| 1. |
- Jiménez-Navarro, Inmaculada C., et al.
(författare)
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Application of an integrated catchment-lake model approach for simulating effects of climate change on lake inputs and biogeochemistry
- 2023
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Ingår i: Science of the Total Environment. - : Elsevier. - 0048-9697 .- 1879-1026. ; 885
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Tidskriftsartikel (refereegranskat)abstract
- Climate change is simultaneously affecting lakes and their catchments, resulting in altered runoff patterns in the catchment and modified mixing and biogeochemical dynamics in lakes. The effects of climate change in a catchment will eventually have an impact on the dynamics of a downstream water body as well. An integrated model would allow considering how changes in the watershed affect the lake, but coupled modelling studies are rare. In this study we integrate a catchment model (SWAT+) and a lake model (GOTM-WET) to obtain holistic predictions for Lake Erken, Sweden. Using five different global climate models, projections of climate, catchment loads and lake water quality for the mid and end of the 21st century have been obtained under two future scenarios (SSP 2-45 and SSP 5-85). Temperature, precipitation and evapotranspiration will increase in the future, overall resulting in an increase in water inflow to the lake. An increasing importance of surface runoff will also have consequences on the catchment soil, hydrologic flow paths, and the input of nutrients to the lake. In the lake, water temperatures will rise, leading to increased stratification and a drop in oxygen levels. Nitrate levels are predicted to remain unchanged, while phosphate and ammonium levels increase. A coupled catchment-lake configuration such as that illustrated here allows prediction of future biogeochemical conditions of a lake, including linking land use changes to changing lake conditions, as well as eutrophication and browning studies. Since climate affects both the lake and the catchment, simulations of climate change should ideally take into account both systems.
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| 2. |
- Lin, Shuqi, et al.
(författare)
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Prediction of algal blooms via data-driven machine learning models : an evaluation using data from a well-monitored mesotrophic lake
- 2023
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Ingår i: Geoscientific Model Development. - : Copernicus Publications. - 1991-959X .- 1991-9603. ; 16:1, s. 35-46
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Tidskriftsartikel (refereegranskat)abstract
- With increasing lake monitoring data, data-drivenmachine learning (ML) models might be able to capture thecomplex algal bloom dynamics that cannot be completely described in process-based (PB) models. We applied two MLmodels, the gradient boost regressor (GBR) and long shortterm memory (LSTM) network, to predict algal blooms andseasonal changes in algal chlorophyll concentrations (Chl) ina mesotrophic lake. Three predictive workflows were tested,one based solely on available measurements and the othersapplying a two-step approach, first estimating lake nutrientsthat have limited observations and then predicting Chl usingobserved and pre-generated environmental factors. The thirdworkflow was developed using hydrodynamic data derivedfrom a PB model as additional training features in the twostep ML approach. The performance of the ML models wassuperior to a PB model in predicting nutrients and Chl. Thehybrid model further improved the prediction of the timingand magnitude of algal blooms. A data sparsity test based onshuffling the order of training and testing years showed theaccuracy of ML models decreased with increasing sampleinterval, and model performance varied with training–testingyear combinations.
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| 3. |
- Mesman, Jorrit P., 1993-
(författare)
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Assessing future effects on lake ecosystem resilience using data analysis and dynamic modelling : Modelling the effects of extreme weather events and climate warming on lakes
- 2021
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Extreme weather events can have short-term and long-term effects on lake thermal structure, nutrient dynamics, and community composition. Moreover, changes in lake variables induced by global climate change may influence the response and recovery of lake ecosystems to extreme weather events. The linkage between extreme weather and lakes includes interactions between physics and biology, and long-term and short-term dynamics, which are not yet well understood. Process-based modelling is used in this thesis to further explore this topic, and to assess how lake responses to extreme weather events may change under the influence of climate warming.Lake-internal feedback mechanisms were shown to potentially cause sudden shifts in climate-induced transitions in lake mixing regimes, with a role for extreme weather events to induce such shifts. Additionally, one-dimensional physical lake models performed well in reproducing trends in lake variables during storms and heatwaves in a study covering multiple locations and models. However, extreme weather events still presented periods of increased model uncertainty, which should be taken into account. A software package was developed to promote the use of ensemble lake modelling, which is one way to include uncertainty in model forecasting efforts. This could be particularly helpful in periods of extreme weather. With tools and theory now in place, a coupled physical-biogeochemical model was then used to assess what are the most important drivers of how lake phytoplankton responds to storms, and how this response might change with climate warming. Storm intensity, thermal structure, nutrients, and light all affected the phytoplankton concentration after storms. Moderate wind speeds had increasing effects compared to high wind speeds, but a sufficiently deep mixed layer reduced the response to wind strongly. Higher nutrients and light promoted increasing effects of wind, and higher temperatures promoted decreasing effects. The response of phytoplankton to storms did not change markedly between present-day and future-climate scenarios.This thesis furthers our understanding of the processes involved in extreme events acting on lakes. A more complete understanding is necessary to develop more reliable models and anticipate future conditions. Furthermore, modelling was shown to be a viable approach to study these events and validation data and tools were provided to increase the reliability of this method. In these times of increasing environmental pressures and changing extreme weather patterns, more insight into future effects of extreme events is much needed.
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| 4. |
- Mesman, Jorrit P., 1993-, et al.
(författare)
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Drivers of phytoplankton responses to summer wind events in a stratified lake : a modelling study
- 2022
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Ingår i: Limnology and Oceanography. - : John Wiley & Sons. - 0024-3590 .- 1939-5590. ; 67:4, s. 856-873
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Tidskriftsartikel (refereegranskat)abstract
- Extreme wind events affect lake phytoplankton amongst others by deepening the mixed layer and increasing internal nutrient loading. Both increases and decreases of phytoplankton biomass after storms have been observed, but the precise mechanisms driving these responses remain poorly understood or quantified. In this study, we coupled a one-dimensional physical model to a biogeochemical model to investigate the factors regulating short-term phytoplankton responses to summer storms, now and under expected warmer future conditions. We simulated physical, chemical and biological dynamics in Lake Erken, Sweden, and found that wind storms could increase or decrease the phytoplankton concentration one week after the storm, depending on antecedent lake physical and chemical conditions. Storms had little effect on phytoplankton biomass if the mixed layer was deep prior to storm exposure. Higher incoming shortwave radiation and hypolimnetic nutrient concentration boosted growth, whereas higher surface water temperatures decreased phytoplankton concentration after storms. Medium-intensity wind speeds resulted in more phytoplankton biomass after storms than high-intensity wind. Simulations under a future climate scenario did not show marked differences in the way wind affects phytoplankton growth following storms. Our study shows that storm impacts on lake phytoplankton are complex and likely to vary as a function of local environmental conditions.
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| 5. |
- Mesman, Jorrit P., 1993-, et al.
(författare)
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Performance of one-dimensional hydrodynamic lake models during short-term extreme weather events
- 2020
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Ingår i: Environmental Modelling & Software. - : Elsevier BV. - 1364-8152 .- 1873-6726. ; 133
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Tidskriftsartikel (refereegranskat)abstract
- Numerical lake models are useful tools to study hydrodynamics in lakes, and are increasingly applied to extreme weather events. However, little is known about the accuracy of such models during these short-term events. We used high-frequency data from three lakes to test the performance of three one-dimensional (1D) hydrodynamic models (Simstrat, GOTM, GLM) during storms and heatwaves. Models reproduced the overall direction and magnitude of changes during the extreme events, with accurate timing and little bias. Changes in volume-averaged and surface temperatures and Schmidt stability were simulated more accurately than changes in bottom temperature, maximum buoyancy frequency, or mixed layer depth. However, in most cases the model error was higher (30-100%) during extreme events compared to reference periods. As a consequence, while 1D lake models can be used to study effects of extreme weather events, the increased uncertainty in the simulations should be taken into account when interpreting results.
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| 6. |
- Mesman, Jorrit P., 1993-, et al.
(författare)
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Timing of spring events changes under modelled future climate scenarios in a mesotrophic lake
- 2024
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Ingår i: Hydrology and Earth System Sciences. - : European Geosciences Union (EGU). - 1027-5606 .- 1607-7938. ; 28:8, s. 1791-1802
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Tidskriftsartikel (refereegranskat)abstract
- Lakes experience shifts in the timing of physical and biogeochemical events as a result of climate warming, and relative changes in the timing of events may have important ecological consequences. Spring, in particular, is a period in which many key processes that regulate the ecology and biogeochemistry of lakes occur and also a time that may experience significant changes under the influence of global warming. In this study, we used a coupled catchment–lake model forced by future climate projections to evaluate changes in the timing of spring discharge, ice-off, the spring phytoplankton peak, and the onset of stratification in a temperate mesotrophic lake. Although the model explained only part of the variation in these events, the overall patterns were simulated with little bias. All four events showed a clear trend towards earlier occurrence under climate warming, with ice cover tending to disappear at the end of the century in the most extreme climate scenario. Moreover, relative shifts in the timing of these springtime events also occurred, with the onset of stratification tending to advance more slowly than the other events and the spring phytoplankton peak and ice-off advancing faster in the most extreme climate scenario. The outcomes of this study stress the impact of climate change on the phenology of events in lakes and especially the relative shifts in timing during spring. This can have profound effects on food web dynamics as well as other regulatory processes and influence the lake for the remainder of the growing season.
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| 7. |
- Thayne, Michael W., et al.
(författare)
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Lake surface water temperature and oxygen saturation resistance and resilience following extreme storms : Chlorophyll a shapes resistance toward storms
- 2023
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Ingår i: Inland Waters. - : Taylor & Francis Group. - 2044-2041 .- 2044-205X. ; , s. 1-53
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Tidskriftsartikel (refereegranskat)abstract
- Extreme storms are becoming more frequent and intense with climate change. Assessing lake ecosystem responses to extreme storms (resistance) and their capacity to recover (resilience) is critical for predicting the future of lake ecosystems in a stormier world. Here we provide a systematic, standardized and quantitative approach for identifying critical processes shaping lake ecosystem resistance following extreme storms. We identified 576 extreme wind storms for eight lakes in Europe and North America. We calculated the resistance and resilience of each lake’s surface water temperature and oxygen saturation following each storm. Sharp decreases and increases in epilimnetic temperature and oxygen saturation caused by extreme storms resulted in unpredictable changes in lake resilience values across lakes, with a tendency not to return to pre-storm conditions. Resistance was primarily shaped by mean annual chlorophyll a concentration and its overall relationship with other physiochemical lake and storm characteristics. We modeled variation in resistance as a function of both lake and storm conditions, and the results suggested that eutrophic lakes were consistently less resistant to extreme storms when compared to oligotrophic lakes. The lakes tended to be most resistant towards extreme storms when antecedent surface waters were warm and oxygen saturated, but overall resistance was highest in lakes with low concentrations of mean annual chlorophyll a and total phosphorus. Our findings suggest physiochemical responses of lakes to meteorological forcing is shaped by ecological and/or physical feedbacks and processes that determine trophic state, such as the influence of differences in nutrient availability and algal growth.
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| 8. |
- Woolway, R. Iestyn, et al.
(författare)
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Phenological shifts in lake stratification under climate change
- 2021
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Ingår i: Nature Communications. - : Springer Nature. - 2041-1723. ; 12:1
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Tidskriftsartikel (refereegranskat)abstract
- One of the most important physical characteristics driving lifecycle events in lakes is stratification. Already subtle variations in the timing of stratification onset and break-up (phenology) are known to have major ecological effects, mainly by determining the availability of light, nutrients, carbon and oxygen to organisms. Despite its ecological importance, historic and future global changes in stratification phenology are unknown. Here, we used a lake-climate model ensemble and long-term observational data, to investigate changes in lake stratification phenology across the Northern Hemisphere from 1901 to 2099. Under the high-greenhouse-gas-emission scenario, stratification will begin 22.0 +/- 7.0 days earlier and end 11.3 +/- 4.7 days later by the end of this century. It is very likely that this 33.3 +/- 11.7 day prolongation in stratification will accelerate lake deoxygenation with subsequent effects on nutrient mineralization and phosphorus release from lake sediments. Further misalignment of lifecycle events, with possible irreversible changes for lake ecosystems, is also likely.
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