Advances in Hydrologic Forecasts and Water Resources Management


Book Description

The impacts of climate change on water resource management, as well as increasingly severe natural disasters over the last decades, have caught global attention. Reliable and accurate hydrological forecasts are essential for efficient water resource management and the mitigation of natural disasters. While the notorious nonlinear hydrological processes make accurate forecasts a very challenging task, it requires advanced techniques to build accurate forecast models and reliable management systems. One of the newest techniques for modeling complex systems is artificial intelligence (AI). AI can replicate the way humans learn and has great capability to efficiently extract crucial information from large amounts of data to solve complex problems. The fourteen research papers published in this Special Issue contribute significantly to the uncertainty assessment of operational hydrologic forecasting under changing environmental conditions and the promotion of water resources management by using the latest advanced techniques, such as AI techniques. The fourteen contributions across four major research areas: (1) machine learning approaches to hydrologic forecasting; (2) uncertainty analysis and assessment on hydrological modeling under changing environments; (3) AI techniques for optimizing multi-objective reservoir operation; (4) adaption strategies of extreme hydrological events for hazard mitigation. The papers published in this issue will not only advance water sciences but also help policymakers to achieve more sustainable and effective water resource management.




Hydrology and Water Resources Management in a Changing World


Book Description

Hydrology and water resources management in a changing world reflects important challenges for both researchers and practitioners in the public and private sectors. This book features contributions from all sectors on the following themes: water in urban areas; groundwater; floods; climate services; hydrological processes and models; hydropower; water consumption; environmental impact and water quality. In Focus – a book series that showcases the latest accomplishments in water research. Each book focuses on a specialist area with papers from top experts in the field. It aims to be a vehicle for in-depth understanding and inspire further conversations in the sector.




Thriving on Our Changing Planet


Book Description

We live on a dynamic Earth shaped by both natural processes and the impacts of humans on their environment. It is in our collective interest to observe and understand our planet, and to predict future behavior to the extent possible, in order to effectively manage resources, successfully respond to threats from natural and human-induced environmental change, and capitalize on the opportunities â€" social, economic, security, and more â€" that such knowledge can bring. By continuously monitoring and exploring Earth, developing a deep understanding of its evolving behavior, and characterizing the processes that shape and reshape the environment in which we live, we not only advance knowledge and basic discovery about our planet, but we further develop the foundation upon which benefits to society are built. Thriving on Our Changing Planet presents prioritized science, applications, and observations, along with related strategic and programmatic guidance, to support the U.S. civil space Earth observation program over the coming decade.




Advances in Water Resources Management


Book Description

This volume provides in-depth coverage of such topics as multi-reservoir system operation theory and practice, management of aquifer systems connected to streams using semi-analytical models, one-dimensional model of water quality and aquatic ecosystem-ecotoxicology in river systems, environmental and health impacts of hydraulic fracturing and shale gas, bioaugmentation for water resources protection, wastewater renovation by flotation for water pollution control, determination of receiving water’s reaeration coefficient in the presence of salinity for water quality management, sensitivity analysis for stream water quality management, river ice process, and computer-aided mathematical modeling of water properties. This critical volume will serve as a valuable reference work for advanced undergraduate and graduate students, designers of water resources systems, and scientists and researchers. The goals of the Handbook of Environmental Engineering series are: (1) to cover entire environmental fields, including air and noise pollution control, solid waste processing and resource recovery, physicochemical treatment processes, biological treatment processes, biotechnology, biosolids management, flotation technology, membrane technology, desalination technology, water resources, natural control processes, radioactive waste disposal, hazardous waste management, and thermal pollution control; and (2) to employ a multimedia approach to environmental conservation and protection since air, water, soil and energy are all interrelated.




Advances in Streamflow Forecasting


Book Description

Advances in Streamflow Forecasting: From Traditional to Modern Approaches covers the three major data-driven approaches of streamflow forecasting including traditional approach of statistical and stochastic time-series modelling with their recent developments, stand-alone data-driven approach such as artificial intelligence techniques, and modern hybridized approach where data-driven models are combined with preprocessing methods to improve the forecast accuracy of streamflows and to reduce the forecast uncertainties. This book starts by providing the background information, overview, and advances made in streamflow forecasting. The overview portrays the progress made in the field of streamflow forecasting over the decades. Thereafter, chapters describe theoretical methodology of the different data-driven tools and techniques used for streamflow forecasting along with case studies from different parts of the world. Each chapter provides a flowchart explaining step-by-step methodology followed in applying the data-driven approach in streamflow forecasting. This book addresses challenges in forecasting streamflows by abridging the gaps between theory and practice through amalgamation of theoretical descriptions of the data-driven techniques and systematic demonstration of procedures used in applying the techniques. Language of this book is kept simple to make the readers understand easily about different techniques and make them capable enough to straightforward replicate the approach in other areas of their interest. This book will be vital for hydrologists when optimizing the water resources system, and to mitigate the impact of destructive natural disasters such as floods and droughts by implementing long-term planning (structural and nonstructural measures), and short-term emergency warning. Moreover, this book will guide the readers in choosing an appropriate technique for streamflow forecasting depending upon the given set of conditions. - Contributions from renowned researchers/experts of the subject from all over the world to provide the most authoritative outlook on streamflow forecasting - Provides an excellent overview and advances made in streamflow forecasting over the past more than five decades and covers both traditional and modern data-driven approaches in streamflow forecasting - Includes case studies along with detailed flowcharts demonstrating a systematic application of different data-driven models in streamflow forecasting, which helps understand the step-by-step procedures




Hydrometeorology


Book Description

This book describes recent developments in hydrometeorological forecasting techniques for a range of timescales, from short term to seasonal and longer terms. It conveniently brings together both meteorological and hydrological aspects in a single volume.




Climate Change and Water Resources Management


Book Description

Many challenges, including climate change, face the Nation¿s water managers. The Intergovernmental Panel on Climate Change (IPCC) has provided estimates of how climate may change, but more understanding of the processes driving the changes, the sequences of the changes, and the manifestation of these global changes at different scales could be beneficial. Since the changes will likely affect fundamental drivers of the hydrological cycle, climate change may have a large impact on water resources and water resources managers. The purpose of this interagency report is to explore strategies to improve water management by tracking, anticipating, and responding to climate change. Charts and tables.




Review of the GAPP Science and Implementation Plan


Book Description

Water managers rely on predicting changes in the hydrologic cycle on seasonal-to-interannual time frames to prepare for water resource needs. Seasonal to interannual predictability of the hydrologic cycle is related to local and remote influences involving land processes and ocean processes, such as the El Niño Southern Oscillation. Although advances in understanding land-surface processes show promise in improving climate prediction, incorporating this information into water management decision processes remains a challenge since current models provide only limited information for predictions on seasonal and longer time scales. To address these needs, the Global Energy and Water Cycle Experiment (GEWEX) Americas Prediction Project (GAPP) was established in 2001 to improve how changes in water resources are predicted on intraseasonal-to-interannual time scales for the continental United States. The GAPP program has developed a science and implementation plan to guide its science activities, which describes strategies for improving prediction and decision support in the hydrologic sciences. This report by the National Research Council provides a review of the GAPP Science and Implementation Plan, outlining suggestions to strengthen the plan and the GAPP program overall.




Toward a New Advanced Hydrologic Prediction Service (AHPS)


Book Description

The National Weather Service (NWS) is responsible for providing flood forecasts and warnings in the United States. The agency established the Advanced Hydrologic Prediction Services (AHPS) program in 1997 to advance technology for hydrologic services, specifically to provide accurate forecasts that support timely warnings for all users of hydrologic predictions. AHPS strives to provide information at the right time to facilitate adequate responses to mitigate damages to life, livelihoods, and property. AHPS is slated to be fully implemented nationwide in 2013. With seven years still remaining in its development and implementation timeline, a review of the program now is critical to providing NWS with information it needs to maximize the effectiveness of the AHPS program. This report assesses AHPS in respect to hydrologic science and technology research, river routing and mechanics, "systems" engineering aspects, and implementation. Overall, this report finds AHPS to be an ambitious program that promises to provide services and products that are timely and necessary. The report calls for AHPS to develop a detailed and comprehensive, multi-year implementation plan and for the program's goals and budget to be brought into closer alignment.




Flood Forecasting Using Machine Learning Methods


Book Description

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.