Long-term effects of climate change on lakes globally will include a substantial modification in the thermal regime and the oxygen solubility of lakes, resulting in the alteration of ecosystem processes, habitats, and concentrations of critical substances. Recent efforts have led to the development of long-term model projections of climate change effects on lake thermal regimes and oxygen solubility. However, such projections
are hardly ever confronted with observations extending over multiple decades. Furthermore, global-scale forcing parameters in lake models present several limitations, such as the need of significant downscaling. In this study, the effects of climate change on thermal regime and oxygen solubility were analyzed in the four largest French peri-alpine lakes over 1850–2100. We tested several one-dimensional (1D) lake models' robustness for long-term variations based on up to 63 years of limnological data collected by the French Observatory of LAkes (OLA). Here, we evaluate the possibility of forcing mechanistic models by following the long-term
evolution of shortwave radiation and air temperature while providing
realistic seasonal trends for the other variables for which local-scale
downscaling often lacks accuracy. Based on this approach, MyLake, forced by
air temperatures and shortwave radiations, predicted accurately the
variations in the lake thermal regime over the last 4 to 6 decades,
with RMSE
Lakes are critical resources providing humanity with key ecosystem services such as hydropower and drinking water production (Jenny et al., 2020) and are considered sentinels of climate change (Williamson et al., 2009). These ecosystems are increasingly altered by anthropogenic pressures and ongoing global warming, which requires continuous water quality monitoring. Water temperature is a critical indicator for long-term lake ecosystems monitoring, which is also needed for adapting management practices (Daufresne et al., 2009). It is an important parameter impacting lake ecosystems' metabolism, composition, and functioning, and reflects their response to climate change. Water temperature directly affects the growth rate and reproductive success of many aquatic organisms (Angilletta and Dunham, 2003; Mari et al., 2016) and their phenology (Parmesan, 2006; Walther et al., 2002). Furthermore, the water temperature can also indirectly affect organisms, by altering the mixing regime of lakes and gas solubility with potential impacts on oxygenation, one of the most fundamental parameters of life in lakes (Roberts et al., 2009a; Wetzel, 2001).
Recent studies from lakes around the world have already shown that increasing air temperature significantly affects the intensification and the duration of their stratification (Woolway and Merchant, 2019; Piccioni et al., 2021; Woolway et al., 2021). In deep temperate lakes, vertical mixing of the water column has experienced a decrease in intensity, frequency, and duration (Råman Vinnå et al., 2021; Danis et al., 2004), thereby increasing the vertical temperature gradient between the surface and deep layers (Livingstone, 2003). However, both retrospective and prospective studies of lake thermal regimes over decadal to centennial timescales are still limited, precluding our understanding of the evolution of lake physicochemical conditions and habitats and the response mechanisms to the forcings involved over such timescales.
Mechanistic lake models have been widely implemented over the last years (Bruce et al., 2018; Snortheim et al., 2017; Shatwell et al., 2019), and are
considered as essential tools for understanding, analyzing, testing different scenarios, and predicting the state of an ecosystem under external constraints over different timescales (Trolle et al., 2012). More specifically, using one-dimensional (1D) models for global-scale studies has become the standard in lake research. These models are suitable to simulate complex ecosystems, as they require minimum configuration parameters (Hamilton and Schladow, 1997; Vinçon-Leite et al., 2014), and to perform reliable predictions of lake responses to global warming (Balsamo et al., 2012). However, such an approach requires global-scale forcing parameters that have several limitations that are barely discussed. Among these limitations, the influence of the rivers and watersheds is not systematically assessed, even though it can have a strong effect on the thermal structure of lakes with a short residence time (e.g.,
To address this limitation, the first aim of our study was to adapt an existing modeling approach for long-term studies constrained by the Intergovernmental Panel on Climate Change (IPCC) scenarios, and to calibrate and validate the model against up to 63 years of limnological records from four peri-alpine lakes monitored by the Observatory of LAkes (OLA) (Rimet et al., 2020): Geneva, Annecy, Bourget, and Aiguebelette. Here we evaluate the possibility of forcing mechanistic models by following the long-term evolution of only shortwave radiation (W m
The second objective of this study was to investigate the evolution of the thermal regime and the solubility of oxygen, as proxies for the species' habitats and their capacity to cope with temperature change (Kraemer et al., 2021), in the lakes over 1850–2100 to assess their different responses and sensitivity to global warming.
We begin as follows: (1) by describing our approach for long-term forecast/hindcast based on a reduced number of meteorological forcing variables; (2) by presenting the MyLake model calibration and validation over a relatively short period of 10 years, using both complete and reduced meteorological inputs; then (3) we test the method over longer timescales, i.e., against 37 to 63 years of monitoring data; and finally (4) we explore trends in lake thermal regimes through 15 physical indices, and we estimate effects of climate change on the dissolved oxygen solubility in the four lakes over the 1850–2100 period using an ensemble of climate projections based on the shared socio-economic pathways (SSP126, SSP370, and SSP585) (Riahi et al., 2017).
Location of the study sites in the peri-alpine region. OLA sampling sites (Rimet et al., 2020), locations of meteorological stations, drainage watersheds, and networks are represented.
Characteristics of the four study sites.
We consider four lakes in France's peri-alpine region: Lake Geneva, Lake Annecy, Lake Bourget, and Lake Aiguebelette (Fig. 1). They are situated in a continental mountain climate, and less than 150 km separates the four lakes from each other. The four lakes are mono or meromictic – they mix only once per year – and are deep and of glacial origin. Lake Geneva and Lake Aiguebelette are mesotrophic lakes, whereas Lake Annecy and Lake Bourget are oligotrophic and oligo-mesotrophic, respectively (Table 1).
The Observatory of LAkes (OLA) managed by the CARRTEL
(
A modeling approach was performed to run five one-dimensional hydrodynamic lake models simultaneously (FLake, GLM, GOTM, Simstrat, and MyLake) to simulate the vertical water temperature profile in the four peri-alpine lakes. The same configuration and driver data were used for each lake to account for different sources of uncertainties in the model predictions. We used the R package LakeEnsemblR version 1.0.0. (Moore et al., 2021). The models were calibrated and validated against OLA limnological data, and further used to assess long-term trends in the thermal regime of each lake. The MyLake model, identified as the most performant for the four peri-alpine lakes based on five performance metrics calculated, was selected to develop and test our approach for long-term reconstruction that extends the simulation period beyond the instrumental one, as this model is well adapted to northern and alpine regions (Couture et al., 2018; Kobler and Schmid, 2019; Saloranta, 2006). MyLake was developed by the Norwegian Institute for Water Research (NIVA), the University of Helsinki (Finland), and Université Laval (Canada). It simulates daily vertical water temperature profiles, density stratification, seasonal ice and snow cover, sediment–water dynamics, and phosphorus–phytoplankton interactions (Saloranta and Andersen, 2007).
The model was forced with statistically bias-adjusted (Lange, 2019a) and downscaled climate projections (Cucchi et al., 2020; Lange, 2019b) (ISIMIP3BASD method) from phase 3b of the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP3b). This was based on the output of phase 6 of the Coupled Model Intercomparison Project (CMIP6; Eyring et al., 2016). The better-performing models, providing daily data for all variables during the period of interest (1850–2100), were selected (Lange, 2019a) (GFDLESM4, IPSL-CM6-LR, UKESM1-0-LL, MPI-ESM1-2-HR, and MRI-ESM2-0; Tables S1 and S2 in the Supplement) and compared to meteorological station data (Fig. S1 in the Supplement).
All five climate models were downscaled at 0.5
CMIP6 experiments used were historical climates from 1850 to 2014, and scenarios SSP126 (SSP1-RCP2.6 climate), SSP370 (SSP3-RCP7 climate), and
SSP585 (SSP5-RCP8.5 climate) from 2015 to 2100. The SSPs consider how societal choices will affect greenhouse emissions, SSP126 being the most sustainable scenario and SSP585 the worst one (Riahi et al., 2017). The
Representative Concentration Pathways (RCPs) correspond to the range of the
year 2100's radiative forcings values, from 2.6 to 8.5 W m
The meteorological forcing variables required in the LakeEnsemblR package are air temperature (
From the chosen climate model (IPSL-CM6-LR), all forcing variables were
extracted for the grid cells containing the four lakes, lakes Bourget and
Aiguebelette being situated in the same grid. A sensitivity test was carried
out on all seven climate variables to validate our hypothesis that forcing
variables can be reduced into the hydrodynamic models to only air temperature and shortwave radiations to identify long-term trends accurately (Table S3). Each climate forcing variable (air temperature, downwelling shortwave radiation, wind speed, cloud cover, relative humidity, rain, and surface pressure) was tested from MyLake water temperature simulations over a 10-year period for the four peri-alpine lakes. A percentage of
Then simulations with the MyLake model for the four lakes were computed with four different climatic configurations: (i) with only air temperature and shortwave radiation from ISIMIP3b while all other variables were extracted from meteorological observations from which daily means were calculated and replicated every year from 1850 to 2100 (Fig. S2); (ii) with all input meteorological forcing variables extracted from ISIMIP3b. The period of meteorological observations extends from 2000 to 2011 for Lake Geneva (MétéoSuisse Data Warehouse) and from 1959 to 2020 for the other lakes (Table 4) (SAFRAN climatic data are provided by Météo-France and were downloaded via the SICLIMA platform developed by AgroClim-INRAE). Decoupling meteorological parameters is a strong assumption, which is addressed in the Discussion section. The cloud cover was available only for Lake Geneva, and values were adopted as the same for the other lakes. Surface pressure was considered constant in this study. Configurations (iii) and (iv) are based on configurations (i) and (ii), respectively, with a correction factor for both air temperature and shortwave radiation (Table 2). These two variables were compared to available data from the closest meteorological stations (from INRAE and Meteo France networks – CLIMATIK and SAFRAN database), encompassing 32 to 61 years of meteorological time series data (Fig. 1) (Table 3). Correction factors were calculated from the difference between raw climatic model data and observed data from local stations, at the daily resolution, to fit better to meteorological data and correct the altitude bias (Figs. S3 and S4). Further, daily corrected meteorological data were used between 1850 and 2100.
Monitoring, calibration, and validation periods for the four peri-alpine lakes.
Meteorological data sources used for the meteorological patterns
calculated from daily means of cloud cover (Cl), relative humidity (RH), wind speed (Ws), and rain (
Daily meteorological data from the SAFRAN analysis system were extracted from the SICLIMA database (Bertuzzi and Clastre, 2022), collected by Meteo France since 1 January 1959. Data have been recalculated from daily local observations at smaller grid cells (8 km
Meteorological forcing configuration and performance metrics for
MyLake (ISIMIP) calculated between daily simulations and observations.
Outputs comparison between four configurations: (i) only air temperature (
Meteorological data sources used to calculate the correction factors applied to air temperature (
MyLake was run through the LakeEnsemblR package. The model was calibrated considering the most sensitive parameters identified in previous studies (Saloranta, 2006) (Table S4): scaling factors for wind speed and shortwave radiation and physical C_shelter parameter. The Latin hypercube calibration (LHC) method was used for calibration. The LHC method uses upper and lower bounds for all parameters considered, and then samples evenly within the parameter space given by these bounds. Then MyLake was run and evaluated for 100 parameter sets. The model's performance was assessed through six statistical metrics: RMSE, Nash–Sutcliffe efficiency (NSE),
The optimal values of model parameters were determined based on the performance metrics. First, calibration and validation were performed over 10 years, depending on each lake's density of observation data (Table S5). This period corresponds to the temporal scale generally covered by modeling studies conducted between 2015 to 2020 (Soares and Calijuri, 2021). Further, the robustness of the model to perform long-term simulations was assessed by computing the performance metrics over the entire period with field data availability, covering 63, 54, 37, and 46 years for lakes Geneva, Annecy, Bourget, Aiguebelette, respectively (Table 2).
For the long-term simulations according to the three scenarios (from 1850 to 2100), the initial water temperature remained unknown. To address this limitation, a method was developed to identify the year with available observation data the closest from climatic conditions estimated on 31 January 1850. Air temperature from 1 to 31 January 1850 was compared to air temperature of the instrumental period (from the OLA database) to identify years with similar climate conditions. The water temperature profile of the year with the lowest RMSE between winter air temperatures (1992 for lakes Bourget and Geneva, 2000 for lakes Annecy and Aiguebelette) was used as the initial profile for 31 January 1850.
The model fit was assessed for 15 thermal indices: lake temperature (complete
profile); surface temperature (
Temporal variations in epilimnion (red) and hypolimnion (blue) temperatures of Lake Geneva
The slope of the significant trends was evaluated by least squares linear
regression and
Daily averaged MyLake water temperature simulations (1) and interpolated observations from the OLA database (2) in Lake
Geneva
The MyLake model, forced by air temperature and shortwave radiation, reproduced well the observed temperature along the water column in the four
deep alpine lakes (Fig. 2). Model performances were compared across a 10-year validation and more extended periods (Table 6), depending on the availability of observations for each lake. During both validation periods (i.e., 10-year and 37 to 63-year periods), the model predicted water temperature with good precision, as RMSE values are generally less than 2 and 1.22
MyLake performance indicators of water temperature simulations (root mean square error, RMSE, and Pearson correlation coefficient,
The ability of the model to predict the evolution of specific thermal indices has been assessed (Table 7). The model performance in predicting epilimnion temperatures was the best for the two deepest lakes (Geneva and Bourget), with RMSEs ranging between 1.92 and 2.08
Comparison of model validation metrics for eight thermal indices
over 10 years and a long-term validation period (37 to 63 years) for the four lakes (see extended Table S6); bold: RMSE
A clear difference in amplitude has been identified between Schmidt stability calculated from simulations and observed water temperature profiles (mean RMSE: 3270.7, 4092.6, 3391.9, and 1967.1 for Geneva, Bourget, Annecy, and Aiguebelette, respectively). However, general seasonal patterns across the four lakes were well simulated by the model (
Selected meteorological forcing variables over the studied period of
1850–2100. Projected evolution of air temperature (1) and shortwave
radiation (2) from IPSL-CM6A-LR (ISIMIP3b) under SSP126
Based on the different scenarios adopted in the present work, mean annual air temperature has increased by
The epilimnion temperature increased by around 0.44
Annual averages of epilimnion (line) and hypolimnion (dashed lines) temperatures from MyLake daily water temperature simulations over the period 1850–2100, for three different climate scenarios (SSP126, SSP370, SSP585) in lakes Geneva
Over the last 30 years, hypolimnion temperature increased by
The water temperature change was quantified as the non-overlapped area of the two daily averaged temperature distributions in the present (2000–2010) and the future (2090–2100) as a percentage of the combined area of those distributions for the intermediate scenario (SSP370) (Fig. 6). The greatest thermal change occurred in Lake Geneva and Bourget with 90 % and 86 % non-overlap, respectively, between the two periods. In Lake Annecy and Aiguebelette, 77 % and 76 % thermal non-overlap were predicted, respectively.
MyLake water temperature simulations from intermediate climate scenario (SSP370). Daily averaged water temperature over the periods 2000–2010 (1) and 2090–2100 (2) in Lake Geneva
The annual average temperature was expected to increase between the two periods on average by
Schmidt stability, describing the stability of the water column and its
resistance to mixing, has significantly increased over the past 30 years by
an annual average of
Stratification trend characteristics for the four lakes – Geneva
No significant trend was identified for the day of onset of stratification (DOY) in the present and the future, except for Lake Annecy according to SSP126 scenario (DOY:
Regarding the break up of stratification, a significant trend was only predicted for Lake Geneva in the present (1990–2020) with an average of 5 d per decade later. Except for Lake Annecy and Aiguebelette SSP126 and Lake Bourget SSP370, the end of stratification appeared significantly later in the future than in the last 30 years. In the SSP126 scenario, the stratification could end on average 6 and 5 d earlier for Lake Geneva and Bourget, respectively. According to the SSP370 scenario, it was predicted to end on average 5.7, 7.4, and 3 d later in Lake Annecy, Geneva, and Aiguebelette, respectively. In the worst-case scenario, with a delay of 7.7, 14.7, 6.8, and 3.6 d in Lake Annecy, Geneva, Bourget, and Aiguebelette, respectively.
As a result, a significant increase in the average stratification duration
was predicted in Lake Geneva – SSP585 of
Changes in thermal habitat between the present (2000–2010) and the future
(2090–2100) were assessed based on the lake volume fraction that exceeded
specific temperature thresholds (
Lake volume fraction with temperature exceeding three characteristics' thresholds – 7
In Lake Annecy, Geneva, and Bourget, temperature could exceed 9
Water volumes above 12
Oxygen solubility was calculated from the Winkler tables, as a function of
temperature. In all scenarios, the model for the four lakes predicted
significant trends in potential oxygen solubility. Over the last 30 years
(1990–2020), an average annual decrease of
Annual averages of potential oxygen solubility over the period
1850–2100, in the epilimnion calculated from MyLake daily water temperature
simulations for three different climate scenarios (SSP126, SSP370, SSP585)
in lakes Geneva
Furthermore, the model predicted a faster decrease in oxygen solubility in
the epilimnion compared to the hypolimnion in the four lakes over the last
30 years, with an average of
Potential change in oxygen solubility was also quantified as the non-overlapped area of the two daily averaged oxygen solubility distributions in the present (2000–2010) and the future (2090–2100) as a percentage of the combined area of those distributions for the intermediate scenario (SSP370) (Fig. 10). As for the thermal regime, the highest changes in oxygen solubility were in lakes Geneva and Bourget with 60 % of non-overlap between the present and the future. In lakes Aiguebelette and Annecy, the non-overlap rate has been reduced to 55 % and 54 %.
Potential oxygen solubility in lake waters of the four lakes, calculated from MyLake water temperature simulations for the intermediate climate scenario (SSP370). Daily averaged oxygen solubility over the present (1) and future (2) in lakes Geneva
Annual potential average oxygen solubility was predicted to decrease by
Lake volume fraction with oxygen solubility exceeding two thresholds – 10 mg L
As for the thermal habitat, water volumes with sufficient dissolved oxygen
levels to support fish survival were assessed based on lake volume fraction
that exceeded certain thresholds (10 and 11 mg L
In the two deepest lakes (Geneva and Bourget), the lake volume fraction with
potential oxygen solubility above 11 mg L
Most lakes in the world tend to warm due to climate change, with a mean
increase of
In the future, simulated water temperatures will show different responses to global warming under different projections. In the most optimistic scenario, where strong environmental and political measures would be implemented, surface water temperatures are expected to decrease, whereas hypolimnetic water is expected to warm. The mechanistic effect of surface cooling in the most optimistic scenario over 1970–2100 is explained by the future development of both air temperature and solar radiation predicted to decrease. The recent past surface warming trend is not expected to persist in other large deep lakes in Central Europe (Schmid and Köster, 2016). However, hypolimnion warming could be explained by the thermal inertia and heat accumulation in deep waters (Crossman et al., 2016). In the intermediate (SSP370) and most pessimistic (SSP585) scenarios, both epilimnion and hypolimnion temperatures are increasing, driven by higher rates of air temperature warming in comparison to the recent past warming, with higher increases in the two deepest lakes (Geneva and Bourget) and faster warmings of the surface layers than deep layers. Similarly, the entire water column of the two shallowest lakes (Annecy and Aiguebelette) could warm up less quickly than the two deepest ones. This might be explained by less frequent complete mixing in deeper lakes, leading to longer inter-mixing periods during which water temperature increases. However, by 2100, there is a high probability that the hydrological regime in the Rhône River upstream Lake Geneva will change because of earlier snow melting leading to an earlier, and maybe shorter, input of cold water into the lake. The effects of hydrological changes on the thermal regime of large deep lakes are expected to be relatively modest, such as observed in preliminary sensitivity tests (results not shown here). However, these interactions would require further investigation, especially in lakes supplied by an upstream snow and glacier area.
The four peri-alpine lakes share the same climate region and, due to their large size, they also share the same topographical properties to varying extents. Despite similarities, the four studied lakes tend to respond differently to climate change. For instance, the highest increase of Schmidt stability was predicted in Lake Geneva according to SSP370 and SSP585 scenarios, Lake Annecy being the least sensitive. These results were consistent, as changes in stability vary by lake archetype, with larger increases in deeper and more turbid lakes (Butcher et al., 2015). Regardless of the climate scenario, an increase in the stratification intensity and duration with depth is expected in the four lakes. Accordingly, Lake Geneva was predicted to experience the highest changes in the start, end, and duration of stratification, with a significant advance in stratification onset, later end of stratification, and longer stratification duration. This is consistent with its greater resistance to mixing. Still, it also has the particularity to mix over the whole water column in particular years under specific meteorological conditions (last complete mixing of its water column was in 2012). Thus, Lake Geneva must be sensitive to the frequency of the complete water column mixing, which should be investigated in more detail in upcoming studies. Conversely, the shallowest lake (Annecy) was predicted to stratify the latest with the shortest duration in all scenarios. This analysis showed that Lake Geneva will be more vulnerable to global warming in future projections than Lake Annecy, with a depth-related vulnerability gradient. These results are coherent with the differential warming of the surface and deep waters, which could influence the strength and duration of a lake's stratification period (Råman Vinnå et al., 2021). Finally, in the four lakes, the stratification duration should last longer with an early spring and a gradual delay of cold temperatures in autumn. The changes in the beginning, end, and period of stratification could also impact oxygenation conditions in deep waters (Roberts et al., 2009b), in addition to the oxygen solubility decreasing when water temperature increases. But all these results should be considered with caution, as the wind exposure is very different within the four lakes (with greater exposure for Lake Geneva) and could counteract the increase in thermal stratification (Butcher et al., 2015).
In all three scenarios, the entire water column in the four lakes would exceed 7
Once again, the two deepest lakes (Geneva and Bourget) were the most sensitive to climate change, with the most important changes in water volumes exceeding the temperature thresholds considered, especially in the worst-case scenario (SSP585). However, when focusing on the lake volume fraction exceeding these characteristic temperature thresholds, without considering the associated duration, Lake Annecy appeared to be the most sensitive, with almost 75 % of the lake above 12
Dissolved oxygen (DO) is one of the most fundamental variables in lake systems (Wetzel, 2001). Dissolved oxygen depends on several variables, such as oxygen solubility and hydrometeorological conditions (Rajwa-Kuligiewicz et al., 2014), but also the intensity of biological processes such as photosynthesis, respiration, and decomposition of organic matter.
Jane et al. (2021) found that a decline in dissolved oxygen is widespread in surface water habitats, primarily associated with reduced solubility under warmer water temperatures. Here we investigate changes in oxygen solubility, i.e., the oxygen concentration in solution in equilibrium with the oxygen pressure in a gas phase, as a function of temperature.
In the four peri-alpine lakes, oxygen solubility as a function of water
temperature has decreased in both surface and deep waters over the last 30 years, with differences in amplitude. Water warming explained average rates of changes of
Despite the decrease in oxygen solubility being a direct inference of the increase in water temperature, our approach allows us to quantitatively assess oxy-thermal habitat changes in a global warming context relative to the long-term evolution of the water temperature. Our analysis provides a broader context for climate change impacts on lake physics that goes further than water warming, but also has implications in terms of oxy-thermal habitat changes that may increase the likelihood of community disruptions due to the disappearance of habitat over their suitable thermal ranges (Kraemer et al., 2021). The oxy-thermal stress substantially impacts the fish population's renewal, as it can substantially increase the yellow perch extirpation (Magee et al., 2018). However, they do not integrate oxygen consumption and production by photosynthesis or lateral flow paths and production in littoral zones which can be important for large and deep lake ecosystems. It would need to be adjusted with studies dealing with ecosystem oxygen production and consumption in the pelagic zone.
Finally, the effect of decreased oxygen solubility on fish habitats was assessed through some potential thresholds. The model predicted faster decreases of the lake volume fraction with oxygen solubility
The approach developed in this study, which consisted of reducing the number
of forcing variables to only air temperature and shortwave radiation, was defined based on the variables with the highest confidence level of the long-term predictions. This assumption is in line with the importance of both variables in warming trends in a peri-alpine lake, which were the main driving variables responding with 60 % and 40 %, respectively, of the increasing temperature trend, while all other meteorological variables showed small to negligible effects, which was assumed as representative for the majority of large deep lakes in Central Europe following a dimictic or monomictic regime (Schmid and Köster, 2016). Furthermore, it seems well adapted to long-term simulation approaches, with potential implications for paleolimnological studies, long-term forecast studies, or studies focused on the effects of climate change on lake ecological dynamics. The model errors
for the long term were relatively small for the four study sites, with RMSE
Thus, applying only air temperature and downwelling shortwave radiation from climatic projections provided a well-adapted model to the study of the four peri-alpine lakes in the long term, even with considering only the seasonal trends in wind speed, cloud cover, air relative humidity, and rainfall. In this sense, the approach seems adequate for long-term simulation approaches. No systematic error has been identified, as the model slightly underestimated (Lake Bourget) or overestimated (Lake Geneva) the water temperature, depending on the lake morphology. Positive biases could be attributed to the measurements carried out around midday and in good weather, whereas model outputs were averaged daily (Vinçon-Leite et al., 2014). Similarly, biases of estimations of the start, end, and duration of stratification may be attributed to the low frequency (i.e., bi-monthly) of limnological measurements, which do not allow precise estimations on the stratification periods. Besides this limitation, good performances for the Schmidt stability index suggest that the model could be used to assess the long-term variations in the stratification regime, while the duration still needs to be carefully interpreted.
This method allowed overcoming certain limitations such as the quality of
the input files related to the climate variables scaling. For instance, the
wind can vary within the same 0.5
A further limitation of this method is related to the correlation between the different climate variables, such as relative humidity and air temperature dependency. As the meteorological patterns replicated the seasonal fluctuations of each variable, this error is limited. Another possible option would have been to use a weather generator to simulate climate variables' evolutions, implemented to integrate these correlations.
Finally, the GLM model, integrating the energy balance for surface mixing and the diffusive transport below thermocline (Hipsey et al., 2019), simulated the water temperature in lakes Geneva and Bourget with quite good precision, but was less performant for lakes Annecy and Aiguebelette. Simstrat has well reproduced the temperature along the water column in Lake Geneva and quite well in Lake Bourget, but was much less efficient at simulating water temperature in the two shallowest lakes, Annecy and Aiguebelette.
In this study, an approach to simulate long-term trends in lake thermal regime and oxygen solubility has been tested and validated against 63 years of limnological data from the OLA lakes observatory. The approach shows that 1D thermal lake models perform well when run only with air temperatures and shortwave radiations as forcing variables, hence allowing to overcome certain limitations related to the quality of climate input data for the long term. Future application of the 1D model approach for long-term variations can be anticipated in paleolimnology, but also to assess past and future effects of climate change on the ecological dynamics and lake habitats.
Simulations show that over the last 30 years, epilimnion temperature has
increased on average by
Regarding oxygen condition, a decrease in oxygen solubility occurred over the last 30 years, at least in lakes Annecy and Bourget, with
Code and data used in this paper are available from the corresponding author upon a reasonable request.
The supplement related to this article is available online at:
JPJ, OD, DB, PAD, and BVL conceived and designed the study. OD and LS collected the data. OD performed the analyses and calculations. All authors actively took part in the interpretation of the results. OD wrote the original draft of the paper, and all the authors reviewed it. JPJ acquired the funding and guided the research.
The contact author has declared that none of the authors has any competing interests.
Publisher's note: Copernicus Publications remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
We thank the HESS editor, the reviewers, and the participants of the lively discussion in HESSD for their comments that helped to improve the paper. We gratefully acknowledge the financial support from the ANR C-ARCHIVES and the Pole ECLA (French Research Organization in Lake Ecology). We would like to thank the French Observatory of LAkes of the platform Analyses et Expérimentations pour les Ecosystèmes (OLA-ANAEE) for providing the long-term limnological data, and Victor Frossard from CARRTEL for thorough advances on the paper conception. We also thank Jean-Christophe Clément from CARRTEL for his proofreading.
This research has been supported by the French National Agency ANR C-ARCHIVES (grant no. 5283) and the Pole ECLA Ecosystèmes lacustres of the Office Français de la Biodiversité (OFB).
This paper was edited by Matthew Hipsey and reviewed by two anonymous referees.