Integrating inland and coastal water quality data for actionable knowledge

Citation

El Serafy GYH, Schaeffer BA, Neely M, Spinosa A, Odermatt D, Weathers KC, Baracchini T, Bouffard D, Carvalho L, Conmy RN, De Keukelaere L, Hunter PD, Jamet C, Joehnk KD & Johnston JM (2021) Integrating inland and coastal water quality data for actionable knowledge. Remote Sensing, 13 (15), Art. No.: 2899. https://doi.org/10.3390/rs13152899

Abstract
Water quality measures for inland and coastal waters are available as discrete samples from professional and volunteer water quality monitoring programs and higher-frequency, near-continuous data from automated in situ sensors. Water quality parameters also are estimated from model outputs and remote sensing. The integration of these data, via data assimilation, can result in a more holistic characterization of these highly dynamic ecosystems, and consequently improve water resource management. It is becoming common to see combinations of these data applied to answer relevant scientific questions. Yet, methods for scaling water quality data across regions and beyond, to provide actionable knowledge for stakeholders, have emerged only recently, particularly with the availability of satellite data now providing global coverage at high spatial resolution. In this paper, data sources and existing data integration frameworks are reviewed to give an overview of the present status and identify the gaps in existing frameworks. We propose an integration framework to provide information to user communities through the the Group on Earth Observations (GEO) AquaWatch Initiative. This aims to develop and build the global capacity and utility of water quality data, products, and information to support equitable and inclusive access for water resource management, policy and decision making.

Keywords
water quality; remote sensing; lake; estuary; coastal; sensors; management; interoperability; integration

Notes
Additional co-authors: Anders Knudby, Camille Minaudo, Nima Pahlevan, Ils Reusen, Kevin C. Rose, John Schalles and Maria Tzortziou

Journal
Remote Sensing: Volume 13, Issue 15