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1. A Supervised Learning Approach to Water Quality Parameter Prediction and Fault Detection

   https://doi.org/10.1109/BigData.2018.8622628  

   Joslyn, Kathleen; Lipor, John (December 2018, 2018 IEEE International Conference on Big Data (Big Data))

   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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2. Total irrigation by crop in the Continental United States from 2008 to 2020

   https://doi.org/10.1038/s41597-024-03244-w  

   Ruess, P J; Konar, Megan; Wanders, Niko; Bierkens, Marc_F P (December 2024, Scientific Data)

   We provide a dataset of irrigation water withdrawals by crop, county, year, and water source within the United States. We employ a framework we previously developed to establish a companion dataset to our original estimates. The main difference is that we now use the U.S. Geological Survey (USGS) variable ‘irrigation — total’ to partition PCR-GLOBWB 2 hydrology model estimates, instead of ‘irrigation — crop’ as used in previous estimates. Our findings for Surface Water Withdrawals (SWW), total Groundwater Withdrawals (GWW), and nonrenewable Groundwater Depletion (GWD) are similar to those of prior estimates but now have better spatial coverage, since several states are missing from the USGS ‘irrigation — crop’ variable that was originally used. Irrigation water use increases in this study, since more states are included and ‘irrigation — total’ includes more categories of irrigation than ‘irrigation — crop’. Notably, irrigation in the Mississippi Embayment Aquifer is now captured for rice and soy. We provide nearly 2.5 million data points with this paper (3,142 counties; 13 years; 3 water sources; and 20 crops). 

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3. Interbasin water transfers in the United States and Canada

   https://doi.org/10.1038/s41597-023-01935-4  

   Siddik, Md. Abu; Dickson, Kerim E.; Rising, James; Ruddell, Benjamin L.; Marston, Landon T. (December 2023, Scientific Data)

   Abstract Interbasin water transfers (IBTs) can have a significant impact on the environment, water availability, and economies within the basins importing and exporting water, as well as basins downstream of these water transfers. The lack of comprehensive data identifying and describing IBTs inhibits understanding of the role IBTs play in supplying water for society, as well as their collective hydrologic impact. We develop three connected datasets inventorying IBTs in the United States and Canada, including their features, geospatial details, and water transfer volumes. We surveyed the academic and gray literature, as well as local, state, and federal water agencies, to collect, process, and verify IBTs in Canada and the United States. Our comprehensive IBT datasets represent all known transfers of untreated water that cross subregion (US) or subdrainage area (CA) boundaries, characterizing a total of 641 IBT projects. The infrastructure-level data made available by these data products can be used to close water budgets, connect water supplies to water use, and better represent human impacts within hydrologic and ecosystem models. 

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4. A Spatially Detailed and Economically Complete Blue Water Footprint of the United States

   https://doi.org/10.5194/hess-2017-650  

   Rushforth, Richard R.; Ruddell, Benjamin L. (January 2017, Hydrology and Earth System Sciences Discussions)

   This paper quantifies and maps a spatially detailed and economically complete blue water footprint for the United States, utilizing the National Water Economy Database version 1.1 (NWED). NWED utilizes multiple mesoscale federal data resources from the United States Geological Survey (USGS), the United States Department of Agriculture (USDA), the U.S. Energy Information Administration (EIA), the U.S. Department of Transportation (USDOT), the U.S. Department of Energy (USDOE), and the U.S. Bureau of Labor Statistics (BLS) to quantify water use, economic trade, and commodity flows to construct this water footprint. Results corroborate previous studies in both the magnitude of the U.S. water footprint (F) and in the observed pattern of virtual water flows. The median water footprint (F_CUMed) of the U.S. is 181 966 Mm³ (F_Withdrawal: 400 844 Mm³; F_CUMax: 222 144 Mm³; F_CUMin: 61 117 Mm³) and the median per capita water footprint (F'_CUMed) of the U.S. is 589 m³ capita^−1 (F'_Withdrawal: 1298 m³ capita^−1; F'_CUMax: 720 m³ capita^−1; F'_CUMin: 198 m³ capita^−1). The U.S. hydro-economic network is centered on cities and is dominated by the local and regional scales. Approximately (58 %) of U.S. water consumption is for the direct and indirect use by cities. Further, the water footprint of agriculture and livestock is 93 % of the total U.S. water footprint, and is dominated by irrigated agriculture in the Western U.S. The water footprint of the industrial, domestic, and power economic sectors is centered on population centers, while the water footprint of the mining sector is highly dependent on the location of mineral resources. Owing to uncertainty in consumptive use coefficients alone, the mesoscale blue water footprint uncertainty ranges from 63 % to over 99 % depending on location. Harmonized region-specific, economic sector-specific consumption coefficients are necessary to reduce water footprint uncertainties and to better understand the human economy's water use impact on the hydrosphere. 

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5. The Nature-Based Paradigm Shift: Identifying and Overcoming Barriers to Sustainable Water Quality Solutions

   https://doi.org/10.1021/acsestwater.4c01053  

   Demaree, Kat; Johnson, Alex; Andersson, Krister; Thomas, Evan (June 2025, ACS ES&T Water)

   This study investigates the barriers and opportunities for implementing nature-based solutions to improve water quality in the United States, utilizing a mixed-methods approach. Data were collected through key informant interviews (n = 27), focus group discussions, and an online survey (n = 167). The triangulation of these methods provided a comprehensive understanding of stakeholder perspectives across various sectors including water treatment plant managers, government officials, regulators, and landowners. Key themes include regulatory hurdles, funding challenges, and the necessity for robust water quality monitoring systems. Regulatory constraints were consistently identified as a primary barrier, highlighting the need for policy reforms to facilitate green infrastructure. Funding availability was another critical challenge, with stakeholders emphasizing the importance of new financing models and incentive-based programs. Continuous water quality monitoring to establish baselines and measure the impacts of restoration projects is also emphasized. Efforts to improve local policy and regulatory frameworks could significantly bolster watershed restoration practices, enhancing riverine water quality and providing broader environmental and social benefits. 

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