Real-Time and Continuous Tracking of Total Phosphorus Using a Ground-Based Hyperspectral Proximal Sensing System

Total phosphorus (TP) is the main limiting factor of eutrophication for most inland waters globally. However, combination limited temporal-spatial ranges traditional manual sampling, poor spectral resolutions, and weather-vulnerable satellite observations, have yielded great data gaps in TP dynamics short-lived, extreme episodic, or unpredictable pollution. Hence, a novel ground-based hyperspectral proximal sensing system (GHPSs) with maximum observation frequency 20 s resolution 1 nm between 400 900 was developed automatic, real-time continuous TP. Focusing on GHRSs, machine learning model validated ideal accuracy (R2 = 0.97, RMSE 0.017 mg·L−1, MAPE 12.8%) using 377 pairs situ measurements collected from Fuchunjiang Reservoir (FR), Liangxi River (LR), Lake Taihu (LT). Second-scale results showed low-value stable period followed by sharp change LT during 29–31 October 1–3 November, respectively. The exponential increase 0.65, p < 0.05) November two complete variations peak values 0.32 mg·L−1 0.42 were recorded 2 3 Simultaneously, significant decrease 0.57, over days observed LR no obvious FR. High consistency GHPSs spectrum standardized at 574 measured reflectance different weather demonstrated > 0.99, slop 0.98). Short rapid changes within one day based minute scale monitoring, which highlighted importance high observations Several advantages real-time, wide applicability to complex monitoring compared equipment. Therefore, there are potential applications integrated space-air-ground as well emergency early-warning systems future, it can raise our awareness driving mechanisms water quality waters.