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Water quality parameters such as dissolved oxygen and turbidity play a key role in policy decisions regarding the maintenance and use of the nation's major bodies of water. In particular, the United States Geological Survey (USGS) maintains a massive suite of sensors throughout the nation's waterways that are used to inform such decisions, with all data made available to the public. However, the corresponding measurements are regularly corrupted due to sensor faults, fouling, and decalibration, and hence USGS scientists are forced to spend costly time and resources manually examining data to look for anomalies. We present a method of automatically detecting such events using supervised machine learning. We first present an extensive study of which water quality parameters can be reliably predicted, using support vector machines and gradient boosting algorithms for regression. We then show that the trained predictors can be used to automatically detect sensor decalibration, providing a system that could be easily deployed by the USGS to reduce the resources needed to maintain data fidelity.
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This content will become publicly available on May 15, 2026
Resilient and Sustainable Water Resources Management in the United States: The Role of Water‐Use Data and Interagency Knowledge Exchange
ABSTRACT The United States SECURE Water Act states that a study of water use is critical for assessing impacts on water and ecological resources and forecasting whether or not available surface and groundwater supplies will meet future needs. The United States Geological Survey (USGS) plays a key role in the SECURE Water Act by providing nationally consistent information on water quantity, quality, and use. Water‐use data maintained by States and Territories are critical for the USGS water‐use estimation and modeling techniques that underlie these efforts. However, water‐use data availability has not been systematically assessed. This study addresses this gap through a survey of USGS Water Science Centers (WSCs). The results indicate that water‐use information varies in its content and level of detail across the United States. Spatially discrete and comprehensive information about water use, such as site‐specific consumptive use, withdrawals, diversions, return flows, and interbasin transfers, is not widely available to and/or shared between State and Territory water‐resource agencies and USGS WSCs. This article presents the survey results and discusses reported barriers to water‐use data availability and sharing, as well as potential implications of limited water‐use information. This study advances understanding of water‐use data availability and sharing and contributes to broader research on US water data governance.
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- Award ID(s):
- 1828902
- PAR ID:
- 10610001
- Publisher / Repository:
- Wiley-Blackwell
- Date Published:
- Journal Name:
- JAWRA Journal of the American Water Resources Association
- Volume:
- 61
- Issue:
- 3
- ISSN:
- 1093-474X
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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