One-dimensional Lake Model Research Articles

Assessing the Impacts of Climate Change and Water Extraction on Thermal Stratification and Water Quality of a Subtropical Lake Using the GLM-AED Model

This study combined a catchment model and one-dimensional lake model (GLM-AED) to simulate the response of hydrodynamics and water quality of subtropical Advancetown Lake (South-East Queensland, Australia) to future changing climates from 2040 to 2069 and 2070 to 2099 under Representative Concentration Pathway (RCP) 4.5 and 8.5 and increased water demand from a 50% increase in population over current levels. The simulation adequately reproduced water temperature (RMSE of 0.6 °C), dissolved oxygen (DO) (RMSE of 2 mg/L), and other water quality variables, such as nitrogen, phosphorus, and chlorophyll a (Chl-a). Warming temperatures dominated the change in thermal structure and hydrodynamic status of the lake under future climate change conditions. Projected changes in precipitation and hydrological response from the upstream catchment might, however, partly offset the warming temperatures under future climate change. Increased water withdrawal due to population growth, which involved water extraction from the epilimnion, showed antagonistic effects on water stability compared to those from climate change. Under a high emission scenario of RCP8.5 during the 2080s, there is an increased likelihood of winter turnover failure in Advancetown Lake. Nutrient concentrations were simulated to decrease from reduced catchment loads under future climate change conditions. However, Chl-a concentrations were simulated to increase, especially during the period after winter turnover, under these future conditions. The depth of the hypoxia front during stratification is expected to decrease and move towards the water surface, attributable to the warming water temperatures and prolonged thermal stratification, which might affect biogeochemical processes and exchange fluxes between the hypolimnion and bottom sediments. These potential changes may present challenges for water resource management under future conditions of climate change and population growth.

Past and future climate change effects on the thermal regime and oxygen solubility of four peri-alpine lakes

Abstract. 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 < 1.95 ∘C. Over the previous 3 decades, water temperatures have increased by 0.46 ∘C per decade (±0.02 ∘C) in the epilimnion and 0.33 ∘C per decade (±0.06 ∘C) in the hypolimnion. Concomitantly and due to thermal change, O2 solubility has decreased by −0.104 mg L−1 per decade (±0.005 mg L−1) and −0.096 mg L−1 per decade (±0.011 mg L−1) in the epilimnion and hypolimnion, respectively. Based on the shared socio-economic pathway SSP370 of the Intergovernmental Panel on Climate Change (IPCC), peri-alpine lakes could face an increase of 3.80 ∘C (±0.20 ∘C) in the next 70 years, accompanied by a decline of 1.0 mg L−1 (±0.1 mg L−1) of O2 solubility. Together, these results highlight a critical alteration in lake thermal and oxygen conditions in the coming decades, and a need for a better integration of long-term lake observatories data and lake models to anticipate climate effects on lake thermal regimes and habitats.

Numerical simulation of thermal stratification in Lake Qiandaohu using an improved WRF-Lake model

Lake thermal stratification is important for regulating lake environments and ecosystems and is sensitive to climate change and human activity. However, numerical simulation of coupled hydrodynamics and heat transfer processes in deep lakes using one-dimensional lake models remains challenging because of the insufficient representation of key parameters. In this study, Lake Qiandaohu, a deep and warm monomictic reservoir, was used as an example to investigate thermal stratification via an improved parameterization scheme of the Weather Research and Forecast (WRF)-Lake. A comparison with in situ observations demonstrated that the default WRF-Lake model was able to simulate well the seasonal variation of the lake thermal structure. However, the simulations exhibited cold biases in lake surface water temperature (LSWT) throughout the year while generating weaker stratification in summer, thereby leading to an earlier cooling period in autumn. With an improved parameterization (i.e., via determination of initial lake water temperature profiles, light extinction coefficients, eddy diffusion coefficients and surface roughness lengths), the modified WRF-Lake model was able to better simulate LSWT and thermal stratification. Critically, employing realistic initial conditions for lake water temperature is essential for producing realistic hypolimnetic water temperatures. The use of time-dependent light extinction coefficients resulted in a deep thermocline and warm LSWT. Enlarging eddy diffusivity led to stronger mixing in summer and further influenced autumn cooling. The parameterized surface roughness lengths mitigated the excessive turbulent heat loss at the lake surface, improved the model performance in simulating LSWT, and generated a warm mixed layer. This study provides guidance on model parameterization for simulating the thermal structure of deep lakes and advances our understanding of the strength and revolution of lake thermal stratification under seasonal changes.

Integration of Photodegradation Process of Organic Micropollutants to a Vertically One-Dimensional Lake Model

Photochemical reactions in the water environments are essential for understanding the fate of organic pollutants, which exist widely in aquatic environments causing potential risks. Therefore, this study aimed to integrate a module of the photodegradation process into a vertically one-dimensional model of the lake to quantify the influence of phytoplankton on the photodegradation process for the first time. After adjusting the code of the APEX (Aqueous Photochemistry of Environmentally occurring Xenobiotics), the suite of photochemical reactions was integrated into the pollutant module of MyLake (Multi-year Lake simulation), as MyLake-Photo. This integrated model was then applied to calculate the concentration of four organic micropollutants under the ranges of solar radiation conditions (0–390 W/m2), phytoplankton biomass (0.01–20 mg/m3 of chlorophyll), and water temperature (1–25 °C). These scenario analyses revealed that phytoplankton biomass and pollutant photodegradation are negatively correlated owing to the light absorption by chlorophyll. Thermal stratification also significantly influenced the vertical distribution of organic micropollutants. Then, the model was applied for calculating a temporal distribution of ibuprofen concentration in Lake Giles (PA, USA) with a simple but realistic assumption. The concentration of organic micropollutants varies with seasons, which was mainly affected by the changes in irradiance and water temperature. In this manner, the integrated model is capable of estimating the temporal and vertical shifts of the concentration of organic micropollutants in lakes, allowing us to investigate the fate of organic micropollutants in lakes. The integrated model also allows us to investigate the effect of phytoplankton and CDOM on the photodegradation of organic micropollutants, which should be combined with field surveys and experimental studies for further improvement.

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

Abstract. The seasonal ice cover in lakes of the Qinghai–Tibet Plateau is a transient and vulnerable part of the cryosphere, whose characteristics depend on the regional climate: strong solar radiation in the context of the dry and cold environment because of the high altitude and relatively low latitude. We use the first under-ice temperature observations from the largest Tibetan freshwater lake, Ngoring Lake, and a one-dimensional lake model to quantify the mechanism of solar thermal accumulation under ice, which relies on the ice optical properties and weather conditions, as well as the effect of the accumulated heat on the land–atmosphere heat exchange after the ice breakup. The model was able to realistically simulate the feature of the Ngoring Lake thermal regime: the “summer-like” temperature stratification with temperatures exceeding the maximum density point of 3.98 ∘C across the bulk of the freshwater column. A series of sensitivity experiments revealed solar radiation was the major source of under-ice warming and demonstrated that the warming phenomenon was highly sensitive to the optical properties of ice. The heat accumulated under ice contributed to the heat release from the lake to the atmosphere for 1–2 months after ice-off, increasing the upward sensible and latent surface heat fluxes on average by ∼ 50 and ∼ 80 W m−2, respectively. Therefore, the delayed effect of heat release on the land–atmosphere interaction requires an adequate representation in regional climate modeling of the Qinghai–Tibet Plateau and other lake-rich alpine areas.

Evaluation of the WRF-Lake Model in the Large Dimictic Reservoir: Comparisons with Field Data and Another Water Temperature Model

Abstract The WRF-lake, as a one-dimensional (1D) lake model popularly used for coupling with the Weather Research and Forecasting (WRF) system and modeling lake–atmosphere interactions, does not consider the heat exchange caused by inflow–outflow, which is an important characteristic of large reservoirs and can affect the energy budget and reservoir–atmosphere interactions. We evaluated the WRF-lake model by applying it at a large dimictic reservoir, Miyun Reservoir, in northern China. The results show that the WRF-lake model, though ignoring inflow–outflow, yields good surface water temperature simulation through reasonable parameterization. The Minlake model, as a better physically based model in reservoirs, was used to test the effect of inflow–outflow, including heat carried by inflow–outflow water exchange and water level change on the 1D model’s performance. The effect of heat carried by inflow–outflow is mainly in summer, negatively correlated with hydraulic residence time and positively correlated with temperature difference between inflow and outflow. For a reservoir with hydraulic residence time of 3 years and temperature difference between inflow and outflow about 10°C in summer, the heat carried by inflow–outflow is far less than the heat exchange through the surface (<2%) and therefore has little influence on total energy balance. The effect of water level change is mainly on latent heat and sensible heat in unit area, rather than outgoing longwave radiation. Though influencing the temperature in deep layers, the water level change does not have a significant impact on the surface temperature. Significance Statement The purpose of this study is to evaluate the applicability of WRF-lake, an important submodule of the Weather Research and Forecasting (WRF) system, in the large dimictic reservoir. This is important because WRF-lake does not consider the effect of inflow–outflow and water level change, which are important characteristics of large reservoirs and can affect the heat budget and reservoir–atmosphere interactions. The applicability of WRF-lake in large reservoirs with frequent inflow–outflow and water level change is widely concerned but has never been discussed in previous studies. Our research explored the applicability of WRF-lake in the large dimictic reservoir and discussed the effect of inflow–outflow and water level change quantitively.

Diagnosing Discrepancies between Observations and Models of Surface Energy Fluxes in a Midlatitude Lake

Abstract The physical processes of heat exchange between lakes and the surrounding atmosphere are important in simulating and predicting terrestrial surface energy balance. Latent and sensible heat fluxes are the dominant physical process controlling ice growth and decay on the lake surface, as well as having influence on regional climate. While one-dimensional lake models have been used in simulating environmental changes in ice dynamics and water temperature, understanding the seasonal to daily cycles of lake surface energy balance and its relationship to lake thermal properties, atmospheric conditions, and how those are represented in models is still an open area of research. We evaluated a pair of one-dimensional lake models, Freshwater Lake (FLake) and the General Lake Model (GLM), to compare modeled latent and sensible heat fluxes against observed data collected by an eddy covariance tower during a 1-yr period in 2017, using Lake Mendota in Madison, Wisconsin, as our study site. We hypothesized transitional periods of ice cover as a leading source of model uncertainty, and we instead found that the models failed to simulate accurate values for large positive heat fluxes that occurred from late August into late December. Our results ultimately showed that one-dimensional models are effective in simulating sensible heat fluxes but are considerably less sensitive to latent heat fluxes than the observed relationships of latent heat flux to environmental drivers. These results can be used to focus future improvement of these lake models especially if they are to be used for surface boundary conditions in regional numerical weather models. Significance Statement While lakes consist of a small amount of Earth’s surface, they have a large impact on local climate and weather. A large amount of energy is stored in lakes during the spring and summer, and then removed from lakes before winter. The effect is particularly noticeable in high latitudes, when the seasonal temperature difference is larger. Modeling this lake energy exchange is important for weather models and measuring this energy exchange is challenging. Here we compare modeled and observed energy exchange, and we show there are large amounts of energy exchange happening in the fall, which models struggle to capture well. During periods of partial ice coverage in early winter, lake behavior can change rapidly.

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

Abstract. The 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 ∼ 100 d, if simulated without inflow and outflow effects, tend to exhibit a statistically significant deviation in the computed surface temperatures regardless of their morphological characteristics.

A new pseudo three-dimensional hydrodynamic model with Lagrangian vertical mixing and Eulerian horizontal mass exchange

The Multi-Basin DYnamic Reservoir Simulation Model (MB-DYRESM) has been developed to bridge the gap between the computationally cheap, one-dimensional lake models and the computationally expensive, three-dimensional lake models. It was extended from the classic one-dimensional lake model DYRESM by incorporating a horizontal water exchange algorithm to simulate gravitational mass transport between adjacent sub-basins. Numerical experiments with increasing complexity were carried out for capacity demonstration, in which MB-DYRESM successfully reproduced the thermal structure and mass distribution in each sub-basin with accuracy comparable to and computational speed approximately 300 times faster than the three-dimensional model applied in parallel. In situations where turbulence was suppressed by stratification it actually provided better simulation results. The combination of low computational demand, reasonable spatial resolution of mass flux path and constrained numerical diffusion makes MB-DYRESM a more applicable option for simulations where the balance between affordable computational power and proper spatial resolution is concerned.

The Effect of the Horizontal Dimensions of Inland Water Bodies on the Thickness of the Upper Mixed Layer

The effect of the horizontal dimensions of inland water bodies (lakes and reservoirs) on the vertical mixing processes is studied. We consider a three-dimensional hydrostatic model and a one-dimensional LAKE model based on the averaging of three-dimensional equations over a horizontal section of the water body. The processes of vertical mixing in both models were simulated with the use of k–e-closure. LAKE model takes into account the seiches through the parameterization of the pressure gradient and horizontal viscosity. The models were verified against the Kato-Phillips experiment data, and a series of numerical experiments was carried out to demonstrate the effect of the horizontal size of the water body on mixed-layer depth. It is shown that the horizontal dimensions of a water body has to be taken into account in the simulation of the vertical temperature distribution in lakes and reservoirs with the size much less than the internal Rossby deformation radius.

Local and continental-scale controls of the onset of spring phytoplankton blooms: Conclusions from a proxy-based model.

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, one-dimensional lake model to simulate the seasonal dynamics of the underwater light climate in 16 lake types characterized by the factorial combination of four lake depths with four levels of water transparency. We did so at 1962 locations across Western Europe and over 31years (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.

Improvements of the coupled WRF-Lake model over Lake Nam Co, Central Tibetan Plateau

A series of model sensitivity simulations are carried out to calibrate and improve the Weather Research and Forecasting Model coupled with a one-dimensional lake model (WRF-Lake) based on observations over Lake Nam Co. Using the default lake model parameters, the solution of WRF-Lake exhibits significant biases in both the lake thermodynamics and regional climatology, i.e., higher lake surface temperature (LST), earlier onset of summer thermal stratification, and overestimated near-surface air temperature and precipitation induced by the lake’s excessive warming and moistening impacts. The performance of WRF-Lake is improved through adjusting the initial lake temperature profile, the temperature of maximum water density (Tdmax), the surface roughness length, and the light extinction coefficient. Results show that initializing the water temperature with spring observation mitigates the LST overestimation and reduces the timing error of the onset of thermal stratification. By further adjusting Tdmax from 4 °C to the observed value of 3.5 °C, the LST increase from June to mid-July is enhanced and the buildup of thermal stratification is more accurately predicted. Through incorporating the parameterized surface roughness length and decreasing the light extinction coefficient, the model better reproduces the observed daily evolution of LST and vertical lake temperature profile. The calibrated WRF-Lake effectively mitigates the overestimation of over-lake air temperature at 2 m height and precipitation over regions downwind the lake. This suggests that an improved lake scheme within the coupled WRF-Lake is essential for realistically simulating the lake–air interactions and the regional climate over the lake-rich Tibetan Plateau.

Reconstructing Six Decades of Surface Temperatures at a Shallow Lake

Lake surface water temperature (LSWT) plays a fundamental role in the lake energy budget. However, direct observations of LSWT require considerable effort for acquisition and hence are rare relative to a large number of lakes. In lakes where LSWT has not been covered sufficiently by in situ measurements, remote sensing and lake modeling can be used to produce a fine spatio-temporal record of LSWTs. In our study, the Moderate-Resolution Imaging Spectroradiometer (MODIS) LSWT was used to compare with in situ data at the overpass times over the six sites in Lake Chaohu, a large shallow lake in China. MODIS-derived LSWT reflected the variation of lake surface temperature well, with a correlation coefficient of 0.96 and a cool bias of 1.25 °C. The bias was modified by an “Upper Envelop” smoothing method and then employed to evaluate the general lake model (GLM) performance, a one-dimensional hydrodynamic model. The GLM simulations showed good performance compared with MODIS LSWT data at an interannual time scale. A 57-year record of simulated LSWT was hindcast by the well-calibrated GLM for Lake Chaohu. The results showed that LSWT decreased by 0.08 °C/year from 1960 to 1981 and then increased by 0.05 °C/year. These trends were most likely caused by a cooling effect of decreased surface incident solar radiation and a warming effect of reduced wind speed. Our study promoted the use of MODIS-derived LSWT as an alternative data source, and then combined with a numerical model for inland water surface temperature, and also further provided an understanding of climate warming effect on such a shallow eutrophic lake. Key points: (1) Moderate-Resolution Imaging Spectroradiometer (MODIS) lake water surface temperature (LSWT) was validated with real-time in situ data collected at Lake Chaohu with high accuracy; (2) MODIS LSWT was modified by the bias correction and employed to evaluate a one-dimensional lake model at interannual and intraannual scale; The LSWT hindcast by a well-calibrated model at Lake Chaohu decreased by 0.08 °C/year from 1960 to 1981 and increased by 0.05 °C/year from 1982 to 2016.

Attribution of Lake Warming in Four Shallow Lakes in the Middle and Lower Yangtze River Basin.

Many physical, chemical, and biological processes in lakes depend on lake water temperature. However, attribution of the warming rate in a shallow lake is not well understood yet. Here, we evaluated a one-dimensional lake model FLake by observed daily lake surface water temperature (LSWT) at four typical lakes in the Middle and Lower Yangtze River basin and then attributed LSWT warming to climate variables during the period 1979-2017. We found that FLake could capture well the seasonal/interannual variation of observed LSWT. During the 39-year study period, LSWT significantly warms at a rate of 0.26-0.28 °C per decade, 24-35% slower than the air temperature. Increased solar radiation and air temperature contributed to most (>80%) of the LSWT warming. The warming trend of LSWT in the spring is the largest among the four seasons, 2-4 times the warming rate of the other seasons. Brightening in the spring contributes 50-64% of the largest spring warming. The future air warming plus the brightening trend with the Clean Air Act in China would amplify LSWT warming and, thus, advance and/or deteriorate algae blooms, especially in spring.

Assessment of coupled CRCM5–FLake on the reproduction of wintertime lake-induced precipitation in the Great Lakes Basin

This study assesses the high-resolution, 0.11° (12 km), Canadian Regional Climate Model Version 5 (CRCM5), interactively coupled to the one-dimensional Freshwater Lake model (FLake), to predict wintertime precipitation along the Canadian snowbelts of Lake Superior and Lake Huron. CRCM5–FLake was compared against various datasets to evaluate the 20-year (1995–2014) SWE and wintertime precipitation, seven lake-induced precipitation events and lake effect snowfall (LES) predictor variables during the months of December and January. The findings of SWE along both snowbelts in December and January show MBD ≤− 10 mm and ≤− 30 mm, respectively. Similarly, precipitation results along both snowbelts in December and January show MBD ≤− 5 mm and ≤− 10 mm, respectively. The negative biases in simulated SWE and precipitation, predominantly along the snowbelts, suggest that the model may un-realistically represent lake effect processes. Comparison of lake-induced precipitation events also indicates that the model mostly under-predicts the daily accumulated precipitation associated with each event but tends to accurately capture the timing and the general location of the squalls along the snowbelts, though not for highly localised snow bands. Furthermore, lake-wide results of LES predictor variables indicate that the model over-estimates lake surface temperature (LST) for both lakes during December and January and under-estimates ice cover concentrations for both lakes in December. The resultant biases could be attributed to limitations within the coupled RCM because the quality of reproducing lake-induced precipitation in this region is highly dependent on the performance of FLake.

Epilimnion and metalimnion thermal water temperature variables in Moroccan’s Lakes using a one-dimensional fresh-water lake model

ABSTRACT Lakes play an important role in the local weather formation and generate specific climate features over the adjacent land. This is caused primarily by the dramatic difference between the lake surface temperature and the temperature of surrounding land that is observed almost always, except when both lake and land are covered by snow. There are also sharp discontinuities at the water bodies’ boundaries of other thermodynamic, radiation and aerodynamic surface characteristics, such as roughness height and albedo. This, in turn, causes significant spatial heterogeneity of surface turbulent and radiation fluxes in regions densely occupied by lakes and other water bodies. A one-dimensional lake model has been used to simulate the thermal water temperature variables, over a 35-yr period. This model is highly parameterized and is designed for long-term calculations of lake thermodynamics at low computational costs and with minimum adjustment. An epilimnion and metalimnion temperatures variables are presented. The result analysis shows that epilimnion temperatures increased, while metalimnion temperatures decreased. On the other hand, an abrupt change in epilimnion temperature after 1998 and 2006 in Lake Sidi Ali; and after 1989, and 1982 for Sidi Boughaba Lake, caused by climate change. The predictive model can be used to obtain a first-order estimation of water temperature in Moroccan's Lakes, affected by climate change.

A multi-lake comparative analysis of the General Lake Model (GLM): Stress-testing across a global observatory network

The modelling community has identified challenges for the integration and assessment of lake models due to the diversity of modelling approaches and lakes. In this study, we develop and assess a one-dimensional lake model and apply it to 32 lakes from a global observatory network. The data set included lakes over broad ranges in latitude, climatic zones, size, residence time, mixing regime and trophic level. Model performance was evaluated using several error assessment metrics, and a sensitivity analysis was conducted for nine parameters that governed the surface heat exchange and mixing efficiency. There was low correlation between input data uncertainty and model performance and predictions of temperature were less sensitive to model parameters than prediction of thermocline depth and Schmidt stability. The study provides guidance to where the general model approach and associated assumptions work, and cases where adjustments to model parameterisations and/or structure are required.

Thermal response of Moroccan lakes to climatic warming: first results

Water temperature plays a primary role in controlling a wide range of physical, geochemical and ecological processes in lakes, with considerable influences on lake water quality and ecosystem functioning. In this paper, we report on the ability of the one-dimensional lake model to simulate the water temperature of Moroccan lakes, i.e., Sidi Boughaba and Sidi Ali lakes, over a 35 yrs period from 1979 to 2014, affected by climate change and based on a freshwater lake model (FLake). During the study periods, two variables are studied, the epilimnion and metalimnion temperatures. The result analysis shows that epilimnion temperatures increased, while metalimnion temperatures decreased. Additionally, we calculate significant air temperature, wind speed and water temperature variation and illustrate, using a sequential t test analysis of regime shifts (STARS) based on the Rodionov method, a substantial increase in annually averaged of all variables, in response to an abrupt shift in the climate. Schmidt stability showed a significant increase for Sidi Ali Lake and near 0 for Sidi Boughaba Lake. On the other hand, the sensitivity analysis (i.e., one-at-a-time (OAT) method) of the atmospheric variable is discussed. The results show good agreement with water temperature observations that suggests that the predictive model can be used to obtain a first-order estimation of water temperature in Moroccan lakes. Hence, it is possible to apply this model in other Moroccan lakes to simulate the behavior of temperature and to investigate the potential future warming of the water column in lakes, affected by climate change.

Parameter sensitivity analysis of a 1-D cold region lake model for land-surface schemes

Abstract. Lakes might be sentinels of climate change, but the uncertainty in their main feedback to the atmosphere – heat-exchange fluxes – is often not considered within climate models. Additionally, these fluxes are seldom measured, hindering critical evaluation of model output. Analysis of the Canadian Small Lake Model (CSLM), a one-dimensional integral lake model, was performed to assess its ability to reproduce diurnal and seasonal variations in heat fluxes and the sensitivity of simulated fluxes to changes in model parameters, i.e., turbulent transport parameters and the light extinction coefficient (Kd). A C++ open-source software package, Problem Solving environment for Uncertainty Analysis and Design Exploration (PSUADE), was used to perform sensitivity analysis (SA) and identify the parameters that dominate model behavior. The generalized likelihood uncertainty estimation (GLUE) was applied to quantify the fluxes' uncertainty, comparing daily-averaged eddy-covariance observations to the output of CSLM. Seven qualitative and two quantitative SA methods were tested, and the posterior likelihoods of the modeled parameters, obtained from the GLUE analysis, were used to determine the dominant parameters and the uncertainty in the modeled fluxes. Despite the ubiquity of the equifinality issue – different parameter-value combinations yielding equivalent results – the answer to the question was unequivocal: Kd, a measure of how much light penetrates the lake, dominates sensible and latent heat fluxes, and the uncertainty in their estimates is strongly related to the accuracy with which Kd is determined. This is important since accurate and continuous measurements of Kd could reduce modeling uncertainty.

Comparison of one-dimensional (1-D) column lake models prediction for surface water temperature in eight selected Moroccan lakes

Water temperature plays a primary role in controlling a wide range of physical, geochemical, and ecological processes in lakes, with considerable influences on lake water quality and ecosystem functioning. In this paper, we report on the ability of two one-dimensional (1-D) lake models, i.e. the Hostetler and FLake models, to simulate the surface water temperature in eight selected Moroccan lakes: Sidi Ali, Tislit, Ifni, Daït Erroumi, Ouiouane, Aguelmam Azegza, Sidi Boughaba, and Iffer, which present a wide range of morphometry and hydrological characteristics, over a five-year period from 2008 to 2012. The FLake and Hostetler lake models perform adequately for small subgrid-scale lakes and for large resolved lakes with shallow depth. The two lake models exhibit specific strengths and weaknesses. Hostetler calculates too rapid spring warming and too warm surface water temperature, especially in large and deep lakes; FLake tends to damp the diurnal cycle of surface water temperature. These differences could be partially attributed to the biases in the driving data and most importantly to the lack of representation of complex processes in the models, such as horizontal transfer of water and heat, etc. Statistical performance evaluation is conducted on the models’ results. On the other hand, Schmidt stability showed a significant increase for deep lakes and near ~0 for shallow depth lakes. The predictive models can be used to obtain a first-order estimation of surface water temperature in Moroccan lakes.