Recursive Streamflow Forecasting

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A01=Andras Szollosi Nagy
A01=Jozsef Szilagyi
approach
aquifer
ARMA Model
Author_Andras Szollosi Nagy
Author_Jozsef Szilagyi
Category=KNA
Deterministic Model
Discrete Time Instants
eq_bestseller
eq_business-finance-law
eq_isMigrated=1
eq_isMigrated=2
eq_nobargain
eq_non-fiction
filter
framework
impulse
Impulse Response Function
Input Detection
interactions
kalman
Kalman Filter
Kinematic Wave
Kinematic Wave Equation
Linear Transformation
Lower Boundary Condition
matrix
Observability Matrix
Ordinary Differential Equation
Real Time Forecasting
Saint Venant Equations
space
State Space Approach
State Space Description
State Space Framework
State Transition Matrix
state-transition
Storage Delay Time
Storage Element
Stored Water Volumes
Stream Aquifer Interactions
Unit Pulse Response
Wave Equation
Yule Walker Equation

Product details

  • ISBN 9780415569019
  • Weight: 390g
  • Dimensions: 160 x 240mm
  • Publication Date: 25 Jun 2010
  • Publisher: Taylor & Francis Ltd
  • Publication City/Country: GB
  • Product Form: Paperback
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This textbook is a practical guide to real-time streamflow forecasting that provides a rigorous description of a coupled stochastic and physically based flow routing method and its practical applications. This method is used in current times of record-breaking floods to forecast flood levels by various hydrological forecasting services. By knowing in advance when, where, and at what level a river will crest, appropriate protection works can be organized, reducing casualties and property damage. Through its real-life case examples and problem listings, the book teaches hydrology and civil engineering students and water-resources practitioners the physical forecasting model and allows them to apply it directly in real-life problems of streamflow simulation and forecasting. Designed as a textbook for courses on hydroinformatics and water management, it includes exercises and a CD-ROM with MATLAB® codes for the simulation of streamflows and the creation of real-time hydrological forecasts.

Jozsef Szilagyi, Andras Szollosi Nagy

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