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Author : L. Ramsamy
Publisher :
ISBN 13 :
Total Pages : 0 pages
Book Rating : 4.:/5 (14 download)
Download or read book Flood Modelling in Large Catchments Using Open-source Data and Data-driven Techniques written by L. Ramsamy and published by . This book was released on 2023 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Renji Remesan
Publisher : Springer
ISBN 13 : 3319092359
Total Pages : 261 pages
Book Rating : 4.3/5 (19 download)
Download or read book Hydrological Data Driven Modelling written by Renji Remesan and published by Springer. This book was released on 2014-11-03 with total page 261 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book explores a new realm in data-based modeling with applications to hydrology. Pursuing a case study approach, it presents a rigorous evaluation of state-of-the-art input selection methods on the basis of detailed and comprehensive experimentation and comparative studies that employ emerging hybrid techniques for modeling and analysis. Advanced computing offers a range of new options for hydrologic modeling with the help of mathematical and data-based approaches like wavelets, neural networks, fuzzy logic, and support vector machines. Recently machine learning/artificial intelligence techniques have come to be used for time series modeling. However, though initial studies have shown this approach to be effective, there are still concerns about their accuracy and ability to make predictions on a selected input space.
Author : Fi-John Chang
Publisher : MDPI
ISBN 13 : 3038975486
Total Pages : 376 pages
Book Rating : 4.0/5 (389 download)
Download or read book Flood Forecasting Using Machine Learning Methods written by Fi-John Chang and published by MDPI. This book was released on 2019-02-28 with total page 376 pages. Available in PDF, EPUB and Kindle. Book excerpt: Nowadays, the degree and scale of flood hazards has been massively increasing as a result of the changing climate, and large-scale floods jeopardize lives and properties, causing great economic losses, in the inundation-prone areas of the world. Early flood warning systems are promising countermeasures against flood hazards and losses. A collaborative assessment according to multiple disciplines, comprising hydrology, remote sensing, and meteorology, of the magnitude and impacts of flood hazards on inundation areas significantly contributes to model the integrity and precision of flood forecasting. Methodologically oriented countermeasures against flood hazards may involve the forecasting of reservoir inflows, river flows, tropical cyclone tracks, and flooding at different lead times and/or scales. Analyses of impacts, risks, uncertainty, resilience, and scenarios coupled with policy-oriented suggestions will give information for flood hazard mitigation. Emerging advances in computing technologies coupled with big-data mining have boosted data-driven applications, among which Machine Learning technology, with its flexibility and scalability in pattern extraction, has modernized not only scientific thinking but also predictive applications. This book explores recent Machine Learning advances on flood forecast and management in a timely manner and presents interdisciplinary approaches to modelling the complexity of flood hazards-related issues, with contributions to integrative solutions from a local, regional or global perspective.
Author : Wei Li ((Ph. D. in computational science, engineering, and mathematics))
Publisher :
ISBN 13 :
Total Pages : 176 pages
Book Rating : 4.:/5 (128 download)
Download or read book Data-driven Modeling for Compound Flooding Simulation written by Wei Li ((Ph. D. in computational science, engineering, and mathematics)) and published by . This book was released on 2021 with total page 176 pages. Available in PDF, EPUB and Kindle. Book excerpt: Accurate simulation of compound flooding is crucial for flood risk management. In coastal regions, both rainfall runoff and storm surge can contribute to flooding and are not mutually exclusive. It is thus necessary to develop a modeling framework for compound flooding that considers both mechanisms. While many hydrologic models have been developed to simulate the rainfall runoff processes, a lot of these methods are either computationally expensive, or incapable of simulating extreme weather events. Thus, they may not be suitable for coupled modeling of compound flooding. In this study, a data-driven hydrologic model based on deep recurrent neural network (RNN) is developed for rainfall runoff simulation at relatively low computational cost. To test the capability of the method, the model is used to infer the streamflow out of an urban watershed, Brays Bayou in Houston, Texas. And the model is validated with real world hydrologic data. Additionally, the proposed synced sequence to sequence RNN architecture is compared with the sequence input single output one that is widely-used in hydrologic modeling. Numerical experiments show that the proposed method provides more accurate predictions using relatively less computational resources than the sequence input single output architecture. Later, downstream water level input is integrated into the RNN model to enable the one-way coupling of rainfall runoff with storm surge. Numerical examples at two different locations demonstrate that the additional information leads to improved predictions. Finally, a two-way dynamic coupling framework is constructed for the RNN hydrologic model and an ocean circulation model, ADvanced CIRCulation. The framework is tested, verified, and validated for the Houston ship channel - Galveston bay estuarine system during Hurricane Harvey (2017). This dissertation is based on the following articles: High temporal resolution rainfall runoff modelling using Long-Short-Term-Memory (LSTM) networks by Wei Li, Amin Kiaghadi, Clint Dawson [1]; Exploring the best sequence LSTM model- ing architecture for flood prediction by Wei Li, Amin Kiaghadi, Clint Dawson [2]; and Simulating compound floods: dynamic coupling of deep learning and physics- based models by Wei Li, Gajanan Choudhary, Amin Kiaghadi, Clint Dawson. This material is based upon work funded by National Oceanic and Atmospheric Admin- istration (Grant No. NA18NOS0120158) and National Science Foundation (NSF, CMMI-1520817)
Author : David Fernando Muñoz
Publisher :
ISBN 13 :
Total Pages : pages
Book Rating : 4.:/5 (129 download)
Download or read book Integration of Physically-Based and Data-Driven Modeling Approaches for Compound Coastal Flood Hazard Assessment Under Uncertainties written by David Fernando Muñoz and published by . This book was released on 2021 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Flood hazard assessment is an essential component of risk and disaster management that helps identify areas exposed to flooding as well as support decision making, and emergency response. Floods can result from isolated, concurrent, or successive drivers of (non-) extreme origin (e.g., fluvial, pluvial, and oceanic) and so put society and the environment at constant risk. Specifically, a combination of either concurrent or successive flood drivers with potential impacts larger than those from isolated drivers is defined as compound flooding (CF). Contemporary studies in compound flood hazard assessment (CFHA) and modeling have focused on simulating inundation extent, water depth, and velocities at local or regional scale. However, those studies often neglect inherent uncertainties associated with forcing data, observations, model parameters, and model structure. A comprehensive analysis of these uncertainty sources is thus imperative, but it requires advanced statistical techniques such as data assimilation (DA) to adequately account for error propagation in compound flood modeling. Chapters 1 to 4 present previous peer-review studies oriented towards a better characterization of uncertainty in CFHA. Those studies include the following research topics: (i) analysis of wetland elevation error and correction of coastal digital elevation models, (ii) compound effects of wetland elevation error and uncertainty from flood drivers, (iii) effects of model selection and model structure error on total water level prediction, and (iv) long-term wetland dynamics associated with urbanization, sea level rise, and hurricane impacts. Chapter 5 presents a cost-effective approach based on deep learning (DL) and data fusion (DF) techniques that enables efficient estimation of exposure to compound coastal flooding at regional scale. Chapter 6 presents a DA scheme based on the Ensemble Kalman Filter (EnKF) technique and hydrodynamic modeling to improve water level (WL) predictions and CFHA in coastal to inland transition zones where pluvial, fluvial, and coastal processes interact. The last section of this dissertation summarizes the main findings of these studies and discusses future research areas that are worth exploring in the context of CFHA.
Author : Thorsten Wagener
Publisher : World Scientific
ISBN 13 : 1783260661
Total Pages : 333 pages
Book Rating : 4.7/5 (832 download)
Download or read book Rainfall-runoff Modelling In Gauged And Ungauged Catchments written by Thorsten Wagener and published by World Scientific. This book was released on 2004-09-09 with total page 333 pages. Available in PDF, EPUB and Kindle. Book excerpt: This important monograph is based on the results of a study on the identification of conceptual lumped rainfall-runoff models for gauged and ungauged catchments. The task of model identification remains difficult despite decades of research. A detailed problem analysis and an extensive review form the basis for the development of a Matlab® modelling toolkit consisting of two components: a Rainfall-Runoff Modelling Toolbox (RRMT) and a Monte Carlo Analysis Toolbox (MCAT). These are subsequently applied to study the tasks of model identification and evaluation. A novel dynamic identifiability approach has been developed for the gauged catchment case. The theory underlying the application of rainfall-runoff models for predictions in ungauged catchments is studied, problems are highlighted and promising ways to move forward are investigated. Modelling frameworks for both gauged and ungauged cases are developed. This book presents the first extensive treatment of rainfall-runoff model identification in gauged and ungauged catchments.
Author : Salvatore Manfreda
Publisher : MDPI
ISBN 13 : 3039435256
Total Pages : 198 pages
Book Rating : 4.0/5 (394 download)
Download or read book Advances in Large Scale Flood Monitoring and Detection written by Salvatore Manfreda and published by MDPI. This book was released on 2020-11-13 with total page 198 pages. Available in PDF, EPUB and Kindle. Book excerpt: Climate change and land use transformations have induced an increased flood risk worldwide. These phenomena are dramatically impacting ordinary life and the economy. Research and technology offer a new strategy to quantify and predict such phenomena and also mitigate the impact of flooding. In particular, the growing computational power is offering new strategies for a more detailed description of the flooding over large scales. This book offers an overview of the most recent outcomes of the research on this argument.
Author : Wan Zurina Binti Wan Jafaar
Publisher :
ISBN 13 :
Total Pages : pages
Book Rating : 4.:/5 (855 download)
Download or read book Index Flood Model Development Using Hydroinformatics written by Wan Zurina Binti Wan Jafaar and published by . This book was released on 2012 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: A reliable model for flood prediction is crucial for many aspects of engineering design in reducing flood risk impact to human lives, both economic and social. Despite an abundance of research on improving flood regionalisation modelling, there are still potential difficulties that require attention by the hydrological community. This thesis attempts to solve some problems concerning the index flood model development encompassing catchment information constraint, model selection process, calibration data issues, model structure and linearisation of regression models. These interrelated factors have largely affected the prediction accuracy of index flood models. First, catchment information data are problematic if acquisition of digital maps is a problem. In a country like UK, not all the digital maps and catchment information are available for free. As a result, freely downloadable digital maps from the internet are useful in deriving catchment information. Besides, by employing these freely available data in conjunction with the automated catchment delineation algorithm and a powerful tool of GIS for data derivation, a large number of alternative catchment characteristics can be produced. As such, the derivation method and catchment characteristics presented in this study are more applicable to other parts of the world. Second, in practice, there are a large number of catchment characteristics (or input variables in mathematical terms) that could be used to develop a model. The problem is how to choose a set of significant input variables as not all of them are important and some may be irrelevant and redundant. Furthermore, the process of input variable selection is time demanding since each validation will need a fully calibrated formula. The Gamma Test tool in conjunction with the cross validation method is proposed which has reduced model development workload besides gaining a reliable prediction model. Third, calibration data are one of the crucial aspects that generally affect the reliability of developed models. Uncertainty of model occurs regardless how many data points are used. This study provides a platform to those in a region where data availability is limited, to choose good quality calibration data so as to enhance prediction estimation. Fourth, model structure is another factor that affects prediction accuracy of the index flood model. This has been explored in this study to demonstrate that there is a room for further improvement over the existing power form models. Finally, a multiple regression approach is a popular method used to relate flood estimate to the catchment characteristics. Linearisation of nonlinear multiple regression model into logarithmic form is the most commonly adopted technique that eventually leads to the bias. To avoid this problem, model parameters are directly solved by nonlinear optimisation techniques.
Author : Hamid Reza Pourghasemi
Publisher : Elsevier
ISBN 13 : 0128156953
Total Pages : 798 pages
Book Rating : 4.1/5 (281 download)
Download or read book Spatial Modeling in GIS and R for Earth and Environmental Sciences written by Hamid Reza Pourghasemi and published by Elsevier. This book was released on 2019-01-18 with total page 798 pages. Available in PDF, EPUB and Kindle. Book excerpt: Spatial Modeling in GIS and R for Earth and Environmental Sciences offers an integrated approach to spatial modelling using both GIS and R. Given the importance of Geographical Information Systems and geostatistics across a variety of applications in Earth and Environmental Science, a clear link between GIS and open source software is essential for the study of spatial objects or phenomena that occur in the real world and facilitate problem-solving. Organized into clear sections on applications and using case studies, the book helps researchers to more quickly understand GIS data and formulate more complex conclusions. The book is the first reference to provide methods and applications for combining the use of R and GIS in modeling spatial processes. It is an essential tool for students and researchers in earth and environmental science, especially those looking to better utilize GIS and spatial modeling. Offers a clear, interdisciplinary guide to serve researchers in a variety of fields, including hazards, land surveying, remote sensing, cartography, geophysics, geology, natural resources, environment and geography Provides an overview, methods and case studies for each application Expresses concepts and methods at an appropriate level for both students and new users to learn by example
Author : Donald Knight
Publisher : CRC Press
ISBN 13 : 9781439824702
Total Pages : 626 pages
Book Rating : 4.8/5 (247 download)
Download or read book River Basin Modelling for Flood Risk Mitigation written by Donald Knight and published by CRC Press. This book was released on 2005-11-17 with total page 626 pages. Available in PDF, EPUB and Kindle. Book excerpt: Flooding accounts for one-third of natural disasters worldwide and for over half the deaths which occur as a result of natural disasters. As the frequency and volume of flooding increases, as a result of climate change, there is a new urgency amongst researchers and professionals working in flood risk management. River Basin Modelling for Flood Risk Mitigation brings together thirty edited papers by leading experts who gathered for the European Union’s Advanced Study Course at the University of Birmingham, UK. The scope of the course ranged from issues concerning the protection of life, to river restoration and wetland management. A variety of topics is covered in the book including climate change, hydro-informatics, hydro-meterology, river flow forecasting systems and dam-break modelling. The approach is broad, but integrated, providing an attractive and informative package that will satisfy researchers and professionals, while offering a sound introduction to students in Engineering and Geography.
Author : Abhas K. Jha
Publisher : World Bank Publications
ISBN 13 : 0821394770
Total Pages : 639 pages
Book Rating : 4.8/5 (213 download)
Download or read book Cities and Flooding written by Abhas K. Jha and published by World Bank Publications. This book was released on 2012-02-01 with total page 639 pages. Available in PDF, EPUB and Kindle. Book excerpt: Urban flooding is an increasing challenge today to the expanding cities and towns of developing countries. This Handbook is a state-of-the art, user-friendly operational guide that shows decision makers and specialists how to effectively manage the risk of floods in rapidly urbanizing settings--and within the context of a changing climate.
Author : Evelyn Fix
Publisher :
ISBN 13 :
Total Pages : 142 pages
Book Rating : 4.:/5 (318 download)
Download or read book Discriminatory Analysis written by Evelyn Fix and published by . This book was released on 1985 with total page 142 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Vorawit Meesuk
Publisher : CRC Press
ISBN 13 : 1351394223
Total Pages : 270 pages
Book Rating : 4.3/5 (513 download)
Download or read book Point Cloud Data Fusion for Enhancing 2D Urban Flood Modelling written by Vorawit Meesuk and published by CRC Press. This book was released on 2017-07-20 with total page 270 pages. Available in PDF, EPUB and Kindle. Book excerpt: Modelling urban flood dynamics requires proper handling of a number of complex urban features. Although high-resolution topographic data can nowadays be obtained from aerial LiDAR surveys, such top-view LiDAR data still have difficulties to represent some key components of urban features. Incorrectly representing features like underpasses through buildings or apparent blockage of flow by sky trains may lead to misrepresentation of actual flood propagation, which could easily result in inadequate flood-protection measures. Hence proper handling of urban features plays an important role in enhancing urban flood modelling. This research explores present-day capabilities of using computer-based environments to merge side-view Structure-from-Motion data acquisition with top-view LiDAR data to create a novel multi-source views (MSV) topographic representation for enhancing 2D model schematizations. A new MSV topographic data environment was explored for the city of Delft and compared with the conventional top-view LiDAR approach. Based on the experience gained, the effects of different topographic descriptions were explored for 2D urban flood models of (i) Kuala Lumpur, Malaysia for the 2003 flood event; and (ii) Ayutthaya, Thailand for the 2011 flood event. It was observed that adopting the new MSV data as the basis for describing the urban topography, the numerical simulations provide a more realistic representation of complex urban flood dynamics, thus enhancing conventional approaches and revealing specific features like flood watermarks identification and helping to develop improved flood-protection measures.
Author : Heather McGrath
Publisher :
ISBN 13 :
Total Pages : 0 pages
Book Rating : 4.:/5 (133 download)
Download or read book Web-based Flood Risk Assessment written by Heather McGrath and published by . This book was released on 2017 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Timely and accurate prediction of flood inundation extent and potential negative impacts and consequences is fundamental for the sustainable development of a given region and allows decision makers and the local community to understand their exposure and vulnerability. Complex computer models exist for flood risk assessment and while technologically sophisticated, these programs are intended, first of all, for use by a small number of technical and scientific experts and require considerable processing time and extensive inputs. These existing solutions are generally not well suited for flood prediction in near real-time and often exceed the data available for any given community. This research developed standardized methods, adapted into user-friendly tools which accept limited user input, are based on hydrologic principles and processes, widely accepted risk computation methods and leverage open data. The developed flood mapping approaches access, and through a novel data fusion method, create a better quality digital elevation model (DEM) from multiple open source elevation datasets. This fused DEM is combined with other open source data (e.g., IDF curves, river flow data, watershed boundaries, etc.) to generate a flood inundation surface through two methods: (i) a 0D bathtub model and (ii) a hybrid 1D/2D raster cell storage approach. The 0D model ignores flow rates and changes over time, producing a grid of the maximum spatial extent and depth, calculated as the difference between the terrain elevation and the computed water surface. The hybrid model solves 1D kinematic wave approximation of shallow water equations in the channel and treats the floodplain as 2D flooding storage cells. Water depths from the flood grid are combined with local inventory data (e.g., building structural type, occupancy, valuation, height of the first floor, etc.) to compute exposure and damage estimates in either a user friendly MS Office application or a web-based API. The developed methods and user-friendly tools allow non-experts the ability to rapidly generate their own flood inundation scenario on demand and assess risk, thus minimizing the gap between the existing sophisticated tools, designed for scientists and engineers, and community needs in order to support informed emergency response and mitigation planning.
Author : Yogi Suardiwerianto
Publisher :
ISBN 13 :
Total Pages : pages
Book Rating : 4.:/5 (983 download)
Download or read book Flash flood modelling using data-driven models: case studies of Kathmandu Valley (Nepal) and Yuna Catchment (Dominican Republic) written by Yogi Suardiwerianto and published by . This book was released on 2017 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Brahim Boutkhamouine
Publisher :
ISBN 13 :
Total Pages : 0 pages
Book Rating : 4.:/5 (137 download)
Download or read book Data-Driven Model for River Flood Forecasting Based on a Bayesian Network Approach written by Brahim Boutkhamouine and published by . This book was released on 2020 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Uncertainty analysis of hydrological models often requires a large number of model runs, which can be time consuming and computationally intensive. In order to reduce the number of runs required for uncertainty prediction, Bayesian networks (BNs) are used to graphically represent conditional probability dependence between the set of variables characterizing a flood event. Bayesian networks (BNs) are relevant due to their capacity to handle uncertainty, combine statistical data and expertise and introduce evidences in real-time flood forecasting. In the present study, a runoff-runoff model is considered. The discharge at a gauging station located is estimated at the outlet of a basin catchment based on discharge measurements at the gauging stations upstream. The BN model shows good performances in estimating the discharges at the basin outlet. Another application of the BN model is to be used as a reverse method. Knowing discharges values at the outlet of the basin, we can propagate back these values through the model to estimate discharges at upstream stations. This turns out to be a practical method to fill the missing data in streamflow records which are critical to the sustainable management of water and the development of hydrological models.
Author : Zoé A. Hamstead
Publisher : Springer Nature
ISBN 13 : 3030631311
Total Pages : 190 pages
Book Rating : 4.0/5 (36 download)
Download or read book Resilient Urban Futures written by Zoé A. Hamstead and published by Springer Nature. This book was released on 2021-04-06 with total page 190 pages. Available in PDF, EPUB and Kindle. Book excerpt: This open access book addresses the way in which urban and urbanizing regions profoundly impact and are impacted by climate change. The editors and authors show why cities must wage simultaneous battles to curb global climate change trends while adapting and transforming to address local climate impacts. This book addresses how cities develop anticipatory and long-range planning capacities for more resilient futures, earnest collaboration across disciplines, and radical reconfigurations of the power regimes that have institutionalized the disenfranchisement of minority groups. Although planning processes consider visions for the future, the editors highlight a more ambitious long-term positive visioning approach that accounts for unpredictability, system dynamics and equity in decision-making. This volume brings the science of urban transformation together with practices of professionals who govern and manage our social, ecological and technological systems to design processes by which cities may achieve resilient urban futures in the face of climate change.
