Flood Extent Mapping Research Articles

THE USE OF LIDAR AND VOLUNTEERED GEOGRAPHIC INFORMATION TO MAP FLOOD EXTENTS AND INUNDATION

Abstract. Floods are one of the most destructive natural disasters that threaten communities and properties. In recent decades, flooding has claimed more lives, destroyed more houses and ruined more agricultural land than any other natural hazard. The accurate prediction of the areas of inundation from flooding is critical to saving lives and property, but relies heavily on accurate digital elevation and hydrologic models. The 2011 Brisbane floods provided a unique opportunity to capture high resolution digital aerial imagery as the floods neared their peak, allowing the capture of areas of inundation over the various city suburbs. This high quality imagery, together with accurate LiDAR data over the area and publically available volunteered geographic imagery through repositories such as Flickr, enabled the reconstruction of flood extents and the assessment of both area and depth of inundation for the assessment of damage. In this study, approximately 20 images of flood damaged properties were utilised to identify the peak of the flood. Accurate position and height values were determined through the use of RTK GPS and conventional survey methods. This information was then utilised in conjunction with river gauge information to generate a digital flood surface. The LiDAR generated DEM was then intersected with the flood surface to reconstruct the area of inundation. The model determined areas of inundation were then compared to the mapped flood extent from the high resolution digital imagery to assess the accuracy of the process. The paper concludes that accurate flood extent prediction or mapping is possible through this method, although its accuracy is dependent on the number and location of sampled points. The utilisation of LiDAR generated DEMs and DSMs can also provide an excellent mechanism to estimate depths of inundation and hence flood damage

Change detection approaches for flood extent mapping: How to select the most adequate reference image from online archives?

Synthetic Aperture Radar images are routinely used for delineating flooded areas. Processing algorithms are often based on change detection techniques that enable a comparison of backscattering signals between the flood image and a reference image. However, as of today, there is little guidance on how to rapidly and reliably extract the most adequate reference image from an online archive. Our study proposes a method that allows the automatic and objective identification of the best reference image with respect to a given flood image. The proposed method consists of two processing steps. First, a subset of archived candidate images acquired on the same track, with the same polarization and in the same period of year as the flood image is created. Next, site-specific time series of regional backscattering values are established and the effects of flooding on the backscattering behaviour are statistically evaluated. We propose two complementary anomaly indexes and their combination in a single index as a means to identify the most adequate reference image for flooding-related change detection applications. The reliability of the proposed method is demonstrated in three representative case studies targeting the flood prone areas of the Severn River (United Kingdom), the Red River (United States) and the Meghna River (Bangladesh).

Simulation of Flood Extent Mapping by InfoWorks RS-Case Study for Tropical Catchment

Simulation of Flood Extent Mapping by InfoWorks RS-Case Study for Tropical Catchment

Timely Low Resolution SAR Imagery To Support Floodplain Modelling: a Case Study Review

It is widely recognised that remote sensing can support flood monitoring, modelling and management. In particular, satellites carrying Synthetic Aperture Radar (SAR) sensors are valuable as radar wavelengths can penetrate cloud cover and are insensitive to daylight. However, given the strong inverse relationship between spatial resolution and revisit time, monitoring floods from space in near real time is currently only possible through low resolution (about 100 m pixel size) SAR imagery. For instance, ENVISAT-ASAR (Advanced Synthetic Aperture Radar) in WSM (wide swath mode) revisit times are of the order of 3 days and the data can be obtained within 24 h at no (or low) cost. Hence, this type of space-borne data can be used for monitoring major floods on medium-to-large rivers. This paper aims to discuss the potential for, and uncertainties of, coarse resolution SAR imagery to monitor floods and support hydraulic modelling. The paper first describes the potential of globally and freely available space-borne data to support flood inundation modelling in near real time. Then, the uncertainty of SAR-derived flood extent maps is discussed and the need to move from deterministic binary maps (wet/dry) of flood extent to uncertain flood inundation maps is highlighted.

Urban pluvial flooding in Jakarta: applying state-of-the-art technology in a data scarce environment

Available data relating to major pluvial flooding events in Jakarta, Indonesia were used to investigate the suitability of two different levels of sophistication in urban modelling tools for modelling these events. InfoWorks CS v9.0 was employed to build 1D and 1D/2D models of a 541 ha area of inner city Ciliwung River catchment which has a history of being particularly badly affected by flooding during heavy rainfall events. The study demonstrated that a 1D model was sufficient to simulate the flood extent of a major event using the limited data available. While the 1D/2D model also performed well, more data and time would have been required to match the 1D model's simulation of flood extent. Much more detailed data would have been required to produce reliable results in the 1D/2D model and to enable any kind of verification or calibration of the two models beyond visual comparison with crude flood extent maps.

Selecting the appropriate hydraulic model structure using low-resolution satellite imagery

This study aims at investigating the value added by an explicit representation of floodplain processes in hydraulic models, by comparing the results of a pure 1D model to the ones of an integrated 1D–2D model. The analysis is performed on a 96 km reach of the River Po (Italy). For this test site, two different model structures (1D and 1D–2D) are implemented and compared. The models are first calibrated using high water marks of a high magnitude event and then validated by means of a coarse resolution space-borne flood extent map of a low-magnitude event. The explicit inclusion of 2D features strongly improves the performance of the model, both in terms of accuracy and robustness. The possible causes of this behaviour are investigated and some statements are drawn based on the analysis of the features of the two flood events. Some general conclusions on the effect of the choice between 1D and 2D models arise from the analysis of the calibration–validation procedure. In this context a new measure of fit is proposed, to be used if binary (wet/dry) observations are available and is proven to be able to better distinguish among different sets of model parameters. Lastly, the study also shows the ability of timely low resolution satellite imagery to assist the selection of the most appropriate hydraulic model structure.

An approach to the implementation of European Directive 2007/60/EC on flood risk management in the Czech Republic

Abstract. Directive 2007/60/EC of the European Parliament and of the Council of 23 October 2007 on the assessment and management of flood risks (the Flood Risk Directive) signifies that flood risk analysis methods are gaining ground in EC Member States and, therefore, also in the Czech Republic (CR). Procedures of flood risk analysis have been developed in the Czech Republic since the catastrophic floods of 1997 in line with European and worldwide trends and have been tested and applied in hundreds of case studies to date. Currently, the Flood Risk Directive Guideline based on past experience with flood risk analysis applications is being processed. The aim of the paper is to present flood risk analysis procedures and specially developed techniques for the assembly of flood hazard, danger and flood risk maps. Methods related to flood risk management plans are briefly mentioned as well. The following particular problems are discussed in more detail: an application and extension of the "danger matrix" approach, the definition of residual danger, the formulation of efficiency criteria and preliminary multi-criteria flood risk assessment. These issues were tested in practical applications at pilot locations in the Czech Republic. Present experience provides evidence that the flood risk analysis methods used in the Czech Republic are in harmony with the requirements of the Flood Risk Directive. The proposed and applied methods are based primarily on existing available data such as flood extent maps, cadastral maps, the Register of Census Districts and Structures and others.

Assimilation of spatially distributed water levels into a shallow-water flood model. Part II: Use of a remote sensing image of Mosel River

With rapid flood extent mapping capabilities, Synthetic Aperture Radar (SAR) images of river inundation prove to be very relevant to operational flood management. In this context, a recently developed method provides distributed water levels from SAR images. Furthermore, in view of improving numerical flood prediction, a variational data assimilation method (4D-var) using such distributed water level has been developed in Part I of this study. This method combines an optimal sense remote sensing data (distributed water levels extracted from spatial images) and a 2D shallow water model. In the present article (Part II of the study), we also derive water levels with a ±40 cm average vertical uncertainty from a RADARSAT-1 image of a Mosel River flood event (1997, France). Assimilated in a 2D shallow water hydraulic model using the 4D-var developed method, these SAR derived spatially distributed water levels prove to be capable of enhancing model calibration. Indeed, the assimilation process can identify optimal Manning friction coefficients, at least in the river channel. Moreover, used as a guide for sensitivity analysis, remote sensing water levels allow also identifying some areas in the floodplain and the channel where Manning friction coefficients are homogeneous. This allows basing the spatial segmentation of roughness coefficient on floodplain hydraulic functioning.

Design Flow and Stage Computations in the Teesta River, Bangladesh, Using Frequency Analysis and MIKE 11 Modeling

A case study was conducted in the Teesta subcatchment in Bangladesh for determining design flood flows and corresponding flood stages for different return periods using frequency analysis and MIKE 11 model. Different distribution functions of frequency analysis were tested for their goodness of fit. The observed discharge data at Kaunia on the river Teesta were used for estimation of design flood. The Pearson type-III distribution was found best fitted by the Kolmogorov-Smirnov, D-index, and L-moment diagram ratio tests, and accordingly 25-, 50-, and 100-year return period design floods were computed. The river network of Teesta River was extracted from SRTM 90-m digital elevation model. The river network of Teesta subcatchment was then simulated by MIKE 11 rainfall-runoff Nedbor-Afstromnings-Model (NAM) and HD model. The resultant time series of river stage was then compared with corresponding observed values. From the model, a stage-discharge relationship (Q-h) curve and respective equation were developed for Kaunia station on the river Teesta. The developed equation determines the corresponding flood stage of estimated flood flow of 25-, 50-, and 100-year return periods. The resulting flows and stages will be useful to design hydraulic structures, prepare flood extent maps, assess vulnerability of flood damage for different return periods, and provide flood forecasting for early warnings of floods. The approach presented would be applicable to similar river basin systems where data are limited and scarce.

Flood-plain mapping: a critical discussion of deterministic and probabilistic approaches

Different methodologies for flood-plain mapping are analysed and discussed by comparing deterministic and probabilistic approaches using hydrodynamic numerical solutions. In order to facilitate the critical discussion, state-of-art techniques in the field of flood inundation modelling are applied to a specific test site (River Dee, UK). Specifically, different flood-plain maps are derived for this test site. A first map is built by applying an advanced deterministic approach: use of a fully two-dimensional finite element model (TELEMAC-2D), calibrated against a historical flood extent, to derive a 1-in-100 year flood inundation map. A second map is derived by using a probabilistic approach: use of a simple raster-based inundation model (LISFLOOD-FP) to derive an uncertain flood extent map predicting the 1-in-100 year event conditioned on the extent of the 2006 flood. The flood-plain maps are then compared and the advantages and disadvantages of the two different approaches are critically discussed. Citation Di Baldassarre, G., Schumann, G., Bates, P. D., Freer, J. E. & Beven, K. J. (2010) Flood-plain mapping: a critical discussion of deterministic and probabilistic approaches. Hydrol. Sci. J. 55(3), 364–376.

Flood risk mapping in Europe, experiences and best practices

AbstractWithin the context of the European Flood Risk Management Directive, adopted in 2007, the European countries are required to prepare flood hazard and flood risk maps before 2014. The Exchange Circle on Flood Mapping (EXCIMAP) has made an inventory of flood mapping practices in Europe. This inventory has resulted in a ‘Handbook on Good Practices for flood mapping in Europe’ and an ‘Atlas of Flood maps containing examples from 19 European countries, Japan and USA’. This paper highlights the main conclusions of the EXCIMAP Handbook and Atlas, regarding the most appropriate ways to present flood‐related information. Distinction is made between different types of use and users, such as land‐use planning, emergency planning, flood risk management, reinsurance and the general public. Many countries disseminate flood maps (mainly flood extent maps) and flood hazard maps (depth or depth–velocity combinations) already via Internet. Many European rivers are part of transboundary water systems. Therefore, uniform approaches in flood (risk) assessments, map legend and presentation are urgently needed.

Flood maps in Europe – methods, availability and use

Abstract. To support the transition from traditional flood defence strategies to a flood risk management approach at the basin scale in Europe, the EU has adopted a new Directive (2007/60/EC) at the end of 2007. One of the major tasks which member states must carry out in order to comply with this Directive is to map flood hazards and risks in their territory, which will form the basis of future flood risk management plans. This paper gives an overview of existing flood mapping practices in 29 countries in Europe and shows what maps are already available and how such maps are used. Roughly half of the countries considered have maps covering as good as their entire territory, and another third have maps covering significant parts of their territory. Only five countries have very limited or no flood maps available yet. Of the different flood maps distinguished, it appears that flood extent maps are the most commonly produced floods maps (in 23 countries), but flood depth maps are also regularly created (in seven countries). Very few countries have developed flood risk maps that include information on the consequences of flooding. The available flood maps are mostly developed by governmental organizations and primarily used for emergency planning, spatial planning, and awareness raising. In spatial planning, flood zones delimited on flood maps mainly serve as guidelines and are not binding. Even in the few countries (e.g. France, Poland) where there is a legal basis to regulate floodplain developments using flood zones, practical problems are often faced which reduce the mitigating effect of such binding legislation. Flood maps, also mainly extent maps, are also created by the insurance industry in Europe and used to determine insurability, differentiate premiums, or to assess long-term financial solvency. Finally, flood maps are also produced by international river commissions. With respect to the EU Flood Directive, many countries already have a good starting point to map their flood hazards. A flood risk based map that includes consequences, however, has yet to be developed by most countries.

Water Level Estimation and Reduction of Hydraulic Model Calibration Uncertainties Using Satellite SAR Images of Floods

Exploitation of river inundation satellite images, particularly for operational applications, is mostly restricted to flood extent mapping. However, there lies significant potential for improvement in a 3-D characterization of floods (i.e., flood depth maps) and an integration of the remote-sensing-derived (RSD) characteristics in hydraulic models. This paper aims at developing synthetic aperture radar (SAR) image analysis methods that go beyond flood extent mapping to assess the potential of these images in the spatiotemporal characterization of flood events. To meet this aim, two research issues were addressed. The first issue relates to water level estimation. The proposed method, which is an adaptation to SAR images of the method developed for water level estimation using flood aerial photographs, is composed of three steps: (1) extraction of flood extent limits that are relevant for water level estimation; (2) water level estimation by merging relevant limits with a Digital Elevation Model; and (3) constraining of the water level estimates using hydraulic coherence concepts. Applied to an ENVISAT image of an Alzette River flood (2003, Grand Duchy of Luxembourg), this provides plusmn54-cm average vertical uncertainty water levels that were validated using a sample of ground surveyed high water marks. The second issue aims at better constraining hydraulic models using these RSD water levels. To meet this aim, a "traditional" calibration using recorded hydrographs is completed via comparison between simulated and RSD water levels. This integration of the RSD characteristics proves to better constrain the model (i.e., the number of parameter sets providing acceptable results with respect to observations has been reduced). Furthermore, simulations of a flood event of a different return period (2007) using the model calibrated for the 2003 flood event shows the reliability of the latter for flood forecasting.

A technique for the calibration of hydraulic models using uncertain satellite observations of flood extent

This paper presents a methodology to calibrate hydraulic models using possibility of inundation maps derived from satellite imagery. The study was performed on a river reach of the Lower Dee, UK, where a coarse resolution image (ENVISAT ASAR) and high resolution satellite image (ERS-2 SAR) were acquired at the same time during the December 2006 flood event. Ten different flood extent maps were derived from the two flood images by using five different procedures to process these data. These flood extent maps were used to perform a sensitivity analysis of a simple raster-based inundation model (LISFLOOD-FP). The sensitivity analysis enabled us to investigate the capability of the two different resolution images to calibrate the friction parameters of the flood inundation model. The analysis showed that the optimal parameters of the model depend on the type of satellite image used to evaluate the model as well as on the particular procedure used to derive the flood extent map. Finally, the study developed a novel methodology to calibrate flood inundation models by comparing the model results to a possibility of inundation map obtained by combining the ten different flood extent maps.

Estimating uncertainty associated with water stages from a single SAR image

It is the goal of remote sensing to infer information about objects or a natural process from a remote location. This invokes that uncertainty in measurement should be viewed as central to remote sensing. In this study, the uncertainty associated with water stages derived from a single SAR image for the Alzette (G.D. of Luxembourg) 2003 flood is assessed using a stepped GLUE procedure. Main uncertain input factors to the SAR processing chain for estimating water stages include geolocation accuracy, spatial filter window size, image thresholding value, DEM vertical precision and the number of river cross sections at which water stages are estimated. Initial results show that even with plausible parameter values uncertainty in water stages over the entire river reach is 2.8 m on average. Adding spatially distributed field water stages to the GLUE analysis following a one-at-a-time approach helps to considerably reduce SAR water stage uncertainty (0.6 m on average) thereby identifying appropriate value ranges for each uncertain SAR water stage processing factor. For the GLUE analysis a Nash-like efficiency criterion adapted to spatial data is proposed whereby acceptable SAR model simulations are required to outperform a simpler regression model based on the field-surveyed average river bed gradient. Weighted CDFs for all factors based on the proposed efficiency criterion allow the generation of reliable uncertainty quantile ranges and 2D maps that show the uncertainty associated with SAR-derived water stages. The stepped GLUE procedure demonstrated that not all field data collected are necessary to achieve maximum constraining. A possible efficient way to decide on relevant locations at which to sample in the field is proposed. It is also suggested that the resulting uncertainty ranges and flood extent or depth maps may be used to evaluate 1D or 2D flood inundation models in terms of water stages, depths or extents. For this, the extended GLUE approach, which copes with the presence of uncertainty in the observed data, may be adopted.

Mapping of flood dynamics and spatial distribution of vegetation in the Amazon floodplain using multitemporal SAR data

This paper presents the use of time series of SAR images to map the flood temporal dynamics and the spatial distribution of vegetation over a large Amazonian floodplain. The region under study (3500 km 2) presents a diversity of landscape units with open lakes, bogs, large meadows, savannahs, alluvial forests and terra firma forest, covered by 21 images acquired by J-ERS between 1993 and 1997. Ground data include in situ observations of vegetation structure and flood extent as well as water level records. Image analysis demonstrates that temporal variations of the radar backscatter can be used to monitor efficiently the flood extent regardless of the landscape units. Also, analysis of the backscatter temporal variation greatly reduces the confusion between smooth surfaces (e.g. open water bodies, bare soils) inherent to L-band backscatter. The mapping method is based on decision rules over two decision variables: 1) the mean backscatter coefficient computed over the whole time series; 2) the total change computed using an “Absolute Change” estimator. The first variable provides classification into rough vegetation types while the second variable yields a direct estimate of the intensity of change that is related to flood dynamics. The classifier is first applied to the whole time series to map the maximum and minimum flood extent by defining 3 flood conditions: never flooded (NF); occasionally flooded (OF); permanently flooded (PF). It also furnishes the broad land cover type: open water/bare soils/low vegetation/forest. The accuracy of the flood extent mapping shows a kappa value of 0.82. Then, the classifier is run iteratively on the OF pixels to monitor flood stages during which the occasionally flooded areas get submerged. The mapping accuracy is assessed on one intermediate flood stage, showing a precision in excess of 90%. The importance of the time sampling for flood mapping is discussed along with the influence of SAR backscatter accuracy and the number of images. Then general guidelines for floodplain mapping are presented. By combining water level reports with maps of different flood stages the flooding pattern can be retrieved along with the vegetation succession processes. It is shown that the spatial distribution of vegetation communities is governed by flood stress and can be modelled as a function of the mean annual exposure to floods.

Integration of SAR-derived river inundation areas, high-precision topographic data and a river flow model toward near real-time flood management

Since several space-borne synthetic aperture radar (SAR) instruments providing high spatial resolutions and multi-polarisation capabilities will be mounted on satellites to be launched from 2006 onwards, radar imagery promises to become an indispensable asset for many environmental monitoring applications. Due to its all weather, day and night capabilities, SAR imagery presents obvious advantages over optical instruments, especially in flood management applications. To date, however, the coarse spatial resolution of available SAR datasets restricts the information that can be reliably extracted and processing techniques tend to be limited to binary floodplain segmentation into ‘flooded’ and ‘non flooded’ areas. It is the purpose of this paper to further improve the exploitation of SAR images in hydraulic modelling and near real-time crisis management by means of developing image processing methodologies that allow for the extraction of water levels at any point of the floodplain. As high-precision digital elevation models (DEM) produced, for instance, from airborne laser scanning become more readily available, methods can be exploited that combine SAR-derived flood extent maps and precise topographic data for retrieving water depth maps. In a case study of a well-documented flood event in January 2003 on the River Alzette, Grand Duchy of Luxembourg, a root mean squared error (R.M.S.E.) of 41cm was obtained by comparing the SAR-derived water heights with surveyed high water marks that were collected during image acquisition. Water levels that were computed by a previously calibrated hydraulic model also suggest that the water surface profiles provided by the combined use of topographic data and SAR accurately reflect the true water line. The extraction of flooded areas within vegetated areas further demonstrates the usefulness of the proposed methodology.

Identifiability of distributed floodplain roughness values in flood extent estimation

In this paper we explore the potential for identifying roughness values for distributed land use types using a comprehensive calibration data set of the 1995 flood event in the River Meuse, including gauged levels, flood extent maps and distributed flood plain level observations. The reach studied is modelled using an integrated 1D–2D hydrodynamic model, with floodplain flow modelled in the 2D domain. Detailed information on floodplain land use types is aggregated to form one, two or five classes of floodplain roughness. Sensitivity analysis of model performance against the calibration data shows that as the number of floodplain classes increases, sensitivity to these roughness values decreases, given allocation of prior roughness values on the basis of constituent land use types and associated roughness values found from literature. Evaluating the identifiability of the roughness in these classes using the Generalised Likelihood Uncertainty Estimation (GLUE) method confirms this insensitivity. As a consequence, application of complex formulae to establish roughness values for changed floodplain land use would seem inappropriate, and evaluation of such changes within a probabilistic framework is suggested.

Using Landsat 7 TM data acquired days after a flood event to delineate the maximum flood extent on a coastal floodplain

In response to Hurricane Floyd, the Tar River crested at a record height of 4.30 m above the flood stage at the river gauge station of Greenville (North Carolina, USA) on 21 September 1999. This resulted in a massive flooding in the area. To delineate the maximum flood extent, an area of 238.4 km2 along the Tar/Pamlico River, North Carolina, and within the overlapped area of Landsat 7 Thematic Mapper (TM) path 14/row 35 and path 15/row 35 scenes was studied. Three TM datasets of 28 July 1999 (path 15/row 35), 23 September 1999 (path 14/row 35) and 30 September 1999 (path 15/row 35) were analysed as pre-flood data, near peak data, and nine days after the peak data, respectively. The 23 and 30 September flood extent maps were derived by change detection and then verified by 85 nonflooded and flooded sites within the study area. The overall accuracies at the sites were between 82.5–99.3% on both inundation extent maps. Although the recorded river surface level fell 2.62 m from 23 to 30 September at the river gauge station of Greenville, comparison of the two flood extent maps on a pixel-by-pixel basis showed an agreement of 90.7% in terms of regular river channels and waterbodies, flooded areas and nonflooded areas. The 30 September map captured over 90% of the flood extent as identified on the 23 September map. These results suggest that it is possible to use remotely sensed data acquired days after a river's crest to capture most of the maximum extent of a flood occurring on a coastal floodplain, and should somewhat reduce the requirement to have concurrently remotely sensed data in mapping a flood extent on a coastal floodplain.

Impact of grid size in GIS based flood extent mapping using a 1D flow model

Flood hazard in areas adjacent to rivers may be estimated by applying hydrological/hydraulic models to calculate parameters such as flood extent, depth and duration. Using a two-dimensional flow model based on the topography has the drawback that computational requirements are high, making this approach unattractive when applying in, for example, a decision support system. This paper presents a simple GIS based method for assessing the extent and depth of flooding based on water levels calculated using a 1-dimensional flow model and an extended inverse distance interpolation method. Local depressions not directly connected to the river by a continuous water surface are easily removed. The method is demonstrated on a 9 km2 floodplain area, where the effect of varying grid size on flood extent estimation and evaluation time is investigated. Possible points of improvement as well as future work to assess the accuracy are discussed.