Exploring the application of topographic indices in urban areas as indicators of pluvial flooding locations

In urban areas, the presence of impervious surfaces limits natural drainage and routes water to stormwater infrastructure with finite capacity, making these areas especially prone to flooding. Though large floods are responsible for endangering lives and causing extensive damage, there is growing evidence that more frequent floods with shallow water depths, termed nuisance flooding, can have a high cumulative cost and many direct and indirect damages. To determine whether locations of nuisance flooding may be linked to topography, we took a parsimonious, spatially distributed approach to explore whether high topographic index values co-occur with citizen-reported nuisance flooding. We obtained nuisance flood reports from the municipal data service 311 for several watersheds in New York City and Baltimore, USA. Our analysis tested two topographic indices (TI)—topographic wetness index (TWI) and sink depth—both calculated from high-resolution (~1 m) digital elevation models. Generally, our findings suggest that not all but many locations of reported flooding tend to coincide with deep sinks or large TWI. However, nuisance flooding reports most commonly coincided with deep sinks and high TWI when using a maximum, instead of coincident, TI value extracted around each reported location of flooding, an approach we used due to the uncertainty in location accuracy of flooding reports. Overall, our results show promise for application of topographic indices, typically applied in more natural settings, as indicators of nuisance flooding areas in urbanized environments. Although limitations to this approach exist, the application of TIs and crowd-sourced reporting in tandem could provide a useful starting point for mapping flood-prone areas in many cities with technologically adept community members and ample geospatial data.     

Flood hazard mapping using synthesis hydraulic and geomorphic properties at watershed scale

The occurrence of natural phenomena such as floods has caused serious consequences for human societies. The simulation of flood hazard maps and its depth in a river is one of the most complex processes in hydrology. In fact both geomorphological and hydraulic procedures for deriving the flood hazard maps and depth are imperfect at watershed scale. In this study, a combination of both procedures, using a probabilistic approach is used. Flood inundation maps for 2-, 10-, 25-,50- and 100-return period floods using flood routine within HEC-RAS in combination of Arc-GIS and topographic wetness index (TWI) map were produced. TWI threshold was identified using a maximum likelihood method in order to produce flood prone areas and calibrated over the reach of Zirab City. The correlation between TWI threshold and the flood depth was carried out and simple linear regression developed for various return periods. The resulting regression model is used in order to create flood hazard maps with various return periods at watershed scale.     

Inundation extent as a key parameter for assessing the magnitude and return period of flooding events in southern Iceland

Abstract

River flow conditions in many watersheds of Iceland are particularly disturbed during winter by the formation, drifting and accumulation of river ice, whose impact on water encroachment and extent of inundations is not reflected in the discharge records. It is therefore necessary to use river discharge with great caution when assessing the magnitude of past inundations in Iceland, and to give attention to other flood magnitude parameters. A GIS-based methodology is presented that focuses on inundation extent as an alternative parameter for the assessment and ranking of the magnitude of past flooding events in the Ölfusá-Hvítá basin, known as one of the most dangerous flood-prone river complexes in Iceland. Relying ultimately on a macro-scale grid, the method enabled the reconstruction of the extent of inundations, the delineation of the flood plain, and, finally, some estimation of the likelihood of flooding of exposed areas that include marine submergences and river floods for both open water and ice conditions.

Citation Pagneux, E., Gísladóttir, G. & Snorrason, Á. (2010) Inundation extent as a key parameter for assessing the magnitude and return period of flooding events in southern Iceland. Hydrol. Sci. J. 55(5), 704–716.     

Modeling and visualizing uncertainties of flood boundary delineation: algorithm for slope and DEM resolution dependencies of 1D hydraulic models

As flood inundation risk maps have become a central piece of information for both urban and risk management planning, also a need to assess the accuracies and uncertainties of these maps has emerged. Most maps show the inundation boundaries as crisp lines on visually appealing maps, whereby many planners and decision makers, among others, automatically believe the boundaries are both accurate and reliable. However, as this study shows, probably all such maps, even those that are based on high-resolution digital elevation models (DEMs), have immanent uncertainties which can be directly related to both DEM resolution and the steepness of terrain slopes perpendicular to the river flow direction. Based on a number of degenerated DEMs, covering areas along the Eskilstuna River, Sweden, these uncertainties have been quantified into an empirically-derived disparity distance equation, yielding values of distance between true and modeled inundation boundary location. Using the inundation polygon, the DEM, a value representing the DEM resolution, and the desired level of confidence as inputs in a new-developed algorithm that utilizes the disparity distance equation, the slope and DEM dependent uncertainties can be directly visualized on a map. The implications of this strategy should benefit planning and help reduce high costs of floods where infrastructure, etc., have been placed in flood-prone areas without enough consideration of map uncertainties.     

Using the present to estimate the future: A simplified approach for the quantification of climate change effects on urban flooding by scenario analysis

Understanding and modelling pluvial flood patterns is pivotal for the estimation of flood impacts in urban areas, especially in a climate change perspective. However, urban flood modelling under climate change conditions poses several challenges. On one hand, the identification and collection of climate change data suitable for flood-related evaluations requires consistent computational and scientific effort. On the other hand, large difficulties can arise in the reproduction of the rainfall-runoff transformation process in cases when only little information about the subsurface processes is known. In this perspective, a simplified approach is proposed to address the challenges regarding the quantitative estimation of climate change effects on urban flooding for real case applications. The approach is defined as “bottom-up” because climate change information is not included in flood modelling, but it is only invoked for the interpretation of results. In other words, the challenge faced in this work is the development of a modelling strategy that is expeditious, because it does not require flood simulations for future rainfall scenarios, but only under current climate conditions, thus reducing the overall computational effort; and it is flexible, because results can be easily updated once new climate change data, scenarios or methods become available, without the need of additional flood simulations. To simulate real case applications, the approach is tested for a scenario analysis, where different return periods and hyetograph shapes are used as input for urban inundation modelling in Naples, Italy. The approach can support public and private stakeholders, such as land administrators and water systems managers; moreover, it represents a valuable and effective basis for climate change risk communication strategies.     

HAND contour: a new proxy predictor of inundation extent

Tools for accurately predicting environmental risks, such as the location and spatial extent of potential inundation, are not widely available. A dependence on calibration and a lack of available flood data have prevented the widespread application of existing hydrodynamic methods for predicting the extent of inundation. We use the height above the nearest drainage (HAND) terrain model to develop a simple static approach for mapping the potential extent of inundation that does not depend on flood observations and extends beyond methods for mapping low‐lying areas. While relying on the contour concept, the method utilizes drainage‐normalized topography and flowpaths to delineate the relative vertical distances (drop) to the nearest river. The HAND‐delineated relative drop is an effective distributed predictor of flood potential, which is directly related to the river stage height. We validated the new HAND contour approach using a flood event in Southern Brazil for which high‐resolution maps were available. The results indicated that the flood hazard‐mapping method accurately predicted the inundation extent of the channel carrying the flood wave and the channels influenced by flooding. For channels positioned outside of the flood‐wave area, the method overestimated the actual flood extent. As an original static assessment of floodwaters across the landscape, the HAND contour method could be used to map flood hazards in areas with poor information and could promote the development of new methods for predicting hydrological hazards. Copyright © 2015 John Wiley & Sons, Ltd.     

Investigating sea-state effects on flash flood hydrograph and inundation forecasting

A common source of uncertainty in flood inundation forecasting is the hydrograph used. Given the role of sea-air-hydro-land chain processes on the water cycle, flood hydrographs in coastal areas can be indirectly affected by sea state. This study investigates sea-state effects on precipitation, discharge, and flood inundation forecasting implementing atmospheric, ocean wave, hydrological, and hydraulic-hydrodynamic coupled models. The Chemical Hydrological Atmospheric Ocean wave System (CHAOS) was used for coupled hydro-meteorological-wave simulations ‘accounting’ or ‘not accounting’ the impact of sea state on precipitation and, subsequently, on flood hydrograph. CHAOS includes the WRF-Hydro hydrological model and the WRF-ARW meteorological model two-way coupled with the WAM wave model through the OASIS3-MCT coupler. Subsequently, the 2D HEC-RAS hydraulic-hydrodynamic model was forced by the flood hydrographs and map the inundated areas. A flash flood event occurred on 15 November 2017 in Mandra, Attica, Greece, causing 24 fatalities, and damages was selected as case study. The calibration of models was performed exploiting historical flood records and previous studies. Human interventions such as hydraulic works and the urban areas were included in the hydraulic modelling geometry domain. The representation of the resistance caused by buildings was based on Unmanned Aerial System (UAS) data while the local elevation rise method was used in the urban-flood simulation. The flood extent results were assessed using the Critical Success Index (CSI), and CSI penalize. Integrating sea-state affected the forecast of precipitation and discharge peaks, causing up to +24% and from −8% to +36% differences, respectively, improving inundation forecast by 4.5% and flooding additional approximately 70 building blocks. The precipitation forcing time step was also highlighted as significant factor in such a small-scale flash flood. The integrated multidisciplinary methodological approach could be adopted in operational forecasting for civil protection applications facilitating the protection of socio-economic activities and human lives during similar future events.     

Bayesian updating of flood inundation likelihoods conditioned on flood extent data

Previously we have detailed an application of the generalized likelihood uncertainty estimation (GLUE) procedure to estimate spatially distributed uncertainty in models conditioned against binary pattern data contained in flood inundation maps. This method was applied to two sites where a single consistent synoptic image of inundation extent was available to test the simulation performance of the method. In this paper, we extend this to examine the predictive performance of the method for a reach of the River Severn, west‐central England. Uniquely for this reach, consistent inundation images of two major floods have been acquired from spaceborne synthetic aperture radars, as well as a high‐resolution digital elevation model derived using laser altimetry. These data thus allow rigorous split sample testing of the previous GLUE application. To achieve this, Monte Carlo analyses of parameter uncertainty within the GLUE framework are conducted for a typical hydraulic model applied to each flood event. The best 10% of parameter sets identified in each analysis are then used to map uncertainty in flood extent predictions using the method previously proposed for both an independent validation data set and a design flood. Finally, methods for combining the likelihood information derived from each Monte Carlo ensemble are examined to determine whether this has the potential to reduce uncertainty in spatially distributed measures of flood risk for a design flood. The results show that for this reach and these events, the method previously established is able to produce sharply defined flood risk maps that compare well with observed inundation extent. More generally, we show that even single, poor‐quality inundation extent images are useful in constraining hydraulic model calibrations and that values of effective friction parameters are broadly stationary between the two events simulated, most probably reflecting their similar hydraulics. Copyright © 2004 John Wiley & Sons, Ltd.     

Forecasting the spatial extent of the annual flood in the Okavango delta, Botswana

The pristine Okavango Delta wetland of northern Botswana is potentially under threat due to water abstraction from its tributaries. We have developed a statistical model which makes it possible to predict the extent of wetland loss which will arise from water abstraction. The model also permits prediction of the maximum area of flooding, and its spatial distribution, three months in advance of the flood maximum. The model was calibrated using maximum areas of seasonal inundation extracted from satellite imagery covering the period 1985–2000, which were correlated with rainfall and total flood discharge. A technique was developed to translate the modelled flood area into a flood map. The methodology can predict maximum area of flooding and its distribution with better than 90% accuracy. An important, although relatively minor, source of error in the spatial distribution of the flood arises from a secular change in flood distribution in the distal Delta which has taken place over the last 15 years. Reconstruction of flooding history back to 1934 suggests that the Delta may be subject to a quasi 80 year climatic oscillation. If this oscillation continues, the extent of flooding will increase in the coming decades.     

Characterisation of flood inundated areas and delineation of poor drainage soil using ERS-1 SAR imagery

Recent years have been marked by a continuous availability of spatial SAR data since the launch of the European remote sensing satellite (ERS-1) in 1991. Consequently, remote sensing techniques now offer an opportunity to map flood inundation fields caused by river overflow or waterlogging in environments characterized by frequent cloud cover. Indeed, inundation fields can clearly be seen on ERS-1 SAR images taken during flooding periods. However, such an identification can be constrained by the similarity in behaviour between water surfaces and other features of the landscape such as extended asphalt areas, permanent water bodies and less illuminated slopes. For consistent flood inundation extent mapping a more robust approach is required. This is provided by a conceptual flood inundation index that is physically sound in relation to radar imaging. Moreover, this index has proved to be useful for highlighting soils located within inundation fields and having significantly different internal drainage. The results achieved in the framework of the research must be seen in the context of intensive use of remote sensing data to support decision methods for sustainable management of land and water resources. Such decision support methods could be provided by river hydraulic models aimed at assessing environmental effects of inundation floods and at early flood warning systems. © 1997 John Wiley & Sons, Ltd.     

Assessing spatial likelihood of flooding hazard using naïve Bayes and GIS: a case study in Bowen Basin,Australia

Flooding hazard evaluation is the basis of flooding risk assessment which has significances to natural environment, human life and social economy. This study develops a spatial framework integrating naïve Bayes (NB) and geographic information system (GIS) to assess flooding hazard at regional scale. The methodology was demonstrated in the Bowen Basin in Australia as a case study. The inputs into the framework are five indices: elevation, slope, soil water retention, drainage proximity and density. They were derived from spatial data processed in ArcGIS. NB as a simplified and efficient type of Bayesian methods was used, with the assistance of remotely sensed flood inundation extent in the sampling process, to infer flooding probability on a cell-by-cell basis over the study area. A likelihood-based flooding hazard map was output from the GIS-based framework. The results reveal elevation and slope have more significant impacts on evaluation than other input indices. Area of high likelihood of flooding hazard is mainly located in the west and the southwest where there is a high water channel density, and along the water channels in the east of the study area. High likelihood of flooding hazard covers 45 % of the total area, medium likelihood accounts for about 12 %, low and very low likelihood represents 19 and 24 %, respectively. The results provide baseline information to identify and assess flooding hazard when making adaptation strategies and implementing mitigation measures in future. The framework and methodology developed in the study offer an integrated approach in evaluation of flooding hazard with spatial distributions and indicative uncertainties. It can also be applied to other hazard assessments.     

The application of integrated urban inundation model in Republic of Korea

In urban areas with a high building density, features such as roads, buildings and river dykes significantly affect flow dynamics and flood propagation. This should therefore be accounted for in the model set‐up. While 2D hydraulic models of densely urban areas are at the forefront of current research into flood inundation mechanisms, these models are constrained by inadequate parameters of topography and insufficient data. In order to solve these problems, topographic information obtained from digital elevation model (DEM) is directly programmed into the urban inundation model for a densely urban area, without exchanging the input data. In this paper, the extraction of building area is described using a tight coupling approach within a GIS environment, and its influence on the extent of flood inundation with a high building density is estimated. Copyright © 2009 John Wiley & Sons, Ltd.     

The use of remotely sensed land cover to derive floodplain friction coefficients for flood inundation modelling

Remotely sensed land cover was used to generate spatially‐distributed friction coefficients for use in a two‐dimensional model of flood inundation. Such models are at the forefront of research into the prediction of river flooding. Standard practice, however, is to use single (static) friction coefficients on both the channel and floodplain, which are varied in a calibration procedure to provide a “best fit” to a known inundation extent. Spatially‐distributed friction provides a physically grounded estimate of friction that does not require fitting to a known inundation extent, but which can be fitted if desired. Remote sensing offers the opportunity to map these friction coefficients relatively straightforwardly and for low cost. Inundation was predicted using the LISFLOOD‐FP model for a reach on the River Nene, UK. Friction coefficients were produced from land cover predicted from Landsat TM imagery using both ML and fuzzy c‐means classifiction. The elevetion data used were from combined contour and differential global positioning system (GPS) elevation data. Predicted inundation using spatially‐distributed and static friction were compared. Spatially‐distributed friction had the greatest effect on the timing of flood inundation, but a small effect on predicted inundation extent. The results indicate that spatially‐distributed friction should be considered where the timing of initial flooding (e.g. for early warning) is important. Copyright © 2007 John Wiley & Sons, Ltd.     

Probabilistic evaluation of flood hazard in urban areas using Monte Carlo simulation

The goal of the presented research was the derivation of flood hazard maps, using Monte Carlo simulation of flood propagation at an urban site in the UK, specifically an urban area of the city of Glasgow. A hydrodynamic model describing the propagation of flood waves, based on the De Saint Venant equations in two‐dimensional form capable of accounting for the topographic complexity of the area (preferential outflow paths, buildings, manholes, etc.) and for the characteristics of prevailing imperviousness typical of the urban areas, has been used to derive the hydrodynamic characteristics of flood events (i.e. water depths and flow velocities). The knowledge of the water depth distribution and of the current velocities derived from the propagation model along with the knowledge of the topographic characteristics of the urban area from digital map data allowed for the production of hazard maps based on properly defined hazard indexes. These indexes are evaluated in a probabilistic framework to overcome the classical problem of single deterministic prediction of flood extent for the design event and to introduce the concept of the likelihood of flooding at a given point as the sum of data uncertainty, model structural error and parameterization uncertainty. Copyright © 2011 John Wiley & Sons, Ltd.     

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

Abstract

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.     

Spatially distributed observations in constraining inundation modelling uncertainties

The performance of two modelling approaches for predicting floodplain inundation is tested using observed flood extent and 26 distributed floodplain level observations for the 1997 flood event in the town of Usti nad Orlici in the Czech Republic. Although the one‐dimensional hydrodynamic model and the integrated one‐ and two‐dimensional model are shown to perform comparably against the flood extent data, the latter shows better performance against the distributed level observations. Comparable performance in predicting the extent of inundation is found to be primarily as a result of the urban reach considered, with flood extent constrained by road and railway embankments. Uncertainty in the elevation model used in both approaches is shown to have little effect on the reliability in predicting flood extent, with a greater impact on the ability in predicting the distributed level observations. These results show that reliability of flood inundation modelling in urban reaches, where flood risk assessment is of more interest than in more rural reaches, can be improved greatly if distributed observations of levels in the floodplain are used in constraining model uncertainties. Copyright © 2005 John Wiley & Sons, Ltd.     

Evaluating the effect of scale in flood inundation modelling in urban environments

Cellular‐based approaches for flood inundation modelling have been extensively calibrated and evaluated for the prediction of flood flows on rural river reaches. However, there has only been limited application of these approaches to urban environments, where the need for flood management is greatest. Practical application of two‐dimensional (2D) flood inundation models is often limited by computation time and processing power on standard desktop PCs when attempting to resolve flows on the high‐resolution grids necessary to replicate urban features. Consequently, it is necessary to evaluate the effectiveness of coarse grids to represent flood flows through urban environments. To examine these effects, LISFLOOD‐FP, a 2D storage cell model, is applied to hypothetical flooding scenarios in Greenfields, Glasgow. Grid resampling techniques in GIS software packages are evaluated and a bilinear gridding technique appears to provide the most accurate and physically intuitive results. A gridding method maintaining sharp elevation changes at building interfaces and neighbouring land is presented and estimates of the discretization noise associated with the coarse resolution grids suggest little improvement over current gridding methods. The variation in model results from the friction sensitivity analysis suggests a non‐stationary response to Manning's n with changing model resolution. Model results suggests that a coarse resolution model for urban applications is limited by the representation of urban media in coarse model grids. Furthermore, critical length scales related to building dimensions and building separation distances exist in urban areas that determine maximum possible grid resolutions for hydraulic models of urban flooding. Copyright ©, 2008 John Wiley & Sons, Ltd.     

Rainfall–runoff–inundation analysis of the 2010 Pakistan flood in the Kabul River basin

Abstract

Pakistan has suffered a devastating flood disaster in 2010. In the Kabul River basin (92 605 km²), large-scale riverine and flash floods caused destructive damage with more than 1100 casualties. This study analysed rainfall–runoff and inundation in the Kabul River basin with a newly developed model that simulates the processes of rainfall–runoff and inundation simultaneously based on two-dimensional diffusion wave equations. The simulation results showed a good agreement with an inundation map produced based on MODIS for large-scale riverine flooding. In addition, the simulation identified flash flood-affected areas, which were confirmed to be severely damaged based on a housing damage distribution map. Since the model is designed to be used even immediately after a disaster, it can be a useful tool for analysing large-scale flooding and to provide supplemental information to agencies for relief operations.

Editor Z.W. Kundzewicz

Citation Sayama, T., Ozawa, G., Kawakami, T., Nabesaka, S. and Fukami, K., 2012. Rainfall–runoff–inundation analysis of the 2010 Pakistan flood in the Kabul River basin. Hydrological Sciences Journal, 57 (2), 298–312.     

Flood hazard and risk analysis in the southwest region of Bangladesh

Flood hazard and risk assessment was conducted to identify the priority areas in the southwest region of Bangladesh for flood mitigation. Simulation of flood flow through the Gorai and Arial Khan river system and its floodplains was done by using a hydrodynamic model. After model calibration and verification, the model was used to simulate the flood flow of 100‐year return period for a duration of four months. The maximum flooding depths at different locations in the rivers and floodplains were determined. The process in determining long flooding durations at every grid point in the hydrodynamic model is laborious and time‐consuming. Therefore the flood durations were determined by using satellite images of the observed flood in 1988, which has a return period close to 100 years. Flood hazard assessment was done considering flooding depth and duration. By dividing the study area into smaller land units for hazard assessment, the hazard index and the hazard factor for each land unit for depth and duration of flooding were determined. From the hazard factors of the land units, a flood hazard map, which indicates the locations of different categories of hazard zones, was developed. It was found that 54% of the study area was in the medium hazard zone, 26% in the higher hazard zone and 20% in the lower hazard zone. Due to lack of sufficient flood damage data, flood damage vulnerability is simply considered proportional to population density. The flood risk factor of each land unit was determined as the product of the flood hazard factor and the vulnerability factor. Knowing the flood risk factors for the land units, a flood risk map was developed based on the risk factors. These maps are very useful for the inhabitants and floodplain management authorities to minimize flood damage and loss of human lives. Copyright © 2005 John Wiley & Sons, Ltd.     

An event simulation approach to the assessment of flood level frequencies: risk maps for the Warsaw reach of the River Vistula

Flood risk assessment is customarily performed using a design flood. Observed past flows are used to derive a flood frequency curve which forms the basis for a construction of a design flood. The simulation of a distributed model with the 1‐in‐T year design flood as an input gives information on the possible inundation areas, which are used to derive flood risk maps. The procedure is usually performed in a deterministic fashion, and its extension to take into account the design flood‐and flow routing model uncertainties is computer time consuming. In this study we propose a different approach to flood risk assessment which consists of the direct simulation of a distributed flow routing model for an observed series of annual maximum flows and the derivation of maps of probability of inundation of the desired return period directly from the obtained simulations of water levels at the model cross sections through an application of the Flood Level Frequency Analysis. The hydraulic model and water level quantile uncertainties are jointly taken into account in the flood risk uncertainty evaluation using the Generalized Likelihood Uncertainty Estimation (GLUE) approach. An additional advantage of the proposed approach lies in smaller uncertainty of inundation predictions for long return periods compared to the standard approach. The approach is illustrated using a design flood level and a steady‐state solution of a hydraulic model to derive maps of inundation probabilities. Copyright © 2016 John Wiley & Sons, Ltd.