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| Type: | Resource | |
| Storage: | The size of this resource is 28.7 MB | |
| Created: | Nov 29, 2023 at 9:53 p.m. | |
| Last updated: | Jan 08, 2024 at 9:10 p.m. (Metadata update) | |
| Published date: | Jan 08, 2024 at 9:10 p.m. | |
| DOI: | 10.4211/hs.58b0f961c81a41939415526c8ad78d33 | |
| Citation: | See how to cite this resource |
| Sharing Status: | Published |
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| Views: | 1478 |
| Downloads: | 128 |
| +1 Votes: | 1 other +1 this |
| Comments: | No comments (yet) |
Abstract
Quantifying water sources to rivers and streams is critical for managing water resources globally. Endmember mixing analysis (EMMA) is a commonly applied method to water sources to streams that uses tracers for hydrograph separation. Most EMMA applications follow similar methods, but several choices must be made such as selecting tracers, endmembers, and stream locations for mixing. With no standardized EMMA approach, these choices may be made subjectively with little regard for resulting errors. We created an open-source software program called EMMALAB, developed in Matlab App Designer, to simplify and standardize the workflow associated with EMMA. EMMALAB guides the user through a uniform process to visualize and select endmembers via principal components analysis, calculate the fractional contribution of each endmember, and calculate errors in the mixing analysis. The files in this HydroShare resource include: EMMALAB v1.0 installers for Mac and PC, a data template, and example dataset from the Provo River, and the transcript for a YouTube video that provides instructions for using the software. The Provo River dataset is the example data used in the training video.
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Funding Agencies
This resource was created using funding from the following sources:
| Agency Name | Award Title | Award Number |
|---|---|---|
| National Science Foundation | Dust in the Critical Zone from the Great Basin to the Rocky Mountains | EAR-2012093 |
| National Science Foundation | A machine-learning approach to quantitative phase analysis of whole rocks and sediments | EAR-2005432 |
How to Cite
This resource is shared under the Creative Commons Attribution CC BY.
http://creativecommons.org/licenses/by/4.0/
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