Sensitivity of a hydraulic model to channel erosion uncertainty during extreme flooding

Recent research into flood modelling has primarily concentrated on the simulation of inundation flow without considering the influences of channel morphology. River channels are often represented by a simplified geometry that is implicitly assumed to remain unchanged during flood simulations. However, field evidence demonstrates that significant morphological changes can occur during floods to mobilize the boundary sediments. Despite this, the effect of channel morphology on model results has been largely unexplored. To address this issue, the impact of channel cross‐section geometry and channel long‐profile variability on flood dynamics is examined using an ensemble of a 1D–2D hydraulic model (LISFLOOD‐FP) of the ~1 : 2000 year recurrence interval floods in Cockermouth, UK, within an uncertainty framework. A series of simulated scenarios of channel erosional changes were constructed on the basis of a simple velocity‐based model of critical entrainment. A Monte‐Carlo simulation framework was used to quantify the effects of this channel morphology together with variations in the channel and floodplain roughness coefficients, grain size characteristics and critical shear stress on measures of flood inundation. The results showed that the bed elevation modifications generated by the simplistic equations reflected an approximation of the observed patterns of spatial erosion that enveloped observed erosion depths. The effect of uncertainty on channel long‐profile variability only affected the local flood dynamics and did not significantly affect the friction sensitivity and flood inundation mapping. The results imply that hydraulic models generally do not need to account for within event morphodynamic changes of the type and magnitude of event modelled, as these have a negligible impact that is smaller than other uncertainties, e.g. boundary conditions. Instead, morphodynamic change needs to happen over a series of events to become large enough to change the hydrodynamics of floods in supply limited gravel‐bed rivers such as the one used in this research. Copyright © 2014 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.     

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.     

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.     

When does spatial resolution become spurious in probabilistic flood inundation predictions?

Advances in remote sensing have enabled hydraulic models to run at fine scale resolutions, producing precise flood inundation predictions. However, running models at finer resolutions increase their computational expense, reducing the feasibility of running the multiple model realizations required to undertake uncertainty analysis. Furthermore, it is possible that precision gained by running fine scale models is smoothed out when treating models probabilistically. The aim of this paper is to determine the level of spatial complexity that is required when making probabilistic flood inundation predictions. The Imera basin, Sicily is used as a case study to assess how changing the spatial resolution of the hydraulic model LISFLOOD‐FP impacts on the skill of conditional probabilistic flood inundation maps given model parameter and boundary condition uncertainties. We find that model performance deteriorates at resolutions coarser than 50 m. This is predominantly caused by changes in flow pathways at coarser resolutions which lead to non‐stationarity in the optimum model parameters at different spatial resolutions. However, although it is still possible to produce probabilistic flood maps that contain a coherent outline of the flood extent at coarser resolutions, the reliability of these maps deteriorates at resolutions coarser than 100 m. Additionally, although the rejection of non‐behavioural models reduces the uncertainty in probabilistic flood maps the reliability of these maps is also reduced. Models with resolutions finer than 50 m offer little gain in performance yet are more than an order of magnitude computationally expensive which can become infeasible when undertaking probabilistic analysis. Furthermore, we show that using deterministic, high‐resolution flood maps can lead to a spurious precision that would be misleading and not representative of the overall uncertainties that are inherent in making inundation predictions. Copyright © 2015 The Authors Hydrological Processes Published by John Wiley & Sons Ltd.     

Uncertainty in floodplain delineation: expression of flood hazard and risk in a Gulf Coast watershed

This paper investigates the development of flood hazard and flood risk delineations that account for uncertainty as improvements to standard floodplain maps for coastal watersheds. Current regulatory floodplain maps for the Gulf Coastal United States present 1% flood hazards as polygon features developed using deterministic, steady‐state models that do not consider data uncertainty or natural variability of input parameters. Using the techniques presented here, a standard binary deterministic floodplain delineation is replaced with a flood inundation map showing the underlying flood hazard structure. Additionally, the hazard uncertainty is further transformed to show flood risk as a spatially distributed probable flood depth using concepts familiar to practicing engineers and software tools accepted and understood by regulators. A case study of the proposed hazard and risk assessment methodology is presented for a Gulf Coast watershed, which suggests that storm duration and stage boundary conditions are important variable parameters, whereas rainfall distribution, storm movement, and roughness coefficients contribute less variability. The floodplain with uncertainty for this coastal watershed showed the highest variability in the tidally influenced reaches and showed little variability in the inland riverine reaches. Additionally, comparison of flood hazard maps to flood risk maps shows that they are not directly correlated, as areas of high hazard do not always represent high risk. Copyright © 2012 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.     

A probabilistic model for real‐time flood warning based on deterministic flood inundation mapping

Deterministic flood inundation mapping is valuable for the investigation of detailed flood depth and extent. However, when these data are used for real‐time flood warning, uncertainty arises while encountering the difficulties of timely response, message interpretation and performance evaluation that makes statistical analysis necessary. By incorporating deterministic flood inundation map outputs statistically by means of logistic regression, this paper presents a probabilistic real‐time flood warning model determining region‐based flood probability directly from rainfall, being efficient in computation, clear in message, and valid in physical meaning. The calibration and validation of the probabilistic model show a satisfactory overall correctness rate, with the hit rate far surpassing the false alarm rate in issuing flood warning for historical events. Further analyses show that the probabilistic model is effective in evaluating the level of uncertainty lying within flood warning which can be reduced by several techniques proposed in order to improve warning performance. Copyright © 2011 John Wiley & Sons, Ltd.     

Assessing the uncertainty in distributed model predictions using observed binary pattern information within GLUE

In this paper we extend the generalized likelihood uncertainty estimation (GLUE) technique to estimate spatially distributed uncertainty in models conditioned against binary pattern data contained in flood inundation maps. Untransformed binary pattern data already have been used within GLUE to estimate domain‐averaged (zero‐dimensional) likelihoods, yet the pattern information embedded within such sources has not been used to estimate distributed uncertainty. Where pattern information has been used to map distributed uncertainty it has been transformed into a continuous function prior to use, which may introduce additional errors. To solve this problem we use here ‘raw’ binary pattern data to define a zero‐dimensional global performance measure for each simulation in a Monte Carlo ensemble. Thereafter, for each pixel of the distributed model we evaluate the probability that this pixel was inundated. This probability is then weighted by the measure of global model performance, thus taking into account how well a given parameter set performs overall. The result is a distributed uncertainty measure mapped over real space. The advantage of the approach is that it both captures distributed uncertainty and contains information on global likelihood that can be used to condition predictions of further events for which observed data are not available. The technique is applied to the problem of flood inundation prediction at two test sites representing different hydrodynamic conditions. In both cases, the method reveals the spatial structure in simulation uncertainty and simultaneously enables mapping of flood probability predicted by the model. Spatially distributed uncertainty analysis is shown to contain information over and above that available from global performance measures. Overall, the paper highlights the different types of information that may be obtained from mappings of model uncertainty over real and n‐dimensional parameter spaces. Copyright © 2002 John Wiley & Sons, Ltd.     

A fast simplified model for predicting river flood inundation probabilities in poorly gauged areas

The capability of a simple kinematic‐storage model (KSM) is analysed to be used as a tool for a Decision Support System for the evaluation of probability inundation maps in near real time in poorly gauged areas. KSM simulates the floodplain as a storage and assumes no exchange of momentum with the channel. For the in‐bank flow, the storage is modified through a coefficient for taking the variations of channel cross sections into account. The generalized likelihood uncertainty estimation approach is used for addressing the probability flood maps along with their associated uncertainties. The model is tested on two river reaches along the Tiber River in Central Italy where observed inundation maps are available for two recent flood events. Despite the inherent uncertainties present in the input data and in the model structure, the results show that the model reproduces reasonably well, in terms of both precision and accuracy, the observed inundated areas. Tests were performed at different digital elevation model resolutions, showing a small effect of the geometry on the maximum performance obtained. The very low computational times, the parsimony of the model and its low sensitivity to the quality of the geometry representation of the channel and the floodplain makes KSM very appealing for flood forecasting and early warning system applications in poorly gauged and inaccessible areas. Copyright © 2014 John Wiley & Sons, Ltd.     

Validation of a full hydrodynamic model for large‐scale hydrologic modelling in the Amazon

A key aspect of large river basins partially neglected in large‐scale hydrological models is river hydrodynamics. Large‐scale hydrologic models normally simulate river hydrodynamics using simplified models that do not represent aspects such as backwater effects and flood inundation, key factors for some of the largest rivers of the world, such as the Amazon. In a previous paper, we have described a large‐scale hydrodynamic approach resultant from an improvement of the MGB‐IPH hydrological model. It uses full Saint Venant equations, a simple storage model for flood inundation and GIS‐based algorithms to extract model parameters from digital elevation models. In the present paper, we evaluate this model in the Solimões River basin. Discharge results were validated using 18 stream gauges showing that the model is accurate. It represents the large delay and attenuation of flood waves in the Solimões basin, while simplified models, represented here by Muskingum Cunge, provide hydrographs are wrongly noisy and in advance. Validation against 35 stream gauges shows that the model is able to simulate observed water levels with accuracy, representing their amplitude of variation and timing. The model performs better in large rivers, and errors concentrate in small rivers possibly due to uncertainty in river geometry. The validation of flood extent results using remote sensing estimates also shows that the model accuracy is comparable to other flood inundation modelling studies. Results show that (i) river‐floodplain water exchange and storage, and (ii) backwater effects play an important role for the Amazon River basin hydrodynamics. Copyright © 2011 John Wiley & Sons, Ltd.     

Projection of extreme flood inundation in the Mekong River basin under 4K increasing scenario using large ensemble climate data

Projecting changes in the frequency and intensity of future precipitation and flooding is critical for the development of social infrastructure under climate change. The Mekong River is among the world's large-scale rivers severely affected by climate change. This study aims to define the duration of precipitation contributing to peak floods based on its correlation with peak discharge and inundation volume in the Lower Mekong Basin (LMB). We assessed the changes in precipitation and flood frequency using a large ensemble Database for Policy Decision-Making for Future Climate Change (d4PDF). River discharge in the Mekong River Basin (MRB) and flood inundation in the LMB were simulated by a coupled rainfall-runoff and inundation (RRI) model. Results indicated that 90-day precipitation counting backward from the day of peak flooding had the highest correlation with peak discharge (R² = .81) and inundation volume (R² = .81). The ensemble mean of present simulation of d4PDF (1951–2010) showed good agreement with observed extreme flood events in the LMB. The probability density of 90-day precipitation shifted from the present to future climate experiments with a large variation of mean (from 777 to 900 mm) and SD (from 57 to 96 mm). Different patterns of sea surface temperature significantly influence the variation of precipitation and flood inundation in the LMB in the future (2051–2110). Extreme flood events (50-year, 100-year, and 1,000-year return periods) showed increases in discharge, inundation area, and inundation volume by 25%–40%, 19%–36%, and 23%–37%, respectively.     

The integrated effects of climate and hydrologic uncertainty on future flood risk assessments

This work examines future flood risk within the context of integrated climate and hydrologic modelling uncertainty. The research questions investigated are (1) whether hydrologic uncertainties are a significant source of uncertainty relative to other sources such as climate variability and change and (2) whether a statistical characterization of uncertainty from a lumped, conceptual hydrologic model is sufficient to account for hydrologic uncertainties in the modelling process. To investigate these questions, an ensemble of climate simulations are propagated through hydrologic models and then through a reservoir simulation model to delimit the range of flood protection under a wide array of climate conditions. Uncertainty in mean climate changes and internal climate variability are framed using a risk‐based methodology and are explored using a stochastic weather generator. To account for hydrologic uncertainty, two hydrologic models are considered, a conceptual, lumped parameter model and a distributed, physically based model. In the conceptual model, parameter and residual error uncertainties are quantified and propagated through the analysis using a Bayesian modelling framework. The approach is demonstrated in a case study for the Coralville Dam on the Iowa River, where recent, intense flooding has raised questions about potential impacts of climate change on flood protection adequacy. Results indicate that the uncertainty surrounding future flood risk from hydrologic modelling and internal climate variability can be of the same order of magnitude as climate change. Furthermore, statistical uncertainty in the conceptual hydrological model can capture the primary structural differences that emerge in flood damage estimates between the two hydrologic models. Copyright © 2014 John Wiley & Sons, Ltd.     

A synergetic use of satellite imagery from SAR and optical sensors to improve coastal flood mapping in the Gulf of Mexico

This work proposes a method for detecting inundation between semi‐diurnal low and high water conditions in the northern Gulf of Mexico using high‐resolution satellite imagery. Radarsat 1, Landsat imagery and aerial photography from the Apalachicola region in Florida were used to demonstrate and validate the algorithm. A change detection approach was implemented through the analysis of red, green and blue (RGB) false colour composites image to emphasise differences in high and low tide inundation patterns. To alleviate the effect of inherent speckle in the SAR images, we also applied ancillary optical data. The flood‐prone area for the site was delineated a priori through the determination of lower and higher water contour lines with Landsat images combined with a high‐resolution digital elevation model. This masking technique improved the performance of the proposed algorithm with respect to detection techniques using the entire Radarsat scene. The resulting inundation maps agreed well with historical aerial photography as the probability of detection reached 83%. The combination of SAR data and optical images, when coupled with a high‐resolution digital elevation model, was shown to be useful for inundation mapping and have a great potential for evaluating wetting/drying algorithms of inland and coastal hydrodynamic models. Copyright © 2011 John Wiley & Sons, Ltd.     

Interactions between sediment delivery,channel change,climate change and flood risk in a temperate upland environment

This paper uses numerical simulation of flood inundation based on a coupled one‐dimensional–two‐dimensional treatment to explore the impacts upon flood extent of both long‐term climate changes, predicted to the 2050s and 2080s, and short‐term river channel changes in response to sediment delivery, for a temperate upland gravel‐bed river. Results show that 16 months of measured in‐channel sedimentation in an upland gravel‐bed river cause about half of the increase in inundation extent that was simulated to arise from climate change. Consideration of the joint impacts of climate change and sedimentation emphasized the non‐linear nature of system response, and the possibly severe and synergistic effects that come from combined direct effects of climate change and sediment delivery. Such effects are likely to be exacerbated further as a result of the impacts of climate change upon coarse sediment delivery. In generic terms, these processes are commonly overlooked in flood risk mapping exercises and are likely to be important in any river system where there are high rates of sediment delivery and long‐term transfer of sediment to floodplain storage (i.e. alluviation involving active channel aggradation and migration). Similarly, attempts to reduce channel migration through river bank stabilization are likely to exacerbate this process as without bank erosion, channel capacity cannot be maintained. Finally, many flood risk mapping studies rely upon calibration based upon combining contemporary bed surveys with historical flood outlines, and this will lead to underestimation of the magnitude and frequency of floodplain inundation in an aggrading system for a flood of a given magnitude. Copyright © 2006 John Wiley & Sons, Ltd.     

Hydraulic model calibration for extreme floods in bedrock‐confined channels: case study from northern Thailand

Palaeoflood reconstructions based on stage evidence are typically conducted in data‐poor field settings. Few opportunities exist to calibrate the hydraulic models used to estimate discharge from this evidence. Consequently, an important hydraulic model parameter, the roughness coefficient (e.g. Manning's n), is typically estimated by a range of approximate techniques, such as ‘visual estimation’ and semi‐empirical equations. These techniques contribute uncertainty to resulting discharge estimates, especially where the study reach exhibits sensitivity in the discharge–Manning's n relation. We study this uncertainty within a hydraulic model for a large flood of known discharge on the Mae Chaem River, northern Thailand. Comparison of the ‘calibrated’ Manning's n with that obtained from semi‐empirical equations indicates that these underestimate roughness. Substantial roughness elements in the extra‐channel zone, inundated during large events, contribute significant additional sources of flow resistance that are captured neither by the semi‐empirical equations, nor by existing models predicting stage–roughness variations. This bedrock channel exhibits a complex discharge–Manning's n relation, and reliable estimates of the former are dependent upon realistic assignment of the latter. Our study demonstrates that a large recent flood can provide a valuable opportunity to constrain this parameter, and this is illustrated when we model a palaeoflood event in the same reach, and subsequently examine the magnitude–return period consequences of discharge uncertainty within a flood frequency analysis, which contributes its own source of uncertainty. Copyright © 2005 John Wiley & Sons, Ltd.     

Dynamic flood topographies in the Terai region of Nepal

Flood hazard maps used to inform and build resilience in remote communities in the Terai region of southern Nepal are based on outdated and static digital elevation models (DEMs), which do not reflect dynamic river configuration or hydrology. Episodic changes in river course, sediment dynamics, and the distribution of flow down large bifurcation nodes can modify the extent of flooding in this region, but these processes are rarely considered in flood hazard assessment. Here, we develop a 2D hydrodynamic flood model of the Karnali River in the Terai region of west Nepal. A number of scenarios are tested examining different DEMs, variable bed elevations to simulate bed aggradation and incision, and updating bed elevations at a large bifurcation node to reflect field observations. By changing the age of the DEM used in the model, a 9.5% increase in inundation extent was observed for a 20-year flood discharge. Reducing horizontal DEM resolution alone resulted in a <1% change. Uniformly varying the bed elevation led to a 36% change in inundation extent. Finally, changes in bed elevation at the main bifurcation to reflect observed conditions resulted in the diversion of the majority of flow into the west branch, consistent with measured discharge ratios between the two branches, and a 32% change in inundation extent. Although the total flood inundation area was reduced (−4%), there was increased inundation along the west bank. Our results suggest that regular field measurements of bed elevation and updated DEMs following large sediment-generating events, and at topographically sensitive areas such as large river bifurcations, could help improve model inputs in future flood prediction models. This is particularly important following flood events carrying large sediment loads out of mountainous regions that could promote bed aggradation and channel switching across densely populated alluvial river systems and floodplains further downstream. © 2020 The Authors. Earth Surface Processes and Landforms published by John Wiley & Sons Ltd     

Historical discharge measurements on the Middle Mississippi River,USA: no basis for ‘changing history’

This study tests the hypothesis that historical float‐based discharge measurements on the Mississippi River systematically over‐stated actual flood flows by 10% to > 30% relative to measurements using current meters. This assertion has been repeated over the past 25 years and recently has been used to adjust historical discharges used for flood‐frequency analysis. This study tests the hypothesis above using 2150 historical discharge measurements digitized from the three principal gauging stations on the Middle Mississippi River (MMR): data that include 626 float‐based discharges and 1516 meter‐based discharges, including 122 paired measurements. Multiple comparative tests show that the hypothesis above cannot be supported; if anything, the float‐based measurements slightly underestimate flows (not over‐estimate) over a broad range of discharges up to large floods. In response to the purported data bias above (‘changing history’; Dieckmann RJ, Dyhouse GR. 1998. Changing history at St. Louis—adjusting historic flows for frequency analysis. First Federal Inter‐Agency Hydrologic Modeling Conference, April 20–22, 1998. Las Vegas, NV; 4·31–4·36), historical flood discharges on the MMR have been modified, most by 10–20% and several by > 30%. These altered discharges are now being promulgated, in particular, through the Upper Mississippi River System Flow Frequency Study (UMRSFFS). New flow frequencies, flood profiles, and new flood maps from the UMRSFFS may significantly underestimate the actual flood hazard on the MMR if the original hydrologic data have been erroneously altered on the basis of an assumption of data bias. Copyright © 2010 John Wiley & Sons, Ltd.     

Flood hazard mapping in Southern Brazil: a combination of flow frequency analysis and the HAND model

The Itajaí River basin is one of the areas most affected by flood-related disasters in Brazil. Flood hazard maps based on digital elevation models (DEM) are an important alternative in the absence of detailed hydrological data and for application in large areas. We developed a flood hazard mapping methodology by combining flow frequency analysis with the Height Above the Nearest Drainage (HAND) model – f2HAND – and applied it in three municipalities in the Itajaí River basin. The f2HAND performance was evaluated through comparison with observed 2011 flood extent maps. Model performance and sensitivity were tested for different DEM resolutions, return periods and streamflow data from stations located upstream and downstream on the main river. The flood hazard mapping with our combined approach matched 92% of the 2011 flood event. We found that the f2HAND model has low sensitivity to DEM resolution and high sensitivity to area threshold of channel initiation.