Proximal VIS-NIR spectrometry to retrieve substance concentrations in surface waters using partial least squares modelling

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Abstract

Many water quality parameters such as concentrations of suspended matter, nutrients and algae directly or indirectly change the electromagnetic reflectance and transmission properties of surface water bodies. Optical measurement approaches have shown great potential to partially substitute water sampling and laboratory analyses, but are obstructed by limited flexibility or high maintenance demands. In order to overcome these problems and to bridge the gap between in situ and remote sensing measurements, the use of close-range, above-surface reflectance measurements in the VIS-NIR domain to measure water quality parameters in surface water bodies was investigated. Remote sensing reflectance in a 1 m3 water tank with increasing, known concentrations of suspended solids was measured. A partial least squares model was trained to predict concentrations from reflectance curves, which performed well, considering the wide range of concentrations and illumination conditions (R2cal ¼ 0.96, R2val ¼ 0.97). The approach was then transferred to the field and further parameters were tested. Using a semi-autonomous spectrometer mounted to a boom stand on a motor boat, we traced substance concentrations in close intervals along a longitudinal gradient from inflow to dam in a drinking water reservoir in Brazil. The method is suitable for parameters directly influencing the reflection properties of the water body (e.g. suspended solids (R2cal ¼ 0.93), chlorophyll-a (R2cal ¼ 0.74)), or for parameters closely related to those (e.g. total phosphorus (R2cal ¼ 0.97)). For chemical oxygen demand, the method is not well suited (R2cal ¼ 0.14, R2val ¼ 0.45). Once calibrated to the local conditions, the spectrometer can be used stationary or on moving platforms to map and monitor surface waters. The integration of the procedure into acoustic and imaging techniques is further investigated.

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Wagner, A., Hilgert, S., Kattenborn, T., & Fuchs, S. (2019). Proximal VIS-NIR spectrometry to retrieve substance concentrations in surface waters using partial least squares modelling. Water Science and Technology: Water Supply, 19(4), 1204–1211. https://doi.org/10.2166/ws.2018.177

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