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A key phenological event in the annual cycle of many pelagic ecosystems is the onset of the spring algal bloom (OAB). Descriptions of the factors controlling the OAB in temperate to polar lakes have been limited to isolated studies of single systems and conceptual models. Here we present a validated modelling approach that, for the first time, enables a quantitative prediction of the OAB and a systematic assessment of the processes controlling its timing on a continental scale. We used a weather-driven, 1-dimensional lake model to simulate the seasonal dynamics of the underwater light climate in 16 lake types characterized by the factorial combination of 4 lake depths with 4 levels of water transparency. We did so at 1,962 locations across western Europe and over 31 years (1979-2009). Assuming that phytoplankton production is light-limited in winter, we identified four patterns of OAB control across lake types and climate zones. OAB timing is controlled by (i) the timing of ice-off in ice-covered clear or shallow lakes, (ii) the onset of thermal stratification in sufficiently deep and turbid lakes, and (iii) the seasonal increase in incident radiation in all other lakes, except for (iv) ice-free, shallow and clear lakes in the south, where phytoplankton is not light-limited. The model predicts that OAB timing should respond to two pervasive environmental changes, global warming and browning, in opposite ways. OAB timing should be highly sensitive to warming in lakes where it is controlled by either ice-off or the onset of stratification, but resilient to warming in lakes where it is controlled by incident radiation. Conversely, OAB timing should be most sensitive to browning where it is controlled by incident radiation, but resilient to browning where it is controlled by ice-off or the onset of stratification. Available lake data are consistent with our findings. published

Here, we present a community perspective on how to explore, exploit and evolve the diversity in aquatic ecosystem models. These models play an important role in understanding the functioning of aquatic ecosystems, filling in observation gaps and developing effective strategies for water quality management. In this spirit, numerous models have been developed since the 1970s. We set off to explore model diversity by making an inventory among 42 aquatic ecosystem modellers, by categorizing the resulting set of models and by analysing them for diversity. We then focus on how to exploit model diversity by comparing and combining different aspects of existing models. Finally, we discuss how model diversity came about in the past and could evolve in the future. Throughout our study, we use analogies from biodiversity research to analyse and interpret model diversity. We recommend to make models publicly available through open-source policies, to standardize documentation and technical implementation of models, and to compare models through ensemble modelling and interdisciplinary approaches. We end with our perspective on how the field of aquatic ecosystem modelling might develop in the next 5-10 years. To strive for clarity and to improve readability for non-modellers, we include a glossary.

The African great lakes are of utmost importance for the local economy (fishing), as well as being essential to the survival of the local people. During the past decades, these lakes experienced fast changes in ecosystem structure and functioning, and their future evolution is a major concern. In this study, for the first time a set of one-dimensional lake models are evaluated for Lake Kivu (2.28°S; 28.98°E), East Africa. The unique limnology of this meromictic lake, with the importance of salinity and subsurface springs in a tropical high-altitude climate, presents a worthy challenge to the seven models involved in the Lake Model Intercomparison Project (LakeMIP). Meteorological observations from two automatic weather stations are used to drive the models, whereas a unique dataset, containing over 150 temperature profiles recorded since 2002, is used to assess the model’s performance. Simulations are performed over the freshwater layer only (60 m) and over the average lake depth (240 m), since salinity increases with depth below 60 m in Lake Kivu and some lake models do not account for the influence of salinity upon lake stratification. All models are able to reproduce the mixing seasonality in Lake Kivu, as well as the magnitude and seasonal cycle of the lake enthalpy change. Differences between the models can be ascribed to variations in the treatment of the radiative forcing and the computation of the turbulent heat fluxes. Fluctuations in wind velocity and solar radiation explain inter-annual variability of observed water column temperatures. The good agreement between the deep simulations and the observed meromictic stratification also shows that a subset of models is able to account for the salinity- and geothermal-induced effects upon deep-water stratification. Finally, based on the strengths and weaknesses discerned in this study, an informed choice of a one-dimensional lake model for a given research purpose becomes possible. Keywords: lake modelling, model intercomparison, surface–atmosphere interactions, tropical lakes, Lake Kivu (Published: 5 February 2014) Citation: Tellus A 2014, 66 , 21390, http://dx.doi.org/10.3402/tellusa.v66.21390 This publication is part of a Thematic Cluster entitled "Parameterization of lakes in numerical weather prediction and climate models". Read the other papers from this thematic cluster here

Results of a lake model intercomparison study conducted within the framework of Lake Model Intercomparison Project are presented. The investigated lake was Großer Kossenblatter See (Germany) as a representative of shallow, (2 m mean depth) turbid midlatitude lakes. Meteorological measurements, including turbulent fluxes and water temperature, were carried out by the Lindenberg Meteorological Observatory of the German Meteorological Service (Deutscher Wetterdienst, DWD). Eight lake models of different complexity were run, forced by identical meteorological variables and model parameters unified as far as possible given different formulations of processes. All models generally captured diurnal and seasonal variability of lake surface temperature reasonably well. However, some models were incapable of realistically reproducing temperature stratification in summer. Total heat turbulent fluxes, computed by the surface flux schemes of the compared lake models, deviated on average from those measured by eddy covariance by 17–28 W m−2. There are a number of possible reasons for these deviations, and the conclusion is drawn that underestimation of real fluxes by the eddy covariance technique is the most probable reason. It is supported by the fact that the eddy covariance fluxes do not allow to close the heat balance of the water column, the residual for the whole period considered being ≈–28 W m−2. The effect of heat flux to bottom sediments can become significant for bottom temperatures. It also has profound influence on the surface temperatures in autumn due to convective mixing but not in summer when the lake stratification is stable. Thus, neglecting sediments shifts the summer–autumn temperature difference in models lacking explicit treatment of sediments considerably. As a practical recommendation based on results of the present study, we also infer that in order to realistically represent lakes in numerical weather prediction and climate models, it is advisable to use depth-resolving turbulence models (or equivalent) in favor of models with a completely mixed temperature profile.

The extreme flood of Lake Constance in 1999 focused attention on the variability of annual lake levels. The year 1999 not only brought one of the highest floods of the last 180 years but also one of the earliest in the season. The 1999 extreme event was caused by heavy rainfall in the alpine and pre-alpine regions. The influence of precipitation in the two distinct regional catchments on lake level variations can be quantified by correlation analysis. The long-term variations in lake level and precipitation show similar patterns. This is seen through the use of spectral analysis, which gives similar bands of spectral densities for precipitation and lake level time series. It can be concluded from the comparison of these results with the analysis of climate change patterns in northern Europe, i.e. the index of the North Atlantic Oscillation, that the regional effects on lake level variations are more pronounced than those of global climate change.