Robust Predictive Design of Field Measurements for Evapotranspiration Barriers Using Universal Multiple linear Regression
Abstract
Surface barriers are normally installed to reduce downward water movement into contaminated zones. Specifically, evapotranspiration (ET) barriers are used to store water and release it, via ET, before it can percolate into an underlying waste zone. To assess the effectiveness of a surface barrier, we used an existing data set, model-simulated data, and a dimensionality reduction approach called universal multiple linear regression (uMLR) to optimize the required number of sensors in a 2-m thick surface barrier. To understand the usefulness of implementing predictive uMLR to accommodate multiple monitoring objectives, we compare several network designs, selected based on down-sampling of existing data, with a recommended sensor design based on model simulations performed without consideration of existing data. We further added consideration of “fuzzy” design, which allows more practical guidelines for field implementation of uMLR. We discovered that uMLR, combined with robust decision-making, provides a simple, flexible, and high-quality network design for monitoring the total water stored in a surface barrier across multiple uncertain conditions.
- Authors:
-
[1];
[2];
[3];
- Fort Lewis College, Durango ,CO (United States)
- Univ. of Arizona, Tucson, AZ (United States)
- Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
- Publication Date:
- Research Org.:
- Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
- Sponsoring Org.:
- USDOE
- OSTI Identifier:
- 1608754
- Report Number(s):
- PNNL-SA-142796
Journal ID: ISSN 0043-1397
- Grant/Contract Number:
- AC05-76RL01830
- Resource Type:
- Accepted Manuscript
- Journal Name:
- Water Resources Research
- Additional Journal Information:
- Journal Volume: 55; Journal Issue: 11; Journal ID: ISSN 0043-1397
- Publisher:
- American Geophysical Union (AGU)
- Country of Publication:
- United States
- Language:
- English
- Subject:
- 58 GEOSCIENCES; Neutron Probe; Sensor Depth; Decision-Making; Monitoring
Citation Formats
Clutter, Melissa, Ferré, Ty P. A., Zhang, Zhuanfang Fred, and Gupta, Hoshin. Robust Predictive Design of Field Measurements for Evapotranspiration Barriers Using Universal Multiple linear Regression. United States: N. p., 2019.
Web. doi:10.1029/2019WR026194.
Clutter, Melissa, Ferré, Ty P. A., Zhang, Zhuanfang Fred, & Gupta, Hoshin. Robust Predictive Design of Field Measurements for Evapotranspiration Barriers Using Universal Multiple linear Regression. United States. https://doi.org/10.1029/2019WR026194
Clutter, Melissa, Ferré, Ty P. A., Zhang, Zhuanfang Fred, and Gupta, Hoshin. Tue .
"Robust Predictive Design of Field Measurements for Evapotranspiration Barriers Using Universal Multiple linear Regression". United States. https://doi.org/10.1029/2019WR026194. https://www.osti.gov/servlets/purl/1608754.
@article{osti_1608754,
title = {Robust Predictive Design of Field Measurements for Evapotranspiration Barriers Using Universal Multiple linear Regression},
author = {Clutter, Melissa and Ferré, Ty P. A. and Zhang, Zhuanfang Fred and Gupta, Hoshin},
abstractNote = {Surface barriers are normally installed to reduce downward water movement into contaminated zones. Specifically, evapotranspiration (ET) barriers are used to store water and release it, via ET, before it can percolate into an underlying waste zone. To assess the effectiveness of a surface barrier, we used an existing data set, model-simulated data, and a dimensionality reduction approach called universal multiple linear regression (uMLR) to optimize the required number of sensors in a 2-m thick surface barrier. To understand the usefulness of implementing predictive uMLR to accommodate multiple monitoring objectives, we compare several network designs, selected based on down-sampling of existing data, with a recommended sensor design based on model simulations performed without consideration of existing data. We further added consideration of “fuzzy” design, which allows more practical guidelines for field implementation of uMLR. We discovered that uMLR, combined with robust decision-making, provides a simple, flexible, and high-quality network design for monitoring the total water stored in a surface barrier across multiple uncertain conditions.},
doi = {10.1029/2019WR026194},
journal = {Water Resources Research},
number = 11,
volume = 55,
place = {United States},
year = {2019},
month = {10}
}
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Figure 1: PHB study site. 12 stations where vertical access tubes were installed to 1.9 m depths and spaced 5 m apart. The six northern stations experienced wet conditions during WY95-WY97 and typical conditions WY98-WY12. The six southern stations experienced typical conditions during the entire data collection period.
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