ALBERT

Description: This study assesses the change of the seasonal runoff characteristics in 98 catchments in central Europe between the reference period of 1981–2010, and in the near future (2011–2040), mid future (2041–2070) and far future (2071–2099). Therefore, a large ensemble of 50 hydrological simulations featuring the model WaSiM-ETH driven by a 50-member ensemble of the Canadian Regional Climate Model, version 5 (CRCM5) under the emission scenario Representative Concentration Pathway (RCP 8.5) is analyzed. A hierarchical cluster analysis is applied to group the runoff characteristics into six flow regime classes. In the study area, (glacio-)nival, nival (transition), nivo-pluvial and three different pluvial classes are identified. We find that the characteristics of all six regime groups are severely affected by climate change in terms of the amplitude and timing of the monthly peaks and sinks. According to our simulations, the monthly peak of nival regimes will occur earlier in the season and the relative importance of rainfall increases towards the future. Pluvial regimes will become less balanced with higher normalized monthly discharge during January to March and a strong decrease during May to October. In comparison to the reference period, 8% of catchments will shift to another regime class until 2011–2040, whereas until 2041–2070 and 2071–2099, 23% and 43% will shift to another class, respectively.

Description: This study introduces a holistic approach for the hydrological modelling of peak flows for the major Bavarian river basins, referred to as Hydrological Bavaria. This approach, intended to develop a robust modelling framework to support water resources management under climate change conditions, comprises a regionalized parameterization of the water balance simulation model (WaSiM) for 98 catchments in high temporal (3 h) and spatial (500 m) resolution using spatially coherent information and an automatized calibration (dynamically dimensioned search–simulated annealing, DDS-SA) for storage components. The performance of the model was examined using common metrics (Nash & Sutcliffe Efficiency (NSE), Kling-Gupta Efficiency (KGE)). The simulations provided the means for the calculation of a level of trust (LOT) by comparing observed and simulated high flows with a five, ten, and 20-year return period. These estimates were derived by the Generalized Pareto Distribution (GPD) applying the peak over threshold (POT) sampling method. Results show that the model overall performs well with regard to the selected objective measures, but also exhibits regional disparities mainly due to the availability of meteorological inputs or water management data. For most catchments, the LOT shows moderate to high confidence in the estimation of return periods with the hydrological model. Therefore, we consider the holistic modelling approach applicable for climate change impact studies concerned with dynamic alterations in peak flows.

Description: Numerical modeling provides the opportunity to quantify the reaction of lakes on alterations in their environment, such as changes in climate or hydrological conditions. The one-dimensional hydrodynamic General Lake Model (GLM) is an open-source software and widely used within the limnological research community. Nevertheless, neither an interface to process the input data and run the model, nor tools for an automatic parameter calibration exist. Hence, we developed glmGUI, a Geographical User Interface (GUI) including a toolbox for an autocalibration, parameter sensitivity analysis, and several plot options. The tool is provided as a package for the freely available scientific code language R. The model parameters can be analyzed and calibrated for the simulation output variables water temperature and lake level. The glmGUI package is tested for two sites (Lake Ammersee, Germany, and Lake Baratz, Italy) distinguishing in size, mixing regime, hydrology of the catchment area (i.e. the number of inflows and their runoff seasonality), and climatic conditions. A robust simulation of water temperature for both lakes (Ammersee: RMSE = 1.17 °C, Baratz: RMSE = 1.30 °C) is achieved by a quick automatic calibration. The quality of a water temperature simulation can be assessed immediately by a difference plot provided by glmGUI, which displays the distribution of the spatial (vertical) and temporal deviations. The calibration of the lake level simulations of Lake Ammersee for multiple hydrological inputs including also unknown inflows yielded a satisfactory model fit (RMSE = 0.20 m). This shows that GLM can be also used to estimate the water balance of lakes correctly. The tools provided by glmGUI enable a less time-consuming and simplified parameter optimization within the calibration process. Due to this, the free availability and the implementation in a GUI, the presented R package expands the application of GLM to a broader field of lake modeling research and even beyond limnological experts.

Description: Numerical modeling provides an opportunity to quantify the reaction of lakes to alterations in their environment, such as changes in climate or hydrological conditions. The one-dimensional hydrodynamic General Lake Model (GLM) is an open-source software and widely used within the limnological research community. Nevertheless, no interface to process the input data and run the model and no tools for an automatic parameter calibration yet exist. Hence, we developed glmGUI, a graphical user interface (GUI) including a toolbox for an autocalibration, parameter sensitivity analysis, and several plot options. The tool is provided as a package for the freely available scientific code language R. The model parameters can be analyzed and calibrated for the simulation output variables water temperature and lake level. The glmGUI package is tested for two sites (lake Ammersee, Germany, and lake Baratz, Italy), distinguishing size, mixing regime, hydrology of the catchment area (i.e., the number of inflows and their runoff seasonality), and climatic conditions. A robust simulation of water temperature for both lakes (Ammersee: RMSE =1.17 ∘C; Baratz: RMSE =1.30 ∘C) is achieved by a quick automatic calibration. The quality of a water temperature simulation can be assessed immediately by means of a difference plot provided by glmGUI, which displays the distribution of the spatial (vertical) and temporal deviations. The calibration of the lake-level simulations of lake Ammersee for multiple hydrological inputs including also unknown inflows yielded a satisfactory model fit (RMSE =0.20 m). This shows that GLM can also be used to estimate the water balance of lakes correctly. The tools provided by glmGUI enable a less time-consuming and simplified parameter optimization within the calibration process. Due to this, i.e., the free availability and the implementation in a GUI, the presented R package expands the application of GLM to a broader field of lake modeling research and even beyond limnological experts.

Description: Information on the frequency and intensity of extreme precipitation is required by public authorities, civil security departments, and engineers for the design of buildings and the dimensioning of water management and drainage schemes. Especially for sub-daily resolutions, at which many extreme precipitation events occur, the observational data are sparse in space and time, distributed heterogeneously over Europe, and often not publicly available. We therefore consider it necessary to provide an impact-orientated data set of 10-year rainfall return levels over Europe based on climate model simulations and evaluate its quality. Hence, to standardize procedures and provide comparable results, we apply a high-resolution single-model large ensemble (SMILE) of the Canadian Regional Climate Model version 5 (CRCM5) with 50 members in order to assess the frequency of heavy-precipitation events over Europe between 1980 and 2009. The application of a SMILE enables a robust estimation of extreme-rainfall return levels with the 50 members of 30-year climate simulations providing 1500 years of rainfall data. As the 50 members only differ due to the internal variability in the climate system, the impact of internal variability on the return level values can be quantified. We present 10-year rainfall return levels of hourly to 24 h durations with a spatial resolution of 0.11∘ (12.5 km), which are compared to a large data set of observation-based rainfall return levels of 16 European countries. This observation-based data set was newly compiled and homogenized for this study from 32 different sources. The rainfall return levels of the CRCM5 are able to reproduce the general spatial pattern of extreme precipitation for all sub-daily durations with Spearman's rank correlation coefficients 〉0.76 for the area covered by observations. Also, the rainfall intensity of the observational data set is in the range of the climate-model-generated intensities in 60 % (77 %, 78 %, 83 %, 78 %) of the area for hourly (3, 6, 12, 24 h) durations. This results in biases between −16.3 % (hourly) to +8.2 % (24 h) averaged over the study area. The range, which is introduced by the application of 50 members, shows a spread of −15 % to +18 % around the median. We conclude that our data set shows good agreement with the observations for 3 to 24 h durations in large parts of the study area. However, for an hourly duration and topographically complex regions such as the Alps and Norway, we argue that higher-resolution climate model simulations are needed to improve the results. The 10-year return level data are publicly available (Poschlod, 2020; https://doi.org/10.5281/zenodo.3878887).