General Lake Model Research Articles

Variable withdrawal elevations as a management tool to counter the effects of climate warming in Germany\u2019s largest drinking water reservoir

BackgroundThermal stratification in reservoirs is a significant factor affecting water quality, and can be strongly influenced by climate change and operational strategies. Reservoirs in the temperate zone react most sensitively to climate warming during winter as ice cover and inversed stratification are about to disappear in a warmer world. In this study, two well-established hydrodynamic models, the one-dimensional General Lake Model (GLM) and the two-dimensional CE-QUAL-W2 (W2), were used to investigate the response of winter inversed stratification in the Rappbode Reservoir to future climate warming, combined with different water withdrawal elevations.ResultsUnder increased air temperature, the duration of inversed stratification is reduced and the inversion phenomenon will entirely disappear under current management if the air temperature is increased high enough (more than 4.5 K) in the future. Under strong climate warming, the Rappbode Reservoir will therefore change from a dimictic to a monomictic mixing type. Changing the reservoir management from deep withdrawal (e.g., below 350 m a.s.l.) to shallow withdrawal elevations (e.g., above 390 m a.s.l.) reduces internal heat energy stored in the reservoir in summer and prolongs the inversed stratification period in winter. This strategy can retain the dimictic behavior even under strong warming.ConclusionsOur study indicates that adjusting the withdrawal elevation is an effective management instrument to control the winter conditions and can, in fact, mitigate climate warming effects on winter hydrodynamics by stabilizing the dimictic mixing type.

A General Lake Model (GLM 3.0) for linking with high-frequency sensor data from the Global Lake Ecological Observatory Network (GLEON)

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.

Applicability of a one-dimensional coupled ecological-hydrodynamic numerical model to future projections in a very deep large lake (Lake Maggiore, Northern Italy/Southern Switzerland)

One-dimensional coupled ecological-hydrodynamic numerical models of lakes require extensive calibration of their chemical and biological parameters. Application of these models to future projections relies on the time invariance of the calibrated model parameters and of the adopted schematisation. This is mere speculation for real ecosystems, so that it is relevant to explore the limits of coupled models over extended periods. To date, almost all applications in literature have been calibrated over a couple of years at most, with comparable validation periods, if present. Furthermore, past studies mostly concerned shallow to moderately deep small lakes, so that reproducing the hypolimnetic chemical evolution of very deep large lakes has generally been overlooked. Last, most works did not compare with observations or even model the succession of phytoplankton species, but only dealt with total Chlorophyll-a. Here, the GLM-AED2 (General Lake Model – Aquatic EcoDynamics) coupled model was calibrated and validated for an overall 16.75-year period for the 370-m deep and 213-km2 wide Lake Maggiore (Northern Italy/Southern Switzerland), focusing on the reproduction of both deep-water chemistry and phytoplankton biomass and succession. Despite the modelling simplifications needed for this complex basin, the resulting performances are comparable to those in literature for shallower and smaller lakes over shorter periods. Still, extreme care must be put when interpreting the results of coupled ecological-hydrodynamic models for long-term projections, especially regarding the evolution of phytoplankton.

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.

Forecasting the evolution in the mixing regime of a deep subalpine lake under climate change scenarios through numerical modelling (Lake Maggiore, Northern Italy/Southern Switzerland)

The impact of air temperature rise is eminent for the large deep lakes in the Italian subalpine district, climate change being caused there by both natural phenomena and anthropogenic greenhouse-gases (GHG) emissions. These oligomictic lakes are experiencing a decrease in the frequency of winter full turnover and an intensification of stability. As a result, hypolimnetic oxygen concentrations are decreasing and nutrients are accumulating in bottom water, with effects on the whole ecosystem functioning. Forecasting the future evolution of the mixing pattern is relevant to assess if a reduction in GHG releases would be able to revert such processes. The study focuses on Lake Maggiore, for which the thermal structure evolution under climate change in the 2016–2085 period was assessed through numerical simulations, performed with the General Lake Model (GLM). Different prospects of regional air temperature rise were considered, given by the Swiss Climate Change Scenarios CH2011. Multiple realisations were performed for each scenario to obtain robust statistical predictions, adopting random series of meteorological data produced with the Vector-Autoregressive Weather Generator (VG). Results show that a reversion in the increasing thermal stability would be possible only if global GHG emissions started to be reduced by ~ 2020, allowing an equilibrium mixing regime to be restored by the end of the twenty-first century. Otherwise, persistent lack of complete-mixing, severe water warming and extensive effects on water quality are to be expected for the centuries to come. These projections can be extended to the other lakes in the subalpine district.

The Warming of Large Lakes on the Tibetan Plateau: Evidence From a Lake Model Simulation of Nam Co, China, During 1979–2012

AbstractLakes are considered as indicators of climate change on the Tibetan Plateau (TP). In the present study, we use the General Lake Model to simulate water temperature changes in Nam Co, the second largest lake on the central TP, for the period 1979–2012. The calibration and validation results demonstrate that this model is well suited for thermal simulation of Nam Co. The simulation results indicate that Nam Co has responded to the recent warming climate. The average summer surface water temperature fluctuated yearly, but its trend is positive at a rate of 0.52 ± 0.25°C per decade. At the same time, the onset of summer stratification advanced by 4.20 ± 2.02 d per decade, and the duration increased at a rate of 6.00 ± 3.54 d per decade. To explore the roles of air temperature and longwave radiation in lake warming, three sensitivity experiments are conducted by removing long‐term trends from time series of air temperature and longwave radiation in the forcing data. These experiments prove that both increased air temperature and downward longwave radiation are two driving factors responsible for the warming of Nam Co.

Groundwater dependence of coastal lagoons: The case of La Pletera salt marshes (NE Catalonia)

Coastal wetlands are among the most productive ecosystems of the world, playing an important role in coastal defense and wildlife conservation. These ecosystems, however, are usually affected by human activities, which may cause a loss and degradation of their ecological status, a decline of their biodiversity, an alteration of their ecological functioning, and a limitation of their ecosystem services. La Pletera salt marshes (NE Spain) are located in a region mainly dominated by agriculture and tourism activities. Part of these wetlands and lagoons has been affected by an incomplete construction of an urban development and in this moment is the focus of a Life+ project, whose aim is to restore this protected area. Several studies have analyzed the role of hydrological regime in nutrients, phytoplankton and zooplankton in this area, however, the role of groundwater was never considered as a relevant factor in the lagoon dynamics, and its influence is still unknown. In this study, the hydrogeological dynamics in La Pletera salt marshes has been analyzed, as a basis to set sustainable management guidelines for this area. In order to determine their dependence on groundwater resources, monthly hydrochemical (with major ions and nutrients) and isotopic (δ18OH2O and δD) campaigns have been conducted, from November 2014 to October 2015. In particular, groundwater from six wells, surface water from two nearby streams and three permanent lagoons, and sea water was considered in these surveys. Taking into account the meteorological data and the water levels in the lagoons, the General Lake Model has been conducted to determine, not only evaporation and rainfall occurring in the lagoons, but also the total inflows and outflows. In addition, the Gonfiantini isotopic model, together with equilibrium chemical-speciation/mass transfer models, has been used to analyze the evaporation and the physicochemical processes affecting the lagoons. Results show that during the dry season groundwater inputs may account for 15–80% of the water in La Pletera lagoons. Besides, water salinity depends on two main processes: 1) mixing of fresh and sea water occurring within the lagoons or in the aquifer; and 2) evaporation. According to the obtained results, the goal of preserving La Pletera lagoons and their salinity conditions implies maintaining groundwater fluxes towards the ocean, and also the hydraulic connectivity of these lagoons with the aquifer.

Using the General Lake Model (GLM) to simulate water temperatures and ice cover of a medium-sized lake: a case study of Lake Ammersee, Germany

Thermal dynamics of lakes has a key role in chemical and biological processes in lakes including nutrient distributions and phytoplankton growth. Applications of hydrodynamic models to lakes can provide insights into possible future alterations in thermal dynamics induced by climate change. In this study, we present the calibration and validation of the newest version of the open-source hydrodynamic model GLM (General Lake Model) to the dimictic Lake Ammersee, located in south-east Germany. The simulation of lake water temperatures for the calibration period revealed an overall root mean square error of 0.65 °C and a mean error of 0.08 °C. The seasonal stratification pattern and the annual thermal structure of this dimictic lake were reproduced by the model. The model simulated the presence of winter ice cover for the only year out of 8 years simulated, when ice cover was observed. Elevated lake water temperatures were also reproduced in model simulations during a period in 2003 of unusually high air temperatures. Statistical analysis of the model calibration results for Lake Ammersee indicates a fit comparable to or better than most other well-established hydrodynamic models and provides an opportunity for continuous simulations through periods of ice cover. Our results indicate a major improvement in GLM compared with earlier model versions and demonstrate the applicability of GLM for limnophysical studies, particularly for altered forcing conditions such as climate change.

GRAPLEr: A distributed collaborative environment for lake ecosystem modeling that integrates overlay networks, high‐throughput computing, and WEB services

SummaryThe GLEON Research And PRAGMA Lake Expedition—GRAPLE—is a collaborative effort between computer science and lake ecology researchers. It aims to improve our understanding and predictive capacity of the threats to the water quality of our freshwater resources, including climate change. This paper presents GRAPLEr, a distributed computing system used to address the modeling needs of GRAPLE researchers. GRAPLEr integrates and applies overlay virtual network, high‐throughput computing, and WEB service technologies in a novel way. First, its user‐level IP‐over‐P2P overlay network allows compute and storage resources distributed across independently administered institutions (including private and public clouds) to be aggregated into a common virtual network, despite the presence of firewalls and network address translators. Second, resources aggregated by the IP‐over‐P2P virtual network run unmodified high‐throughput‐computing middleware to enable large numbers of model simulations to be executed concurrently across the distributed computing resources. Third, a WEB service interface allows end users to submit job requests to the system using client libraries that integrate with the R statistical computing environment. The paper presents the GRAPLEr architecture, describes its implementation and reports on its performance for batches of general lake model simulations across 3 cloud infrastructures (University of Florida, CloudLab, and Microsoft Azure).

Relevance of inflows on the thermodynamic structure and on the modeling of a deep subalpine lake (Lake Maggiore, Northern Italy/Southern Switzerland)

• An enclosed 1D thermodynamic model of a subalpine lake gives satisfactory results. • An unrealistically low light extinction coefficient is used to heat lower layers. • Simulating the intrusion of main inflows gives better results over the thermocline. • Bottom hypolimnion dynamics cannot be precisely reproduced by 1D models in any case. • Major riverine interflows are crucial for heating the deep layers of Lake Maggiore. Atmospheric exchanges largely dominate the heat budget of deep lakes in temperate regions. Heat import and export by through-flows is of much lower entity and has been neglected or simplified in many numerical thermodynamic models of lakes. This is often due either to the unavailability of data for inflows and outflows, or to the difficulties in forecasting the evolution of their discharge and temperature in climate change studies. While disregarding through-flows may seem correct, riverine intrusions can bring warmer water than the deep hypolimnetic one to the lower metalimnion and upper hypolimnion, where sunlight does not penetrate and mixing is poor. For holomictic lakes with significant inflow contributions, this can affect the thermal structure at intermediate depths, hampering any numerical model which neglects through-flows. This study focuses on a relevant basin under such aspect, Lake Maggiore (Northern Italy/Southern Switzerland), which drains the rainiest watershed of the Southern Alps. First, we quantify to what extent a one-dimensional fixed-level model ignoring through-flows is able to predict the observed evolution of the thermal structure of the lake and the improvements resulting from reproducing the main inflows and outflows. Then, we directly discuss the influence of through-flows on the thermodynamic structure of Lake Maggiore. The General Lake Model (GLM) was here adopted, reproducing the 1998–2014 period, spanning years with different meteorological and hydrological features. Results show that a calibrated enclosed-lake model can give satisfactory results only if it employs an unrealistically low light extinction coefficient to allow heating of the deep metalimnion and hypolimnion, whose real warming strongly depends on interflows.

Comparing ice and temperature simulations by four dynamic lake models in Harp Lake: past performance and future predictions

AbstractThe physical dynamics of lake temperature and ice phenology are important in the modelling and management of temperate aquatic ecosystems. One‐dimensional hydrothermal lake models have not been well evaluated in terms of how they simulate ice dynamics in particular. We chose four models (Hostetler, Minlake, Simple Ice Model or SIM and General Lake Model) to test and compare their performance modelling water temperature and ice dynamics using 16 years of field data from Harp Lake, an extensively studied inland lake in south‐central Ontario. Each model produced satisfactory water temperature profiles over the simulated period, with small differences in the model performance. Model fits for ice phenology and ice thickness were, however, considerably lower than those for water temperature, with Minlake generating the best agreement with observed ice‐on and ice‐off dates as well as ice thickness, followed by SIM. The responses of lake ice dynamics to future climate scenarios were simulated by running each of the four models for 91 years, from 2010 to 2100. The predicted decrease in ice season length was significantly different among models, varying between 30 and 81 days, with an average of 48 days. Corresponding decreases in ice thickness varied between 0.11 and 0.20 m, averaging 0.17 m. This study demonstrates that uncertainty due to model performance and selection is considerable, and further testing and refinement of hydrothermal lake dynamic models are needed to improve predictive abilities for ice dynamics. Copyright © 2014 John Wiley & Sons, Ltd.

A general approach to transform a lake model for one radionuclide (radiocesium) to another (radiostrontium) and critical model tests using data for four Ural lakes contaminated by the fallout from the Kyshtym accident in 1957

This paper presents results of a model test carried out within the framework of the COMETES project (EU). The aim of the work was to change the structure of the MOIRA lake model for radiocesium so that it can be applied more generally for, in principle, all types of radionuclides and heavy metals. This general lake model is used within the MOIRA decision support system (DSS; MOIRA and COMETES are acronyms for EU-projects). The model is based on a set of differential equations and a specific modelling structure. It incorporates all important fluxes to, from and within lakes in a general manner. Yet the model is driven by a minimum of variables accessible from standard maps and monitoring programs. The model can be separated into two parts, a general part with equations applicable for all types of water pollutants and a substance-specific part. This model has previously been validated for 137Cs from many lakes covering a wide domain and yielded excellent predictive power. The alterations discussed in this work are meant to be general and radiostrontium is used as a typical element. Radiostrontium is known to be more mobile than radiocesium and all abiotic parts of the model handling fixation and mobility have been altered. The new model for 90Sr has been critically tested using data from four lakes heavily contaminated with 90Sr from the Kyshtym accident in the Southern Urals, Russia, using empirical data from a period from 1958 to 1995 for 90Sr in fish (here goldfish), water and sediments.