Nonstationary extreme value analysis (NEVA) can improve the statistical representation of observed flood peak distributions compared to stationary (ST) analysis, but management of flood risk relies ...on predictions of out‐of‐sample distributions for which NEVA has not been comprehensively evaluated. In this study, we apply split‐sample testing to 1250 annual maximum discharge records in the United States and compare the predictive capabilities of NEVA relative to ST extreme value analysis using a log‐Pearson Type III (LPIII) distribution. The parameters of the LPIII distribution in the ST and nonstationary (NS) models are estimated from the first half of each record using Bayesian inference. The second half of each record is reserved to evaluate the predictions under the ST and NS models. The NS model is applied for prediction by (1) extrapolating the trend of the NS model parameters throughout the evaluation period and (2) using the NS model parameter values at the end of the fitting period to predict with an updated ST model (uST). Our analysis shows that the ST predictions are preferred, overall. NS model parameter extrapolation is rarely preferred. However, if fitting period discharges are influenced by physical changes in the watershed, for example from anthropogenic activity, the uST model is strongly preferred relative to ST and NS predictions. The uST model is therefore recommended for evaluation of current flood risk in watersheds that have undergone physical changes. Supporting information includes a MATLAB® program that estimates the (ST/NS/uST) LPIII parameters from annual peak discharge data through Bayesian inference.
Key Points
Stationary predictions of flood peak distributions are preferred, overall
Extrapolation of the nonstationary model parameter trend rarely improves the stationary prediction, even if an observed trend continues
Using the most recent nonstationary parameters to predict with an updated stationary model is preferred for physically changing watersheds
Since flood frequency increases with the impact of climate change, the damage that is emphasized on flood-risk maps is based on actual flooded area data; therefore, flood-susceptibility maps for the ...Seoul metropolitan area, for which random-forest and boosted-tree models are used in a geographic information system (GIS) environment, are created for this study. For the flood-susceptibility mapping, flooded-area, topography, geology, soil and land-use datasets were collected and entered into spatial datasets. From the spatial datasets, 12 factors were calculated and extracted as the input data for the models. The flooded area of 2010 was used to train the model, and the flooded area of 2011 was used for the validation. The importance of the factors of the flood-susceptibility maps was calculated and lastly, the maps were validated. As a result, the distance from the river, geology and digital elevation model showed a high importance among the factors. The random-forest model showed validation accuracies of 78.78% and 79.18% for the regression and classification algorithms, respectively, and boosted-tree model showed validation accuracies of 77.55% and 77.26% for the regression and classification algorithms, respectively. The flood-susceptibility maps provide meaningful information for decision-makers regarding the identification of priority areas for flood-mitigation management.
Identifying flood risk-prone areas in the regions of extreme aridity conditions is essential for mitigating flood risk and rainwater harvesting. Accordingly, the present work is addressed to the ...assessment of the flood risk depending on spatial analytic hierarchy process of the integration between both Remote Sensing Techniques (RST) and Geographic Information Systems (GIS). This integration results in enhancing the analysis with the savings of time and efforts. There are several remote sensing-based data used in conducting this research, including a digital elevation model with an accuracy of 30 m, spatial soil and geologic maps, historical daily rainfall records, and data on rainwater drainage systems. Five return periods (REPs) (2, 5, 10, 25, 50, 100, and 200 years) corresponding to flood hazards and vulnerability developments maps were applied via the weighted overlay technique. Although the results indicate lower rates of annual rainfall (53–71 mm from the southeast to the northwest), the city has been exposed to destructive flash floods. The flood risk categories for a 100-year REP were very high, high, medium, low, and very low with 17%, 41%, 33%, 8%, and 1% of total area, respectively. These classes correspond to residential zones and principal roads, which lead to catastrophic flash floods. These floods have caused socioeconomic losses, soil erosion, infrastructure damage, land degradation, vegetation loss, and submergence of cities, as well life loss. The results prove the GIS and RST effectiveness in mitigating flood risks and in helping decision makers in flood risk mitigation and rainwater harvesting.
Urbanization increases regional impervious surface area, which generally reduces hydrologic response time and therefore increases flood risk. The objective of this work is to investigate the ...sensitivities of urban flooding to urban land growth through simulation of flood flows under different urbanization conditions and during different flooding stages. A sub-watershed in Toronto, Canada, with urban land conversion was selected as a test site for this study. In order to investigate the effects of urbanization on changes in urban flood risk, land use maps from six different years (1966, 1971, 1976, 1981, 1986, and 2000) and of six simulated land use scenarios (0%, 20%, 40%, 60, 80%, and 100% impervious surface area percentages) were input into coupled hydrologic and hydraulic models. The results show that urbanization creates higher surface runoff and river discharge rates and shortened times to achieve the peak runoff and discharge. Areas influenced by flash flood and floodplain increases due to urbanization are related not only to overall impervious surface area percentage but also to the spatial distribution of impervious surface coverage. With similar average impervious surface area percentage, land use with spatial variation may aggravate flash flood conditions more intensely compared to spatially uniform land use distribution.
Using a combination of stream gauge, historical, and paleoflood records to extend extreme flood records has proven to be useful in improving flood frequency analysis (FFA). The approach has typically ...been applied in localities with long historical records and/or suitable river settings for paleoflood reconstruction from slack‐water deposits (SWDs). However, many regions around the world have neither extensive historical information nor bedrock gorges suitable for SWDs preservation and paleoflood reconstruction. This study from subtropical Australia demonstrates that confined, semialluvial channels such as macrochannels provide relatively stable boundaries over the 1000–2000 year time period and the preserved SWDs enabled paleoflood reconstruction and their incorporation into FFA. FFA for three sites in subtropical Australia with the integration of historical and paleoflood data using Bayesian Inference methods showed a significant reduction in uncertainty associated with the estimated discharge of a flood quantile. Uncertainty associated with estimated discharge for the 1% Annual Exceedance Probability (AEP) flood is reduced by more than 50%. In addition, sensitivity analysis of possible within‐channel boundary changes shows that FFA is not significantly affected by any associated changes in channel capacity. Therefore, a greater range of channel types may be used for reliable paleoflood reconstruction by evaluating the stability of inset alluvial units, thereby increasing the quantity of temporal data available for FFA. The reduction in uncertainty, particularly in the prediction of the ≤1% AEP design flood, will improve flood risk planning and management in regions with limited temporal flood data.
Key Points
Quantifying improvements to flood frequency analysis with addition of paleoflood and historical information
Sensitive analysis to evaluate effects of changing cross sections on paleoflood magnitude reconstruction
Use of slack‐water deposits in semialluvial setting for paleoflood reconstruction
Clumsy Floodplains Hartmann, Thomas
2011, 20160523, 2016-05-23, 2016-05-31, 2011-02-01
eBook
Extreme floods cause enormous damage in floodplains, which levees cannot prevent. Therefore, it is vital for spatial planning to provide space for water retention in these areas. Land use planners, ...water management agencies, landowners, and policymakers all agree on this challenge, but attempts to make the space for rivers to provide retention are generally not very successful. Adopting an innovative interdisciplinary approach, this book examines how society can manage the use of the floodplains along rivers in the face of extreme floods, focusing in particular on the relation between social arrangements and the elemental forces of floods. The book firstly analyses why contemporary floodplain management is so often clumsy and ineffective by looking at various real-life situations in Germany, using Cultural Theory to provide a much-needed, but previously neglected social perspective. These analyses show a pattern of activity resulting from different rationalities which dominate the floodplains in different phases. During extreme floods, it is rational to manage floodplains as dangerous areas; sandbags and disaster management dominate the scene. After some time, the rationality of control takes over the floodplain management; policymakers discuss flood risk and water managers build levees. When public attention diminishes, floodplains become inconspicuous until more and more stakeholders regard floodplains as profitable land. The current system of planning, law, and property rights even encourages stakeholders to act out their plural rationalities. A permanent dynamic imbalance of different rationalities leads to a robust social construction of the floodplains which results in viable but clumsy floodplains. In the course of time, however, the patterns of activity in the floodplains lead to an increase in intensity and frequency of extreme floods, and to more vulnerable potential damages in the floodplains. Risk increases. Coping with this situation needs another ki
The height above nearest drainage (HAND) model is frequently used to calculate properties of the soil and predict flood inundation extents. HAND is extremely useful due to its lack of reliance on ...prior data, as only the digital elevation model (DEM) is needed. It is close to optimal, running in linear or linearithmic time in the number of cells depending on the values of the heights. It can predict watersheds and flood extent to a high degree of accuracy. We applied a client-side HAND model on the web to determine extent of flood inundation in several flood prone areas in Iowa, including the city of Cedar Rapids and Ames. We demonstrated that the HAND model was able to achieve inundation maps comparable to advanced hydrodynamic models (i.e., Federal Emergency Management Agency approved flood insurance rate maps) in Iowa, and would be helpful in the absence of detailed hydrological data. The HAND model is applicable in situations where a combination of accuracy and short runtime are needed, for example, in interactive flood mapping and supporting mitigation decisions, where users can add features to the landscape and see the predicted inundation.
Floods in southwestern Saudi Arabia, especially in the Asir region, are among the major natural disasters caused by natural and human factors. In this region, flash floods that occur in the Wadi Hail ...Basin greatly affect human life and activities, damaging property, the built environment, infrastructure, landscapes, and facilities. A previous study carried out for the same basin has effectively revealed zones of flood risk using such an approach. However, the utilization of the HEC–HMS (Hydrologic Engineering Center–Hydrologic Modeling System) model and IMERG data for delineating areas prone to flash floods remain unexplored. In response to this advantage, this work primarily focused on flood generation assessment in the Wadi Hail Basin, one of the major basins in the region that is frequently prone to severe flash flood damage, from a single extreme rainfall event. We employed a fully physical-based, distributed hydrological model run with HEC–HMS software version 4.11 and Integrated Multi-satellite Retrievals of Global Precipitation Measurement (IMERG V.06) data, as well as other geo-environmental variables, to simulate the water flow within the Wadi Basin, and predict flash flood hazard. Discharge from the wadi and its sub-basins was predicted using 1 mm rainfall over an 8-h occurrence time. Significant peak discharge (3.6 m3/s) was found in eastern and southern upstream sub-basins and crossing points, rather than those downstream, due to their high-density drainage network (0.12) and CNs (88.4). Generally, four flood hazard levels were identified in the study basin: ‘low risk’, ‘moderate risk’, ‘high risk’, and ‘very high risk’. It was found that 43.8% of the total area of the Wadi Hail Basin is highly prone to flooding. Furthermore, medium- and low-hazard areas make up 4.5–11.2% of the total area, respectively. We found that the peak discharge value of sub-basin 11 (1.8 m3/s) covers 13.2% of the total Wadi Hail area; so, it poses more flood risk than other Wadi Hail sub-basins. The obtained results demonstrated the usefulness of the methods used to develop useful hydrological information in a region lacking ungagged data. This study will play a useful role in identifying the impact of extreme rainfall events on locations that may be susceptible to flash flooding, which will help authorities to develop flood management strategies, particularly in response to extreme events. The study results have potential and valuable policy implications for planners and decision-makers regarding infrastructural development and ensuring environmental stability. The study recommends further research to understand how flash flood hazards correlate with changes at different land use/cover (LULC) classes. This could refine flash flood hazards results and maximize its effectiveness.
Floods in England and Wales have the potential to cause billions of pounds of damage. You might think such extreme events are rare, but they are likely to occur more frequently than expected. By Ross ...Towe, Jonathan Tawn and Rob Lamb
Floods in England and Wales have the potential to cause billions of pounds of damage. You might think such extreme events are rare, but they are likely to occur more frequently than expected. By Ross Towe, Jonathan Tawn and Rob Lamb.
Flooding is a major hazard to lives and infrastructure, but trends in flood hazard are poorly understood. The capacity of river channels to convey flood flows is typically assumed to be stationary, ...so changes in flood frequency are thought to be driven primarily by trends in streamflow. We have developed new methods for separately quantifying how trends in both streamflow and channel capacity have affected flood frequency at gauging sites across the United States Flood frequency was generally nonstationary, with increasing flood hazard at a statistically significant majority of sites. Changes in flood hazard driven by channel capacity were smaller, but more numerous, than those driven by streamflow. Our results demonstrate that accurately quantifying changes in flood hazard requires accounting separately for trends in both streamflow and channel capacity. They also show that channel capacity trends may have unforeseen consequences for flood management and for estimating flood insurance costs.
Key Points
Flood frequency is nonstationary and increasing at the majority of our sites
Geomorphology is a weaker but more common flood hazard driver than hydrology
Trends in channel capacity measurably alter flood hazards
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