Efficient incorporation of channel cross-section geometry uncertainty into regional and global scale flood inundation models

This paper investigates the challenge of representing structural differences in river channel cross-section geometry for regional to global scale river hydraulic models and the effect this can have on simulations of wave dynamics. Classically, channel geometry is defined using data, yet at larger scales the necessary information and model structures do not exist to take this approach. We therefore propose a fundamentally different approach where the structural uncertainty in channel geometry is represented using a simple parameterization, which could then be estimated through calibration or data assimilation. This paper first outlines the development of a computationally efficient numerical scheme to represent generalised channel shapes using a single parameter, which is then validated using a simple straight channel test case and shown to predict wetted perimeter to within 2% for the channels tested. An application to the River Severn, UK is also presented, along with an analysis of model sensitivity to channel shape, depth and friction. The channel shape parameter was shown to improve model simulations of river level, particularly for more physically plausible channel roughness and depth parameter ranges. Calibrating channel Manning’s coefficient in a rectangular channel provided similar water level simulation accuracy in terms of Nash-Sutcliffe efficiency to a model where friction and shape or depth were calibrated. However, the calibrated Manning coefficient in the rectangular channel model was ~2/3 greater than the likely physically realistic value for this reach and this erroneously slowed wave propagation times through the reach by several hours. Therefore, for large scale models applied in data sparse areas, calibrating channel depth and/or shape may be preferable to assuming a rectangular geometry and calibrating friction alone.

Assessing the reliability of probabilistic flood inundation model predictions

An ability to quantify the reliability of probabilistic flood inundation predictions is a requirement not only for guiding model development but also for their successful application. Probabilistic flood inundation predictions are usually produced by choosing a method of weighting the model parameter space, but previous study suggests that this choice leads to clear differences in inundation probabilities. This study aims to address the evaluation of the reliability of these probabilistic predictions. However, a lack of an adequate number of observations of flood inundation for a catchment limits the application of conventional methods of evaluating predictive reliability. Consequently, attempts have been made to assess the reliability of probabilistic predictions using multiple observations from a single flood event. Here, a LISFLOOD-FP hydraulic model of an extreme (>1 in 1000 years) flood event in Cockermouth, UK, is constructed and calibrated using multiple performance measures from both peak flood wrack mark data and aerial photography captured post-peak. These measures are used in weighting the parameter space to produce multiple probabilistic predictions for the event. Two methods of assessing the reliability of these probabilistic predictions using limited observations are utilized; an existing method assessing the binary pattern of flooding, and a method developed in this paper to assess predictions of water surface elevation. This study finds that the water surface elevation method has both a better diagnostic and discriminatory ability, but this result is likely to be sensitive to the unknown uncertainties in the upstream boundary condition

Hurricane Surge Inundation and Critical Resources in Maine

http://digitalcommons.colby.edu/atlasofmaine2009/1010/thumbnail.jpg

Bird species of black water inundation forests in the Jau National Park (Amazonas state, Brazil): their contribution to regional species richness

We compared the relative contribution of blackwater inundation forest (igapo) and unflooded (terra firme) forest for regional bird species diversity in the lower Rio Negro region. For analyses of habitat preference we used mist-net samples and an unpublished bird species check-list. The igapo forest had lower bird species diversity than the terra firme forest. However, some 14% of the forest bird species in the region are restricted to igapo forest. Species composition was found to be distinct between the understories of the two forest types. Common forest bird guilds in the Neotropics such as ant-following birds avoid igapo forest. The differential habitat selection among birds in the inundated and unflooded forest is likely to result from vegetation structure and biological interactions such as aggressive behaviour. Since the inundated forest has a typical biota, conservation efforts needs to be directed to protect these habitats. Unfortunately, inundation forests are threatened by several human actions, especially dam construction. The extent of protected areas in the Brazilian Amazon is insufficient for the adequate protection of the inundated habitats, because it includes only 3% of the total area.

The igapó of the Negro River in central Amazonia: Linking late-successional inundation forest with fluvial geomorphology

Despite important progress on Amazonian floodplain research, the flooded forest of the Negro River igapó has been little investigated. In particular, no study has previously focused the linkage between fluvial geomorphology and the floristic variation across the course of the river. In this paper we describe and interpret relations between igapó forest, fluvial geomorphology and the spatial evolution of the igapó forest through the Holocene. Therefore, we investigate the effect of geomorphological units of the floodplain and channel patterns on tree diversity, composition and structural parameters of the late-successional igapó forest. Our results show that sites sharing almost identical flooding regime, exhibit variable tree assemblages, species richness and structural parameters such as basal area, tree density and tree heights, indicating a trend in which the geomorphologic styles seem to partially control the organization of igapó's tree communities. This can be also explained by the high variability of well-developed geomorphologic units in short distances and concentrated in small areas. In this dynamic the inputs from the species pool of tributary rivers play a crucial role, but also the depositional and erosional processes associated with the evolution of the floodplain during the Holocene may control floristic and structural components of the igapó forests. These results suggest that a comprehensive approach integrating floristic and geomorphologic methods is needed to understand the distribution of the complex vegetation patterns in complex floodplains such as the igapó of the Negro River. This combination of approaches may introduce a better comprehension of the temporal and spatial evolutionary analysis and a logic rationale to understand the vegetation distribution and variability in function of major landforms, soil distributions and hydrology. Thus, by integrating the past into macroecological analyses will sharpen our understanding of the underlying forces for contemporary floristic patterns along the inundation forests of the Negro River. © 2013 Elsevier Ltd.

Combining ALOS/PALSAR derived vegetation structure and inundation patterns to characterize major vegetation types in the Mamiraua Sustainable Development Reserve, Central Amazon floodplain, Brazil

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Development of parallelizable flood inundation models for large scale analysis

Flood disasters are a major cause of fatalities and economic losses, and several studies indicate that global flood risk is currently increasing. In order to reduce and mitigate the impact of river flood disasters, the current trend is to integrate existing structural defences with non structural measures. This calls for a wider application of advanced hydraulic models for flood hazard and risk mapping, engineering design, and flood forecasting systems. Within this framework, two different hydraulic models for large scale analysis of flood events have been developed. The two models, named CA2D and IFD-GGA, adopt an integrated approach based on the diffusive shallow water equations and a simplified finite volume scheme. The models are also designed for massive code parallelization, which has a key importance in reducing run times in large scale and high-detail applications. The two models were first applied to several numerical cases, to test the reliability and accuracy of different model versions. Then, the most effective versions were applied to different real flood events and flood scenarios. The IFD-GGA model showed serious problems that prevented further applications. On the contrary, the CA2D model proved to be fast and robust, and able to reproduce 1D and 2D flow processes in terms of water depth and velocity. In most applications the accuracy of model results was good and adequate to large scale analysis. Where complex flow processes occurred local errors were observed, due to the model approximations. However, they did not compromise the correct representation of overall flow processes. In conclusion, the CA model can be a valuable tool for the simulation of a wide range of flood event types, including lowland and flash flood events.

Probability inundation map for a scenario combining storm surge and sea-level rise

Coastal managers require reliable spatial data on the extent and timing of potential coastal inundation, particularly in a changing climate. Most sea level rise (SLR) vulnerability assessments are undertaken using the easily implemented bathtub approach, where areas adjacent to the sea and below a given elevation are mapped using a deterministic line dividing potentially inundated from dry areas. This method only requires elevation data usually in the form of a digital elevation model (DEM). However, inherent errors in the DEM and spatial analysis of the bathtub model propagate into the inundation mapping. The aim of this study was to assess the impacts of spatially variable and spatially correlated elevation errors in high-spatial resolution DEMs for mapping coastal inundation. Elevation errors were best modelled using regression-kriging. This geostatistical model takes the spatial correlation in elevation errors into account, which has a significant impact on analyses that include spatial interactions, such as inundation modelling. The spatial variability of elevation errors was partially explained by land cover and terrain variables. Elevation errors were simulated using sequential Gaussian simulation, a Monte Carlo probabilistic approach. 1,000 error simulations were added to the original DEM and reclassified using a hydrologically correct bathtub method. The probability of inundation to a scenario combining a 1 in 100 year storm event over a 1 m SLR was calculated by counting the proportion of times from the 1,000 simulations that a location was inundated. This probabilistic approach can be used in a risk-aversive decision making process by planning for scenarios with different probabilities of occurrence. For example, results showed that when considering a 1% probability exceedance, the inundated area was approximately 11% larger than mapped using the deterministic bathtub approach. The probabilistic approach provides visually intuitive maps that convey uncertainties inherent to spatial data and analysis.

The inundation, or, Pardon and peace : a Christmas story /

Cohn, A.M. Cruikshank,

A short account of the late inundation, in the neighborhood of Boston ; occasioned by a violent gale of wind, an extraordinary high tide, and breaking of the sea banks: with a statement of the loss and damage occasioned thereby ...

Mode of access: Internet.

Extent and frequency of inundation of flood plain in vicinity of Bound Brook in Somerset and Middlesex Counties, New Jersey,

Open-file report [no. 3]

Extent and frequency of inundation of Millstone River flood plain in Somerset County, New Jersey,

Open-file report [no. 4]

Biogeochemical Contributions of Tree Islands to Everglades Wetland Landscape Nitrogen Cycling During Seasonal Inundation

In the Florida Everglades, tree islands are conspicuous heterogeneous elements in the herbaceous wetland landscape. We characterized the biogeochemical role of a seasonally flooded tree island during wet season inundation, specifically examining hydrologically mediated flows of nitrogen (N) and N retention by the tree island. We estimated ecosystem N standing stocks and fluxes, soil and litter N transformation rates, and hydrologic fluxes of N to quantify the net ecosystem N mass flux. Results showed that hydrologic sources of N were dominated by surface water loads of nitrate (NO3) and ammonium (NH4). Nitrate immobilization by soils and surficial leaf litter was an important sink for surface water dissolved inorganic N (DIN). We estimated that the net annual DIN retention by a seasonally flooded tree island was 20.5 ± 5.0 g m−2 during wet season inundation. Based on the estimated tree island surface water DIN loading rate, a seasonally flooded tree island retained 76% of imported DIN. As such, seasonally flooded tree islands have the potential to retain 55% of DIN entering the marsh landscape via upstream canal overland flow in the wet season. By increasing reactive surface area and DOC availability, we suggest that tree islands promote convergence of elements that enhance DIN retention. Tree islands of this region are thus important components of landscape-scale restoration efforts that seek to reduce sources of anthropogenic DIN to downstream estuaries.