Improving probabilistic flood forecasting through a data assimilation scheme based on genetic programming

Abstract

Abstract.Opportunities offered by high performance computing provide a significant degree of promise in the enhancement of the performance of real-time flood forecasting systems. In this paper, a real-time framework for probabilistic flood forecasting through data assimilation is presented. The distributed rainfall-runoff real-time interactive basin simulator (RIBS) model is selected to simulate the hydrological process in the basin. Although the RIBS model is deterministic, it is run in a probabilistic way through the results of calibration developed in a previous work performed by the authors that identifies the probability distribution functions that best characterise the most relevant model parameters. Adaptive techniques improve the result of flood forecasts because the model can be adapted to observations in real time as new information is available. The new adaptive forecast model based on genetic programming as a data assimilation technique is compared with the previously developed flood forecast model based on the calibration results. Both models are probabilistic as they generate an ensemble of hydrographs, taking the different uncertainties inherent in any forecast process into account. The Manzanares River basin was selected as a case study, with the process being computationally intensive as it requires simulation of many replicas of the ensemble in real time.

Hydrometeorological multi-model ensemble simulations of the 4 November 2011 flash flood event in Genoa, Italy, in the framework of the DRIHM project

“…Input data and state variables are also represented as data layers using the same scheme. Model philosophy is based on the idea of stressing the role of topography in the runoff generation process, but keeping model complexity within reasonable limits to allow for the real time application of flood forecasting in midsize and large basins (Mediero et al, 2012). The basic objective is to map the topographically driven evolution of saturated areas as the storm progresses.…”

Hydrometeorological multi-model ensemble simulations of the 4 November 2011 flash-flood event in Genoa, Italy, in the framework of the DRIHM project

“…For smallto-medium-size catchments, rainfall-discharge hydrological models are appropriate, acknowledged tools to forecast flash floods. Given the short hydrological response times of these catchments, it is necessary to use quantitative precipitation forecasts instead of single observations to drive these hydrological models in order to enhance the forecast lead times (Melone et al, 2005).…”