Ensemble modelling of ice cover for a reservoir affected by pumped‐storage operation and climate change

Abstract

Ensemble modelling was used to assess the robustness of projected impacts of pumped‐storage (PS) operation and climate change on reservoir ice cover. To this end, three one‐dimensional and a two‐dimensional laterally averaged hydrodynamic model were set up. For the latter, the strength of the impacts with increasing distance from the dam was also investigated. Climate change effects were simulated by forcing the models with 150 years of synthetic meteorological time series created with a weather generator based on available air temperature scenarios for Switzerland. Future climate by the end of the 21st century was projected to shorten the ice‐covered period by ~2 months and decrease ice thicknesses by ~13 cm. Under current climate conditions, the ice cover would already be affected by extended PS operation. For example, the average probability of ice coverage on a specific day was projected to decrease by ~13% for current climate and could further be reduced from ~45% to ~10% for future climate. Overall, the results of all models were consistent. Although the number of winters without ice cover was projected to increase for all one‐dimensional models, studying individual segments of the two‐dimensional model showed that the impact was pronounced for segments close to the PS intake/outlet. In summary, the reservoir's ice cover is expected to partially vanish with higher probability of open water conditions closer to the PS intake/outlet.

LakeEnsemblR: An R package that facilitates ensemble modelling of lakes

“…The model has been used to simulate water temperature, ice and phytoplankton dynamics in mostly Northern and alpine regions (Couture et al, 2018;Kobler and Schmid, 2019;Saloranta et al, 2009). The version used in LakeEnsemblR version 1.0.0 is written in R and corresponds to the MyLake Matlab version 1.2.…”

“…Multiple options for external forcing are available, as well as variable wind drag coefficients, inflow settings, and ice and snow formation (Gaudard et al, 2019). Simstrat has been successfully applied in lakes and reservoirs of varying morphometry in different climate zones, and in scenarios regarding climate warming (Kobler and Schmid, 2019;Schwefel et al, 2016;Stepanenko et al, 2013;. The model is currently maintained by the "Surface Waters -Research and Management" Department of EAWAG (Switzerland) and version 2.4.1 is currently used in LakeEnsemblR.…”

“…equifinality -see Beven, 2006) in parameter sets (Gal et al, 2014;Nielsen et al, 2014). The average of individual model runs from different models can be a more robust predictor than any of the individual model runs (Kobler and Schmid, 2019;Trolle et al, 2014 and sources therein). If only the "best" model is retained, valuable information in other model fits is disregarded (Baker and Ellison, 2008).…”

“…We believe the limnology community recognizes the benefits of using ensembles and multi-model simulations (Nielsen et al, 2014;Stepanenko et al, 2010), but lacks scientific software to facilitate lake ensemble modelling. Past efforts to apply multiple lake models to the same study systems (Nielsen et al, 2014;Trolle et al, 2014;Yao et al, 2014;ISIMIP: Frieler et al, 2016;Gal et al, 2020;Kobler and Schmid, 2019;LakeMIP: Stepanenko et al, 2010) have often been the result of large international collaborations. While these initiatives have revealed pertinent new information, the labour required to build these networks is a barrier to broader implementation.…”

A Simplified Climate Change Model and Extreme Weather Model Based on a Machine Learning Method

“…The surface temperature of the sea https://www.esrl.noaa.gov/psd/data/gridded [28][29][30][31] Ice coating https://www.ecmwf.int/en/research/modellingand-prediction/marine [32][33][34] Monthly average long-wave radiation https://climatedataguide.ucar.edu/climatedata/outgoing-longwave-radiation-olr-hirs [14,35,36] Monthly average near-infrared beam downward sun flux https://climatedataguide.ucar.edu/climatedata/outgoing-longwave-radiation-olr-hirs [37,38] Average monthly precipitation https://www.esrl.noaa.gov/psd/cgi-bin/data/ getpage.pl [32,39] Monthly average evaporation rate https://www.esrl.noaa.gov/psd/data/gridded [27,[39][40][41][42][43] Earth surface wind speed https://www.esrl.noaa.gov/psd/data/gridded [6,43] Earth surface cloud amount https: //www.ecmwf.int/en/forecasts/datasets/set-i [44] Average temperature https://climate.weather.gc.ca [5,45,46] Relative humidity https: //www.ecmwf.int/en/forecasts/datasets/set-i [7,45] Total carbon dioxide emissions https://www.ecmwf.int/en/annual-report-2014/ developing-european-infrastructure [47] Soil moisture https://www.esrl.noaa.gov/psd/data/gridded [48,49] Land-sea mask https://www.esrl.noaa.gov/psd/data/gridded [38] Mean sea level pressure https://www.esrl.noaa.gov/psd/data/gridded [50] Snow density https: //www.ecmwf.int/en/forecasts/datasets/set-i [38] Total column ozone https: //www.ecmwf.int/en/forecasts/datasets/set-i [51] Cooling degree-days https://climatedataguide.ucar.edu/climatedata/outgoing-longwave-radiation-olr-hirs …”