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Staff Profiles

Amber S. Jones

Physical Scientist - Product Owner

Water Resources Mission Area

asjones@usgs.gov

0000-0002-5694-9034

Expertise

Amber S. Jones is a Physical Scientist for the USGS Water Resources Mission Area.

Amber is an expert on data workflows for the Hydrologic Networks Branch. Her work focuses on streamlining records processing, automated data screening, and other National Water Information System related applications. Amber’s background is in watershed hydrology, surface water quality, data science and machine learning, hydroinformatics, and environmental engineering. Amber has degrees in Civil and Environmental Engineering from Utah State University. Her PhD work focused on data science applications for water including anomaly detection for aquatic sensor data, current developments in water data science instruction, and hydrologic information systems. She has also worked as an environmental scientist and as a river guide. She is located in Logan, UT.

Professional Experience

Physical Scientist. USGS Water Mission Area. 2022- present
Research Assistant. Utah State University. 2019-2022
Research Engineer. Utah Water Research Laboratory. 2011-2018
Data Manager. iUTAH Project. Utah State University. 2013-2018
Environmental Scientist. Hillsborough County. 2009-2010

Education and Certifications

PhD, Utah State University, Water Resources Engineering
MS, Utah State University, Civil and Environmental Engineering
BS, Utah State University, Environmental Engineering

Honors and Awards

USU Civil and Environmental Engineering Doctoral Research Student of the Year, 2022
Purdue University FAIR CyberTraining Fellow for Climate and Water, 2021
USU Cyberinfrastructure for Intelligent Water Supply, Data Visualization Challenge, First Place, 2020
USU College of Engineering Technical Writing Competition Award Winner, Graduate Division, 2021 and 2019

Science and Products

Publications

Non-USGS Publications**

1. Jones, A.S., Horsburgh, J.S. (2025). Hydrologic information systems: An introductory overview. Environmental Modelling and Software, 185. https://doi.org/10.1016/j.envsoft.2024.106308

Jones, A.S., Horsburgh, J.S., Bastidas Pacheco, C.J., Flint, C.G., Lane, B.A. (2022). Advancing Hydroinformatics and Water Data Science Instruction: Community Perspectives and Online Learning Resources. Frontiers in Water. https://doi.org/10.3389/frwa.2022.901393

Jones, A.S., Jones, T.L., Horsburgh, J.S. (2022). Toward automating post processing of aquatic sensor data. Environmental Modelling and Software, 151. https://doi.org/10.1016/j.envsoft.2022.105364

Jones, A.S., Horsburgh, J.S., Eiriksson, D.P. (2018) Assessing Subjectivity in Environmental Sensor Data Post Processing via a Controlled Experiment. Ecological Informatics, 46, 86-96, doi: 10.1016/j.ecoinf.2018.05.001.

Jones, A.S., Aanderud, Z.T., Horsburgh, J.S., Eiriksson, D.P., Dastrup, D., Cox, C., Jones, S.B., Bowling, D.R., Carlisle, J., Carling, G.T., Baker, M.A. (2017) Designing and Implementing a Network for Sensing Water Quality and Hydrology Across Mountain to Urban Transitions. Journal of the American Water Resources Association, 53:5, 1095-1120, doi: 10.1111/1752-1688.12557.

Flint, C.G., Jones, A.S., Horsburgh, J.S. (2017). Data Management Dimensions of Social Water Science: The iUTAH Experience. Journal of the American Water Resources Association, 53:5, 988-996, doi: 10.1111/1752-1688.12568.

Jones, A.S., Horsburgh, J.S., Jackson-Smith, D., Ramirez, M., Flint, C.G., and Caraballo, J. (2016). A Web-based, interactive visualization tool for social environmental survey data, Environmental Modelling & Software, 84, 412-426, doi:10.1016/j.envsoft.2016.07.013.

Horsburgh, J. S., Aufdenkampe, A. K., Mayorga, E., Lehnert, K. A., Hsu, L., Song, L., Jones, A.S., Damiano, S. G., Tarboton, D. G., Valentine, D., Zaslavsky, I., Whitenack, T. (2016). Observations Data Model 2: A community information model for spatially discrete Earth observations, Environmental Modelling & Software, 79, 55-74, doi:10.1016/j.envsoft.2016.01.010.

Jones, A.S., J. S. Horsburgh, S.L. Reeder, M. Ramirez, J. Caraballo (2015). A data management and publication workflow for a large-scale, heterogeneous sensor network, Environmental Monitoring and Assessment, 187:348, doi:10.1007/s10661-015-4594-3.

Horsburgh, J. S., S. L. Reeder, A. S. Jones, J. Meline (2015). Open source software for visualization and quality control of continuous hydrologic and water quality sensor data, Environmental Modelling & Software, 70, 32-44, doi:10.1016/j.envsoft.2015.04.002.

Jones, A. S., J. S. Horsburgh, N. O. Mesner, R. J. Ryel, and D. K. Stevens (2012), Inﬂuence of Sampling Frequency on Estimation of Annual Total Phosphorus and Total Suspended Solids Loads. Journal of the American Water Resources Association, 1-18, doi:10.1111/j.1752-1688.2012.00684.x.

Jones, A.S., D. K. Stevens, J. S. Horsburgh, and N. O. Mesner (2011), Surrogate measures for providing high frequency estimates of total suspended solids and total phosphorus concentrations, Journal of the American Water Resources Association, 47(2), 239-253, doi:10.1111/j.1752-1688.2010.00505.x.

Horsburgh, J. S., A. S. Jones, D. K. Stevens, D. G. Tarboton, and N. O. Mesner (2010), A sensor network for high frequency estimation of water quality constituent fluxes using surrogates, Environmental Modelling & Software, 25, 1031-1044, doi:10.1016/j.envsoft.2009.10.012.

**Disclaimer: The views expressed in Non-USGS publications are those of the author and do not represent the views of the USGS, Department of the Interior, or the U.S. Government.