Multi-model projections of future evaporation in a sub-tropical lake

Lake evaporation plays an important role in the water budget of lakes. Predicting lake evaporation responses to climate change is thus of paramount importance for the planning of mitigation and adaption strategies. However, most studies that have simulated climate change impacts on lake evaporation have typically utilised a single mechanistic model. Whilst such studies have merit, projected changes in lake evaporation from any single lake model can be considered uncertain. To better understand evaporation responses to climate change, a multi-model approach (i.e., where a range of projections are considered), is desirable. In this study, we present such multi-model analysis, where five lake models forced by four different climate model projections are used to simulate historic and future change (1901–2099) in lake evaporation. Our investigation, which focuses on sub-tropical Lake Kinneret (Israel), suggested considerable differences in simulated evaporation rates among the models, with the annual average evaporation rates varying between 1232 mm year−1 and 2608 mm year−1 during the historic period (1901–2005). We explored these differences by comparing the models with reference evaporation rates estimated using in-situ data (2000–2005) and a bulk aerodynamic algorithm. We found that the model ensemble generally captured the intra-annual variability in reference evaporation rates, and compared well at seasonal timescales (RMSEc = 0.19, R = 0.92). Using the model ensemble, we then projected future change in evaporation rates under three different Representative Concentration Pathway (RCP) scenarios: RCP 2.6, 6.0 and 8.5. Our projections indicated that, by the end of the 21st century (2070–2099), annual average evaporation rates would increase in Lake Kinneret by 9–22 % under RCPs 2.6–8.5. When compared with projected regional declines in precipitation, our projections suggested that the water balance of Lake Kinneret could experience a deficit of 14–40 % this century. We anticipate this substantial projected deficit combined with a considerable growth in population expected for this region could have considerable negative impacts on water availability and would consequently increase regional water stress

Annual water residence time effects on thermal structure: a potential lake restoration measure?

Innovative methods to combat internal loading issues in eutrophic lakes are urgently needed to speed recovery and restore systems within legislative deadlines. In stratifying lakes, internal phosphorus loading is particularly problematic during the summer stratified period when anoxia persists in the hypolimnion, promoting phosphorus release from the sediment. A novel method to inhibit stratification by reducing residence times is proposed as a way of controlling the length of the hypolimnetic anoxic period, thus reducing the loading of nutrients from the sediments into the water column. However, residence time effects on stratification length in natural lakes are not well understood. We used a systematic modelling approach to investigate the viability of changes to annual water residence time in affecting lake stratification and thermal dynamics in Elterwater, a small stratifying eutrophic lake in the northwest of England. We found that reducing annual water residence times shortened and weakened summer stratification. Based on finer-scale dynamics of lake heat fluxes and water column stability we propose seasonal or sub-seasonal management of water residence time is needed for the method to be most effective at reducing stratification as a means of controlling internal nutrient loading

Sources of skill in lake temperature, discharge and ice-off seasonal forecasting tools

Despite high potential benefits, the development of seasonal forecasting tools in the water sector has been slower than in other sectors. Here we assess the skill of seasonal forecasting tools for lakes and reservoirs set up at four sites in Australia and Europe. These tools consist of coupled hydrological catchment and lake models forced with seasonal meteorological forecast ensembles to provide probabilistic predictions of seasonal anomalies in water discharge, temperature and ice-off. Successful implementation requires a rigorous assessment of the tools' predictive skill and an apportionment of the predictability between legacy effects and input forcing data. To this end, models were forced with two meteorological datasets from the European Centre for Medium-Range Weather Forecasts (ECMWF), the seasonal forecasting system, SEAS5, with 3-month lead times and the ERA5 reanalysis. Historical skill was assessed by comparing both model outputs, i.e. seasonal lake hindcasts (forced with SEAS5), and pseudo-observations (forced with ERA5). The skill of the seasonal lake hindcasts was generally low although higher than the reference hindcasts, i.e. pseudo-observations, at some sites for certain combinations of season and variable. The SEAS5 meteorological predictions showed less skill than the lake hindcasts. In fact, skilful lake hindcasts identified for selected seasons and variables were not always synchronous with skilful SEAS5 meteorological hindcasts, raising questions on the source of the predictability. A set of sensitivity analyses showed that most of the forecasting skill originates from legacy effects, although during winter and spring in Norway some skill was coming from SEAS5 over the 3-month target season. When SEAS5 hindcasts were skilful, additional predictive skill originates from the interaction between legacy and SEAS5 skill. We conclude that lake forecasts forced with an ensemble of boundary conditions resampled from historical meteorology are currently likely to yield higher-quality forecasts in most cases.publishedVersio

Forecasting water temperature in lakes and reservoirs using seasonal climate prediction

ABSTRACT: Seasonal climate forecasts produce probabilistic predictions of meteorological variables for subsequent months. This provides a potential resource to predict the influence of seasonal climate anomalies on surface water balance in catchments and hydro-thermodynamics in related water bodies (e.g., lakes or reservoirs). Obtaining seasonal forecasts for impact variables (e.g., discharge and water temperature) requires a link between seasonal climate forecasts and impact models simulating hydrology and lake hydrodynamics and thermal regimes. However, this link remains challenging for stakeholders and the water scientific community, mainly due to the probabilistic nature of these predictions. In this paper, we introduce a feasible, robust, and open-source workflow integrating seasonal climate forecasts with hydrologic and lake models to generate seasonal forecasts of discharge and water temperature profiles. The workflow has been designed to be applicable to any catchment and associated lake or reservoir, and is optimized in this study for four catchment-lake systems to help in their proactive management. We assessed the performance of the resulting seasonal forecasts of discharge and water temperature by comparing them with hydrologic and lake (pseudo)observations (reanalysis). Precisely, we analysed the historical performance using a data sample of past forecasts and reanalysis to obtain information about the skill (performance or quality) of the seasonal forecast system to predict particular events. We used the current seasonal climate forecast system (SEAS5) and reanalysis (ERA5) of the European Centre for Medium Range Weather Forecasts (ECMWF). We found that due to the limited predictability at seasonal time-scales over the locations of the four case studies (Europe and South of Australia), seasonal forecasts exhibited none to low performance (skill) for the atmospheric variables considered. Nevertheless, seasonal forecasts for discharge present some skill in all but one case study. Moreover, seasonal forecasts for water temperature had higher performance in natural lakes than in reservoirs, which means human water control is a relevant factor affecting predictability, and the performance increases with water depth in all four case studies. Further investigation into the skillful water temperature predictions should aim to identify the extent to which performance is a consequence of thermal inertia (i.e., lead-in conditions).This is a contribution of the WATExR project (watexr.eu/), which is part of ERA4CS, an ERA-NET initiated by JPI Climate, and funded by MINECO-AEI (ES), FORMAS (SE), BMBF (DE), EPA (IE), RCN (NO), and IFD (DK), with co-funding by the European Union (Grant 690462 ). MINECO-AEI funded this research through projects PCIN- 2017-062 and PCIN-2017-092. We thank all water quality and quantity data providers: Ens d’Abastament d’Aigua Ter-Llobregat (ATL, https://www.atl.cat/es ), SA Water ( https://www.sawater.com. au/ ), Ruhrverband ( www.ruhrverband.de ), NIVA ( www.niva.no ) and NVE ( https://www.nve.no/english/ ). We acknowledge the contribution of the Copernicus Climate Change Service (C3S) in the production of SEAS5. C3S provided the computer time for the generation of the re-forecasts for SEAS5 and for the production of the ocean reanalysis (ORAS5), used as initial conditions for the SEAS5 re-forecasts

Warming winters threaten peripheral Arctic charr populations of Europe

As the global climate warms, the fate of lacustrine fish is of huge concern, especially given their sensitivity as ectotherms to changes in water temperature. The Arctic charr (Salvelinus alpinus L.) is a salmonid with a Holarctic distribution, with peripheral populations persisting at temperate latitudes, where it is found only in sufficiently cold, deep lakes. Thus, warmer temperatures in these habitats particularly during early life stages could have catastrophic consequences on population dynamics. Here, we combined lake temperature observations, a 1-D hydrodynamic model, and a multi-decadal climate reanalysis to show coherence in warming winter water temperatures in four European charr lakes near the southernmost limit of the species’ distribution. Current maximum and mean winter temperatures are on average ~ 1 °C warmer compared to early the 1980s, and temperatures of 8.5 °C, adverse for high charr egg survival, have frequently been exceeded in recent winters. Simulations of winter lake temperatures toward century-end showed that these warming trends will continue, with further increases of 3–4 °C projected. An additional 324 total accumulated degree-days during winter is projected on average across lakes, which could impair egg quality and viability. We suggest that the perpetuating winter warming trends shown here will imperil the future status of these lakes as charr refugia and generally do not augur well for the fate of coldwater-adapted lake fish in a warming climate

LakeEnsemblR: an R package that facilitates ensemble modelling of lakes

Model ensembles have several benefits compared to single-model applications but are not frequently used within the lake modelling community. Setting up and running multiple lake models can be challenging and time consuming, despite the many similarities between the existing models (forcing data, hypsograph, etc.). Here we present an R package, LakeEnsemblR, that facilitates running ensembles of five different vertical one-dimensional hydrodynamic lake models (FLake, GLM, GOTM, Simstrat, MyLake). The package requires input in a standardised format and a single configuration file. LakeEnsemblR formats these files to the input required by each model, and provides functions to run and calibrate the models. The outputs of the different models are compiled into a single file, and several post-processing operations are supported. LakeEnsemblR's workflow standardisation can simplify model benchmarking and uncertainty quantification, and improve collaborations between scientists. We showcase the successful application of LakeEnsemblR for two different lakes

A framework for ensemble modelling of climate change impacts on lakes worldwide : the ISIMIP Lake Sector

Empirical evidence demonstrates that lakes and reservoirs are warming across the globe. Consequently, there is an increased need to project future changes in lake thermal structure and resulting changes in lake biogeochemistry in order to plan for the likely impacts. Previous studies of the impacts of climate change on lakes have often relied on a single model forced with limited scenario-driven projections of future climate for a relatively small number of lakes. As a result, our understanding of the effects of climate change on lakes is fragmentary, based on scattered studies using different data sources and modelling protocols, and mainly focused on individual lakes or lake regions. This has precluded identification of the main impacts of climate change on lakes at global and regional scales and has likely contributed to the lack of lake water quality considerations in policy-relevant documents, such as the Assessment Reports of the Intergovernmental Panel on Climate Change (IPCC). Here, we describe a simulation protocol developed by the Lake Sector of the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP) for simulating climate change impacts on lakes using an ensemble of lake models and climate change scenarios for ISIMIP phases 2 and 3. The protocol prescribes lake simulations driven by climate forcing from gridded observations and different Earth system models under various representative greenhouse gas concentration pathways (RCPs), all consistently bias-corrected on a 0.5 degrees x 0.5 degrees global grid. In ISIMIP phase 2, 11 lake models were forced with these data to project the thermal structure of 62 well-studied lakes where data were available for calibration under historical conditions, and using uncalibrated models for 17 500 lakes defined for all global grid cells containing lakes. In ISIMIP phase 3, this approach was expanded to consider more lakes, more models, and more processes. The ISIMIP Lake Sector is the largest international effort to project future water temperature, thermal structure, and ice phenology of lakes at local and global scales and paves the way for future simulations of the impacts of climate change on water quality and biogeochemistry in lakes.Peer reviewe

Phenological shifts in lake stratification under climate change

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

Impact of COVID-19 on cardiovascular testing in the United States versus the rest of the world

Objectives: This study sought to quantify and compare the decline in volumes of cardiovascular procedures between the United States and non-US institutions during the early phase of the coronavirus disease-2019 (COVID-19) pandemic. Background: The COVID-19 pandemic has disrupted the care of many non-COVID-19 illnesses. Reductions in diagnostic cardiovascular testing around the world have led to concerns over the implications of reduced testing for cardiovascular disease (CVD) morbidity and mortality. Methods: Data were submitted to the INCAPS-COVID (International Atomic Energy Agency Non-Invasive Cardiology Protocols Study of COVID-19), a multinational registry comprising 909 institutions in 108 countries (including 155 facilities in 40 U.S. states), assessing the impact of the COVID-19 pandemic on volumes of diagnostic cardiovascular procedures. Data were obtained for April 2020 and compared with volumes of baseline procedures from March 2019. We compared laboratory characteristics, practices, and procedure volumes between U.S. and non-U.S. facilities and between U.S. geographic regions and identified factors associated with volume reduction in the United States. Results: Reductions in the volumes of procedures in the United States were similar to those in non-U.S. facilities (68% vs. 63%, respectively; p = 0.237), although U.S. facilities reported greater reductions in invasive coronary angiography (69% vs. 53%, respectively; p < 0.001). Significantly more U.S. facilities reported increased use of telehealth and patient screening measures than non-U.S. facilities, such as temperature checks, symptom screenings, and COVID-19 testing. Reductions in volumes of procedures differed between U.S. regions, with larger declines observed in the Northeast (76%) and Midwest (74%) than in the South (62%) and West (44%). Prevalence of COVID-19, staff redeployments, outpatient centers, and urban centers were associated with greater reductions in volume in U.S. facilities in a multivariable analysis. Conclusions: We observed marked reductions in U.S. cardiovascular testing in the early phase of the pandemic and significant variability between U.S. regions. The association between reductions of volumes and COVID-19 prevalence in the United States highlighted the need for proactive efforts to maintain access to cardiovascular testing in areas most affected by outbreaks of COVID-19 infection

Predicting in-lake responses to short and long-term changes using lake physical models

Lakes and reservoirs are under increasing pressure from urbanisation, agricultural intensification, and directional climate change, including an increasing occurrence of extreme climatic events. These pressures can reduce water quality by promoting the occurrence of nuisance algal blooms and higher levels of dissolved organic carbon (DOC), two issues that can cause substantial problems for water treatment, aquatic ecology and recreational users. Thus, there is a need to develop a modelling framework that is flexible, adaptable and provides information that can be utilised to mitigate potential risks to lakes and reservoirs. This thesis describes three specific pieces of work which in combination, further the use of hydrodynamic models for adaptive management. Firstly, the suitability of different meteorological datasets for forcing one-dimensional hydrodynamic models and accurately simulating water temperatures was examined. The European Centre for Medium-Range Weather Forecasts produces freely available gridded meteorological datasets: ERA-Interim, ERA5 and EWEMBI. Lake temperature simulations produced using these three datasets were compared to those based on local meteorological data. Simulations with ERA5 and ERA-Interim simulated water temperatures to a similar degree of accuracy as those forced with local measured data. This highlighted how gridded meteorological datasets can be used to simulate lake thermodynamics in areas where there is no locally measured meteorological data. Secondly, the improvement in short-term model performance when assimilating observed water temperature profile data into model simulations was assessed. Single profiles were inserted into simulations for three lakes that reflected potential monitoring programmes of different temporal frequencies. These monitoring data were compiled by subsetting high frequency data from the sites. Assimilating measured temperature profiles of up to one month prior to the forecast, greatly reduced forecast error. This will allow for short-term forecasting frameworks to be developed for low-frequency monitoring programmes. In the last results section, the effects of different future climate change scenarios on water temperature for a global set of lakes were characterised, using an ensemble of lake models forced with an ensemble of General Circulation Models. The responses in lake temperature and in functional characteristics such as the strength and length of stratification were shown to be highly variable across 46 lakes of varying morphometries. Comprehensively, there was an unequivocal warming of lake water temperature throughout the water column and an extension of the duration of stratification. Such increases in water temperature, heighten the risk of anoxia and the occurrence of algal blooms which are water quality issues which can be actively managed. Overall, this study has found that lake forecasting frameworks (short and long term) can be setup using open access software and data, for sites with low-frequency monitoring data, forced with freely available meteorological data and produce high quality forecasts. These finding will be of increasing importance as we seek to simulate our freshwater ecosystems in a rapidly changing climate to aid in their management