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. 2024 Nov 18;11(1):1243.
doi: 10.1038/s41597-024-03994-7.

Historical datasets (1950-2022) of monthly water balance components for the Laurentian Great Lakes

Nicole L O'Brien  1 , Frank Seglenieks  2 , Lauren M Fry  3 , Deanna Fielder  4 , André G T Temgoua  2 , Jacob Bruxer  2 , Vincent Fortin  5 , Dorothy Durnford  6 , Andrew D Gronewold  7   8
Affiliations

Historical datasets (1950-2022) of monthly water balance components for the Laurentian Great Lakes

Nicole L O'Brien et al. Sci Data. .

Abstract

This study develops a 73-year dataset of water balance components from 1950 to 2022 for the Laurentian Great Lakes Basins. This is carried out using the Large Lakes Statistical Water Balance Model (L2SWBM), which provides a Bayesian statistical framework that assimilates binational input datasets sourced from the United States and Canada. The L2SWBM infers feasible water balance component estimates through this Bayesian framework by constraining the output with a standard water balance equation. The result is value-added time series, including expressions of uncertainty, that ultimately close the water balance across the interconnected Great Lakes system. Therefore, the L2SWBM facilitates the understanding of discrepancies in datasets and hydroclimate parameters. This enhanced reliability stemming from coordinated data, with an understanding and quantification of uncertainty, could significantly boost confidence in decision support tools for water resources practitioners and policymakers. This joint effort advances scientific understanding and strengthens strategies and policies designed to bolster resilience in Great Lakes communities and its ecosystem in the face of a shifting climate.

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Conflict of interest statement

Competing interests The authors declare no competing interests.

Figures

Fig. 1
Fig. 1
Image of the Great Lakes subbasins, connecting channels, and diversions.
Fig. 2
Fig. 2
Rank histograms of the independent datasets of over-lake precipitation from the operational model (Run ID 0) of over-lake precipitation for Lake Superior. Note: E denotes entropy.
Fig. 3
Fig. 3
Rank histograms of the independent datasets of over-lake evaporation from the operational model (Run ID 0) of over-lake evaporation for Lake Superior. Note: E denotes entropy.
Fig. 4
Fig. 4
Rank histograms of the independent datasets of lateral tributary inflow from the operational model (Run ID 0) of lateral tributary inflow for Lake Superior. Note: E denotes entropy.
Fig. 5
Fig. 5
Rank histograms of L2SWBM over-lake precipitation model output and RDPA, NOAA-NMS MPE, and L2SWBM NBSc and CCGLHHD NBSr.for Lake Superior, Lake Michigan-Huron, Lake Erie, and Lake Ontario for Run ID 4. Note: E denotes entropy.
Fig. 6
Fig. 6
Rank histograms of L2SWBM over-lake precipitation model output and RDPA, NOAA-NMS MPE, and L2SWBM NBSc and CCGLHHD NBSr.for Lake Superior, Lake Michigan-Huron, Lake Erie, and Lake Ontario for Run ID 43. Note: E denotes entropy.
Fig. 7
Fig. 7
Rank histograms of L2SWBM over-lake precipitation model output and RDPA, NOAA-NMS MPE, and L2SWBM NBSc and CCGLHHD NBSr.for Lake Superior, Lake Michigan-Huron, Lake Erie, and Lake Ontario for Run ID 46. Note: E denotes entropy.
Fig. 8
Fig. 8
Comparison of NBSc from the L2SWBM, NBSr and the associated 95% credible intervals for 2019.
Fig. 9
Fig. 9
Overview of L2SWBM credible intervals and input datasets for Lake Erie, which includes results for over-lake precipitation (P), over-lake evaporation (E), lateral tributary inflow (R), connecting channel flow (Q), diversions(D), and the change in lake storage (ΔH).
See this image and copyright information in PMC

References

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