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Abstract Brine beneath Taylor Glacier has been proposed to enter the proglacial west lobe of Lake Bonney (WLB) as well as from Blood Falls, a surface discharge point at the Taylor Glacier terminus. The brine strongly influences the geochemistry of the water column of WLB. Year-round measurements from this study are the first to definitively identify brine intrusions from a subglacial entry point into WLB. Furthermore, we excluded input from Blood Falls by focusing on winter dynamics when the absence of an open water moat prevents surface brine entry. Due to the extremely high salinities below the chemocline in WLB, density stratification is dominated by salinity, and temperature can be used as a passive tracer. Cold brine intrusions enter WLB at the glacier face and intrude into the water column at the depth of neutral buoyancy, where they can be identified by anomalously cold temperatures at that depth. High-resolution measurements also reveal under-ice internal waves associated with katabatic wind events, a novel finding that challenges long-held assumptions about the stability of the WLB water column. 

Abstract. The General Lake Model (GLM) is a one-dimensional open-source 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 researchers using sensors to understand lake functioning and address questions about how lakes around the world respond to climate and land use change. The scale and diversity of lake types, locations, and sizes, and the expanding observational datasets created the need for a robust community model of lake dynamics with sufficient flexibility to accommodate a range of scientific and management questions relevant to the GLEON community. This paper summarizes 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. We demonstrate the suitability of the model for different lake types that vary substantially in their morphology, hydrology, and climatic conditions. GLM supports a dynamic coupling with biogeochemical and ecological modelling libraries for integrated simulations of water quality and ecosystem health, and options for integration with other environmental models are outlined. Finally, we discuss utilities for the analysis of model outputs and uncertainty assessments, model operation within a distributed cloud-computing environment, and as a tool to support the learning of network participants.

 

Lake surface temperatures are warming in many regions and have the potential to alter seasonal thermal stratification. However, the effects of climate change on thermal stratification can be difficult to characterize because trends in thermal stratification can be regulated by changes in multiple climate variables and other characteristics, such as water clarity. Here, we use long‐term (1993–2017) data from near‐pristine Crater Lake (Oregon) to understand long‐term changes in the depth and strength of summer stratification, measured by the center of buoyancy and Schmidt Stability, respectively. The depth of stratification has shoaled significantly (2.4 m decade⁻¹), while stratification strength exhibited no long‐term trend. Empirical observations and modeling scenarios demonstrate that atmospheric stilling at Crater Lake is associated with the 25‐year shoaling trend as spring wind speeds declined over the observation period. While summer lake surface water and air temperatures warmed during the study period, spring air temperatures were variable and correlated with summer Schmidt Stability. Our results indicate that warmer spring air temperature resulted in earlier onset of stratification and stronger summer stratification. The observed shoaling of stratification depth at Crater Lake may have important ecological consequences, especially for non‐motile primary producers who can become constrained within a thinner epilimnion and exposed to higher solar radiation and reduced upwelling of nutrients. Driven by climate changes, many large lakes may be experiencing similar trends in seasonal stratification.

 

Increases in the concentration of dissolved organic matter (DOM) have been documented in many inland waters in recent decades, a process known as “browning”. Previous studies have often used space‐for‐time substitution to examine the direct consequences of increased DOM on lake ecosystems. However, browning often occurs concomitant with other ecologically important water chemistry changes that may interact with or overwhelm any potential ecological response to browning itself. Here we examine a long‐term (~20 year) dataset of 28 lakes in the Adirondack Park, New York, USA, that have undergone strong browning in response to recovery from acidification. With these data, we explored how primary producer and zooplankton consumer populations changed during this time and what physical and chemical changes best predicted these long‐term ecosystem changes. Our results indicate that changes in primary producers are likely driven by reduced water clarity due to browning, independent of changes in nutrients, counter to previously hypothesized primary producer response to browning. In contrast, declines in calcium concomitant with browning play an important role in driving long‐term declines in zooplankton biomass. Our results indicate that responses to browning at different trophic levels are decoupled from one another. Concomitant chemical changes have important implications for our understanding of the response of aquatic ecosystems to browning.

 

Lake depth is an important characteristic for understanding many lake processes, yet it is unknown for the vast majority of lakes globally. Our objective was to develop a model that predicts lake depth using map-derived metrics of lake and terrestrial geomorphic features. Building on previous models that use local topography to predict lake depth, we hypothesized that regional differences in topography, lake shape, or sedimentation processes could lead to region-specific relationships between lake depth and the mapped features. We therefore used a mixed modeling approach that included region-specific model parameters. We built models using lake and map data from LAGOS, which includes 8164 lakes with maximum depth (Zmax) observations. The model was used to predict depth for all lakes ≥4 ha (n = 42 443) in the study extent. Lake surface area and maximum slope in a 100 m buffer were the best predictors of Zmax. Interactions between surface area and topography occurred at both the local and regional scale; surface area had a larger effect in steep terrain, so large lakes embedded in steep terrain were much deeper than those in flat terrain. Despite a large sample size and inclusion of regional variability, model performance (R2 = 0.29, RMSE = 7.1 m) was similar to other published models. The relative error varied by region, however, highlighting the importance of taking a regional approach to lake depth modeling. Additionally, we provide the largest known collection of observed and predicted lake depth values in the United States.