Publication

Application of an Ensemble Kalman filter to a semi-distributed hydrological flood forecasting system in alpine catchments

Abstract

One of the key success factor for hydrological forecasts is the establishment of initial conditions that represent well the conditions of the simulated basin at the beginning of the forecast. Real-time Data Assimilation (DA) has been shown to allow improving these initial conditions. In this article, two DA approaches are compared with the reference scenario working without DA (Control). In both approaches, discharge data at gauging station are assimilated. In the first approach, a volume-based update (VBU) compares the simulated and observed volumes over the past 24 hours to compute a correction factor used to update the soil water saturation in the upstream part of the semi-distributed hydrological model. In the second approach, an Ensemble Kalman Filter (EnKF) is implemented to account for the uncertainty in precipitation, temperature and discharge data. The comparison is carried out over 2 sub-basins of the Upper Rhône River basin upstream of Lake Geneva, where the MINERVE flood forecasting and management system is implemented. Results differ over the two studied basins. In one basin, the two data assimilation perform better than the Control simulation with the lowest error given by the VBU up to a forecast horizon of 35 hour and by the EnKF for higher forecast horizons. In the second basin, EnKF gives the lowest error over the few first hours of forecast, but then provides the weakest performance. The lowest error is given by the Control simulation, because the model already performs very well on the event without data assimilation.

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Related concepts (34)
Data assimilation
Data assimilation is a mathematical discipline that seeks to optimally combine theory (usually in the form of a numerical model) with observations. There may be a number of different goals sought – for example, to determine the optimal state estimate of a system, to determine initial conditions for a numerical forecast model, to interpolate sparse observation data using (e.g. physical) knowledge of the system being observed, to set numerical parameters based on training a model from observed data.
Lake Geneva
Lake Geneva (le Léman lə lemɑ̃, lac Léman lak lemɑ̃, rarely lac de Genève lak də ʒ(ə)nɛv; Lago Lemano; Genfersee ˈɡɛnfərˌzeː; Lai da Genevra) is a deep lake on the north side of the Alps, shared between Switzerland and France. It is one of the largest lakes in Western Europe and the largest on the course of the Rhône. Sixty per cent () of the lake belongs to Switzerland (the cantons of Vaud, Geneva and Valais) and forty per cent () to France (the department of Haute-Savoie).
Rhône
The Rhône (rəʊn , ʁon) is a major river in France and Switzerland, rising in the Alps and flowing west and south through Lake Geneva and southeastern France before discharging into the Mediterranean Sea. At Arles, near its mouth, the river divides into the Great Rhône (le Grand Rhône) and the Little Rhône (le Petit Rhône). The resulting delta forms the Camargue region. The river's source is the Rhône Glacier, at the east edge of the Swiss canton of Valais.
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