Climate Change Demands Adaptive Management of Urban Lakes: Model-Based Assessment of Management Scenarios for Lake Tegel (Berlin, Germany)

Lakes are known to be strongly affected by climate change as a result of their sensitivity to atmospheric forcing. The combined response of urban lakes to climatic changes and to urbanization of the catchment may be further altered by water quality management measures. We studied Lake Tegel in Berlin, Germany as a representative urban lake profoundly influenced by intense water management measures and a resulting complex hydrodynamic situation: Lake Tegel is fed by nutrient-rich river discharges and effluents from a phosphorus elimination plant (PEP). We estimated changes in water temperatures, the Wedderburn number, and the buoyancy frequency, as well as concentrations of dissolved oxygen and phosphate under climate change using a one-dimensional vertical hydrodynamic model coupled to a water quality model. Further, we investigated how four management scenarios with varying discharges of the PEP could affect the lake system. In all simulations, water temperatures increased and summer stratification extended. The modeling results demonstrated that the water management system buffers the high nutrient supply from the river inflow and can effectively mitigate negative effects of climate change on Lake Tegel, thus highlighting its importance for the lake ecosystem.DFG, 248198858, GRK 2032: Grenzzonen in urbanen Wassersysteme

Ice cover decay and heat balance in Lake Kilpisjärvi in Arctic tundra

To gain more understanding of lake ice melting process, field research was carried out in an arctic tundra lake, Kilpisjärvi (surface area 37.1 km2, maximum depth 57 m) in the melting periods of 2013 and 2014. The heat budget of the ice cover was dominated by the radiation balance; turbulent heat fluxes were large in 2013 due to warm air advection but small in 2014. Transmittance of solar radiation through ice was 0.25 in 2013 and 0.10 in 2014, snow-ice was absent in 2013 but in 2014 accounted for 50% of the ice cover. The melting rate was 4.4 cm    d-1 in 2013, 1.9 cm d-1 in 2014. The portions of surface, bottom and internal melting were, respectively, 2.9, 1.0 and 0.5 cm d-1 in 2013 and 0.8, 1.0 and 0.1 cm d-1 in 2014. Internal melting was realized in increase of ice porosity. In 2013 a rapid ice breakage event completed the ice breakup in short time when ice porosity had reached 40-50%. A lake ice melting model should include the thickness and porosity of ice, with porosity connected to an ice strength criterion

Effects of the Largest Lake of the Tibetan Plateau on the Regional Climate

Qinghai Lake is the largest lake in China. However, its influence on the local climate remains poorly understood. By using an atmosphere-lake coupled model, we investigated the impact of the lake on the local climate. After the adjustment of four key parameters, the model reasonably reproduced the lake-air interaction. Superimposed by the orographic effects on lake-land breeze circulation, the presence of the lake enhanced precipitation over the southern part of the lake and its adjacent land, while slightly reduced precipitation along the northern shore of the lake. The lake effect on local precipitation revealed a distinct seasonal and diurnal variability, reducing precipitation in May (-6.6%) and June (-4.5%) and increasing it from July (5.7%) to November (125.6%). During the open water season, the lake's daytime cooling effect weakened and the nighttime warming effect strengthened, affecting spatial distribution and intensity of lake-induced precipitation. In early summer, precipitation slightly decreased over the north part of the lake due to the lake's daytime cooling. In turn, lake-induced nighttime warming increased precipitation over the southern section of the lake and its adjacent land. With the start of the autumn cooling in September, heat and moisture fluxes from the lake resulted in precipitation increase in both daytime and nighttime over the entire lake. In October, the background atmospheric circulation coupled with the strong lake effects lead to a small amount but high proportion of lake-induced precipitation spreading evenly over the lake.Peer reviewe

Thermal Responses of the Largest Freshwater Lake in the Tibetan Plateau and Its Nearby Saline Lake to Climate Change

There are thousands of lakes in the Tibetan Plateau (TP), and most are saline. However, little is known about the responses of TP lakes to climate change, especially saline ones. We investigated the thermal responses of the largest freshwater lake (Ngoring Lake) in the TP and its nearby small saline lake (Hajiang Salt Pond) to climate change using the improved lake scheme in the Community Land model (CLM4-LISSS), in which we primarily developed the salinity parameterizations previously evaluated in the Great Salt Lake in USA and further considered the effect of salinity on the temperature of the maximum density of saline water in the present study. The improved lake model with salinity parameterizations was first applied to a saline lake in the TP, where saline lakes make up the majority of water bodies. The CLM4-LISSS model could effectively simulate lake surface water temperature (LSWT), lake water temperature (LT) and ice thickness in Ngoring Lake. Additionally, the model including our salinity parameterizations significantly improved simulations of LSWT and LT in Hajiang Salt Pond, especially in winter. The LSWT of the two completely opposite lakes were warming in the simulations at a rate above 0.6 °C/decade. Meteorological forces were the main driving factor, with increasing downward longwave radiation, air temperature and air humidity, as well as weakening winds contributing to LSWT increase. Compared to a hypothetical shallow freshwater lake, the greater depth of Ngoring Lake made its surface warm faster, and salinity slightly accelerated the warming of Hajiang Salt Pond. Monthly mean LSWT differences between the two lakes were induced by salinity effects in cold periods and lake depth in the unfrozen period. In response to a warming climate, the LSWT in the ice-free Hajiang Salt Pond rapidly increased from January to April due to the warming climate, whereas the LSWT of Ngoring Lake increased faster in the first and last month of the ice-cover period due to later ice-on and earlier ice-off. This study will provide a useful tool for saline lakes in the TP and help deepen our knowledge about the responses of TP lakes, especially the saline lakes, to climate change, as well as response differences between freshwater and saline lakes and the reasons for these differences

Thermal Responses of the Largest Freshwater Lake in the Tibetan Plateau and Its Nearby Saline Lake to Climate Change

There are thousands of lakes in the Tibetan Plateau (TP), and most are saline. However, little is known about the responses of TP lakes to climate change, especially saline ones. We investigated the thermal responses of the largest freshwater lake (Ngoring Lake) in the TP and its nearby small saline lake (Hajiang Salt Pond) to climate change using the improved lake scheme in the Community Land model (CLM4-LISSS), in which we primarily developed the salinity parameterizations previously evaluated in the Great Salt Lake in USA and further considered the effect of salinity on the temperature of the maximum density of saline water in the present study. The improved lake model with salinity parameterizations was first applied to a saline lake in the TP, where saline lakes make up the majority of water bodies. The CLM4-LISSS model could effectively simulate lake surface water temperature (LSWT), lake water temperature (LT) and ice thickness in Ngoring Lake. Additionally, the model including our salinity parameterizations significantly improved simulations of LSWT and LT in Hajiang Salt Pond, especially in winter. The LSWT of the two completely opposite lakes were warming in the simulations at a rate above 0.6 °C/decade. Meteorological forces were the main driving factor, with increasing downward longwave radiation, air temperature and air humidity, as well as weakening winds contributing to LSWT increase. Compared to a hypothetical shallow freshwater lake, the greater depth of Ngoring Lake made its surface warm faster, and salinity slightly accelerated the warming of Hajiang Salt Pond. Monthly mean LSWT differences between the two lakes were induced by salinity effects in cold periods and lake depth in the unfrozen period. In response to a warming climate, the LSWT in the ice-free Hajiang Salt Pond rapidly increased from January to April due to the warming climate, whereas the LSWT of Ngoring Lake increased faster in the first and last month of the ice-cover period due to later ice-on and earlier ice-off. This study will provide a useful tool for saline lakes in the TP and help deepen our knowledge about the responses of TP lakes, especially the saline lakes, to climate change, as well as response differences between freshwater and saline lakes and the reasons for these differences

Mechanisms and effects of under-ice warming water in Ngoring Lake of Qinghai-Tibet Plateau

Peer reviewe

Modeling reservoir surface temperatures for regional and global climate models: A multi-model study on the inflow and level variation effects

UIDB/04292/2020 KI-853/13 KI-853- 16 UIDB/04292/2020The complexity of the state-of-the-art climate models requires high computational resources and imposes rather simplified parameterization of inland waters. The effect of lakes and reservoirs on the local and regional climate is commonly parameterized in regional or global climate modeling as a function of surface water temperature estimated by atmosphere-coupled one-dimensional lake models. The latter typically neglect one of the major transport mechanisms specific to artificial reservoirs: heat and mass advection due to inflows and outflows. Incorporation of these essentially two-dimensional processes into lake parameterizations requires a trade-off between computational efficiency and physical soundness, which is addressed in this study. We evaluated the performance of the two most used lake parameterization schemes and a machine-learning approach on high-resolution historical water temperature records from 24 reservoirs. Simulations were also performed at both variable and constant water level to explore the thermal structure differences between lakes and reservoirs. Our results highlight the need to include anthropogenic inflow and outflow controls in regional and global climate models. Our findings also highlight the efficiency of the machine-learning approach, which may overperform process-based physical models in both accuracy and computational requirements if applied to reservoirs with long-term observations available. Overall, results suggest that the combined use of process-based physical models and machine-learning models will considerably improve the modeling of air-lake heat and moisture fluxes. A relationship between mean water retention times and the importance of inflows and outflows is established: reservoirs with a retention time shorter than ĝ1/4g100gd, if simulated without inflow and outflow effects, tend to exhibit a statistically significant deviation in the computed surface temperatures regardless of their morphological characteristics.publishersversionpublishe

Multi-model projections of future evaporation in a sub-tropical lake

Lake evaporation plays an important role in the water budget of lakes. Predicting lake evaporation responses to climate change is thus of paramount importance for the planning of mitigation and adaption strategies. However, most studies that have simulated climate change impacts on lake evaporation have typically utilised a single mechanistic model. Whilst such studies have merit, projected changes in lake evaporation from any single lake model can be considered uncertain. To better understand evaporation responses to climate change, a multi-model approach (i.e., where a range of projections are considered), is desirable. In this study, we present such multi-model analysis, where five lake models forced by four different climate model projections are used to simulate historic and future change (1901–2099) in lake evaporation. Our investigation, which focuses on sub-tropical Lake Kinneret (Israel), suggested considerable differences in simulated evaporation rates among the models, with the annual average evaporation rates varying between 1232 mm year−1 and 2608 mm year−1 during the historic period (1901–2005). We explored these differences by comparing the models with reference evaporation rates estimated using in-situ data (2000–2005) and a bulk aerodynamic algorithm. We found that the model ensemble generally captured the intra-annual variability in reference evaporation rates, and compared well at seasonal timescales (RMSEc = 0.19, R = 0.92). Using the model ensemble, we then projected future change in evaporation rates under three different Representative Concentration Pathway (RCP) scenarios: RCP 2.6, 6.0 and 8.5. Our projections indicated that, by the end of the 21st century (2070–2099), annual average evaporation rates would increase in Lake Kinneret by 9–22 % under RCPs 2.6–8.5. When compared with projected regional declines in precipitation, our projections suggested that the water balance of Lake Kinneret could experience a deficit of 14–40 % this century. We anticipate this substantial projected deficit combined with a considerable growth in population expected for this region could have considerable negative impacts on water availability and would consequently increase regional water stress

The under-ice microbiome of seasonally frozen lakes

Compared to the well-studied open water of the “growing” season, under-ice conditions in lakes are characterized by low and rather constant temperature, slow water movements, limited light availability, and reduced exchange with the surrounding landscape. These conditions interact with ice-cover duration to shape microbial processes in temperate lakes and ultimately influence the phenology of community and ecosystem processes. We review the current knowledge on microorganisms in seasonally frozen lakes. Specifically, we highlight how under-ice conditions alter lake physics and the ways that this can affect the distribution and metabolism of auto- and heterotrophic microorganisms. We identify functional traits that we hypothesize are important for understanding under-ice dynamics and discuss how these traits influence species interactions. As ice coverage duration has already been seen to reduce as air temperatures have warmed, the dynamics of the under-ice microbiome are important for understanding and predicting the dynamics and functioning of seasonally frozen lakes in the near future