A Coupling Method of Ensemble Precipitation Forecast and Real-time Flood Probabilistic Forecast

Abstract

The invention provides an ensemble rainfall forecast and real-time flood probability forecast coupling method. The method comprises the steps of collecting hydro-meteorological basic materials of drainage basins and ensemble forecast rainfall data and building a hydrological model to obtain ensemble flood certainty forecasts; on the basis of real-time correction of error, converting corrected ensemble flood certainty forecasts into ensemble flood probability forecasts; performing weight fusion on the obtained ensemble flood probability forecasts to obtain comprehensive real-time flood probability forecasts. The method couples ensemble rainfall forecast information and Copula-BFS and is capable of considering the comprehensive influence of uncertainties such as rainfall forecast input, hydrological model parameters and model structures and estimating the total uncertainty of flood forecasts quantitatively. By performing error real-time correction on corresponding flood certainty forecasts before flood probability forecasts, the flood forecast precision can be increased and the performance of flood uncertainty forecast intervals is improved.

Description

technical field [0001] The invention belongs to the field of flood forecasting, and in particular relates to a coupling method of integrated precipitation forecasting and real-time flood probability forecasting. Background technique [0002] Flood forecasting is one of the important contents of non-engineering measures for flood control and disaster reduction, and it directly serves for flood control and emergency rescue and reservoir operation scheduling. Due to the influence of uncertainties in hydrological model input, model parameters and model structure, the forecast results inevitably have uncertainties. Therefore, quantitatively estimating the uncertainty of flood forecast has important theoretical significance and practical value. [0003] The Bayesian Probabilistic Forecasting System (BFS) proposed by American scholar Krzysztofowicz is a theoretical framework to solve the uncertainty of flood forecasting through the probabilistic forecasting of deterministic hydrol...

AI Technical Summary

Problems solved by technology

However, Copula-BFS still has the following deficiencies: (1) It does not consider the uncertainty of precipitation forecast in the forecast period

(2) No real-time correction of errors in deterministic flood forecasting

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