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Abstract The Great Salt Lake reached the lowest water volume in its entire 170+ year record in 2022. To explain this record low we develop and apply a lake mass‐balance model and perform four simulations: one where all input and output variables are fixed to their mid‐20th century average resulting in an equilibrium lake volume, and three others where one of the input variables (precipitation or streamflow) or the output variable (evaporation) follows observations while the other two are fixed to their mid‐20th century average. Results show anomalously low streamflow accounting for the largest proportion of the lake volume departure from the equilibrium state by 2022, resulting in about three times the additional water loss over 1950–2022 as increasing evaporation, which played the second largest role. Precipitation changes played a minimal role. Though streamflow had a greater effect, the lake would not have reached the record low volume without increasing evaporation.
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A hybrid empirical and parametric approach for managing ecosystem complexity: Water quality in Lake Geneva under nonstationary futures
Severe deterioration of water quality in lakes, characterized by overabundance of algae and declining dissolved oxygen in the deep lake (DO B ), was one of the ecological crises of the 20th century. Even with large reductions in phosphorus loading, termed “reoligotrophication,” DO B and chlorophyll (CHL) have often not returned to their expected pre–20th-century levels. Concurrently, management of lake health has been confounded by possible consequences of climate change, particularly since the effects of climate are not neatly separable from the effects of eutrophication. Here, using Lake Geneva as an iconic example, we demonstrate a complementary alternative to parametric models for understanding and managing lake systems. This involves establishing an empirically-driven baseline that uses supervised machine learning to capture the changing interdependencies among biogeochemical variables and then combining the empirical model with a more conventional equation-based model of lake physics to predict DO B over decadal time-scales. The hybrid model not only leads to substantially better forecasts, but also to a more actionable description of the emergent rates and processes (biogeochemical, ecological, etc.) that drive water quality. Notably, the hybrid model suggests that the impact of a moderate 3°C air temperature increase on water quality would be on the same order as the eutrophication of the previous century. The study provides a template and a practical path forward to cope with shifts in ecology to manage environmental systems for non-analogue futures.
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- PAR ID:
- 10400009
- Date Published:
- Journal Name:
- Proceedings of the National Academy of Sciences
- Volume:
- 119
- Issue:
- 26
- ISSN:
- 0027-8424
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.1073/pnas.2102466119
