ABSTRACT
Information on possible changes in future flood risk is essential for successful adaptation planning and risk management. However, various sources of uncertainty arise along the model chains used for the assessment of flood risk under climate change. Knowledge on the importance of these different sources of uncertainty can help to design future assessments of flood risk, and to identify areas of focus for further research that aims to reduce existing uncertainties. Here we investigate the role of four sources of epistemic uncertainty affecting the estimation of flood loss for changed climate conditions for a meso-scale, pre-alpine catchment. These are: the choice of a scenario-neutral method, climate projection uncertainty, hydrological model parameter sets, and the choice of the vulnerability function. To efficiently simulate a large number of loss estimates, a surrogate inundation model was used. 46,500 loss estimates were selected according to the change in annual mean precipitation and temperature of an ensemble of regional climate models, and considered for the attribution of uncertainty. Large uncertainty was found in the estimated loss for a 100-year flood event with losses ranging from a decrease of loss compared to estimations for present day climate, to more than a 7-fold increase. The choice of the vulnerability function was identified as the most important source of uncertainty explaining almost half of the variance in the estimates. However, uncertainty related to estimating floods for changed climate conditions contributed nearly as much. Hydrological model parametrisation was found to be negligible in the present setup. For our study area, these results highlight the importance of improving vulnerability function formulation even in a climate change context where additional major sources of uncertainty arise.
ABSTRACT
The Tambora volcano erupted in April 1815 caused many direct and indirect impacts on the climate system, as well as ecosystems and societies around the world. In Switzerland, the eruption contributed to the 1816 "Year Without a Summer", which is considered to be a key factor in generating the highest flooding ever documented of the Lake Constance (7th July 1817) and the flood of the Rhine in Basel. Snow was reported to remain during the summer of 1816, which laid the basis for a massive snow accumulation in the spring of 1817. The meltwater together with a triggering event led to the reported flooding. We aim to create a hydro-meteorological reconstruction of the 1816/1817 period in Switzerland to verify and quantify the historical sources and place them into present-day context. We used an analogue method that was based on historical measurements to generate temperature and precipitation fields for 1816/1817. These data drove a hydrological model that covers the Rhine Basin to Basel. We reproduced the reported features of the hydroclimate, especially in regards to the temperature and snow storage. We showed that the snow storage in spring 1816 and 1817 was substantial and attained the magnitude of a recent extreme, snow-rich winter (1999). However, simulations suggest that the snowfall alone in the spring of 1817, rather than the enduring snow from 1815/1816, led to the meltwater produced from the snow pack that contributed to the flooding in Lake Constance and Basel. These events were strongly underestimated, as the triggering rainfall event was reconstructed too weak. Artificial scenarios reveal that a precipitation amount with a magnitude higher than the largest recent flood (2005) was necessary to generate the documented flood levels. We conclude that these Tambora-following flood events were a product of an adverse combination of extreme weather within an extreme climate.
