Author: Publisher:
ISBN: 9814464759
Category :
Languages : en
Pages :
Book Description
Advances in Data-Based Approaches for Hydrologic Modeling and Forecasting
Author: Advances in Hydrological Forecasting
Author: Minxue HePublisher:
ISBN: 9783036516806
Category :
Languages : en
Pages : 110
Book Description
This book collected recent studies on the latest methodological and operational advances in hydrological forecasting. Specifically, the collection of papers covers a range of topics related to improving hydrological forecasting via new datasets and innovative approaches.
Advances in Hydrologic Forecasts and Water Resources Management
Author: Fi-John ChangPublisher: MDPI
ISBN: 3039368044
Category : Technology & Engineering
Languages : en
Pages : 274
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.
Advances in Data-based Approaches for Hydrologic Modeling and Forecasting
Author: Bellie SivakumarPublisher: World Scientific
ISBN: 9814307971
Category : Science
Languages : en
Pages : 542
Book Description
This book comprehensively accounts the advances in data-based approaches for hydrologic modeling and forecasting. Eight major and most popular approaches are selected, with a chapter for each stochastic methods, parameter estimation techniques, scaling and fractal methods, remote sensing, artificial neural networks, evolutionary computing, wavelets, and nonlinear dynamics and chaos methods. These approaches are chosen to address a wide range of hydrologic system characteristics, processes, and the associated problems. Each of these eight approaches includes a comprehensive review of the fundamental concepts, their applications in hydrology, and a discussion on potential future directions.
Advances in Hydrologic Forecasts and Water Resources Management
Author: Fi-John ChangPublisher:
ISBN: 9783036516790
Category :
Languages : en
Pages : 109
Book Description
This book collected recent studies on the latest methodological and operational advances in hydrological forecasting. Specifically, the collection of papers covers a range of topics related to improving hydrological forecasting via new datasets and innovative approaches.
Advances in Streamflow Forecasting
Author: Priyanka SharmaPublisher: Elsevier
ISBN: 0128209240
Category : Science
Languages : en
Pages : 404
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
Toward a New Advanced Hydrologic Prediction Service (AHPS)
Author: National Research CouncilPublisher: National Academies Press
ISBN: 0309101441
Category : Science
Languages : en
Pages : 84
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.
Advanced Hydroinformatics
Author: Gerald A. Corzo PerezPublisher: John Wiley & Sons
ISBN: 111963931X
Category : Science
Languages : en
Pages : 483
Book Description
Advanced Hydroinformatics Advanced Hydroinformatics Machine Learning and Optimization for Water Resources The rapid development of machine learning brings new possibilities for hydroinformatics research and practice with its ability to handle big data sets, identify patterns and anomalies in data, and provide more accurate forecasts. Advanced Hydroinformatics: Machine Learning and Optimization for Water Resources presents both original research and practical examples that demonstrate how machine learning can advance data analytics, accuracy of modeling and forecasting, and knowledge discovery for better water management. Volume Highlights Include: Overview of the application of artificial intelligence and machine learning techniques in hydroinformatics Advances in modeling hydrological systems Different data analysis methods and models for forecasting water resources New areas of knowledge discovery and optimization based on using machine learning techniques Case studies from North America, South America, the Caribbean, Europe, and Asia The American Geophysical Union promotes discovery in Earth and space science for the benefit of humanity. Its publications disseminate scientific knowledge and provide resources for researchers, students, and professionals.
Advanced Hydrologic Prediction Services
Author: Publisher:
ISBN:
Category : Flood forecasting
Languages : en
Pages : 24
Book Description
Hydrometeorology
Author: Kevin SenePublisher: Springer Science & Business Media
ISBN: 904813403X
Category : Science
Languages : en
Pages : 355
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.
