Index Catalog // Deep Blue Data

Start Over

Filtering by: Creator Smith, Joeseph P. Keyword statistical inference Discipline Science

Monthly water balance estimates for the Laurentian Great Lakes from 1950 to 2019 (v1.0) [Deprecated]

Creator:

Do, Hong X., Smith, Joeseph P., Fry, Lauren M., and Gronewold, Andrew D.

Description:

This data set contains a new estimate of monthly water balance components from 1950 to 2019 for the Laurentian Great Lakes, the largest freshwater system on Earth. The source code and inputs to derive the new estimates are also included in this dataset.

Keyword:

Great Lakes water levels, statistical inference, water balance, and data assimilation

Citation to related publication:

Do, H.X., Smith, J., Fry, L.M., and Gronewold, A.D., Seventy-year long record of monthly water balance estimates for Earth’s largest lake system (pending for submission) and Version Note: This dataset is deprecated and has been replaced by version 1.1, found at https://deepblue.lib.umich.edu/data/concern/data_sets/sb3978457

Discipline:

Science
Estimates of the water balance of the Laurentian Great Lakes using the Large Lakes Statistical Water Balance Model (L2SWBM)
User Collection

Creator:

Smith, Joeseph P., Fry, Lauren M., Do, Hong X., and Gronewold, Andrew D.

Description:

This collection contains estimates of the water balance of the Laurentian Great Lakes that were produced by the Large Lakes Statistical Water Balance Model (L2SWBM). Each data set has a different configuration and was used as the supplementary for a published peer-reviewed article (see "Citations to related material" section in the metadata of individual data sets). The key variables that were estimated by the L2SWBM are (1) over-lake precipitation, (2) over-lake evaporation, (3) lateral runoff, (4) connecting-channel outflows, (5) diversions, and (6) predictive changes in lake storage. and Contact: Andrew Gronewold Office: 4040 Dana Phone: (734) 764-6286 Email: drewgron@umich.edu

Keyword:

Great Lakes water levels, statistical inference, water balance, data assimilation, Great Lakes, Laurentian, Machine learning, Bayesian, and Network

Citation to related publication:

Smith, J. P., & Gronewold, A. D. (2017). Development and analysis of a Bayesian water balance model for large lake systems. arXiv preprint arXiv:1710.10161., Gronewold, A. D., Smith, J. P., Read, L., & Crooks, J. L. (2020). Reconciling the water balance of large lake systems. Advances in Water Resources, 103505., and Do, H.X., Smith, J., Fry, L.M., and Gronewold, A.D., Seventy-year long record of monthly water balance estimates for Earth’s largest lake system (under revision)

Discipline:

Science and Engineering

5Works

Monthly water balance estimates for the Laurentian Great Lakes from 1950 to 2019 (v1.0) [Deprecated]

Estimates of the water balance of the Laurentian Great Lakes using the Large Lakes Statistical Water Balance Model (L2SWBM)

Limit your search

Resource type

Creator

Discipline

Language

Search Results

Search Constraints

Search Results

Monthly water balance estimates for the Laurentian Great Lakes from 1950 to 2019 (v1.0) [Deprecated]

Estimates of the water balance of the Laurentian Great Lakes using the Large Lakes Statistical Water Balance Model (L2SWBM)

Limit your search

Resource type

Creator

Discipline

Language