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Please use this identifier to cite or link to this item:
http://krishi.icar.gov.in/jspui/handle/123456789/49596
Title: | Advances in Streamflow Forecasting – from Traditional to Modern Approaches |
Other Titles: | Not Available |
Authors: | Deepesh Machiwal Priyanka Sharma |
ICAR Data Use Licennce: | http://krishi.icar.gov.in/PDF/ICAR_Data_Use_Licence.pdf |
Author's Affiliated institute: | ICAR::Central Arid Zone Research Institute National Institute of Hydrology, Roorkee |
Published/ Complete Date: | 2021-07-05 |
Project Code: | Not Available |
Keywords: | Streamflow forecasting Data driven techniques Traditional methods Advanced methods Time series modeling |
Publisher: | Elsevier |
Citation: | Sharma, P. and Machiwal, D. (Editors) (2021). Advances in Streamflow Forecasting – from Traditional to Modern Approaches. Elsevier, Netherlands, 381pp. |
Series/Report no.: | Not Available; |
Abstract/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 modeling 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 pre-processing methods to improve the forecast accuracy of streamflows and to reduce the forecast uncertainties. The 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 the 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 non-structural 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. Key Features • 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 |
Description: | Not Available |
ISBN: | 978-0-12-820673-7 |
Type(s) of content: | Book |
Sponsors: | Not Available |
Language: | English |
Name of Journal: | Not Available |
Volume No.: | Not Available |
Page Number: | Not Available |
Name of the Division/Regional Station: | Division of Natural Resources |
Source, DOI or any other URL: | Not Available |
URI: | http://krishi.icar.gov.in/jspui/handle/123456789/49596 |
Appears in Collections: | NRM-CAZRI-Publication |
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