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Recursive streamflow forecasting : a state-space approach

✍ Scribed by József Szilágyi; András Szöllösi-Nagy

Publisher
CRC Press
Year
2010
Leaves
192
Series
UNESCO-IHE lecture note series
Category
Library
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✦ Table of Contents


Content: 1.Introduction --
2. Overview Of Continuous Flow-Routing Techniques --
2.1. Basic equations of the one-dimensional, gradually varied non-permanent open-channel flow --
2.2. Diffusion wave equation --
2.3. Kinematic wave equation --
2.4. Flow-routing methods --
2.4.1. Derivation of the storage equation from the Saint-Venant equations --
2.4.2. Kalinin[-]Milyukov[-]Nash cascade --
2.4.3. Muskingum channel routing technique --
3. State[-]space Description Of The Spatially Discretized Linear Kinematic Wave --
3.1. State[-]space formulation of the continuous, spatially discrete linear kinematic wave --
3.2. Impulse response of the continuous, spatially discrete linear kinematic wave --
4. State[-]space Description Of The Continuous Kalinin[-]Milyukov[-]Nash (KMN) Cascade --
4.1. State equation of the continuous KMN-cascade --
4.2. Impulse[-]response of the continuous KMN-cascade and its equivalence with the continuous, spatially discrete, linear kinematic wave --
4.3. Continuity, steady state, and transitivity of the KMN-cascade --
5. State[-]space Description Of The Discrete Linear Cascade Model (DLCM) And Its Properties: The Pulse-Data System Approach --
5.1. Trivial discretization of the continuous KMN-cascade and its consequences --
5.2. conditionally adequate discrete model of the continuous KMN-cascade --
5.2.1. Derivation of the discrete cascade, its continuity, steady state, and transitivity --
5.2.2. Relationship between conditionally adequate discrete models with different sampling intervals --
5.2.3. Temporal discretization and numerical diffusion --
5.3. Deterministic prediction of the state variables of the discrete cascade using a linear transformation --
5.4. Calculation of system characteristics --
5.4.1. Unit-pulse response of the discrete cascade --
5.4.2. Unit-step response of the discrete cascade --
5.5. Calculation of initial conditions for the discrete cascade --
5.6. Deterministic prediction of the discrete cascade output and its asymptotic behavior --
5.7. inverse of prediction: input detection --
6. Linear Interpolation (LI) Data System Approach --
6.1. Formulation of the discrete cascade in the LI-data system framework --
6.2. Discrete state[-]space approximation of the continuous KMN-cascade of noninteger storage elements --
6.3. Application of the discrete cascade for flow-routing with unknown rating curves --
6.4. Detecting historical channel flow changes by the discrete linear cascade --
7. DLCM And Stream[-]aquifer Interaction --
7.1. Accounting for stream[-]aquifer interactions in DLCM --
7.2. Assessing groundwater contribution to the channel via input detection --
8. Handling Of Model Error: The Deterministic[-]stochastic Model And Its Prediction Updating --
8.1. stochastic model of forecast errors --
8.2. Recursive prediction and updating --
9. Some Practical Aspects Of Model Application For Real-Time Operational Forecasting --
9.1. Model parameterization --
9.2. Comparison of a pure stochastic, a deterministic (DLCM), and deterministic[-]stochastic models --
9.3. Application of the deterministic[-]stochastic model for the Danube basin in Hungary --
A.I.1. State[ --
]space description of linear dynamic systems --
A.I.2. Algorithm of the discrete linear Kalman filter --
A.II.1. Sample MATLAB scripts.

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