1,251 research outputs found

    Flood hazard hydrology: interdisciplinary geospatial preparedness and policy

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    Thesis (Ph.D.) University of Alaska Fairbanks, 2017Floods rank as the deadliest and most frequently occurring natural hazard worldwide, and in 2013 floods in the United States ranked second only to wind storms in accounting for loss of life and damage to property. While flood disasters remain difficult to accurately predict, more precise forecasts and better understanding of the frequency, magnitude and timing of floods can help reduce the loss of life and costs associated with the impact of flood events. There is a common perception that 1) local-to-national-level decision makers do not have accurate, reliable and actionable data and knowledge they need in order to make informed flood-related decisions, and 2) because of science--policy disconnects, critical flood and scientific analyses and insights are failing to influence policymakers in national water resource and flood-related decisions that have significant local impact. This dissertation explores these perceived information gaps and disconnects, and seeks to answer the question of whether flood data can be accurately generated, transformed into useful actionable knowledge for local flood event decision makers, and then effectively communicated to influence policy. Utilizing an interdisciplinary mixed-methods research design approach, this thesis develops a methodological framework and interpretative lens for each of three distinct stages of flood-related information interaction: 1) data generation—using machine learning to estimate streamflow flood data for forecasting and response; 2) knowledge development and sharing—creating a geoanalytic visualization decision support system for flood events; and 3) knowledge actualization—using heuristic toolsets for translating scientific knowledge into policy action. Each stage is elaborated on in three distinct research papers, incorporated as chapters in this dissertation, that focus on developing practical data and methodologies that are useful to scientists, local flood event decision makers, and policymakers. Data and analytical results of this research indicate that, if certain conditions are met, it is possible to provide local decision makers and policy makers with the useful actionable knowledge they need to make timely and informed decisions

    Increasing Resiliency to Natural Hazards—A Strategic Plan for the Multi-Hazards Demonstration Project in Southern California

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    The U.S. Geological Survey (USGS) is initiating a new project designed to improve resiliency to natural hazards in southern California through the application of science to community decision making and emergency response. The Multi-Hazards Demonstration Project will assist the region’s communities to reduce their risk from natural hazards by directing new and existing research towards the community’s needs, improving monitoring technology, producing innovative products, and improving dissemination of the results. The natural hazards to be investigated in this project include coastal erosion, earthquakes, floods, landslides, tsunamis, and wildfires. Americans are more at risk from natural hazards now than at any other time in our Nation’s history. Southern California, in particular, has one of the Nation’s highest potentials for extreme catastrophic losses due to natural hazards, with estimates of expected losses exceeding $3 billion per year. These losses can only be reduced through the decisions of the southern California community itself. To be effective, these decisions must be guided by the best information about hazards, risk, and the cost-effectiveness of mitigation technologies. The USGS will work with collaborators to set the direction of the research and to create multi-hazard risk frameworks where communities can apply the results of scientific research to their decision-making processes. Partners include state, county, city, and public-lands government agencies, public and private utilities, companies with a significant impact and presence in southern California, academic researchers, the Federal Emergency Management Agency (FEMA), National Oceanic and Atmospheric Administration (NOAA), and local emergency response agencies. Prior to the writing of this strategic plan document, three strategic planning workshops were held in February and March 2006 at the USGS office in Pasadena to explore potential relationships. The goal of these planning sessions was to determine the external organizations’ needs for mitigation efforts before potential natural hazard events, and response efforts during and after the event. On the basis of input from workshop participants, four priority areas were identified for future research to address. They are (1) helping decision makers design planning scenarios, (2) improving upon the mapping of multiple hazards in urban areas, (3) providing real-time information from monitoring networks, and (4) integrating information in a risk and decision-making analysis. Towards this end, short-term and out-year goals have been outlined with the priorities in mind. First-year goals are (1) to engage the user community to establish the structures and processes for communications and interactions, (2) to develop a program to create scenarios of anticipated disasters, beginning in the first year with a scenario of a southern San Andreas earthquake that triggers secondary hazards, (3) to compile existing datasets of geospatial data, and (4) to target research efforts to support more complete and robust products in future years. Both the first-year and out-year goals have been formulated around a working-group structure that builds on existing research strengths within the USGS. The project is intended to demonstrate how developments in methodology and products can lead to improvement in our management of natural hazards in an urban environment for application across the Nation

    ICT Applications in Disaster Resilience in a Smart City in Colombo Area of Sri Lanka

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    Public policy on Smart City, in terms of disaster resilience, is a developing concept in Sri Lanka. To manage disasters in Sri Lanka, several disaster resilience plans have been implemented in collaboration with responsible government bodies. With the purpose of flood mitigation in the Metro Colombo area, a disaster management plan, called “Metro Colombo Urban Development Project” (MCUDP) was initiated in 2012. This plan consists of a sub-project called Real-Time Control System which embeds ICT. The main purpose of this paper is to discuss how the government utilizes advanced ICT applications in disaster resilience in the Colombo area with reference to the Real-Time Control System (RTC). With the use of both secondary data and primary data, the study examines the effectiveness of ICT application in the disaster resilience plan. The data collection was conducted during August 2019 and November 2019. Descriptive methods were used to analyze the data. The Real-Time Control system in the Colombo area has not succeeded as intended due to improper utilization of ICT in disaster resilience. Other drawbacks are; the same data is processed by various authorities, lack of free data sharing policies and lack of free data dissemination. To make a Colombo area a Smart City, a proper disaster resilience system needs to be initiated. For that, all planned activities should be implemented without any delay and the Municipalities should be the central coordination point. Also, a proper early warning system, a free data sharing policy with a proper monitoring system must be established, all parties should also collaborate with government agencies, and continuous training must be provided to the relevant officials.Keywords: Smart City, Disaster Resilience, Real-Time Control System, Sri Lanka

    SATELLITE REMOTE SENSING AND HYDROLOGIC MODELING FOR FLOOD MONITORING IN DATA POOR ENVIRONMENTS

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    Study of hydroclimatology at a range of temporal scales is important in understanding and ultimately mitigating the potential severe impacts of hydrological extreme events such as floods and droughts. Using daily in-situ data combined with the recently available satellite remote sensing data, the hydroclimatology of Nzoia basin, one of the contributing sub-catchments of Lake Victoria in the East African highlands is analyzed. The basin, with a semi-arid climate, has no sustained base flow contribution to Lake Victoria. The short spell of high discharge showed that rain is the primary cause of floods in the basin. There is only a marginal increase in annual mean discharge over the last 21 years. The 2-, 5- and 10- year peak discharges, for the entire study period showed that more years since the mid 1990s have had high peak discharges despite having relatively less annual rain.The study also presents the hydrologic model calibration and validation results over the Nzoia basin. The spatiotemporal variability of the water cycle components were quantified using a hydrologic model, with in-situ and multi-satellite remote sensing datasets. The model is calibrated using daily observed discharge data for the period between 1985 and 1999, for which model performance is estimated with a Nash Sutcliffe Efficiency (NSCE) of 0.87 and 0.23% bias. The model validation showed an error metrics with NSCE of 0.65 and 1.04% bias. Moreover, the hydrologic capability of satellite precipitation (TRMM-3B42 V6) is evaluated. In terms of reconstruction of the water cycle components the spatial distribution and time series of modeling results for precipitation and runoff showed considerable agreement with the monthly model runoff estimates and gauge observations. Runoff values responded to precipitation events that occurred across the catchment during the wet season from March to early June.The spatially distributed model inputs, states, and outputs, were found to be useful for understanding the hydrologic behavior at the catchment scale. The monthly peak runoff is observed in the months of April, May and November. The analysis revealed a linear relationship between rainfall and runoff for both wet and dry seasons. Satellite precipitation forcing data showed the potential to be used not only for the investigation of water balance but also for addressing issues pertaining to sustainability of the resources at the catchment scale.Implementation of a flood prediction system can potentially help mitigate flood induced hazards. Such a system typically requires implementation and calibration of a hydrologic model using in-situ observations (e.g. rain gauges and stream gauges). Recently, satellite remote sensing data has emerged as a viable alternative or supplement to the in-situ observations due to its availability over vast ungauged regions. The focus of this study is to integrate the best available satellite products within a semi-distributed hydrologic model to characterize the spatial extent of flooding over sparsely-gauged or ungauged basins. A satellite remote sensing based approach is proposed to calibrate a hydrologic model, simulate the spatial extent of flooding, and evaluate the probability of detecting inundated areas. A raster-based semi-distributed hydrologic model, CREST, is implemented for the Nzoia basin, a sub-basin of Lake Victoria in Africa. MODIS Terra and ASTER-based raster flood inundation maps were produced over the region and used to benchmark the hydrologic model simulations of inundated areas. The analysis showed the value of integrating satellite data such as precipitation, land cover type, topography and other data products along with space based flood inundation extents as inputs for the hydrologic model. It is concluded that the quantification of flooding spatial extent through optical sensors can help to evaluate hydrologic models and hence potentially improve hydrologic prediction and flood management strategies in ungauged catchments

    Moving from water problems to water solutions: research needs assessment for the Eastern Gangetic plains

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    Spatial decision support system for coastal flood management in Victoria, Australia

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    Coastal climate impact can affect coastal areas in a variety of ways, such as flooding, storm surges, reduction in beach sands and increased beach erosion. While each of these can have major impacts on the operation of coastal drainage systems, this thesis focuses on coastal and riverine flooding in coastal areas. Coastal flood risk varies within Australia, with the northern parts in the cyclone belt most affected and high levels of risk similar to other Asian countries. However, in Australia, the responsibility for managing coastal areas is shared between the Commonwealth government, Australian states and territories, and local governments. Strategies for floodplain management to reduce and control flooding are best implemented at the land use planning stage. Local governments make local decisions about coastal flood risk management through the assessment and approval of planning permit applications. Statutory planning by local government is informed by policies related to coastal flooding and coastal erosion, advice from government departments, agencies, experts and local community experts. The West Gippsland Catchment Management Authority (WGCMA) works with local communities, Victorian State Emergency Services (VCSES), local government authorities (LGAs), and other local organizations to prepare the West Gippsland Flood Management Strategy (WGFMS). The strategy aims at identifying significant flood risks, mitigating those risks, and establishing a set of priorities for implementation of the strategy over a ten-year period. The Bass Coast Shire Council (BCSC) region has experienced significant flooding over the last few decades, causing the closure of roads, landslides and erosion. Wonthaggi was particularly affected during this period with roads were flooded causing the northern part of the city of Wonthaggi to be closed in the worst cases. Climate change and increased exposure through the growth of urban population have dramatically increased the frequency and the severity of flood events on human populations. Traditionally, while GIS has provided spatial data management, it has had limitations in modelling capability to solve complex hydrology problems such as flood events. Therefore, it has not been relied upon by decision-makers in the coastal management sector. Functionality improvements are therefore required to improve the processing or analytical capabilities of GIS in hydrology to provide more certainty for decision-makers. This research shows how the spatial data (LiDAR, Road, building, aerial photo) can be primarily processed by GIS and how by adopting the spatial analysis routines associated with hydrology these problems can be overcome. The aim of this research is to refine GIS-embedded hydrological modelling so they can be used to help communities better understand their exposure to flood risk and give them more control about how to adapt and respond. The research develops a new Spatial Decision Support System (SDSS) to improve the implementation of coastal flooding risk assessment and management in Victoria, Australia. It is a solution integrating a range of approaches including, Light Detection and Ranging (Rata et al., 2014), GIS (Petroselli and sensing, 2012), hydrological models, numerical models, flood risk modelling, and multi-criteria techniques. Bass Coast Shire Council is an interesting study region for coastal flooding as it involves (i) a high rainfall area, (ii) and a major river meeting coastal area affected by storm surges, with frequent flooding of urban areas. Also, very high-quality Digital Elevation Model (DEM) data is available from the Victorian Government to support first-pass screening of coastal risks from flooding. The methods include using advanced GIS hydrology modelling and LiDAR digital elevation data to determine surface runoff to evaluate the flood risk for BCSC. This methodology addresses the limitations in flood hazard modelling mentioned above and gives a logical basis to estimate tidal impacts on flooding, and the impact and changes in atmospheric conditions, including precipitation and sea levels. This study examines how GIS hydrological modelling and LiDAR digital elevation data can be used to map and visualise flood risk in coastal built-up areas in BCSC. While this kind of visualisation is often used for the assessment of flood impacts to infrastructure risk, it has not been utilized in the BCSC. Previous research identified terrestrial areas at risk of flooding using a conceptual hydrological model (Pourali et al., 2014b) that models the flood-risk regions and provides flooding extent maps for the BCSC. It examined the consequences of various components influencing flooding for use in creating a framework to manage flood risk. The BCSC has recognised the benefits of combining these techniques that allow them to analyse data, deal with the problems, create intuitive visualization methods, and make decisions about addressing flood risk. The SDSS involves a GIS-embedded hydrological model that interlinks data integration and processing systems that interact through a linear cascade. Each stage of the cascade produces results which are input into the next model in a modelling chain hierarchy. The output involves GIS-based hydrological modelling to improve the implementation of coastal flood risk management plans developed by local governments. The SDSS also derives a set of Coastal Climate Change (CCC) flood risk assessment parameters (performance indicators), such as land use, settlement, infrastructure and other relevant indicators for coastal and bayside ecosystems. By adopting the SDSS, coastal managers will be able to systematically compare alternative coastal flood-risk management plans and make decisions about the most appropriate option. By integrating relevant models within a structured framework, the system will promote transparency of policy development and flood risk management. This thesis focuses on extending the spatial data handling capability of GIS to integrate climatic and other spatial data to help local governments with coastal exposure develop programs to adapt to climate change. The SDSS will assist planners to prepare for changing climate conditions. BCSC is a municipal government body with a coastal boundary and has assisted in the development and testing of the SDSS and derived many benefits from using the SDSS developed as a result of this research. Local governments at risk of coastal flooding that use the SDSS can use the Google Earth data sharing tool to determine appropriate land use controls to manage long-term flood risk to human settlement. The present research describes an attempt to develop a Spatial Decision Support System (SDSS) to aid decision makers to identify the proper location of new settlements where additional land development could be located based on decision rules. Also presented is an online decision-support tool that all stakeholders can use to share the results

    Interlocal Adaptations to Climate Change in East and Southeast Asia

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    This Open Access book’s main focus is agriculture and natural resource management, disaster risk reduction, and human resource development in the countries of East and Southeast Asia and Japan. Asia is one of the regions which is the most vulnerable to the impacts of climate change. More than sixty percent of the world’s people live in the region, making it the growth center of the world. Asia is vast and includes various countries and regions, this book is focused on East and Southeast Asia including Japan. It is essential to share the knowledge and experiences for adapting climate change among these areas. In order to tackle these issues, the book aims to: Promote inter-local lessons learnt sharing climate change adaptations; "agriculture and natural resource management" and "disaster risk reduction and human resource development" Provides insights into new adaptation measures and research approaches that can consider the regional nature of Southeast Asia Share practical adaptation options permeated by society in each country/region This book will be of interest to researchers and students examining climate change impacts in East and Southeast Asia

    Remote Sensing in Applications of Geoinformation

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    Remote sensing, especially from satellites, is a source of invaluable data which can be used to generate synoptic information for virtually all parts of the Earth, including the atmosphere, land, and ocean. In the last few decades, such data have evolved as a basis for accurate information about the Earth, leading to a wealth of geoscientific analysis focusing on diverse applications. Geoinformation systems based on remote sensing are increasingly becoming an integral part of the current information and communication society. The integration of remote sensing and geoinformation essentially involves combining data provided from both, in a consistent and sensible manner. This process has been accelerated by technologically advanced tools and methods for remote sensing data access and integration, paving the way for scientific advances in a broadening range of remote sensing exploitations in applications of geoinformation. This volume hosts original research focusing on the exploitation of remote sensing in applications of geoinformation. The emphasis is on a wide range of applications, such as the mapping of soil nutrients, detection of plastic litter in oceans, urban microclimate, seafloor morphology, urban forest ecosystems, real estate appraisal, inundation mapping, and solar potential analysis

    Concept to Practice of Geospatial-Information Tools to Assist Forest Management and Planning under Precision Forestry Framework: a review

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    Precision forestry is a new direction for better forest management. Precision forestry employs information technology and analytical tools to support economic, environmental and sustainable decision; the use of geospatial information tools enables highly repeatable measurements, actions and processes to manage and harvest forest stands, simultaneously allowing information linkages between production and wood supply chain, including resource managers and environmental community. In this report, we reviewed the most recent advances in the use of geospatial information technologies in forestry, and discussed their potential opportunities and challenges towards forest management and planning in the framework of precision forestry
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