Projected changes in Rhine River flood seasonality under global warming

Abstract

Abstract. Climatic change alters the frequency and intensity of natural hazards. In order to assess potential future changes in flood seasonality in the Rhine River basin, we analyse changes in streamflow, snowmelt, precipitation and evapotranspiration at 1.5, 2.0 and 3.0 ∘C global warming levels. The mesoscale hydrological model (mHM) forced with an ensemble of climate projection scenarios (five general circulation models under three representative concentration pathways) is used to simulate the present and future climate conditions of both pluvial and nival hydrological regimes. Our results indicate that future changes in flood characteristics in the Rhine River basin are controlled by increases in antecedent precipitation and diminishing snowpacks. In the pluvial-type sub-basin of the Moselle River, an increasing flood potential due to increased antecedent precipitation encounters declining snowpacks during winter. The decrease in snowmelt seems to counterbalance increasing precipitation, resulting in only small and transient changes in streamflow maxima. For the Rhine Basin at Basel, rising temperatures cause changes from solid to liquid precipitation, which enhance the overall increase in precipitation sums, particularly in the cold season. At the gauge at Basel, the strongest increases in streamflow maxima show up during winter, when strong increases in liquid precipitation encounter almost unchanged snowmelt-driven runoff. The analysis of snowmelt events for the gauge at Basel suggests that at no point in time during the snowmelt season does a warming climate result in an increase in the risk of snowmelt-driven flooding. Snowpacks are increasingly depleted with the course of the snowmelt season. We do not find indications of a transient merging of pluvial and nival floods due to climate warming. To refine attained results, next steps need to be the representation of glaciers and lakes in the model set-up, the coupling of simulations to a streamflow component model and an independent validation of the snow routine using satellite-based snow cover maps.

Continuous Negotiation in Climate Adaptation: The Challenge of Co-Evolution for the Capability Approach to Justice

“…Due to climate change, in the long term, the discharge pattern of the Rhine river is expected to become more variable, with higher and lower extremes [87][88][89][90][91]. In the Rhine watershed, researchers already measured a change between 1981 and 2010: precipitation decreased with 80 mm and evaporation increased with 70 mm [90].…”

“…The Royal Dutch Meteorological Institute (KNMI) translates the IPCC scenarios to the Dutch context with the KNMI'14 scenarios [89]. In all KNMI'14 scenarios, the chance of discharges above 12.000 m 3 /s increases from once every 100 years to once every 30 years [88]. In the more extreme scenarios, beyond 2085, this can even be once every ten years [88].…”

“…In all KNMI'14 scenarios, the chance of discharges above 12.000 m 3 /s increases from once every 100 years to once every 30 years [88]. In the more extreme scenarios, beyond 2085, this can even be once every ten years [88]. Lower discharges are currently only projected to occur with the high-end scenarios.…”

Machine Learning Reveals a Significant Shift in Water Regime Types Due to Projected Climate Change

“…The presented modeling chain that connects GCM outputs with hydrological models has been established in numerous research projects to estimate the impact of projected climate change on river runoff [18][19][20]. Depending on the underlying hydrological model used, runoff estimates could be represented at different spatial (global, regional, basinscale) and temporal (daily, monthly, annual) resolutions.…”

“…Depending on the underlying hydrological model used, runoff estimates could be represented at different spatial (global, regional, basinscale) and temporal (daily, monthly, annual) resolutions. Then these estimates serve as a basis of impact assessment-e.g., depicting trends [21] or analyzing differences between runoff characteristics such as flood magnitude and timing on historical and projected periods [13,[16][17][18][19][20]22]. Thus, individual runoff characteristics are in the strong focus of studies devoted to climate change impact assessment.…”