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Flood Forecasting Using Machine Learning Methods

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ISBN: 9783038975489 Year: Pages: 376 DOI: 10.3390/books978-3-03897-549-6 Language: English
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Technology (General) --- General and Civil Engineering --- Environmental Engineering
Added to DOAB on : 2019-03-08 11:42:05
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Abstract

This book is a printed edition of the Special Issue Flood Forecasting Using Machine Learning Methods that was published in Water

Keywords

data scarce basins --- runoff series --- data forward prediction --- ensemble empirical mode decomposition (EEMD) --- stopping criteria --- method of tracking energy differences (MTED) --- deep learning --- convolutional neural networks --- superpixel --- urban water bodies --- high-resolution remote-sensing images --- monthly streamflow forecasting --- artificial neural network --- ensemble technique --- phase space reconstruction --- empirical wavelet transform --- hybrid neural network --- flood forecasting --- self-organizing map --- bat algorithm --- particle swarm optimization --- flood routing --- Muskingum model --- machine learning methods --- St. Venant equations --- rating curve method --- nonlinear Muskingum model --- hydrograph predictions --- flood routing --- Muskingum model --- hydrologic models --- improved bat algorithm --- Wilson flood --- Karahan flood --- flood susceptibility modeling --- ANFIS --- cultural algorithm --- bees algorithm --- invasive weed optimization --- Haraz watershed --- ANN-based models --- flood inundation map --- self-organizing map (SOM) --- recurrent nonlinear autoregressive with exogenous inputs (RNARX) --- ensemble technique --- artificial neural networks --- uncertainty --- streamflow predictions --- sensitivity --- flood forecasting --- extreme learning machine (ELM) --- backtracking search optimization algorithm (BSA) --- the upper Yangtze River --- deep learning --- LSTM network --- water level forecast --- the Three Gorges Dam --- Dongting Lake --- Muskingum model --- wolf pack algorithm --- parameters --- optimization --- flood routing --- flash-flood --- precipitation-runoff --- forecasting --- lag analysis --- random forest --- machine learning --- flood prediction --- flood forecasting --- hydrologic model --- rainfall–runoff, hybrid & --- ensemble machine learning --- artificial neural network --- support vector machine --- natural hazards & --- disasters --- adaptive neuro-fuzzy inference system (ANFIS) --- decision tree --- survey --- classification and regression trees (CART), data science --- big data --- artificial intelligence --- soft computing --- extreme event management --- time series prediction --- LSTM --- rainfall-runoff --- flood events --- flood forecasting --- data assimilation --- particle filter algorithm --- micro-model --- Lower Yellow River --- ANN --- hydrometeorology --- flood forecasting --- real-time --- postprocessing --- machine learning --- early flood warning systems --- hydroinformatics --- database --- flood forecast --- Google Maps

Adaptive Catchment Management and Reservoir Operation

Authors: --- ---
ISBN: 9783038977384 9783038977391 Year: Pages: 498 DOI: 10.3390/books978-3-03897-739-1 Language: English
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Technology (General) --- General and Civil Engineering
Added to DOAB on : 2019-08-28 11:21:27
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Abstract

River catchments and reservoirs play a central role in water security, food supply, flood risk management, hydropower generation, and ecosystem services; however, they are now under increasing pressure from population growth, economic activities, and changing climate means and extremes in many parts of the world. Adaptive management of river catchments and reservoirs requires an in-depth understanding of the impacts of future uncertainties and thus the development of robust, sustainable solutions to meet the needs of various stakeholders and the environment. To tackle the huge challenges in moving towards adaptive catchment management, this book presents the latest developments in cutting-edge knowledge, novel methodologies, innovative management strategies, and case studies, focusing on the following themes: reservoir dynamics and impact analysis of dam construction, optimal reservoir operation, climate change impacts on hydrological processes and water management, and integrated catchment management.

Keywords

Siemianówka --- hydrology --- Narew River --- dam --- reservoir --- discharge --- flow regime --- reservoir flushing --- numerical simulation --- flushing efficiency --- Kurobe River --- two-dimensional bed evolution model --- sediment flushing of empty storage --- shaft spillway pipe --- sediment flushing efficiency --- sediment regime --- suspended sediment concentration --- vertical profiles of concentration --- Jingjiang River Reach --- Yangtze River --- CO2 --- reservoirs --- general regression neural network --- back propagation neural network --- climate change --- CMIP3 --- CMIP5 --- downscaling --- runoff response --- SWAT model --- stochastic linear programming --- Markov chain --- reliability --- vulnerability --- reservoir operation --- stochastic dynamic programming --- protection zone --- nutrient uptake --- NPP --- South-to-North Water Transfer Project --- Miyun Reservoir --- reservoir operation --- optimization --- SWAT --- HEC-ResPRM --- climate change --- CORDEX-Africa --- Tekeze basin --- long distance water diversion --- inverted siphon --- sensitivity analysis --- integrated supply system modeling --- sediment regime --- suspended sediment concentration --- vertical profiles of concentration --- the Jingjiang River Reach --- the Yangtze River --- reservoir operation --- multi-stage stochastic optimization --- TB-MPC --- flood control --- real-time control --- energy --- hydropower stations --- differential evolution algorithm --- optimal scheduling --- ?-constrained method --- drinking water resources --- water environmental capacity (WEC) --- Environmental Fluid Dynamics Code (EFDC) model --- the Huangshi Reservoir --- seasonal rainfall --- upper Chao Phraya River Basin --- El Niño/Southern Oscillation --- Indian Monsoon --- sea surface temperatures --- reverse regulation --- coupling model --- aftereffect --- accompanying progressive optimality algorithm --- Dokan Dam --- runoff --- sediment load --- SWAT --- natural flow regime --- multi-objective model --- uncertainty --- genetic algorithm --- land and water resources --- system dynamics --- modeling --- scenario analysis --- Heilongjiang --- tropical reservoir --- heating impact --- Langcang-Mekong River --- Kappa distribution --- parameter relation --- partial gauged basin --- power function --- ratio curve --- ungauged basin --- reservoir operation --- integrated surface water-groundwater model --- Heihe River Basin --- environmental flow --- irrigation --- design and operation of the multipurpose reservoir --- water deficit --- reservoir simulation model --- climate change --- multi-objective optimization NSGA II --- resilience and robustness --- costs and benefits --- water energy --- multi-agent of river basin --- game theory --- water resources allocation --- optimal flood control operation --- cascade reservoirs --- dynamic programming with progressive optimality algorithm (DP-POA) --- the upper Yangtze River Basin --- parameterization --- simulation --- optimization --- direct policy search --- hedging policy --- shortage ratio: Vulnerability --- NSGA-II --- lentic habitats --- bitterling --- mussel --- floodplain vertical shape index --- sediment management --- adaptive management --- catchment modelling --- integrated management --- reservoir operation

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MDPI - Multidisciplinary Digital Publishing Institute (2)


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CC by-nc-nd (2)


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english (2)


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2019 (2)