Freshwater ecosystems provide vital services, yet are facing increasing risks from global change. In particular, lake thermal dynamics have been altered around the world as a result of climate change, necessitating a predictive understanding of how climate will continue to alter lakes in the future as well as the associated uncertainty in these predictions. Numerous sources of uncertainty affect projections of future lake conditions but few are quantified, limiting the use of lake modeling projections as management tools. To quantify and evaluate the effects of two potentially important sources of uncertainty, lake model selection uncertainty and climate model selection uncertainty, we developed ensemble projections of lake thermal dynamics for a dimictic lake in New Hampshire, USA (Lake Sunapee). Our ensemble projections used four different climate models as inputs to five vertical one-dimensional (1-D) hydrodynamic lake models under three different climate change scenarios to simulate thermal metrics from 2006 to 2099. We found that almost all the lake thermal metrics modeled (surface water temperature, bottom water temperature, Schmidt stability, stratification duration, and ice cover, but not thermocline depth) are projected to change over the next century. Importantly, we found that the dominant source of uncertainty varied among the thermal metrics, as thermal metrics associated with the surface waters (surface water temperature, total ice duration) were driven primarily by climate model selection uncertainty, while metrics associated with deeper depths (bottom water temperature, stratification duration) were dominated by lake model selection uncertainty. Consequently, our results indicate that researchers generating projections of lake bottom water metrics should prioritize including multiple lake models for best capturing projection uncertainty, while those focusing on lake surface metrics should prioritize including multiple climate models. Overall, our ensemble modeling study reveals important information on how climate change will affect lake thermal properties, and also provides some of the first analyses on how climate model selection uncertainty and lake model selection uncertainty interact to affect projections of future lake dynamics.
more »
« less
Ensemble of models shows coherent response of a reservoir’s stratification and ice cover to climate warming
Abstract Water temperature, ice cover, and lake stratification are important physical properties of lakes and reservoirs that control mixing as well as bio-geo-chemical processes and thus influence the water quality. We used an ensemble of vertical one-dimensional hydrodynamic lake models driven with regional climate projections to calculate water temperature, stratification, and ice cover under the A1B emission scenario for the German drinking water reservoir Lichtenberg. We used an analysis of variance method to estimate the contributions of the considered sources of uncertainty on the ensemble output. For all simulated variables, epistemic uncertainty, which is related to the model structure, is the dominant source throughout the simulation period. Nonetheless, the calculated trends are coherent among the five models and in line with historical observations. The ensemble predicts an increase in surface water temperature of 0.34 K per decade, a lengthening of the summer stratification of 3.2 days per decade, as well as decreased probabilities of the occurrence of ice cover and winter inverse stratification by 2100. These expected changes are likely to influence the water quality of the reservoir. Similar trends are to be expected in other reservoirs and lakes in comparable regions.
more »
« less
- PAR ID:
- 10354283
- Date Published:
- Journal Name:
- Aquatic Sciences
- Volume:
- 84
- Issue:
- 4
- ISSN:
- 1015-1621
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
More Like this
-
-
Abstract Although perennially ice‐covered Antarctic lakes have experienced variable ice thicknesses over the past several decades, future ice thickness trends and associated aquatic biological responses under projected global warming remain unknown. Heat stored in the water column in chemically stratified Antarctic lakes that have middepth temperature maxima can significantly influence the ice thickness trends via upward heat flux to the ice/water interface. We modeled the ice thickness of the west lobe of Lake Bonney, Antarctica, based on possible future climate scenarios utilizing a 1D thermodynamic model that accounts for surface radiative fluxes as well as the heat flux associated with the temperature evolution of the water column. Model results predict that the ice cover of Lake Bonney will shift from perennial to seasonal within one to four decades, a change that will drastically influence ecosystem processes within the lake.more » « less
-
The General Lake Model (GLM) is a one-dimensional open-source model code designed to simulate the hydrodynamics of lakes, reservoirs and wetlands. GLM was developed to support the science needs of the Global Lake Ecological Observatory Network (GLEON), a network of lake sensors and researchers attempting to understand lake functioning and address questions about how lakes around the world vary in response to climate and land-use change. The scale and diversity of lake types, locations and sizes, as well as the observational data within GLEON, created the need for a robust community model of lake dynamics with sufficient flexibility to accommodate a range of scientific and management needs of the GLEON community. This paper summarises the scientific basis and numerical implementation of the model algorithms, including details of sub-models that simulate surface heat exchange and ice-cover dynamics, vertical mixing and inflow/outflow dynamics. A summary of typical parameter values for lakes and reservoirs collated from a range of sources is included. GLM supports a dynamic coupling with biogeochemical and ecological modelling libraries for integrated simulations of water quality and ecosystem health. An overview of approaches for integration with other models, and utilities for the analysis of model outputs and for undertaking sensitivity and uncertainty assessments is also provided. Finally, we discuss application of the model within a distributed cloud-computing environment, and as a tool to support learning of network participants.more » « less
-
Abstract The concentration of dissolved oxygen (DO) is an important attribute of aquatic ecosystems, influencing habitat, drinking water quality, biodiversity, nutrient biogeochemistry, and greenhouse gas emissions. While average summer DO concentrations are declining in lakes across the temperate zone, much remains unknown about seasonal factors contributing to deepwater DO losses. It is unclear whether declines are related to increasing rates of seasonal DO depletion or changes in seasonal stratification that limit re‐oxygenation of deep waters. Furthermore, despite the presence of important biological and ecological DO thresholds, there has been no large‐scale assessment of changes in the amount of habitat crossing these thresholds, limiting the ability to understand the consequences of observed DO losses. We used a dataset from >400 widely distributed lakes to identify the drivers of DO losses and quantify the frequency and volume of lake water crossing biologically and ecologically important threshold concentrations ranging from 5 to 0.5 mg/L. Our results show that while there were no consistent changes over time in seasonal DO depletion rates, over three‐quarters of lakes exhibited an increase in the duration of stratification, providing more time for seasonal deepwater DO depletion to occur. As a result, most lakes have experienced summertime increases in the amount of water below all examined thresholds in deepwater DO concentration, with increases in the proportion of the water column below thresholds ranging between 0.9% and 1.7% per decade. In the 30‐day period preceding the end of stratification, increases were greater at >2.2% per decade and >70% of analyzed lakes experienced increases in the amount of oxygen‐depleted water. These results indicate ongoing climate‐induced increases in the duration of stratification have already contributed to reduction of habitat for many species, likely increased internal nutrient loading, and otherwise altered lake chemistry. Future warming is likely to exacerbate these trends.more » « less
-
To increase geospatial awareness about local water resources, our team developed learning resources for the 150 km² Lake Sidney Lanier reservoir located in North Georgia, USA. The reservoir is vital for hydroelectric power generation, recreation, tourism, and consumptive uses. Using geospatial analysis in Google Earth Engine (GEE), we analyzed precipitation trends in the watershed using Climate Hazards Group InfraRed Precipitation with Station (CHIRPS) data. We also quantified expansion and contraction of reservoir surface area using Landsat-derived Global Surface Water data. As Lake Sidney Lanier is a managed reservoir, surface water extent fluctuations are related to climatic variables, consumptive use, and hydropower generation. Water temperature varies based on seasonality, water depth, water clarity, and lake stratification. Changing temperature dynamics affect ecosystem health and determine other important water quality parameters such as dissolved oxygen concentrations. Landsat 8 Thermal Infrared Sensor (TIRS) data were used to examine temperature trends over multiple years and investigate the timing of lake stratification and mixing. Highly turbid waters are associated with pollutants and lower water quality and can affect ecosystem productivity by minimizing sunlight penetration into the water column. Sentinel 2 MSI data were processed using a turbidity algorithm to analyze temporal trends and spatial correlations with reservoir inflows. Finally, high concentrations of chlorophyll a were used as a proxy to identify harmful algal blooms. The spatial differences in headwaters and near-dam locations were examined and near real-time satellite data were explored for potential development of early-warning systems to protect ecosystem and human health.more » « less