Advances in Streamflow Forecasting

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  • Author : Priyanka Sharma
  • Publisher : Elsevier
  • Pages : 404 pages
  • ISBN : 0128209240
  • Rating : /5 from reviews
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Download or Read online Advances in Streamflow Forecasting full in PDF, ePub and kindle. this book written by Priyanka Sharma and published by Elsevier which was released on 20 June 2021 with total page 404 pages. We cannot guarantee that Advances in Streamflow Forecasting book is available in the library, click Get Book button and read full online book in your kindle, tablet, IPAD, PC or mobile whenever and wherever You Like. 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

Advances in Streamflow Forecasting

Advances in Streamflow Forecasting
  • Author : Priyanka Sharma,Deepesh Machiwal
  • Publisher : Elsevier
  • Release : 20 June 2021
GET THIS BOOK Advances in Streamflow Forecasting

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

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GET THIS BOOK Climate Models

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GET THIS BOOK Stochasticity Nonlinearity and Forecasting of Streamflow Processes

"Streamflow forecasting is of great importance to water resources management and flood defense. On the other hand, a better understanding of the streamflow process is fundamental for improving the skill of streamflow forecasting. The methods for forecasting streamflows may fall into two general classes: process-driven methods and data-driven methods. Equivalently, methods for understanding streamflow processes may also be broken into two categories: physically-based methods and mathematically-based methods. This publication focuses on using mathematically-based methods to analyze stochasticity and nonlinearity of

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GET THIS BOOK Flood Forecasting Using Machine Learning Methods

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GET THIS BOOK Feature Papers of Forecasting

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GET THIS BOOK Handbook of Engineering Hydrology Three Volume Set

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  • Release : 29 June 2017
GET THIS BOOK Recursive Streamflow Forecasting

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GET THIS BOOK Computational Science and Its Applications ICCSA 2019

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GET THIS BOOK Flood Forecasting

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