4,244 research outputs found

    Flood risk modeling of urbanized estuarine areas under uncertainty: a case study for Whitesands, UK

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    Aims: The impacts of catastrophic flooding have steadily increased over the last few decades. This work investigated the effectiveness of flood modeling, with low dimensionality models along with a wealth of soft (qualitative) and hard (quantitative) data. In the presence of very low resolution or qualitative data this approach has the potential of assessing a plethora of different scenarios with little computational cost, without compromise in prediction accuracy. Study Design: A flood risk modeling approach was implemented for the urbanized and flood prone region of Whitesands, at the Scottish town of Dumfries. This involved collection of a wide range of data: a) topographical maps and data from field visits were used to complement existing cross-sectional data, for building the river’s geometry, b) appropriate hydrological data were employed to run the simulations, while historical information about the extent, depth and impacts of flooding were utilized for calibrating the hydraulic model, and c) a wealth of photographic data obtained during the most recent December 2013 flood, were used for the model’s validation. Place and Duration of Study: Desk study: School of Engineering, University of Glasgow; September 2013 to May 2014. Field study: Dumfries; November 2013 to January 2014. Methodology: The HEC-RAS 1D model has been used to represent the hydraulics of the system. Flood maps were produced considering the local topography and predicted inundation depths. Flood cost and risk takes further into account the type and value of inundated property as well as the extent and depth of flooding. Results: The model predictions (inundation depths and flood extents presented in the flood maps) were in fairly good agreement with the observed results along the studied section of the river. Conclusion: This study presented a flood modeling approach that utilized an appropriate range of accessible data in the absence of detailed information. As the level of performance was comparable to other inundation models the results can be used for identification of flood mitigation measures and to inform best management strategies for waterways and floodplains

    Sea Level Rise Adaptation Plan for Transportation Infrastructure and Other Critical Resources in the Eureka Slough Hydrographic Area, Humboldt Bay

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    This plan (study) presents a framework for developing sea level rise adaptation strategies within the highly vulnerable Eureka Slough hydrographic area of Humboldt Bay. The purpose of the study was to work with public agencies, landowners, scientists, and stakeholders to better understand the specific flood risks to the transportation infrastructure and other critical resources within the study area and to identify viable adaptation measures in the near-term planning horizon (now through mid-century) for the most at-risk locations. A primary focus of the study was to develop a scenario-based planning approach for understanding the range of possible impacts and consequences resulting from tidal and fluvial flood hazards under current conditions and with future sea level rise. This approach included detailed hydraulic analysis and an evaluation of the anticipated response of the coastal landscape to various flooding events. The plan is intended to help advance the collective understanding of flood risks and improve the readiness for implementing effective sea level rise adaptation projects. This plan is a technical resource for ongoing planning and adaptation efforts but is not a decision document and does not represent a commitment to implement the project concepts discussed in the plan

    NCR-days 2008 : 10 years NCR: November 20-21

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    De verschillende subthema’s van de NCR-dagen 2008, (i) Stroomgebied en Overstromingsrisico management (ii) Hydrologie en (iii) Geomorfodynamica en Morfologie, dekken een groot gedeelte van het hedendaagse onderzoek dat in Nederland op rivierkundig gebied wordt uitgevoerd

    The impact of flooding on aquatic ecosystem services

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    Flooding is a major disturbance that impacts aquatic ecosystems and the ecosystem services that they provide. Predicted increases in global flood risk due to land use change and water cycle intensification will likely only increase the frequency and severity of these impacts. Extreme flooding events can cause loss of life and significant destruction to property and infrastructure, effects that are easily recognized and frequently reported in the media. However, flooding also has many other effects on people through freshwater aquatic ecosystem services, which often go unrecognized because they are less evident and can be difficult to evaluate. Here, we identify the effects that small magnitude frequently occurring floods (\u3c 10-year recurrence interval) and extreme floods (\u3e 100-year recurrence interval) have on ten aquatic ecosystem services through a systematic literature review. We focused on ecosystem services considered by the Millennium Ecosystem Assessment including: (1) supporting services (primary production, soil formation), (2) regulating services (water regulation, water quality, disease regulation, climate regulation), (3) provisioning services (drinking water, food supply), and (4) cultural services (aesthetic value, recreation and tourism). The literature search resulted in 117 studies and each of the ten ecosystem services was represented by an average of 12 ± 4 studies. Extreme floods resulted in losses in almost every ecosystem service considered in this study. However, small floods had neutral or positive effects on half of the ecosystem services we considered. For example, small floods led to increases in primary production, water regulation, and recreation and tourism. Decision-making that preserves small floods while reducing the impacts of extreme floods can increase ecosystem service provision and minimize losses

    Inundation Risk Index as an Urban Planning Supportive Tool

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    Urban densification and severe housing deficit of the low and middle-income population have been worsening as the urbanization process grew. It is not uncommon that lower income population finds some shelter irregularly occupying riverine areas. Today, flood risk processes associated with river dynamics generate significant expenses and concerns for public management. In view of this, the main objective of this work is to develop a flood risk supporting tool, which deals with some of the current urban planning drawbacks, being simple and accessible even to cities with little technical and investment capacities. This tool results from a multi-criteria analysis, and it is represented by a quantitative index, called the Inundation Risk Index, varying from 0 to 100. This new index is capable of combining factors related to both the natural characteristics of the watershed, which respond to the physical susceptibility to flooding, simulating the hazard, and to socioeconomic characteristics of the population and of the region affected, representing the vulnerability. Once normalized, each of the factors that compose the index is operated, in a relatively simple formulation, composed of weighted sums and weighted products. The Inundation Risk Index was applied to a case study in the Bacanga river basin, in the municipality of SĂŁo LuĂ­s-MaranhĂŁo State/Brazil. In this work, was used a hydrodynamic model to validate the hazard component of the index. The results obtained by the mathematical modeling are consistent with the situation measured by Inundation Risk Index, which are also consistent with real practical observations and historical reports

    Modeling riparian vegetation responses to flow alteration by dams and and climate change

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    2013 Fall.Includes bibliographical references.As the interface between freshwater and terrestrial ecosystems, riparian vegetation is a critical influence on biodiversity maintenance and ecosystem service production along river corridors. Understanding how altered environmental drivers will affect this vegetation is therefore central to sound watershed management. A river's flow regime exerts a primary control on the type and abundance of riparian vegetation, as differing adaptations to changing discharge levels mediate plant recruitment and persistence. Models of the relationships between flow and vegetation, generalized across species in terms of flow response traits such as flood tolerance, provide a means to explore the consequences of hydrologic alteration resulting from dams and climate change. I addressed these issues through development of a stage-structured model of woody riparian vegetation driven by variation in annual high flows. Simulation experiments offered insight into the potential trajectories of competing vegetation trait types relative to scenarios of dam construction, re-operation and removal. Modifying the size and frequency of the floods responsible for both disturbance mortality and establishment opportunities altered the relative abundance of pioneer and upland cover. Yet, qualitative differences in simulated outcomes resulted from alternative assumptions regarding seed limitation and floodplain stabilization, illustrating the need to carefully consider how these factors may shape estimated and actual vegetation responses to river regulation. In addition, I linked this simulation approach with an integrated watershed-modeling framework to assess the relative risk of invasion by the introduced plant Tamarix under multiple climate change scenarios. Though warming may increase the potential for Tamarix range expansion by weakening thermal constraints, the results of this work supported the expectation that hydrogeomorphic variation will control how this potential is realized. With simulated invasion risk strongly dependent on shifts in both the magnitude and timing of high flows, model outcomes underscored the importance of accounting for multiple, interacting flow regime attributes when evaluating the spread of introduced species in river networks. This research suggested the utility of simplified but process-based simulations of riparian flow-ecology relationships, demonstrating that such models can establish a first approximation of the potential consequences of management decisions and can highlight key questions for additional research, particularly where data are scarce and uncertainty is high

    Impacts of Landscape Change on Water Resources

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    Changes in land use and land cover can have many drivers, including population growth, urbanization, agriculture, demand for food, evolution of socio-economic structure, policy regulations, and climate variability. The impacts of these changes on water resources range from changes in water availability (due to changes in losses of water to evapotranspiration and recharge) to degradation of water quality (increased erosion, salinity, chemical loadings, and pathogens). The impacts are manifested through complex hydro-bio-geo-climate characteristics, which underscore the need for integrated scientific approaches to understand the impacts of landscape change on water resources. Several techniques, such as field studies, long-term monitoring, remote sensing technologies, and advanced modeling studies, have contributed to better understanding the modes and mechanisms by which landscape changes impact water resources. Such research studies can help unlock the complex interconnected influences of landscape on water resources in terms of quantity and quality at multiple spatial and temporal scales. In this Special Issue, we published a set of eight peer-reviewed articles elaborating on some of the specific topics of landscape changes and associated impacts on water resources

    Smart Classifiers and Bayesian Inference for Evaluating River Sensitivity to Natural and Human Disturbances: A Data Science Approach

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    Excessive rates of channel adjustment and riverine sediment export represent societal challenges; impacts include: degraded water quality and ecological integrity, erosion hazards to infrastructure, and compromised public safety. The nonlinear nature of sediment erosion and deposition within a watershed and the variable patterns in riverine sediment export over a defined timeframe of interest are governed by many interrelated factors, including geology, climate and hydrology, vegetation, and land use. Human disturbances to the landscape and river networks have further altered these patterns of water and sediment routing. An enhanced understanding of river sediment sources and dynamics is important for stakeholders, and will become more critical under a nonstationary climate, as sediment yields are expected to increase in regions of the world that will experience increased frequency, persistence, and intensity of storm events. Practical tools are needed to predict sediment erosion, transport and deposition and to characterize sediment sources within a reasonable measure of uncertainty. Water resource scientists and engineers use multidimensional data sets of varying types and quality to answer management-related questions, and the temporal and spatial resolution of these data are growing exponentially with the advent of automated samplers and in situ sensors (i.e., “big data”). Data-driven statistics and classifiers have great utility for representing system complexity and can often be more readily implemented in an adaptive management context than process-based models. Parametric statistics are often of limited efficacy when applied to data of varying quality, mixed types (continuous, ordinal, nominal), censored or sparse data, or when model residuals do not conform to Gaussian distributions. Data-driven machine-learning algorithms and Bayesian statistics have advantages over Frequentist approaches for data reduction and visualization; they allow for non-normal distribution of residuals and greater robustness to outliers. This research applied machine-learning classifiers and Bayesian statistical techniques to multidimensional data sets to characterize sediment source and flux at basin, catchment, and reach scales. These data-driven tools enabled better understanding of: (1) basin-scale spatial variability in concentration-discharge patterns of instream suspended sediment and nutrients; (2) catchment-scale sourcing of suspended sediments; and (3) reach-scale sediment process domains. The developed tools have broad management application and provide insights into landscape drivers of channel dynamics and riverine solute and sediment export

    Integrated flood vulnerability assessment of villages in the Waimanu River Catchment in the South Pacific: the case of Viti Levu, Fiji

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    This paper uses a holistic approach within a catchment scale, through the application of both climatic and non-climatic parameters, to analyze the impacts of river floods on the human security needs of rural riverine communities in the Waimanu Catchment situated in Nausori, Fiji. Consideration of both climatic and non-climatic factors is required since non-climatic factors could be controlled to build resilience against floods. The indicator-based flood vulnerability index methodology is applicable worldwide, but the indicators used in this study were specifically related to the Pacific Island context. In the context of fluvial flood vulnerability, effects of land management and climate change are not mutually exclusive of each other. Consequently, vulnerability assessments should consider the connection between people’s actions and ecosystems for the entire catchment area since upstream land use practices influence flood vulnerabilities downstream. In our research, a community-based flood vulnerability index system in conjunction with rainfall variability and land use assessments was used to quantitatively and qualitatively analyze the flood vulnerability, and it was found that increased rainfall, poor agricultural practices, gravel extraction, and improper waste management predominantly increased the exposure and sensitivity of midstream and downstream communities to river floods by modifying river morphology. Midstream communities in the Waimanu Catchment were most vulnerable to river floods due to their very low adaptive capacity in terms of poor ecosystem health and lack of natural resources to cope with the subsequent impacts of floods, being most sensitive to changes in land use and land cover
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