Return Period Flood Research Articles

A new multiple return-period framework of flood regulation service—applied in Yangtze River basin

An ecosystem’s flood regulation service (EFRS) is important for alleviating flood risk. Both the EFRS and the relationship between EFRS supply and demand may change across flood return periods. However, most studies only considered the EFRS under a single flood return period. In this regard, a new framework is proposed that integrates multiple flood return periods to assess the expected annual EFRS supply and demand. It also considers the upstream EFRS supply flowing from the headwaters toward the downstream. A case study in the Yangtze River Basin, China, shows that the EFRS demand increases dramatically from 25- to 200-year return periods, while the EFRS supplies remain relatively constant. In terms of the expected annual EFRSs that integrate the four return-period EFRS demands and local supplies, 47 (or 43.12%) sub-basins are found to be unsatisfied (the demand is larger than the supply). This number could be reduced to 17 (or 15.60%) sub-basins if the upstream EFRS supply is considered in comparing the EFRS supply and demand, implying the importance of a catchment-wide EFRS management, particularly protecting the upstream forests, rivers and lakes, grasslands, as well as properly regulating the dams. The proposed framework could be readily applied in other basins and shed light on a comprehensive understanding and management of the EFRSs.

Plastic in global rivers: are floods making it worse?

Riverine plastic pollution is of global concern due to its negative impact on ecosystem health and human livelihood. Recent studies show a strong link between river discharge and plastic transport, but the role of floods is still unresolved. We combined high-resolution mismanaged plastic waste data and river flood extents with increasing return periods to estimate flood-driven plastic mobilisation, from local to global scale. We show that 10 year return period floods already tenfold the global plastic mobilisation potential compared to non-flood conditions. In the worst affected regions, plastic mobilisation increases up to five orders of magnitude. Our results suggest a high inter-annual variability in plastic mobilisation, previously ignored by global plastic transport models. Flood defences reduce plastic mobilisation substantially, but regions vulnerable to flooding often coincide with high plastic mobilisation potential during floods. Consequentially, clean-up and mitigation measures and flood risk management are inherently interdependent and need to be managed holistically.

Daily maximum runoff frequency analysis under non-stationary conditions due to climate change in the future period: Case study Ghareh Sou basin

Abstract The frequency analysis of the maximum instantaneous flood is mostly based on the stationary assumption. The purpose of the present study is to compare the results of maximum instantaneous flood analysis under stationary and non-stationary conditions in Ghareh Sou basin, and also answer the question as to whether there is a difference between estimating the return period of maximum instantaneous flood in stationary and non-stationary conditions. First, the values of the temperature, wind speed, and rainfall of the study area under the two scenarios of Representative Concentration Pathway (RCP) 2.6 and 8.5 of the Hadley Centre coupled Model, version3 (HadCM3) model were downscaled. In the following, the Variable Infiltration Capacity (VIC) model was utilized to generate daily runoff. For converting the daily discharge to the maximum instantaneous flood, four methods of Fuller, Sangal, Fill Steiner, and artificial neural network (ANN) were compared. Finally, the maximum instantaneous floods of the future period were introduced to the Non-stationary Extreme Value Analysis (NEVA) software. Based on the results obtained from the research, the lack of considering the non-stationary conditions in the flood frequency analysis can result in underestimating the maximum instantaneous flood, which can also provide more risks for the related hydraulic structures.

Probabilistic Projections of Multidimensional Flood Risks at a Convection‐Permitting Scale

AbstractUnderstanding future river flood risk is a prerequisite for developing climate change adaptation strategies and enhancing disaster resilience. Previous flood risk assessments can barely take into account future changes of fine‐scale hydroclimatic characteristics and hardly quantify multivariate interactions among flood variables, thereby resulting in an unreliable assessment of flood risk. In this study, for the first time, we develop probabilistic projections of multidimensional river flood risks at a convection‐permitting scale through the Weather Research and Forecasting (WRF) climate simulations with 4‐km horizontal grid spacing. Vine copula has been widely used to assess the multidimensional dependence structure of hydroclimate variables, but the commonly used frequentist approach may fail to identify the correct vine model and to obtain the uncertainty interval. Thus, a Bayesian vine copula approach is proposed to explicitly address the multidimensional dependence of flood characteristics (i.e., flood peak, volume, and duration) and underlying uncertainties. The proposed approach enables a robust assessment of return periods of future floods for Guadalupe and Mission river basins located in South Texas of the United States. Our findings reveal that the South Texas region is projected to experience more flood events with longer duration and greater discharge volume. The flood peak, however, will not necessarily increase even though precipitation extremes are expected to become more frequent. The projected flood return periods over the Guadalupe river basin do not show an obvious increase while the Mission river basin is projected to face a dramatic increase in flood risk with exposed to 100‐year and even severer floods nearly every 2 years, on average, when considering the combined effects of flood peak, volume, and duration.

Decrease process analysis of urban system resilience based on the extreme flood simulation

Urban flood is growing worldwide due to climate change, rapid urbanization and population increase. Although the concept of resilience is an effective tool to deal with urban flood, urban flood resilience remains difficult to put into practice nowadays. The attenuation process of urban flood control capacity under the influence of flood is still a challenge. And the stage damage of flood resilience is strongly linked with the recovery of urban system to floods. But current studies failed to capture the change characteristic of flood resilience in time stage. Therefore, this study made stage damage analysis based on flood simulation and modelling in Jianye and Gulou District. Results reveal that Jianye has the higher inundated area and exposed population and asset to flood. Gulou shows more resilience to urban flood with flood return periods of 100 years. Moreover, the stage damage curve benefits the comprehensive understanding of loss and recovery process. This study provides a theoretical support for effective adaptive strategy to urban flood.

Analisis Numerik 1D Pengendalian Banjir pada Wilayah Padat Penduduk dengan Persamaan St. Venant

As one of the densest populations in Bandung City, Ujung Berung District has suffered because of flood disaster, which resulted several problems in that area. These problems arose due to non-optimal land handling, especially about a sporadic land alteration from agricultural to residential areas on the upstream. One of the disastrous area is the northern Ujung Berung at Griya Winaya Resident. The drainage channel on this resident was originally an irrigation channel system which been changed without an appropriate technical justification. Therefore, the residents, with ±800 population or 300 household/Ha, struggled to deal with flood problems when they get rainfalls with an intensity more than 30 mm/hour. This research conducted at RT 05 RW 12 as the worst affected area, and used Storm Water Management Model (SWMM) software to determine flood routing by 1D St. Venant equation. Using a rainfall data from Cibiru rainfall station for 2005-2016 periods, the model successfully developed flood simulation at dense area with a narrow and winding channel. Moreover, the 10 (ten) years return period of annual flood can be managed with the increasing of drainage channel until 100 percent in dimension.

Climate change impacts on peak river flows: Combining national-scale hydrological modelling and probabilistic projections

Potential future increases in flooding due to climate change need to be taken into consideration when designing flood defences or planning new infrastructure or housing developments. Existing guidance on climate change allowances in Great Britain was based on research that developed a sensitivity-based approach to estimating the impacts of climate change on flood peaks, which was applied with catchment-based hydrological models. Here, the sensitivity-based approach is applied with a national-scale grid-based hydrological model, producing modelled flood response surfaces for every river cell on a 1 km grid. This provides a nationally consistent assessment of the sensitivity of flood peaks across Britain to climatic changes. The flood response surfaces are then combined with the most recent climate change projections, UK Climate Projections 2018 (UKCP18), to provide location-specific information on the potential range of impacts on floods across the country, for three flood return periods, three future time-slices and four emissions scenarios. An accompanying web-tool provides a convenient way to explore the large amount of data produced. Consideration is now being given to how to use the latest work to update guidance on climate change and flood peaks, including a workshop held to gather stakeholder views.

Flood Modeling Assessment: A Case of Bishnumati River

Flood, a common water induced disaster of a monsoon season, is the recurring phenomenon in Nepal. To study this disaster, different flood modelling had been conducted for different river basins following different modelling tools. This study describes the technical approach of probable flood vulnerability and hazard analysis of Bishnumati river catchment and analyze the result with previous study done for the same study area. The method adopted for previous study in 2009 was adopted in this study as well in order to compare the results. One dimensional hydraulic model HEC-RAS with HEC GeoRAS interface in co-ordination with Arc GIS was applied for the analysis.. Hazard maps, landuse vulnerability maps of various return periods (10 Yrs, 20Yrs, 50Yrs and 100Yrs), were prepared in ArcGIS. The results of flood frequency analyzed by WECS/ DHM method showed discharges of 445 m³/s, 541m³/s, 648m/s, 725 m³/s for 10, 20, 50 and 100 years return period floods. The primary data of the study showed most of the flooding area had water depth greater than 3m. The assessment of the flood inundated area showed that large percentage of vulnerable area lied in built up areas followed by barren land.

Comparing earth observation and inundation models to map flood hazards

Global flood models (GFMs) and earth observation (EO) play a crucial role in characterising flooding, especially in data-sparse, under-resourced regions of the world. However, validation studies are often limited to a handful of historic events and do not directly assess the ability of these products to simulate flood hazard—the probability that flooding will occur in a given location. As a result, it is difficult for stakeholders to decipher the ability of either models or observations to identify flood hazard and make decisions to mitigate for flooding. Here, we leverage flood observations from 20 years of MODIS data to compare the recorded flooding with what would be expected given the hazard simulated by a GFM. We devise an approach, Flood Expectation Per Pixel, and apply it across four large basins in Africa—Congo, Niger, Nile and Volta representing a variety of biomes. We estimate the uncertainty of EO to capture flood events due to burned areas, cloud cover and vegetation, incorporating uncertainty estimates when comparing to modelled hazard. We found that at lower return periods (RPs) (<20 years), the EO data records less flooding than the GFM, suggesting GFMs overpredict frequent flooding. For RPs between 50 and 100 years, GFM and EO data show greater consistency given the uncertainties we consider. For large RPs (100 years) the EO observations show more flooding than expected given the GFM data, potentially due to data errors and non-fluvial flooding, however there are too few observations to draw significant conclusions at these RPs. The EO record indicates that the GFM can differentiate between flood RPs. We find EO and GFM complement each other and thus should be used in tandem to inform strategies to mitigate floods across the hazard spectrum from frequent to extreme flood events.

Impacts of climate change on hurricane flood hazards in Jamaica Bay, New York

Sea level rise (SLR) and tropical cyclone (TC) climatology change could impact future flood hazards in Jamaica Bay—an urbanized back-barrier bay in New York—yet their compound impacts are not well understood. This study estimates the compound effects of SLR and TC climatology change on flood hazards in Jamaica Bay from a historical period in the late twentieth century (1980–2000) to future periods in the mid- and late-twenty-first century (2030–2050 and 2080–2100, under RCP8.5 greenhouse gas concentration scenario). Flood return periods are estimated based on probabilistic projections of SLR and peak storm tides simulated by a hydrodynamic model for large numbers of synthetic TCs. We find a substantial increase in the future flood hazards, e.g., the historical 100-year flood level would become a 9- and 1-year flood level in the mid- and late-twenty-first century and the 500-year flood level would become a 143- and 4-year flood level. These increases are mainly induced by SLR. However, TC climatology change would considerably contribute to the future increase in low-probability, high-consequence flood levels (with a return period greater than 100 year), likely due to an increase in the probability of occurrence of slow-moving but intense TCs by the end of twenty-first century. We further conduct high-resolution coastal flood simulations for a series of SLR and TC scenarios. Due to the SLR projected with a 5% exceedance probability, 125- and 1300-year flood events in the late-twentieth century would become 74- and 515-year flood events, respectively, in the late-twenty-first century, and the spatial extent of flooding over coastal floodplains of Jamaica Bay would increase by nearly 10 and 4 times, respectively. In addition, SLR leads to larger surface waves induced by TCs in the bay, suggesting a potential increase in hazards associated with wave runup, erosion, and damage to coastal infrastructure.

New Approach to Estimate Extreme Flooding Using Continuous Synthetic Simulation Supported by Regional Precipitation and Non-Systematic Flood Data

Stochastic weather generators combined with hydrological models have been proposed for continuous synthetic simulation to estimate return periods of extreme floods. Yet, this approach relies upon the length and spatial distribution of the precipitation input data series, which often are scarce, especially in arid and semiarid regions. In this work, we present a new approach for the estimation of extreme floods based on the continuous synthetic simulation method supported with inputs of (a) a regional study of extreme precipitation to improve the calibration of the weather generator (GWEX), and (b) non-systematic flood information (i.e., historical information and/or palaeoflood records) for the validation of the generated discharges with a fully distributed hydrological model (TETIS). The results showed that this complementary information of extremes allowed for a more accurate implementation of both the weather generator and the hydrological model. This, in turn, improved the flood quantile estimates, especially for those associated with return periods higher than 50 years but also for higher quantiles (up to approximately 500 years). Therefore, it has been proved that continuous synthetic simulation studies focused on the estimation of extreme floods should incorporate a generalized representation of regional extreme rainfall and/or non-systematic flood data, particularly in regions with scarce hydrometeorological records.

The Flood Analysis of Karadere Stream in the Mustafakemalpaşa District of Bursa Province and Determination of Its Effect on the Sünlük District Settlement

Floods shows an increase both in number and in terms of damages they cause in tropical climates as well as in Turkey which is not located in tropical region. With the increasing population density and unplanned urbanization, life and property losses become inevitable as a result of these floods. In this study, the flood analysis of the section between the beginning and the end of the S&amp;amp;uuml;nl&amp;amp;uuml;k District settlement located on the border of Karadere Stream in the Mustafakemalpaşa District of Bursa Province was assessed. The planning works of the S&amp;amp;uuml;nl&amp;amp;uuml;k Dam on the Karadere Stream, which is intended to provide drinking water and industrial water to the Mustafakemalpaşa and Karacabey Districts of Bursa Province, are continuing by the 1st Regional Directorate of State Hydraulic Works of Turkey (DSI). Flood areas were determined with the help of the HEC-RAS (Hydrologic Engineering Centers River Analysis System) software and applying the Q1000, Q10000 and QMMF (probable maximum flood) flood return period flow rates at the Karadere Stream which obtained from the dam planning studies. It was concluded that the damage caused by QMMF can reach up to 1000000 TL once flood occur.

Will Evolving Climate Conditions Increase the Risk of Floods of the Large U.S.‐Canada Transboundary Richelieu River Basin?

AbstractIn spring 2011, an unprecedented flood hit the complex eastern United States (U.S.)–Canada transboundary Lake Champlain–Richelieu River (LCRR) Basin, destructing properties and inducing negative impacts on agriculture and fish habitats. The damages, covered by the Governments of Canada and the U.S., were estimated to C$90M. This natural disaster motivated the study of mitigation measures to prevent such disasters from reoccurring. When evaluating flood risks, long‐term evolving climate change should be taken into account to adopt mitigation measures that will remain relevant in the future. To assess the impacts of climate change on flood risks of the LCRR basin, three bias‐corrected multi‐resolution ensembles of climate projections for two greenhouse gas concentration scenarios were used to force a state‐of‐the‐art, high‐resolution, distributed hydrological model. The analysis of the hydrological simulations indicates that the 20‐year return period flood (corresponding to a medium flood) should decrease between 8% and 35% for the end of the 21st Century (2070–2099) time horizon and for the high‐emission scenario representative concentration pathway (RCP) 8.5. The reduction in flood risks is explained by a decrease in snow accumulation and an increase in evapotranspiration expected with the future warming of the region. Nevertheless, due to the large climate inter‐annual variability, short‐term flood probabilities should remain similar to those experienced in the recent past.

Annual flood damage influenced by El Niño in the Kan River basin, Iran

Abstract. Although many studies have explored the effect of teleconnection patterns on floods, few investigations have focused on the assessment of expected flood damage under such large-scale atmospheric signals. This study aims to determine the effect of the most emblematic teleconnection, El Niño, on the expected damage due to floods with short return periods in the Kan River basin, Iran. To determine the flood damage costs, the median of annual precipitation changes (ΔP) during El Niño conditions was used, although ΔP cannot necessarily be transferred to extreme values. Then the flooded area was determined under the increased rainfall due to El Niño for 5-, 10-, and 50-year return periods. The results showed that El Niño has increased the annual precipitation by 12.2 %. Flood damage assessment using damage–depth curves showed that the relative increase in expected damage during El Niño conditions is much higher for short return period floods than that for long return period floods. In general, a 12.2 % increase in the annual precipitation would increase the damage by 1671 % and 176 %, respectively, for the return periods of 5 and 10 years. However, in the case of a 50-year flood, this increased percentile decreased to 52 %. These results indicate the importance of small flood events in flood management planning during El Niño.

Flood frequency analysis using generalized distributions and entropy-based model selection method

Flood frequency analysis (FFA) is used for estimating the return period of a design flood. Fundamental to FFA is the selection of a frequency distribution fitted to the data set, where an inappropriate choice of a distribution can lead to significant error and bias in the design flood estimate. The usual criteria for selecting a distribution are Akaike Information Criterion (AIC), Bayesian Information Criterion (BIC), and Root Mean Square Error (RMSE), although these criteria have limitations. This paper performed FFA using three main steps. First, five generalized distributions were considered as candidate distributions for FFA; second, the principle of maximum entropy (POME) and the method of maximum likelihood (MLE) were used for parameter estimation; and third a new model selection criterion based on the value of entropy was proposed to choose the best-fitted distribution. Monte Carlo simulation was carried out to test this entropy-based method for four sample sizes equal to 50, 200, 1000, and 10000, and simulation was repeated 1000 times for each sample size. Then, the probability that a given method identified the correct distribution was determined. The probabilities affected by the sample size, skewness, and shape of the probability density function (PDF) were assessed. Using Qing River basin, China, as a case study, the design flood values were calculated and compared. Results of simulation showed that the proposed method was better than other methods for the following cases: (a) the sample size of data set X is small; (b) the skewness coefficient CS>0; and (c) the shape of PDFs is bell-shaped.

Investigation of Attributes for Identifying Homogeneous Flood Regions for Regional Flood Frequency Analysis in Canada

The identification of homogeneous flood regions is essential for regional flood frequency analysis. Despite the type of regionalization framework considered (e.g., region of influence or hierarchical clustering), selecting flood-related attributes to reflect flood generating mechanisms is required to discriminate flood regimes among catchments. To understand how different attributes perform across Canada for identifying homogeneous regions, this study examines five distinctive attributes (i.e., geographical proximity, flood seasonality, physiographic variables, monthly precipitation pattern, and monthly temperature pattern) for their ability to identify homogeneous regions at 186 gauging sites with their annual maximum flow data. We propose a novel region revision procedure to complement the well-known region of influence and L-Moments techniques that automates the identification of homogeneous regions across continental domains. Results are presented spatially for Canada to assess patterning of homogeneous regions. Memberships of two selected regions are investigated to provide insight into membership characteristics. Sites in eastern Canada are highly likely to identify homogeneous flood regions, while the western prairie and mountainous regions are not. Overall, it is revealed that the success of identifying homogeneous regions depends on local hydrological complexities, whether the considered attribute(s) reflect primary flooding mechanism(s), and on whether catchment sites are clustered in a small geographic region. Formation of effective pooling groups affords the extension of record lengths across the Canadian domain (where gauges typically have &lt;50 years of record), facilitating more comprehensive analysis of higher return period flood needs for climate change assessment.

Mitigation Plan and Water Harvesting of Flashflood in Arid Rural Communities Using Modelling Approach: A Case Study in Afouna Village, Egypt

This paper aims to propose methods to mitigate the risks of flash flood events in arid rural communities with poor infrastructure. A flash flood management case study was conducted at Afouna Village in Egypt, which is characterized by an arid climate and faced a devasting flash flood in 2015. First, the flash flood was modelled and it was found that it corresponds to a 100 year return period flood that led to an almost 13 million m3 total runoff volume. A structural protection approach, using an artificial infiltration pond, was applied to mitigate the flooding risks through water harvesting and recharging the groundwater of the Moghra aquifer. In this study, a novel approach was proposed, which is substituting the low permeability silty sand (2.0 × 10−4 m/s) in the pond area with a high permeability one (9.6 × 10−3 m/s), which will enhance water harvesting and reduce direct evaporation. Modern techniques of hydrological modelling were utilized in order to achieve the optimal use, and harvesting, of flash flood water.

Restoration of the shifting mosaic of floodplain forests under a flow regime altered by a dam

A braided gravel-bed river provides essential habitats for various plants and animals. However, human regulation of rivers, such as dams, channelization, and other engineering works, alter flow and sediment regimes, which generally cause the degradation of river and riparian ecosystems. One of the prominent changes prevailing in Japanese rivers is forest expansion over gravel bars, and many native plants and animals that depend on gravel-bar habitat are now endangered. The Satsunai River is typical of rivers experiencing forest expansion, so the Japanese government launched a restoration project in 2012 to partially restore its riparian ecosystems. This is a large-scale experiment developed jointly by an interdisciplinary science team and river managers, who conduct monitoring and evaluation under an adaptive management scheme. The main measure to restore gravel bed habitat was an artificial flood regime, releasing a maximum water volume of 120 m3/s, which was a 2-year return period flood before dam construction. A unique feature of the project is that we considered the role of high-magnitude floods with recurrence intervals greater than 20 years after dam construction. We hypothesize that the artificial floods can be timed seasonally to create sites for regeneration and nesting of riparian species, and the high-magnitude floods contribute to maintaining a shifting mosaic structure of floodplain forest and unvegetated gravel-bar patches. We also used critical non-dimensional shear stress analysis to define “flood-disturbance areas” that can be disturbed under the artificial flow regime created by a dam. Artificial floods have been initiated once a year since 2012 at the end of June, synchronized with the seed dispersal period of Salix arbutifolia, which is endangered and a high conservation priority in the project. Thus far, the idea of setting floodplain-disturbance areas and the strategy of using both artificial and high-magnitude floods to restore a shifting mosaic of floodplain habitat patches is appropriate, as we found successful regeneration of S. arbutifolia and an exponential decay curve of the age distribution of floodplain forest patches. However, the sediment regime regulated by the dam was not addressed in this research, so future monitoring should track changes in river morphology associated with reduced sediment supply caused by the dam.

Ultra-high resolution regional climate projections for assessing changes in hydrological extremes and underlying uncertainties

The frequency and intensity of extreme hydrological events (droughts and floods) have been increasing over the past few decades, which has been posing a threat to water security and agriculture production. Thus, projecting the future evolution of hydrological extremes plays a crucial role in sustainable water management and agriculture development in a changing climate. In this study, we develop the high-resolution projections of multidimensional drought characteristics and flood risks using the convection-permitting Weather Research and Forecasting (WRF) model with the horizontal grid spacing of 4 km for the Blanco and Mission River basins over South Texas. Uncertainties in model parameters are addressed explicitly, thereby leading to probabilistic assessments of hydrological extremes. Our findings reveal that the probabilistic multivariate assessments of drought and flood risks can reduce the underestimation and the biased conclusions generated from the univariate assessment. Furthermore, our findings disclose that future droughts are expected to become more severe over South Texas even though the frequency of the occurrence of droughts is projected to decrease, especially for the long-term drought episodes. In addition, South Texas region is expected to experience more floods with an increasing river discharge. Moreover, the Blanco and Mission river basins will suffer from higher flood risks as flood return periods are expected to become longer under climate change.

Pemetaan Tingkat Rawan Bencana Banjir di Daerah Aliran Sungai Maros Provinsi Sulawesi Selatan

Indonesia is an archipelago with a tropical climate with very high rainfall. In the rainy season floods occur which cause losses, namely loss of life and property. This condition is a routine disaster that always threatens people's lives. Therefore, research needs to be done to identify flood-prone areas and flood-causing factors in the Maros River Basin. The method used to determine flood-prone areas is used by a combination of remote sensing, terrestrial, secondary data and interviews using the criteria of Sutikno et al (1995) with development. The variables used topography (flat and sloping), soil texture, drainage, inundation time and flood return period. The analysis shows that in the Maros watershed there are 3 classes that are prone to flooding namely not prone, prone and very prone. Most are vulnerable because more than 50 percent of the area is at a vulnerable and very vulnerable level. The class is very prone to spread from downstream to the middle of the watershed, covering the southern sub-districts of Maros Baru, Marusu, Turikale, southern Bantimurung, western Simbang, northern Mandai and northern Tanralili. The contributing factors are high rainfall, flat and sloping topography, fine soil texture in the downstream river, poor drainage due to poor waste management, land use dominated by ponds and paddy fields and high flood return periods.