Internet of Things and citizen science as alternative water quality monitoring approaches and the importance of effective water quality communication

Journal of Environmental Management, Год журнала: 2024, Номер 352, С. 119959 - 119959

Опубликована: Янв. 9, 2024

Язык: Английский

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A Multi‐Model Ensemble of Baseline and Process‐Based Models Improves the Predictive Skill of Near‐Term Lake Forecasts

Water Resources Research, Год журнала: 2024, Номер 60(3)

Опубликована: Март 1, 2024

Abstract Water temperature forecasting in lakes and reservoirs is a valuable tool to manage crucial freshwater resources changing more variable climate, but previous efforts have yet identify an optimal modeling approach. Here, we demonstrate the first multi‐model ensemble (MME) reservoir water forecast, method that combines individual model strengths single framework. We developed two MMEs: three‐model process‐based MME five‐model includes empirical models forecast profiles at temperate drinking reservoir. found improved performance by 8%–30% relative MME, as quantified using aggregated probabilistic skill score. This increase was due large improvements bias despite increases uncertainty. High correlation among resulted little improvement models. The utility of MMEs highlighted results: (a) no performed best every depth horizon (days future), (b) avoided poor performances rarely producing worst for any forecasted period (<6% ranked forecasts over time). work presents example how existing can be combined improve discusses value utilizing MMEs, rather than models, operational forecasts.

Язык: Английский

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Data assimilation experiments inform monitoring needs for near‐term ecological forecasts in a eutrophic reservoir

Ecosphere, Год журнала: 2024, Номер 15(2)

Опубликована: Фев. 1, 2024

Abstract Ecosystems around the globe are experiencing changes in both magnitude and fluctuations of environmental conditions due to land use climate change. In response, ecologists increasingly using near‐term, iterative ecological forecasts predict how ecosystems will change future. To date, many forecasting systems have been developed high temporal frequency (minute hourly resolution) data streams for assimilation. However, this approach may be cost‐prohibitive or impossible variables that lack high‐frequency sensors latency (i.e., a delay before available modeling after collection). explore effects assimilation on forecast skill, we water temperature eutrophic drinking reservoir conducted experiments by selectively withholding observations examine effect availability accuracy. We used situ sensors, manually collected data, calibrated quality ecosystem model driven forecasted weather generate future Forecasting Lake Reservoir (FLARE), an open source system. tested daily, weekly, fortnightly, monthly skill 1‐ 35‐day‐ahead forecasts. found varied depending season, horizon, depth, frequency, but overall performance was high, with mean 1‐day‐ahead root square error (RMSE) 0.81°C, 7‐day RMSE 1.15°C, 35‐day 1.94°C. Aggregated across year, daily yielded most skillful at 7‐day‐ahead horizons, weekly resulted 8‐ horizons. Within consistently outperformed 8‐day horizon during mixed spring/autumn periods 5‐ 14‐day‐ahead horizons summer‐stratified period, depth. Our results suggest lower weekly) adequate developing accurate some applications, further enabling development broadly without sensor data.

Язык: Английский

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Day-ahead statistical forecasting of algal bloom risk to support reservoir release decisions in a highly engineered watershed

Journal of Environmental Management, Год журнала: 2025, Номер 376, С. 124327 - 124327

Опубликована: Фев. 6, 2025

Язык: Английский

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What can we learn from 100,000 freshwater forecasts? A synthesis from the NEON Ecological Forecasting Challenge

Ecological Applications, Год журнала: 2025, Номер 35(1)

Опубликована: Янв. 1, 2025

Abstract Near‐term, iterative ecological forecasts can be used to help understand and proactively manage ecosystems. To date, more have been developed for aquatic ecosystems than other worldwide, likely motivated by the pressing need conserve these essential threatened increasing availability of high‐frequency data. Forecasters implemented many different modeling approaches forecast freshwater variables, which demonstrated promise at individual sites. However, a comprehensive analysis performance varying models across multiple sites is needed broader controls on performance. Forecasting challenges (i.e., community‐scale efforts generate while also developing shared software, training materials, best practices) present useful platform bridging this gap evaluate how range methods perform axes space, time, systems. Here, we analyzed from aquatics theme National Ecological Observatory Network (NEON) Challenge hosted Initiative. Over 100,000 probabilistic water temperature dissolved oxygen concentration 1–30 days ahead seven NEON‐monitored lakes were submitted in 2023. We assessed varied among with structures, covariates, sources uncertainty relative baseline null models. A similar proportion skillful both variables (34%–40%), although outperformed forecasting (10 out 29) (6 15). These top performing came classes structures. For temperature, found that skill degraded increases horizons, process‐based models, included air as covariate generally exhibited highest performance, most often accounted lower The where observations divergent historical conditions (resulting poor model performance). Overall, NEON provides an exciting opportunity intercomparison learn about strengths diverse suite advance our understanding ecosystem predictability.

Язык: Английский

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The need for advancing algal bloom forecasting using remote sensing and modeling: Progress and future directions

Ecological Indicators, Год журнала: 2025, Номер 172, С. 113244 - 113244

Опубликована: Фев. 21, 2025

Язык: Английский

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Causes and consequences of changing oxygen availability in lakes

Inland Waters, Год журнала: 2023, Номер 13(3), С. 316 - 326

Опубликована: Июль 3, 2023

Changing oxygen availability in lakes and reservoirs is a fundamental limnological challenge of our time, with massive consequences for freshwater ecosystem functioning water quality. Cross-lake surveys, paleolimnological studies, long-term monitoring records indicate that many are exhibiting declines both surface- bottom-water due to climate land use change, although few increases oxygen. By analyzing time series data from ∼400 lakes, I found some may be experiencing decoupling surface bottom dynamics; variability concentrations decreasing while increasing. Changes have implications lake because control processes. Consequently, provisioning cultural services (e.g., drinking water, fisheries, recreation) will likely impaired by declining oxygen, whereas the effects changing on regulatory supporting nitrate removal through denitrification, carbon burial, sediment fluxes phosphorus) more equivocal. These challenges motivate research agenda focused expanding geographical range, temporal duration, spatial extent monitoring, as well new approaches studying managing (whole-ecosystem experiments, near-term forecasts). Looking ahead, advances sensor technology, networks, sharing, forecasting, demonstrated success environmental legislation hypoxia, provide important opportunities guiding restoration science

Язык: Английский

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Process-based forecasts of lake water temperature and dissolved oxygen outperform null models, with variability over time and depth

Ecological Informatics, Год журнала: 2024, Номер 83, С. 102825 - 102825

Опубликована: Сен. 11, 2024

Язык: Английский

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Preparation of C-CuxO composite from biosorption product of lactic acid bacteria and its application in solar evaporator for desalination

Separation and Purification Technology, Год журнала: 2023, Номер 330, С. 125223 - 125223

Опубликована: Окт. 7, 2023

Язык: Английский

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Modelling the potential for local management practices to offset climate change impacts on freshwater macroinvertebrate communities

Freshwater Biology, Год журнала: 2024, Номер 69(3), С. 435 - 449

Опубликована: Янв. 22, 2024

Abstract A robust understanding of the interactions between global and local anthropogenic stressors is crucial for ecosystem management in Anthropocene. Manipulative experiments laboratory or field can be used to build knowledge about physiological ecological effects stressors, but predicting combined landscape‐scale such as climate change, land‐use change requires a different approach. Here we water quality hydrology process‐based models entire river catchments combination with large biomonitoring dataset predict responses macroinvertebrate communities under scenarios. Using River Thames U.K. model system, predicted changes (temperature, flow, phosphorus [P], nitrogen, dissolved oxygen [DO]) subsequent two scenarios, individually intensified agriculture reduced P pollution (representing improved wastewater treatment). Our that water‐quality associated may not influence total species richness, community composition will shift towards more pollution‐tolerant common taxa based on indices taxon‐specific responses. We also found negative impacts (e.g., increased concentration, decreased DO concentration) accumulate through catchment, practices influencing dynamics modify this trend. Furthermore, although scenario was have minimal (a result potentially related shifting baselines already heavily polluted), resulting from treatment able mostly offset communities. results demonstrate using study networks interacting at landscape scale provide useful insights into adds support idea has potential mitigate some ecosystems.

Язык: Английский

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