statistical modeling and apply it to a case study in the Sofala province of Mozambique. The framework broadly consists of three steps. First, a large stochastic event set is derived from reanalysis data, taking into account co-occurrence of and dependence between all annual maximum flood drivers. Then, both flood hazard and impact are simulated for different combinations of drivers at non-flood and flood conditions. Finally, the impact of each stochastic event is interpolated from the simulated events to derive a complete flood risk profile. Our case study results show that from all drivers, coastal flooding causes the largest risk in the region despite a more widespread fluvial and pluvial flood hazard. Events with return periods longer than 25 years are more damaging when considering the observed statistical dependence compared to independence, e.g., 12 % for the 100-year return period. However, the total compound flood risk in terms of expected annual damage is only 0.55 % larger. This is explained by the fact that for frequent events, which contribute most to the risk, limited physical interaction between flood drivers is simulated. We also assess the effectiveness of three measures in terms of risk reduction. For our case, zoning based on the 2-year return period flood plain is as effective as levees with a 10-year return period protection level, while dry proofing up to 1 m does not reach the same effectiveness. As the framework is based on global datasets and is largely automated, it can easily be repeated for other regions for first-order assessments of compound flood risk. While the quality of the assessment will depend on the accuracy of the global models and data, it can readily include higher-quality (local) datasets where available to further improve the assessment.

Co-occurrence of pluvial and fluvial floods exacerbates inundation and economic losses: evidence from a scenario-based analysis in Longyan, China

Hydrodynamics and socio-economic impacts of compound floods as the result of co-occurring pluvial and fluvial floods, have not been well studied, which challenges conventional urban flood risk management that treats different types of floods separately. This study generates a high-resolution land surface digital surface model based on images from unmanned aerial vehicles, and incorporates it into a combined flooding model that integrates the 1D river hydrodynamic model, 1D urban drainage hydrodynamic model and 2D overland flow model, in order to simulate the inundation characteristics of extreme floods when local pluvial floods coincide with upstream fluvial floods, and in a further step to quantify the direct economic losses on urban physical systems. As demonstrated by an empirical study of Longyan, China, the combination of pluvial and fluvial floods leads to substantial exacerbation in inundation extent and depth. Consequently, the joining of pluvial and fluvial floods greatly amplifies economic losses to urban physical systems, indicating that ignoring co-occurrence of different types of floods will potentially lead to underestimation of flood risk and insufficient adaptation. Our study emphasizes the need to account for the co-occurrence of multiple types of floods in flood risk assessment and management, to avoid the shortcomings of fragmented responses.

Model-based assessment of flood generation mechanisms over Poland: The roles of precipitation, snowmelt, and soil moisture excess

Hydrometeorological variability, such as changes in extreme precipitation, snowmelt, or soil moisture excess, in Poland can lead to fluvial flooding. In this study we employed the dataset covering components of the water balance with a daily time step at the sub-basin level over the country for 1952–2020. The data set was derived from the previously calibrated and validated Soil & Water Assessment Tool (SWAT) model for over 4000 sub-basins. We applied the Mann Kendall test and circular statistics-based approach on annual maximum floods and various potential flood drivers to estimate the trend, seasonality, and relative importance of each driver. In addition, two sub-periods (1952–1985 and 1986–2020) were considered to examine changes in flood mechanism in the recent decades. We show that floods in the northeast Poland were decreasing, while in the south the trend showed a positive behavior. Moreover, the snowmelt is a primary driver of flooding across the country, followed by soil moisture excess and precipitation. The latter seemed to be the dominant driver only in a small, mountain-dominated region in the south. Soil moisture excess gained importance mainly in the northern part, suggesting that the spatial pattern of flood generation mechanisms is also governed by other features. We also found a strong signal of climate change in large parts of northern Poland, where snowmelt is losing importance in the second sub-period in favor of soil moisture excess, which can be explained by the temperature warming and diminishing role of snow processes.

Forecasting tropical cyclone rainfall and flooding hazards and impacts

This review summarizes the rapporteur report on advances in monitoring and forecasting of rainfall associated with tropical cyclones (TCs) and its impact during 2014–18, as presented to the 10th International Workshop on TCs (IWTC-10) held in Bali, Indonesia during 5th – 9th December 2022. Major physical processes that can modulate TC rainfall distribution, including topography, storm motion, vertical wind shear, and intensity, along with the fundamental physics of rain bands and clouds as simulated by numerical models, diurnal variation of rainfall, and various synoptic and mesoscale features controlling the rainfall distribution are briefly discussed. Improvements to the dynamic core and physical processes in global models are providing useable forecasts nearly up to 7 days. This report also summarizes, some tools that have been developed to predict TC rainfall. Lately there is a tendency for operational forecasting centers to utilize multi-model ensemble systems for rainfall forecasting that demonstrate superior performance than individual models, ensemble members, or even single model ensembles. Major impacts include pluvial and fluvial floods, and landslides. The techniques developed by various forecasting centers to assist in predicting and communicating the impacts associated with these events are also presented in this report.

River plastic transport and deposition amplified by extreme flood

Plastic pollution in the world’s rivers and ocean is increasingly threatening ecosystem health and human livelihood. In contrast to what is commonly assumed, most mismanaged plastic waste that enters the environment is not exported into the ocean. Rivers are therefore not only conduits but also reservoirs of plastic pollution. Plastic mobilization, transport and retention dynamics are influenced by hydrological processes and river catchment features (for example, land use, vegetation and river morphology). Increased river discharge has been associated with elevated plastic transport rates, although the exact relation between the two can vary over time and space. However, the precise role of an extreme discharge event on plastic transport is still unknown. Here we show that fluvial floods drive macroplastic (>2.5 cm) transport (items h−1) and accumulation (items m−2) in river systems. We collected unique observational evidence during the July 2021 flood along the whole Dutch part of the Meuse. Plastic transport multiplied by a factor of over 100 compared with non-flood conditions (3.3 × 104 versus 2.3 × 102 items h−1). Over one-third of the modelled annual plastic item transport was estimated to occur within 6 days of extreme discharge. Between Maastricht and Ravenstein (291 km and 131 km from the river mouth), plastic transport during the flood period decreased by 90%, suggesting that the dispersal of plastic mobilized during the flood is limited due to the entrapment on riverbanks, in vegetation and on the floodplains. Plastic transport and accumulation on the riverbanks decreased significantly along the river, corroborating the river’s function as a plastic reservoir. Using new observational evidence, we demonstrate the crucial role of floods as drivers of plastic transport and accumulation in river systems. Floods amplify the mobilization of plastics, but the effects are local, and the river-scale dispersal is limited. We anticipate that our findings will serve as a starting point for improving global estimates of river plastic transport, retention and export into the sea. Moreover, our results provide essential insights for future large-scale and long-term quantitative assessments of river plastic pollution. Reliable observations and a fundamental understanding of plastic transport are key to designing effective prevention and reduction strategies.

A probabilistic approach to levee reliability based on sliding, backward erosion and overflowing mechanisms: Application to an inspired Canadian case study

AbstractImproving protection against fluvial floods requires a better estimation of levee failure. We developed an assessment method of levee failure probabilities for sliding, backward erosion, and overflowing each represented by fragility curves. We tested two approaches to aggregate those fragility curves into a global fragility curve respectively using: an enveloping curve and Monte‐Carlo simulations. We implemented this approach to earthen levee reliability for several flood return periods to the Bow River in Calgary, Canada. We used limit equilibrium method to estimate the safety factor of the levee segment and Monte‐Carlo simulations to estimate sliding probabilities. We used Terzaghi's critical hydraulic gradient to estimate backward erosion failure probabilities. The estimation of overflowing probabilities required expert judgment. We discussed how the choice of the hydraulic gradient area and the consideration of a steady state or transient model impact backward erosion failure probabilities. The results showed for our study case that, even though the transient model is a closer representation of reality, the levee saturation parameter has little impact on hydraulic gradient values, by extension, on sliding and backward erosion failure probabilities. The Monte‐Carlo aggregated fragility curve is more realistic than the envelop curve of the failure mechanisms for an equivalent computation time.

Neural networks for fast fluvial flood predictions: Too good to be true?

AbstractAccurate models with low computational times are required to predict the consequences of fluvial floods in real‐time. Even though detailed hydraulic models can predict flood water levels and corresponding inundation extents with high accuracy, their computational times limit their applicability to being used as a flood early‐warning system. Therefore, conceptual models were developed in the literature for many years. These types of models do not attempt to represent the complex dynamic flood generation processes but are based on simplified hydraulic concepts, generally only using a digital elevation model as input. However, a shift in this research field is currently present from conceptual models to data‐driven models, and more specifically to neural networks. This paper discusses the benefits and drawbacks of both modelling approaches and speculates which method is most promising to be used as a flood warning system to predict the consequences of fluvial floods in real‐time.

Quantitative evaluation of sea reclamation activities on tidal creek connectivity

Deltas are in a dynamic balance due to the impact of fluvial and coastal flooding, and hydrological connectivity plays an important role. In recent decades, the dynamic equilibrium has been influenced by upstream and local human activities, including sea reclamation activities. However, in most instances, the influence of human activities has not been explicitly distinguished and quantified in detail. In this paper, the influence of sea reclamation activities on hydrological connectivity in the Yellow River Delta was quantified by parameterizing the resistance surfaces (a spatial layer that assigns a value to each landscape feature, indicating the degree to which that variable impedes or promotes movement) that includes sea reclamation activities. By optimizing a functional relationship between landscape features and hydrological connectivity (water flow movement patterns), the values in the resistance surfaces could be assigned. We first calculated hydrological distances among bifurcations from 1985 to 2020 with a 5-year interval representing the hydrological connectivity of each tidal creek. The sea reclamation activities in the YRD were classified into four: reclaimed land, sea enclosure activity, freshwater resource facilities, and engineering in the oil field to create resistance surfaces. We identified that the periods of 1990–1995 and 2000–2005 were under the most severe influence of sea reclamation activities. Sea enclosure activity, freshwater resource facilities, and engineering in oil fields played major roles in composing resistance surfaces. Mariculture (quantified relative resistance value, 1.00), reservoir (0.92), agriculture (0.91), and river (0.97) were the features with the highest resistance values in the initial and mature development stages. The formation of resistance (costs to movement) was due to human activities and natural factors, for example, the evolution of tidal creeks. To develop the resource in tidal flats sustainably, systematic monitoring and sufficient conservation awareness were required. This study contributed to coastal management and planning by providing a quantified assessment of different types of sea reclamation activities.

Spatiotemporal variations of riverine flood fatalities: 70 years global to regional perspective

AbstractFloods are among the most devastating natural hazards worldwide. While rainfall is the primary trigger of floods, human activities and climate change can exacerbate the impacts of floods and lead to more significant economic and social consequences. In this research, fluvial flood fatalities in the 1951–2020 period have been studied, analyzing the information reported in the Emergency Database (EM‐DAT). The EM‐DAT data were classified into five categories in terms of the number of events and fatalities connected with riverine floods, considering only events that caused more than 10 fatalities. The results show that the severity of flood‐related fatalities is not equally distributed worldwide, but presents specific geographical patterns. The flood fatality coefficient, which represents the ratio between the total number of fatalities and the number of flood events, calculated for different countries, identified that the Southern, Eastern, and South‐Eastern regions of Asia have the deadliest floods in the world. The number of flood events has been increasing since 1951 and peaked in 2007, following a relative decline since then. Though, the resulting fatalities do not follow a statistically significant trend. An analysis of the number of flood events in different decades shows that the 2001–2010 decade saw the highest number of events, which corresponds to the largest precipitation anomaly in the world. The lethality of riverine floods decreased over time, from 412 per flood in 1951–1960 to 67 in the 2011–2020 decade. This declining trend is probably a consequence of a more resilient environment and better risk reduction strategies. Based on the presented data and using regression analysis, relationships between flood fatalities and the number of flood events with population density and gross domestic product are developed and discussed.