Developing remote sensing methods for monitoring water quality of alpine rivers on the Tibetan Plateau - Siyuan Wang; Ming Shen; Weihua Liu; Yuanxu Ma; Hao Shi; Jingting Zhang; Di Liu (GIScience & Remote Sensing, 2022)
Water quality in alpine rivers on the Tibetan Plateau is a key indicator for eco-environment security in China, which, however, is difficult to be monitored over the plateau. In this study, several regression methods and physicals models based on hyperspectral satellite data and field observations are proposed to monitor critical water quality parameters, including water turbidity (WT), total nitrogen (TN), total phosphorus (TP), and total organic carbon (TOC) in alpine rivers. Three remote sensing and field joint observation experiments were firstly carried out in these rivers in different seasons. Then, novel statistical and semi-analytical models were built to calculate the water quality parameters in these alpine rivers using hyperspectral remote sensing data. An integrated air-ground database containing long-term water quality parameters of alpine rivers was further generated to capture the spatial heterogeneity of the water environment of these rivers by using the novel models. The results indicate that WT, TP, TN, and TOC concentrations showed clear interannual cyclical variations and seasonal variations, which reflect that the water environment has a strong seasonality and are mainly controlled by climate change in the alpine plateau.