1,150 research outputs found

    Flood dynamics derived from video remote sensing

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    Flooding is by far the most pervasive natural hazard, with the human impacts of floods expected to worsen in the coming decades due to climate change. Hydraulic models are a key tool for understanding flood dynamics and play a pivotal role in unravelling the processes that occur during a flood event, including inundation flow patterns and velocities. In the realm of river basin dynamics, video remote sensing is emerging as a transformative tool that can offer insights into flow dynamics and thus, together with other remotely sensed data, has the potential to be deployed to estimate discharge. Moreover, the integration of video remote sensing data with hydraulic models offers a pivotal opportunity to enhance the predictive capacity of these models. Hydraulic models are traditionally built with accurate terrain, flow and bathymetric data and are often calibrated and validated using observed data to obtain meaningful and actionable model predictions. Data for accurately calibrating and validating hydraulic models are not always available, leaving the assessment of the predictive capabilities of some models deployed in flood risk management in question. Recent advances in remote sensing have heralded the availability of vast video datasets of high resolution. The parallel evolution of computing capabilities, coupled with advancements in artificial intelligence are enabling the processing of data at unprecedented scales and complexities, allowing us to glean meaningful insights into datasets that can be integrated with hydraulic models. The aims of the research presented in this thesis were twofold. The first aim was to evaluate and explore the potential applications of video from air- and space-borne platforms to comprehensively calibrate and validate two-dimensional hydraulic models. The second aim was to estimate river discharge using satellite video combined with high resolution topographic data. In the first of three empirical chapters, non-intrusive image velocimetry techniques were employed to estimate river surface velocities in a rural catchment. For the first time, a 2D hydraulicvmodel was fully calibrated and validated using velocities derived from Unpiloted Aerial Vehicle (UAV) image velocimetry approaches. This highlighted the value of these data in mitigating the limitations associated with traditional data sources used in parameterizing two-dimensional hydraulic models. This finding inspired the subsequent chapter where river surface velocities, derived using Large Scale Particle Image Velocimetry (LSPIV), and flood extents, derived using deep neural network-based segmentation, were extracted from satellite video and used to rigorously assess the skill of a two-dimensional hydraulic model. Harnessing the ability of deep neural networks to learn complex features and deliver accurate and contextually informed flood segmentation, the potential value of satellite video for validating two dimensional hydraulic model simulations is exhibited. In the final empirical chapter, the convergence of satellite video imagery and high-resolution topographical data bridges the gap between visual observations and quantitative measurements by enabling the direct extraction of velocities from video imagery, which is used to estimate river discharge. Overall, this thesis demonstrates the significant potential of emerging video-based remote sensing datasets and offers approaches for integrating these data into hydraulic modelling and discharge estimation practice. The incorporation of LSPIV techniques into flood modelling workflows signifies a methodological progression, especially in areas lacking robust data collection infrastructure. Satellite video remote sensing heralds a major step forward in our ability to observe river dynamics in real time, with potentially significant implications in the domain of flood modelling science

    Regional water balance analysis of glacierised river basins in the north-eastern Himalaya applying the J2000 hydrological model

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    The glacierised basins of the Northeast Himalayan region are highly vulnerable to climate-change impacts. The spatio-temporal hydroclimatic and physiographic variability impact the water balance of these glacierised basins across the region. This study assesses the glaciohydrological processes and dynamics in the data scarce region for the present as well future climate change scenarios by regional water balance analysis. The J2000 hydrological model was adapted to incorporate the frozen ground as well as glacier dynamics in a stepwise, nested basin calibration approach. The modelled ERA-Interim precipitation data cannot capture the high amplitude orographic and convective events. Therefore, Orographic correction factors were used to inversely correct the ERA-Interim precipitation data to account for the orographic as well as cyclonic precipitation in the region from reported glacier mass balance and evapotranspiration estimates. Monthly temperature lapse rate was adopted for correcting the ERA-Interim temperature dataset. The Beki basin was selected as the donor basin for model development and evaluation. The parameters from the Beki basin were regionalised to the receptor Lohit and the Noadihing basins by the Proxy-basin method. Multi-objective optimization criteria such as the Kling-Gupta efficiency (KGE) for temporal dynamics and flow distribution and Bias for overall water balance showed high to moderate conformity between measured and simulated discharge at the corresponding basin outlets. The variability in the water balance and runoff components among the three basins was primarily related to the spatio-temporal variation in the mean annual precipitation, runoff and evapotranspiration estimates. The impact of climate-change scenarios on the study basins indicated that water availability would sustain until the end of the century due to higher projected precipitation even though after the depletion of glaciers in the region

    Science and Innovations for Food Systems Transformation

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    This Open Access book compiles the findings of the Scientific Group of the United Nations Food Systems Summit 2021 and its research partners. The Scientific Group was an independent group of 28 food systems scientists from all over the world with a mandate from the Deputy Secretary-General of the United Nations. The chapters provide science- and research-based, state-of-the-art, solution-oriented knowledge and evidence to inform the transformation of contemporary food systems in order to achieve more sustainable, equitable and resilient systems

    Examining the Relationships Between Distance Education Students’ Self-Efficacy and Their Achievement

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    This study aimed to examine the relationships between students’ self-efficacy (SSE) and students’ achievement (SA) in distance education. The instruments were administered to 100 undergraduate students in a distance university who work as migrant workers in Taiwan to gather data, while their SA scores were obtained from the university. The semi-structured interviews for 8 participants consisted of questions that showed the specific conditions of SSE and SA. The findings of this study were reported as follows: There was a significantly positive correlation between targeted SSE (overall scales and general self-efficacy) and SA. Targeted students' self-efficacy effectively predicted their achievement; besides, general self- efficacy had the most significant influence. In the qualitative findings, four themes were extracted for those students with lower self-efficacy but higher achievement—physical and emotional condition, teaching and learning strategy, positive social interaction, and intrinsic motivation. Moreover, three themes were extracted for those students with moderate or higher self-efficacy but lower achievement—more time for leisure (not hard-working), less social interaction, and external excuses. Providing effective learning environments, social interactions, and teaching and learning strategies are suggested in distance education

    Towards Improved Flood Defences

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    Without our dikes and dunes, 60% of the Netherlands would flood on a regular basis. This area is home to 9 million people. The latest report of the Intergovernmental Panel on Climate Change (IPCC, February 2022) underlines the importance of reinforcing water safety. Sea levels are rising and extreme weather is becoming increasingly common. The Flood Protection Programme, the largest Dutch water safety operation since the Delta Works, will help us minimise the likelihood of flooding. New knowledge and innovation are urgently needed The Dutch dikes have stood firm for more than 1,000 years. After disasters in 1916 and 1953, storm surge barriers and dams have been added to the network of protective dikes. Following the floods in 1993 and 1995, the Room for the River programme was implemented. New knowledge of flood risks led to the introduction of new, often stricter standards for flood defences in 2017

    Land Surface Monitoring Based on Satellite Imagery

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    This book focuses attention on significant novel approaches developed to monitor land surface by exploiting satellite data in the infrared and visible ranges. Unlike in situ measurements, satellite data provide global coverage and higher temporal resolution, with very accurate retrievals of land parameters. This is fundamental in the study of climate change and global warming. The authors offer an overview of different methodologies to retrieve land surface parameters— evapotranspiration, emissivity contrast and water deficit indices, land subsidence, leaf area index, vegetation height, and crop coefficient—all of which play a significant role in the study of land cover, land use, monitoring of vegetation and soil water stress, as well as early warning and detection of forest ïŹres and drought
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