Suchergebnisse

Abstract. The 2018 drought event had severe ecological, economic, and social impacts. How extreme was it in Switzerland? We addressed this question by looking at different types of drought, including meteorological, hydrological, agricultural, and groundwater drought, and at the two characteristics deficit and deficit duration. The analysis consisted of three main steps: (1) event identification using a threshold-level approach, (2) drought frequency analysis, and (3) comparison of the 2018 event to the severe 2003 and 2015 events. In Step 2 the variables precipitation, discharge, soil moisture, and low-flow storage were first considered separately in a univariate frequency analysis; pairs of variables were then investigated jointly in a bivariate frequency analysis using a copula model for expressing the dependence between the two variables under consideration. Our results show that the 2018 event was especially severe in north-eastern Switzerland in terms of soil moisture, with return periods locally exceeding 100 years. Slightly longer return periods were estimated when discharge and soil moisture deficits were considered together. The return period estimates depended on the region, variable, and return period considered. A single answer to the question of how extreme the 2018 drought event was in Switzerland is therefore not possible – rather, it depends on the processes one is interested in.

Abstract. Flash floods evolve rapidly during and after heavy precipitation events
and represent a potential risk for society. To predict the timing and
magnitude of a peak runoff, it is common to couple meteorological and
hydrological models in a forecasting chain. However, hydrological models rely
on strong simplifying assumptions and hence need to be calibrated. This makes
their application difficult in catchments where no direct observation of
runoff is available. To address this gap, a flash-flood forecasting chain is presented based on
(i) a nowcasting product which combines radar and rain gauge rainfall data
(CombiPrecip); (ii) meteorological data from state-of-the-art numerical
weather prediction models (COSMO-1, COSMO-E); (iii) operationally available
soil moisture estimations from the PREVAH hydrological model; and (iv) a
process-based runoff generation module with no need for calibration
(RGM-PRO). This last component uses information on the spatial distribution
of dominant runoff processes from the so-called maps of runoff types, which
can be derived with different mapping approaches with increasing involvement
of expert knowledge. RGM-PRO is event-based and parametrised a priori based
on the results of sprinkling experiments. This prediction chain has been evaluated using data from April to September
2016 in the Emme catchment, a medium-sized flash-flood-prone basin in the
Swiss Prealps. Two novel forecasting chains were set up with two different
maps of runoff types, which allowed sensitivity of the forecast performance
to the mapping approaches to be analysed. Furthermore, special emphasis was
placed on the predictive power of the new forecasting chains in nested
subcatchments when compared with a prediction chain including an original
version of the runoff generation module of PREVAH calibrated for one event. Results showed a low sensitivity of the predictive power to the amount of
expert knowledge included for the mapping approach. The forecasting chain
including a map of runoff types with high involvement of expert knowledge did
not guarantee more skill. In the larger basins of the Emme region,
process-based forecasting chains revealed comparable skill to a prediction
system including a conventional hydrological model. In the small nested
subcatchments, although the process-based forecasting chains outperformed the
original runoff generation module, no forecasting chain showed satisfying
skill in the sense that it could be useful for decision makers. Despite the short period available for evaluation, preliminary outcomes of
this study show that operational flash-flood predictions in ungauged basins
can benefit from the use of information on runoff processes, as no long-term
runoff measurements are needed for calibration.

Abstract. Heavy precipitation on the south side of the central Alps
produced a catastrophic flood in October 1868. We assess the damage and
societal impacts, as well as the atmospheric and hydrological drivers using
documentary evidence, observations and novel numerical weather and runoff
simulations. The greatest damage was concentrated close to the Alpine divide and Lago
Maggiore. An atmospheric reanalysis emphasizes the repeated occurrence of
streamers of high potential vorticity as precursors of heavy precipitation.
Dynamical downscaling indicates high freezing levels (4000 m a.s.l.),
extreme precipitation rates (max. 270 mm 24 h−1) and weather dynamics that agree well with observed
precipitation and damage, and with existing concepts of forced low-level
convergence, mid-level uplift and iterative northeastward propagation of
convective cells. Simulated and observed peak levels of Lago Maggiore differ
by 2 m, possibly because the exact cross section of the lake outflow is
unknown. The extreme response of Lago Maggiore cannot be attributed to low
forest cover. Nevertheless, such a paradigm was adopted by policy makers
following the 1868 flood, and used to implement nationwide afforestation
policies and hydraulic structures. These findings illustrate the potential of high-resolution,
hydrometeorological models – strongly supported by historical methods –
to shed new light on weather events and their socio-economic implications in
the 19th century.