An operational hydrological ensemble prediction system for the city of Zurich (Switzerland): skill, case studies and scenarios

Abstract

Abstract. The Sihl River flows through Zurich, Switzerland's most populated city, for which it represents the largest flood threat. To anticipate extreme discharge events and provide decision support in case of flood risk, a hydrometeorological ensemble prediction system (HEPS) was launched operationally in 2008. This model chain relies on limitedarea atmospheric forecasts provided by the deterministic model COSMO-7 and the probabilistic model COSMO-LEPS. These atmospheric forecasts are used to force a semidistributed hydrological model (PREVAH), coupled to a hydraulic model (FLORIS). The resulting hydrological forecasts are eventually communicated to the stakeholders involved in the Sihl discharge management. This fully operational setting provides a real framework with which to compare the potential of deterministic and probabilistic discharge forecasts for flood mitigation.To study the suitability of HEPS for small-scale basins and to quantify the added-value conveyed by the probability information, a reforecast was made for the period June 2007 to December 2009 for the Sihl catchment (336 km 2 ). Several metrics support the conclusion that the performance gain can be of up to 2 days lead time for the catchment considered. Brier skill scores show that overall COSMO-LEPS-based hydrological forecasts outperforms their COSMO-7-based counterparts for all the lead times and event intensities considered. The small size of the Sihl catchment does not prevent skillful discharge forecasts, but makes them particularlyCorrespondence to: N. Addor (nans.addor@geo.uzh.ch) dependent on correct precipitation forecasts, as shown by comparisons with a reference run driven by observed meteorological parameters. Our evaluation stresses that the capacity of the model to provide confident and reliable mid-term probability forecasts for high discharges is limited. The two most intense events of the study period are investigated utilising a novel graphical representation of probability forecasts, and are used to generate high discharge scenarios. They highlight challenges for making decisions on the basis of hydrological predictions, and indicate the need for a tool to be used in addition to forecasts to compare the different mitigation actions possible in the Sihl catchment. No definitive conclusion on the model chain capacity to forecast flooding events endangering the city of Zurich could be drawn because of the under-sampling of extreme events. Further research on the form of the reforecasts needed to infer on floods associated to return periods of several decades, centuries, is encouraged.

A Comparison of Ensemble Strategies for Flash Flood Forecasting: The 12 October 2007 Case Study in Valencia, Spain

“…Nowadays, state-of-the-art convection-permitting NWP models realistically capture the initiation and intensification of convectively driven rainfalls with similar spatial and temporal scales to the flash flood-prone catchments. QPFs can be directly used to drive rainfall-runoff models without the need to implement additional downscaling procedures (Verbunt et al 2007;Amengual et al 2008;Vincendon et al 2011;Addor et al 2011).…”

Crash tests for forward-looking flood control in the city of Zürich (Switzerland)

“…1). A similar setup is implemented in real-time since 2008 (Addor et al, 2011). Data sources and data processing follows the procedures described in Viviroli et al (2009a).…”

“…Buchecker et al, 2013). As a first measure in 2008 a state-of-the-art hydrological ensemble prediction system was established (Addor et al, 2011). More recently a series of studies was completed to provide the scientific basis for decision concerning future flood control measures.…”

“…This small river represents the most severe flood threat for the city of Zürich. Damages of several billions Euros including the complete flooding of the central railway station are possible (Addor et al, 2011). Continuous measurements of the Sihl discharge in Zürich started in 1919.…”

Do probabilistic forecasts lead to better decisions?

“…Krzysztofowicz, 2001;Pappenberger et al, 2005;Bogner and Pappenberger, 2011;Addor et al, 2011). To make the best possible decisions, forecasts with uncertainty estimates are essential.…”