Managing Flood Hazard in a Complex Cross-Border Region Using Sentinel-1 SAR and Sentinel-2 Optical Data: A Case Study from Prut River Basin (NE Romania)

In this study, an alternative solution for flood risk management in complex cross-border regions is presented. In these cases, due to different flood risk management legislative approaches, there is a lack of joint cooperation between the involved countries. As a main consequence, LiDAR-derived digital elevation models and accurate flood hazard maps obtained by means of hydrological and hydraulic modeling are missing or are incomplete. This is also the case for the Prut River, which acts as a natural boundary between European Union (EU) member Romania and non-EU countries Ukraine and Republic of Moldova. Here, flood hazard maps were developed under the European Floods Directive (2007/60/EC) only for the Romanian territory and only for the 1% exceeding probability (respectively floods that can occur once every 100 years). For this reason, in order to improve the flood hazard management in the area and consider all cross-border territories, a fully remote sensing approach was considered. Using open-source SAR Sentinel-1 and Sentinel-2 data characterized by an improved temporal resolution, we managed to capture the maximum spatial extent of a flood event that took place in the aforementioned river sector (middle Prut River course) during the 24 and 27 June 2020. Moreover, by means of flood frequency analysis, the development of a transboundary flood hazard map with an assigned probability, specific to the maximum flow rate recorded during the event, was realized.

Generating Flood Hazard Maps Based on an Innovative Spatial Interpolation Methodology for Precipitation

In this study, a new approach for rainfall spatial interpolation in the Luxembourgian case study is introduced. The method used here is based on a Fuzzy C-Means (FCM) clustering method. In a typical FCM procedure, there are a lot of available data and each data point belongs to a cluster, with a membership degree [0 1]. On the other hand, in our methodology, the center of clusters is determined first and then random data are generated around cluster centers. Therefore, this approach is called inverse FCM (i-FCM). In order to calibrate and validate the new spatial interpolation method, seven rain gauges in Luxembourg, Germany and France (three for calibration and four for validation) with more than 10 years of measured data were used and consequently, the rainfall for ungauged locations was estimated. The results show that the i-FCM method can be applied with acceptable accuracy in validation rain gauges with values for R2 and RMSE of (0.94–0.98) and (9–14 mm), respectively, on a monthly time scale and (0.86–0.89) and (1.67–2 mm) on a daily time scale. In the following, the maximum daily rainfall return periods (10, 25, 50 and 100 years) were calculated using a two-parameter Weibull distribution. Finally, the LISFLOOD FP flood model was used to generate flood hazard maps in Dudelange, Luxembourg with the aim to demonstrate a practical application of the estimated local rainfall return periods in an urban area.

Global riverine flood risk – how do hydrogeomorphic floodplain maps compare to flood hazard maps?

Riverine flood risk studies often require the identification of areas prone to potential flooding. This modelling process can be based on either (hydrologically derived) flood hazard maps or (topography-based) hydrogeomorphic floodplain maps. In this paper, we derive and compare riverine flood exposure from three global products: a hydrogeomorphic floodplain map (GFPLAIN250m, hereinafter GFPLAIN) and two flood hazard maps (Flood Hazard Map of the World by the European Commission's Joint Research Centre, hereinafter JRC, and the flood hazard maps produced for the Global Assessment Report on Disaster Risk Reduction 2015, hereinafter GAR). We find an average spatial agreement between these maps of around 30 % at the river basin level on a global scale. This agreement is highly variable across model combinations and geographic conditions, influenced by climatic humidity, river volume, topography, and coastal proximity. Contrary to expectations, the agreement between the two flood hazard maps is lower compared to their agreement with the hydrogeomorphic floodplain map. We also map riverine flood exposure for 26 countries across the global south by intersecting these maps with three human population maps (Global Human Settlement population grid, hereinafter GHS; High Resolution Settlement Layer, hereinafter HRSL; and WorldPop). The findings of this study indicate that hydrogeomorphic floodplain maps can be a valuable way of producing high-resolution maps of flood-prone zones to support riverine flood risk studies, but caution should be taken in regions that are dry, steep, very flat, or near the coast.

Probabilistic Flood Hazard Maps from Monte Carlo Derived Peak Flow Values—An Application to Flood Risk Management in Zamora City (Spain)

All flood hazard and risk assessment suffer from a certain degree of uncertainty due to multiple factors, such as flood frequency analysis, hydrodynamic model calibration, or flood damage (magnitude–damage functions) models. The uncertainty linked to the flood frequency analysis is one of the most important factors (previous and present estimation point to 40%). Flood frequency analysis uncertainty has been approached from different points of view, such as the application of complex statistical models, the regionalization processes of peak flows, or the inclusion of non-systematic data. Here, we present an achievable approach to defining the uncertainty linked to flood frequency analysis by using the Monte Carlo method. Using the city of Zamora as the study site, the uncertainty is delimited by confidence intervals of a peak flow quantile of a 500-year return period. Probabilistic maps are derived from hydrodynamic results, and further analysis include flood hazard maps for human loss of stability and vehicle damage. Although the effect of this uncertainty is conditioned by the shape of the terrain, the results obtained may allow managers to achieve more consistent land-use planning. All those Zamora city results point out the probable underestimation of flood hazard (the higher hazard areas increase around 20%) and risk when the uncertainty analysis is not considered, thus limiting the efficiency of flood risk management tasks.

Design Floods Considering the Epistemic Uncertainty

The Design Flood (DF) concept is an essential tool in designing hydraulic works, defining reservoir operation programs, and identifying reliable flood hazard maps. The purpose of this paper is to present a methodology for deriving a Design Flood hydrograph considering the epistemic uncertainty. Several appropriately identified statistical distributions allow for the acceptable approximation of the frequent values of maximum discharges or flood volumes, and display a significant spread for their medium/low Probabilities of Exceedance (PE). The referred scattering, as a consequence of epistemic uncertainty, defines an area of uncertainty for both recorded data and extrapolated values. In considering the upper and lower values of the uncertainty intervals as limits for maximum discharges and flood volumes, and by further combining them compatibly, a set of DFs as completely defined hydrographs with different shapes result for each PE. The herein proposed procedure defines both uni-modal and multi-modal DFs. Subsequently, such DFs help water managers in examining and establishing tailored approaches for a variety of input hydrographs, which might be typically generated in river basins.

Improving Urban Flood Mapping by Merging Synthetic Aperture Radar-Derived Flood Footprints with Flood Hazard Maps

Remotely sensed flood extents obtained in near real-time can be used for emergency flood incident management and as observations for assimilation into flood forecasting models. High-resolution synthetic aperture radar (SAR) sensors have the potential to detect flood extents in urban areas through clouds during both day- and night-time. This paper considers a method for detecting flooding in urban areas by merging near real-time SAR flood extents with model-derived flood hazard maps. This allows a two-way symbiosis, whereby currently available SAR urban flood extent improves future model flood predictions, while flood hazard maps obtained after the SAR overpasses improve the SAR estimate of urban flood extents. The method estimates urban flooding using SAR backscatter only in rural areas adjacent to urban ones. It was compared to an existing method using SAR returns in both rural and urban areas. The method using SAR solely in rural areas gave an average flood detection accuracy of 94% and a false positive rate of 9% in the urban areas and was more accurate than the existing method.

THE USE OF GEOGRAPHIC INFORMATION SYSTEM FOR FLOOD PREDICTIONS

The article examines the issue of using geographic information systems (GIS) and WEBGIS technologies to predict areas likely to be flooded. Probabilistic flood hazard maps (0.5%, 0.1% and 1% flood risks) were used, obtained from a model installation in an area subject to flood risk, in this case, the municipality of Ungheni in the Republic Moldova, which has been flooded in the past. The application of GIS technologies is necessary to prevent floods affecting households, infrastructure and to minimize its effects. For this purpose, were analyzed the previous floods that occurred in the region. Also were applied and overlaid thematic digital maps such as Land Use, river network, DTM, Delineation Methodology of water bodies which represents the transposition of the EU Water Framework Directive 2000/60/EC and at the end were uploaded on an ESRI Web GIS platform http://www.dbga.md/siga.html. The Coordinate system used here was WGS-84.

Rye Island, 2010: Impact of the flooding on the groundwater level

During the flood situations in May and June 2010, the culmination of the Váh River and the Danube River was accompanied by the groundwater level rising in the Rye Island, in some boreholes even to their maximum measured levels. The increased groundwater level caused major problems, e.g. flooded cellars and underground spaces, contaminated drinking water in wells, flooded railways and farmlands. As a part of the research concentrating on the groundwater flooding phenomena in the Rye Island, the flood situation from the year 2010 was reconstructed, establishing the basis for a construction of the flood hazard maps and flood risk management plans. The problem was solved with a MODFLOW numerical model using the Groundwater Modeling System.

Global riverine flood risk – how do hydrogeomorphic floodplain maps compare to flood hazard maps?

Riverine flood risk studies require the identification of areas prone to potential flooding. This process can be based on either (hydrologically-derived) flood hazard maps or (topography-based) hydrogeomorphic floodplain maps. In this paper, we derive and compare riverine flood exposure from three global products: a hydrogeomorphic floodplain map (GFPLAIN) and two flood hazard maps (JRC and GAR). We find an average spatial agreement between these maps of around 30% at river basin level on a global scale. This agreement is highly variable across model combinations and geographic conditions, influenced by climatic humidity, river volume, topography, and coastal proximity. Contrary to expectations, the agreement between the two flood hazard maps is lower compared to their agreement with the hydrogeomorphic floodplain map. We also map riverine flood exposure for 26 countries across the Global South, by intersecting these maps with three human population maps (GHS, HRSL and WorldPop). The findings of this study indicate that hydrogeomorphic floodplain maps can be a valuable way of producing high-resolution maps of flood-prone zones to support riverine flood risk studies, but caution should be taken in regions that are dry, steep, very flat or near the coast.

How Flood Hazard Maps Improve the Understanding of Ecologically Active Floodplains

Floodplains are threatened ecosystems and are not only ecologically meaningful but also important for humans by creating multiple benefits. Many underlying functions, like nutrient retention, carbon sequestration or water regulation, strongly depend on regular inundation. So far, these are approached on the basis of what are called ‘active floodplains’. Active floodplains, defined as statistically inundated once every 100 years, represent less than 10% of a floodplain’s original size. Still, should this remaining area be considered as one homogenous surface in terms of floodplain function, or are there any alternative approaches to quantify ecologically active floodplains? With the European Flood Hazard Maps, the extent of not only medium floods (T-medium) but also frequent floods (T-frequent) needs to be modelled by all member states of the European Union. For large German rivers, both scenarios were compared to quantify the extent, as well as selected indicators for naturalness derived from inundation. It is assumed that the more naturalness there is, the more inundation and the better the functioning. Real inundation was quantified using measured discharges from relevant gauges over the past 20 years. As a result, land uses indicating strong human impacts changed significantly from T-frequent to T-medium floodplains. Furthermore, the extent, water depth and water volume stored in the T-frequent and T-medium floodplains is significantly different. Even T-frequent floodplains experienced inundation for only half of the considered gauges during the past 20 years. This study gives evidence for considering regulation functions on the basis of ecologically active floodplains, meaning in floodplains with more frequent inundation that T-medium floodplains delineate.