Abstract As lake and reservoir ecosystems transition across major environmental regimes (e.g., mixing regime) resulting from anthropogenic change, setting predictive expectations is imperative. We tested the hypothesis that (dissolved) oxygen is more predictable in monomictic reservoirs that thermally stratify throughout the summer (warm) season compared to polymictic reservoirs that stratify intermittently. Using two‐hourly vertical profiles of oxygen, we compared daily‐aggregated errors of oxygen predictions from random forests across and within two monomictic and two polymictic reservoirs in the south‐central (subtropical) USA. Although one monomictic reservoir was typically more predictable than the polymictic reservoirs, the hypereutrophic, small monomictic reservoir had less predictable oxygen patterns potentially related to rapid oxygen cycling and intrusions of oxygenated waters in the hypolimnion without mixing. Daily mixing did not relate strongly to model errors. Water temperature, depth, and wind were the most important predictors, but were not clearly related to season or mixing. Lastly, we compared multiple model types (regression, neural network, and process‐based) in one polymictic reservoir to test how our interpretations of oxygen predictability were sensitive to model type, finding that the models generally agreed; however, the process‐based model poorly predicted oxygen in the middle of the vertical profiles (5 m) where most models performed poorly due to a temporally unstable, vacillating metalimnion. Our results suggest predicting reservoir oxygen dynamics may be easier in stratified reservoirs, but eutrophication and complex hydrodynamics may cause forecasting surprises especially for those who use or manage water resources in mono‐ or dimictic reservoirs.
Abstract Background Groundwater abstraction can cause a decline in the water table, and thereby affects surface streamflow connected to the aquifer, which may impair the sustainability of both the water resource itself and the ecosystem that it supports. To quantify the streamflow response to groundwater abstractions for either irrigation or drinking water at catchment scale and compared the performance of the widely used semi-distributed hydrological model SWAT and an recently integrated surface–subsurface model SWAT–MODFLOW, we applied both SWAT and SWAT–MODFLOW to a groundwater-dominated catchment in Denmark and tested a range of groundwater abstraction scenarios. Results To accommodate the study area characteristics, the SWAT–MODFLOW model complex was further developed to enable the Drain package and an auto-irrigation routine to be used. A PEST (parameter estimation by sequential testing)-based approach which enables simultaneous calibration of SWAT and MODFLOW parameters was developed to calibrate SWAT–MODFLOW. Both models demonstrated generally good statistical performance for the temporal pattern of streamflow, with better R 2 and NSE (Nash–Sutcliffe efficiency) for SWAT–MODFLOW but slightly better P BIAS (percent bias) for SWAT. Both models indicated that drinking water abstractions caused some degree of streamflow depletion, while abstractions for returned irrigation led to a slight total flow increase, but may influence the hydrology outside the catchment. However, the streamflow decrease caused by drinking water abstractions simulated by SWAT was unrealistically low, and the streamflow increase caused by irrigation abstractions was exaggerated compared with SWAT–MODFLOW. Conclusion We conclude that the SWAT–MODFLOW model produces much more realistic signals relative to the SWAT model when quantifying the streamflow response to groundwater abstractions for irrigation or drinking water; hence, it has great potential to be a useful tool in the management of water resources in groundwater-dominated catchments. With further development of SWAT–MODFLOW and the PEST-based approach developed for its calibration, this study would broaden the SWAT–MODFLOW application and benefit catchment managers.
We investigated the ability of the process-based, 1-dimensional hydrodynamic-ecosystem lake model GOTM-WET to reproduce the fluctuating dynamics and shifts between turbid and clear water states following restoration in temperate, shallow Lake Arreskov, Denmark. The lake model was calibrated on a comprehensive 12-year dataset with a multiple single-model ensemble approach to address model parameter and performance metric uncertainty. Compared to earlier modelling attempts on this lake, the GOTM-WET model, which enables simulation of water column hydrodynamics such as stratification events and two zooplankton groups, improved the simulation of the maximum chlorophyll a concentrations during cyanobacteria blooms and zooplankton dynamics. However, the timing of shifts between phytoplankton and submerged macrophytes dominance following fish removal was not well reproduced, although both states were simulated. We discuss potential improvements of the model to enhance the ability to simulate the effects of restoration on the food web and ecological states in this and similar lakes.
Much information can be gained from the net ecosystem production (NEP) of freshwater lakes, and NEP has attracted new interest due to climate change, which may change the importance of freshwaters as a source and sink of CO 2 . Direct measurement of NEP in freshwater lakes is, however, time‐consuming, and high frequency monitoring of diel variations in oxygen levels for metabolism estimation has only recently been commonly employed. However, midday snap‐shot oxygen data is available from numerous monitoring programs worldwide, occasionally covering decades. We hypothesize that midday oxygen saturation levels may provide information on NEP in lakes as oxygen super‐saturation, indicative of high NEP, is observed in very productive lakes, whereas very low oxygen levels may occur in lakes with great input of organic matter or in lakes experiencing sudden decline in primary producers, indicative of low NEP. By analysis of a high frequency dataset encompassing 24 fully mixed mesocosms with contrasting trophic states and temperatures, we show that midday oxygen saturation provides a reasonable description of daily NEP only marginally affected by trophic state, temperature, and season. Oxygen sampling conducted in the afternoon gave a slightly better prediction than at midday, whereas predictions based on NEP representing an average of the previous 3 days led to a 2‐fold increase in R 2 . Moreover, an analysis of high frequency data sampled in a shallow Danish lake suggests that the method is transferable to natural shallow lakes. This method may therefore allow estimation of NEP based on oxygen measurements available from monitoring programs.
We wish to introduce QWET, a new version of the free and open-source QGIS plugin for the aquatic ecosystem model WET. QWET is as a graphical user interface for the application, evaluation and experimentation of WET. Several new features have been incorporated since its predecessor and, here, we demonstrate elements of the new plugin by applying it to Danish Lake Ravn. Among others, we compare model simulations against observations and describe how the scenario platform now supports scheduling of state-variable manipulation, which allows users to explore lake or reservoir restoration interventions such as biomanipulation and oxygenation. With QWET, we seek to aid practitioners who do not possess the sufficient technical expertise to operate a state-of-the art complex model system, such as WET, and thereby hope to facilitate a wider use and adaptation of aquatic ecosystem models.
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