A paleo‐hydro‐geomorphological perspective on urban flood risk assessment

Comprehensive flood risk assessment requires enhanced understanding of the coevolution of the river and its floodplain occupation. Paleoflood analysis to determine flood prone areas in combination with numerical simulations to estimate flood hazard and a historical analysis of urban development to consider the evolution of exposure to floods is a possible way forward. The well‐documented 2006 extreme flood in the Biobío River system and the impacted metropolitan area of Concepción, Chile (~1 million inhabitants) was used as a complex scenario to test the reliability of the proposed method. Results showed that flood prone areas determined with hydro‐geomorphological methods are consistent with those computed with numerical models based on detailed digital elevation models. The flood generation via superficial flow pathways resulting in inundated areas could explain that rivers tend to reactivate paleochannels in extreme conditions. Urban development progressively increased the city's exposure to floods from 0 ha in 1,751 to 1,363 ha in 2006 evidencing a lack of appropriate flood risk management. The 100‐year peak discharge resulted in a high flood risk for about 5% of the total urbanized area of Concepción, and higher discharges are likely to reactivate a paleochannel that crosses the current city centre. We conclude that the proposed paleo hydro‐geomorphology, hydraulic, and urban planning multimethod approach is a necessary tool to enhance understanding of flood risk in complex scenarios to improve flood risk management.     

Advances in pan‐European flood hazard mapping

Flood hazard maps at trans‐national scale have potential for a large number of applications ranging from climate change studies, reinsurance products, aid to emergency operations for major flood crisis, among others. However, at continental scales, only few products are available, due to the difficulty of retrieving large consistent data sets. Moreover, these are produced at relatively coarse grid resolution, which limits their applications to qualitative assessments. At finer resolution, maps are often limited to country boundaries, due to limited data sharing at trans‐national level. The creation of a European flood hazard map would currently imply a collection of scattered regional maps, often lacking mutual consistency due to the variety of adopted approaches and quality of the underlying input data. In this work, we derive a pan‐European flood hazard map at 100 m resolution. The proposed approach is based on expanding a literature cascade model through a physically based approach. A combination of distributed hydrological and hydraulic models was set up for the European domain. Then, an observed meteorological data set is used to derive a long‐term streamflow simulation and subsequently coherent design flood hydrographs for a return period of 100 years along the pan‐European river network. Flood hydrographs are used to simulate areas at risk of flooding and output maps are merged into a pan‐European flood hazard map. The quality of this map is evaluated for selected areas in Germany and United Kingdom against national/regional hazard maps. Despite inherent limitations and model resolution issues, simulated maps are in good agreement with reference maps (hit rate between 59% and 78%, critical success index between 43% and 65%), suggesting strong potential for a number of applications at the European scale. Copyright © 2013 John Wiley & Sons, Ltd.     

Floodplain stratigraphy of the ice jam dominated middle Yukon River: a new approach to long‐term flood frequency

Floodplain stratigraphy is used as a new method for reconstructing ice jam flood histories of northern rivers. The method, based on reconstruction of the sedimentary record of vertically‐accreting floodplains, relies on stratigraphic logging and interpretation of floodplain sediments, which result from successive ice jam floods, and radiocarbon dating of inter‐flood organic material for chronology. In a case study along a reach of the Yukon River that straddles the Yukon–Alaska border, the method is used to develop a record of ice jam flooding for the last 2000 years. Detailed chronostratigraphic logs from three sites along the Yukon River indicates that the long‐term recurrence interval varies depending on location, but ranges from approximately once in 25 years to once in 38 years (or a probability of ca 3–4% in any given year). This is broadly similar to the 4·5% probability of recurrence calculated from archival and gauged data at Dawson City, Yukon Territory, for the period 1898–2006. Two of the three study locations, with sufficient chronology, suggest a decrease in flood frequency in the last several hundred years relative to the preceding period at each site, broadly corresponding to the Little Ice Age, suggesting climate exerts some control over long‐term ice jam flood frequency. This study demonstrates that the floodplain sedimentary record offers the potential to extend records of ice jam flooding in remote, ungauged northern rivers and provides a broader temporal context for assessing the frequency and variability of ice jam flooding. Copyright © 2008 John Wiley & Sons, Ltd.     

A comparison of one‐ and two‐dimensional approaches to modelling flood inundation over complex upland floodplains

A much understudied aspect of flood inundation is examined, i.e. upland environments with topographically complex floodplains. Although the presence of high‐resolution topographic data (e.g. lidar) has improved the quality of river flood inundation predictions, the optimum dimensionality of hydraulic models for this purpose has yet to be fully evaluated for situations of both topographic and topological (i.e. the connectivity of floodplain features) complexity. In this paper, we present the comparison of three treatments of upland flood inundation using: (a) a one‐dimensional (1D) model (HEC‐RAS v. 3·1·2) with the domain defined as series of extended cross‐sections; (b) the same 1D model, but with the floodplain defined by a series of storage cells, hydraulically connected to the main river channel and other storage cells on the floodplain according to floodplain topological characteristics; (c) a two‐dimensional (2D) diffusion wave treatment, again with explicit representation of floodplain structural features. The necessary topographic and topological data were derived using lidar and Ordnance Survey Landline data. The three models were tested on a 6 km upland reach of the River Wharfe, UK. The models were assessed by comparison with measured inundation extent. The results showed that both the extended cross‐section and the storage cell 1D modes were conceptually problematic. They also resulted in poorer model predictions, requiring incorrect parameterization of the main river to floodplain flux in order to approach anything like the level of agreement observed when the 2D diffusion wave treatment was assessed. We conclude that a coupled 1D–2D treatment is likely to provide the best modelling approach, with currently available technology, for complex floodplain configurations. Copyright © 2007 John Wiley & Sons, Ltd.     

Ice‐cover variability on shallow lakes at high latitudes: model simulations and observations

A one‐dimensional thermodynamic model for simulating lake‐ice phenology is presented and evaluated. The model can be driven with observed daily or hourly atmospheric forcing of air temperature, relative humidity, wind speed, cloud amount and snowfall. In addition to computing the energy balance components, key model output includes the temperature profile at an arbitrary number of levels within the ice/snow (or the water temperature if there is no ice) and ice thickness (clear ice and snow‐ice) on a daily basis, as well as freeze‐up and break‐up dates. The lake‐ice model is used to simulate ice‐growth processes on shallow lakes in arctic, sub‐arctic, and high‐boreal forest environments. Model output is compared with field and remote sensing observations gathered over several ice seasons. Simulated ice thickness, including snow‐ice formation, compares favourably with field measurements. Ice‐on and ice‐off dates are also well simulated when compared with field and satellite observations, with a mean absolute difference of 2 days. Model simulations and observations illustrate the key role that snow cover plays on the seasonal evolution of ice thickness and the timing of spring break‐up. It is also shown that lake morphometry, depth in particular, is a determinant of ice‐off dates for shallow lakes at high latitudes. Copyright © 2003 John Wiley & Sons, Ltd.     

The potential for agricultural land use change to reduce flood risk in a large watershed

Effects of agricultural land management practices on surface runoff are evident at local scales, but evidence for watershed‐scale impacts is limited. In this study, we used the Soil and Water Assessment Tool model to assess changes in downstream flood risks under different land uses for the large, intensely agricultural, Raccoon River watershed in Iowa. We first developed a baseline model for flood risk based on current land use and typical weather patterns and then simulated the effects of varying levels of increased perennials on the landscape under the same weather patterns. Results suggest that land use changes in the Raccoon River could reduce the likelihood of flood events, decreasing both the number of flood events and the frequency of severe floods. The duration of flood events were not substantially affected by land use change in our assessment. The greatest flood risk reduction was associated with converting all cropland to perennial vegetation, but we found that converting half of the land to perennial vegetation or extended rotations (and leaving the remaining area in cropland) could also have major effects on reducing downstream flooding potential. We discuss the potential costs of adopting the land use change in the watershed to illustrate the scale of subsidies required to induce large‐scale conversion to perennially based systems needed for flood risk reduction. Copyright © 2013 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.     

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.     

A multi‐temporal analysis of AMSR‐E data for flood and discharge monitoring during the 2008 flood in Iowa

The objective of this work is to demonstrate the potential of using passive microwave data to monitor flood and discharge conditions and to infer watershed hydraulic and hydrologic parameters. The case study is the major flood in Iowa in summer 2008. A new Polarisation Ratio Variation Index (PRVI) was developed based on a multi‐temporal analysis of 37 GHz satellite imagery from the Advanced Microwave Scanning Radiometer (AMSR‐E) to calculate and detect anomalies in soil moisture and/or inundated areas. The Robust Satellite Technique (RST) which is a change detection approach based on the analysis of historical satellite records was adopted. A rating curve has been developed to assess the relationship between PRVI values and discharge observations downstream. A time‐lag term has been introduced and adjusted to account for the changing delay between PRVI and streamflow. Moreover, the Kalman filter has been used to update the rating curve parameters in near real time. The temporal variability of the b exponent in the rating curve formula shows that it converges toward a constant value. A consistent 21‐day time lag, very close to an estimate of the time of concentration, was obtained. The agreement between observed discharge downstream and estimated discharge with and without parameters adjustment was 65 and 95%, respectively. This demonstrates the interesting role that passive microwave can play in monitoring flooding and wetness conditions and estimating key hydrologic parameters. Copyright © 2011 John Wiley & Sons, Ltd.     

Flood-hazard assessment and risk-based zoning of a tropical flood plain: case study of the Yom River,Thailand

Abstract

This study contributes to the comprehensive assessment of flood hazard and risk for the Phrae flood plain of the Yom River basin in northern Thailand. The study was carried out using a hydrologic–hydrodynamic model in conjunction with a geographic information system (GIS). The model was calibrated and verified using the observed rainfall and river flood data during flood seasons in 1994 and 2001, respectively. Flooding scenarios were evaluated in terms of flooding depth for events of 25-, 50-, 100- and 200-year return periods. An impact-based hazard estimation technique was applied to assess the degree of hazard across the flood plain. The results showed that 78% of the Phrae flood-plain area of 476 km² in the upper Yom River basin lies in the hazard zone of the 100-year return-period flood. Risk analyses were performed by incorporating flood hazard and the vulnerability of elements at risk. Based on relative magnitude of risk, flood-prone areas were divided into low-, moderate-, high- and severe-risk zones. For the 100-year return-period flood, the risk-free area was found to be 22% of the total flood plain, while areas under low, medium, high and severe risk were 33, 11, 28 and 6%, respectively. The outcomes are consistent with overall property damage recorded in the past. The study identifies risk areas for priority-based flood management, which is crucial when there is a limited budget to protect the entire risk zone simultaneously.

Citation Tingsanchali, T. & Karim, F. (2010) Flood-hazard assessment and risk-based zoning of a tropical flood plain: case study of the Yom River, Thailand. Hydrol. Sci. J. 55(2), 145–161.     

The use of historical flood information in the English Midlands to improve risk assessment

Abstract

The Easter 1998 flood was the largest flood event in the gauged record of many basins of the English Midlands. Flood frequency analysis, using such gauged records only, placed the 1998 event at a return period of over 100 years on several basins. However a review of historical (pre-gauged) flooding on some rivers gives a different perspective. Examples are given of the use of historical flood information on the River Leam, the River Wreake at Melton Mowbray, the River Sence (tributary to the River Soar) and the River Frome at Stroud. The cost of acquiring such historical flood data is trivial in comparison to gauged data, but the benefits are demonstrated as significant. In particular, historical flood data provide a better basis for risk assessment and planning on flood plains through revised estimates of flood discharge and depth.     

The effects of river restoration on catchment scale flood risk and flood hydrology

A rising exposure to flood risk is a predicted consequence of increased development in vulnerable areas and an increase in the frequency of extreme weather events due to climate change. In the face of this challenge, a continued reliance on engineered at‐a‐point flood defences is seen as both unrealistic and undesirable. The contribution of ‘soft engineering’ solutions (e.g. riparian forests, wood in rivers) to integrated, catchment scale flood risk management has been demonstrated at small scales but not larger ones. In this study we use reduced complexity hydrological modelling to analyse the effects of land use and channel changes resulting from river restoration upon flood flows at the catchment scale. Results show short sections of river‐floodplain restoration using engineered logjams, typical of many current restoration schemes, have highly variable impacts on catchment‐scale flood peak magnitude and so need to be used with caution as a flood management solution. Forested floodplains have a more general impact upon flood hydrology, with areas in the middle and upper catchment tending to show reductions in peak magnitude at the catchment outflow. The most promising restoration scenarios for flood risk management are for riparian forest restoration at the sub‐catchment scale, representing 20–40% of the total catchment area, where reductions in peak magnitude of up to 19% are observed through de‐synchronization of the timings of sub‐catchment flood waves. Sub‐catchment floodplain forest restoration over 10–15% of total catchment area can lead to reductions in peak magnitude of 6% at 25 years post‐restoration. Copyright © 2016 John Wiley & Sons, Ltd.     

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.     

Tree ring analysis of hydro‐climatic thresholds that trigger ice jams on the Mistassini River,Quebec

This study documents the spatiotemporal variations in the frequency and magnitude of ice jams in the Mistassini River and applies that information to the identification of the hydro‐climatic threshold conditions associated with major events. Ice jams cause severe upheavals in water flow, which result in flooding upstream of the ice jam front, and therefore represent a significant geohazard to riparian populations. To analyze the spatiotemporal variations in the magnitude–frequency of ice jams, the Mistassini River was first divided into six different sites representing different geomorphological contexts. A 50‐year ice jam chronology was constructed from 85 damaged trees from all of the study sites. This chronology was then coupled with hydro‐climatic variables to construct classification trees, which helped identify the conditions and hydro‐climatic thresholds favourable to the triggering of ice jams in a predictive model. The results indicate complex interactions between the characteristics of flow, ice cover and river morphology that affect the frequency and magnitude of ice jam events on the Mistassini River. These factors affect the frequency and magnitude of ice jam events. The triggering of extreme events seems particularly influenced by exceptional ice conditions and sites with high sinuosity and islands. Copyright © 2015 John Wiley & Sons, Ltd.     

Defining the floodplain in hydrologically‐variable settings: implications for flood risk management

Flood risk management is an essential responsibility of state governments and local councils to ensure the protection of people residing on floodplains. Globally, floodplains are under increasing pressure from growing populations. Typically, the engineering‐type solutions that are used to predict local flood magnitude and frequency based on limited gauging data are inadequate, especially in settings which experience high hydrological variability. This study highlights the importance of incorporating geomorphological understanding into flood risk management in southeast Queensland (SEQ), an area badly affected by extreme flood events in 2011 and 2013. The major aim of this study is to outline the hydrological and sedimentological characteristics of various ‘inundation surfaces’ that are typical of catchments in the sub‐tropics. It identifies four major inundation surfaces; within‐channel bench [Q ~ 2.33 yr average recurrence interval (ARI)]; genetic floodplain (Q = 20 yr ARI); hydraulic floodplain (20 yr < Q ≤ 200 yr ARI) and terrace (Q > 1000 yr ARI). These surfaces are considered typical of inundation areas within, and adjacent to, the large macrochannels common to this region and others of similar hydrological variability. An additional area within genetic floodplains was identified where flood surfaces coalesce and produce an abrupt reduction in channel capacity. This is referred to here as a Spill‐out Zone (SOZ). The associated vulnerability and risk of these surfaces is reviewed and recommendations made based on incorporating this geomorphological understanding into flood risk assessments. These recommendations recognize the importance to manage for risks associated with flow inundation and sediment erosion, delivery and deposition. The increasing availability of high resolution topographic data opens up the possibility of more rapid and spatially extensive assessments of key geomorphic processes which can readily be used to predict flood risk. Copyright © 2016 John Wiley & Sons, Ltd.     

The data‐driven approach as an operational real‐time flood forecasting model

Accurate water level forecasts are essential for flood warning. This study adopts a data‐driven approach based on the adaptive network–based fuzzy inference system (ANFIS) to forecast the daily water levels of the Lower Mekong River at Pakse, Lao People's Democratic Republic. ANFIS is a hybrid system combining fuzzy inference system and artificial neural networks. Five ANFIS models were developed to provide water level forecasts from 1 to 5 days ahead, respectively. The results show that although ANFIS forecasts of water levels up to three lead days satisfied the benchmark, four‐ and five‐lead‐day forecasts were only slightly better in performance compared with the currently adopted operational model. This limitation is imposed by the auto‐ and cross‐correlations of the water level time series. Output updating procedures based on the autoregressive (AR) and recursive AR (RAR) models were used to enhance ANFIS model outputs. The RAR model performed better than the AR model. In addition, a partial recursive procedure that reduced the number of recursive steps when applying the AR or the RAR model for multi‐step‐ahead error prediction was superior to the fully recursive procedure. The RAR‐based partial recursive updating procedure significantly improved three‐, four‐ and five‐lead‐day forecasts. Our study further shows that for long lead times, ANFIS model errors are dominated by lag time errors. Although the ANFIS model with the RAR‐based partial recursive updating procedure provided the best results, this method was able to reduce the lag time errors significantly for the falling limbs only. Improvements for the rising limbs were modest. Copyright © 2011 John Wiley & Sons, Ltd.     

Theoretical link between rainfall and flood magnitude

The rainfall–run‐off convolution integral is analytically solved for several models for the elementary hydrograph. These solutions can be combined with available rainfall frequency analyses to predict flood flows along streams for different recurrence intervals, using no free parameters for gauged streams and one estimable parameter for ungauged streams. Extreme discharge magnitudes at gauged sites can be typically estimated within a factor of two of actual records, using no historical data on extreme flows. The flow predictions reproduce several important characteristics of the flood phenomenon, such as the slope of the regression line between observed extreme flows and basin area on the conventional logQ versus logA plot. Importantly, for the models and data sets investigated, the storm duration of greatest significance to flooding was found to approximate the intrinsic transport timescale of the particular watershed, which increases with basin size. Thus, storms that deliver extraordinary amounts of rainfall over a particular time interval will most greatly activate basins whose time constants approximately equal that interval. This theoretical finding is supported by examination of the regional hydrological response to the massive storms of September 14, 2008, and April 28–30, 2017, which caused extraordinary record flooding of basins of about 5–100 km² and 500–4,000 km², respectively, but produced few records in basins that were larger or smaller than those ranges.     

Interactions between subgrid‐scale resolution,feature representation and grid‐scale resolution in flood inundation modelling

Numerical modelling of flood inundation over large and complex floodplains often requires mesh resolutions coarser than the structural features (e.g. buildings) that are known to influence the inundation process. Recent research has shown that this mismatch is not well represented by conventional roughness treatments, but that finer‐scale features can be represented through porosity‐based subgrid‐scale treatments. This paper develops this work by testing the interactions between feature representation, subgrid‐scale resolution and mesh resolution. It uses as the basis for this testing a 2D diffusion‐based flood inundation model which is applied to a 2004 flood event in a topologically complex upland floodplain in northern England. This study formulated simulations with different grid mesh resolution and subgrid mesh ratio. The sensitivity of the model to mesh resolution and roughness specification was investigated. Model validation and verification suggest that the subgrid treatment with higher subgrid mesh ratio can give much improved predictions of flood propagation, in particular, in terms of the predicted water depth. This study also highlighted the limitation of using at‐a‐point in time inundation extent for validation of flood models of this type. Copyright © 2010 John Wiley & Sons, Ltd.     

Distributed rainfall‐runoff modelling for flood frequency estimation and flood forecasting

Nowadays, in the scientific literature many rainfall‐runoff (RR) models are available ranging from simpler ones, with a limited number of parameters, to highly complex ones, with many parameters. Therefore, the selection of the best structure and parameterisation for a model is not straightforward as it is dependent on a number of factors: climatic conditions, catchment characteristics, temporal and spatial resolution, model objectives, etc. In this study, the structure of a continuous semi‐distributed RR model, named MISDc (‘Modello Idrologico Semi‐Distribuito in continuo’) developed for flood simulation in the Upper Tiber River (central Italy) is presented. Most notably, the methodology employed to detect the more relevant processes involved in the modelling of high floods, and hence, to build the model structure and its parameters, is developed. For this purpose, an intense activity of monitoring soil moisture and runoff in experimental catchments was carried out allowing to derive a parsimonious and reliable continuous RR model operating at an hourly (or smaller) time scale. Specifically, in order to determine the catchment hydrological response, the important role of the antecedent wetness conditions is emphasized. The application of MISDc both for design flood estimation and for flood forecasting is reported here demonstrating its reliability and also its computational efficiency, another important factor in hydrological practice. As far as the flood forecasting applications are concerned, only the accuracy of the model in reproducing discharge hydrographs by assuming rainfall correctly known throughout the event is investigated indepth. In particular, the MISDc has been implemented in the framework of Civil Protection activities for the Upper Tiber River basin. Copyright © 2011 John Wiley & Sons, Ltd.