TY - JOUR

T1 - Advances in real-time flood forecasting.

AU - Young, Peter C.

PY - 2002/7/15

Y1 - 2002/7/15

N2 - This paper discusses the modelling of rainfall-flow (rainfall-run-off) and flow-routeing processes in river systems within the context of real-time flood forecasting. It is argued that deterministic, reductionist (or 'bottom-up') models are inappropriate for real-time forecasting because of the inherent uncertainty that characterizes river-catchment dynamics and the problems of model over-parametrization. The advantages of alternative, efficiently parametrized data-based mechanistic models, identified and estimated using statistical methods, are discussed. It is shown that such models are in an ideal form for incorporation in a real-time, adaptive forecasting system based on recursive state-space estimation (an adaptive version of the stochastic Kalman filter algorithm). An illustrative example, based on the analysis of a limited set of hourly rainfall-flow data from the River Hodder in northwest England, demonstrates the utility of this methodology in difficult circumstances and illustrates the advantages of incorporating real-time state and parameter adaption.

AB - This paper discusses the modelling of rainfall-flow (rainfall-run-off) and flow-routeing processes in river systems within the context of real-time flood forecasting. It is argued that deterministic, reductionist (or 'bottom-up') models are inappropriate for real-time forecasting because of the inherent uncertainty that characterizes river-catchment dynamics and the problems of model over-parametrization. The advantages of alternative, efficiently parametrized data-based mechanistic models, identified and estimated using statistical methods, are discussed. It is shown that such models are in an ideal form for incorporation in a real-time, adaptive forecasting system based on recursive state-space estimation (an adaptive version of the stochastic Kalman filter algorithm). An illustrative example, based on the analysis of a limited set of hourly rainfall-flow data from the River Hodder in northwest England, demonstrates the utility of this methodology in difficult circumstances and illustrates the advantages of incorporating real-time state and parameter adaption.

KW - Rainfall-Flow Processes

KW - Data-Based Mechanistic Models

KW - Recursive Estimation

KW - Real-Time Forecasting

KW - Parameter Adaption

KW - Variance Adaption

U2 - 10.1098/rsta.2002.1008

DO - 10.1098/rsta.2002.1008

M3 - Journal article

VL - 360

SP - 1433

EP - 1450

JO - Philosophical Transactions A: Mathematical, Physical and Engineering Sciences

JF - Philosophical Transactions A: Mathematical, Physical and Engineering Sciences

SN - 1364-503X

IS - 1796

ER -