An integrated assessment of water quality stressors at watershed scale is the basis for timely and effective management actions. The capacity of remote sensing to deliver spatial and temporal information about fundamental environmental dynamics makes it an ideal tool for determining the causes of water quality deterioration. This chapter focuses on harmful algal blooms in Lake Taihu (China), as a case study, demonstrating the potential of remote sensing for integrated assessment of watershed dynamics. The temporal and spatial variability of the conditions in Lake Taihu and its watershed were derived from satellite data to produce a monthly time series of algal bloom coverage, aquatic vegetation extent, and land cover from 2000 to 2013. Environmental features related to nutrient loading, climate conditions, and agricultural practices were also used to analyze the driving forces of algal blooms. Two distinct temporal patterns were identified. Prior to 2006, bloom initiation date was sensitive to agricultural activities (winter crop productivity and nutrient loading). After 2006-2007, an inversion of this relationship was observed, suggesting nutrient saturation with a shift to other watershed scale stressors, mainly climate related. After 2009, a return to pre-2006 conditions was shown. These results demonstrate how remote sensing can be used to monitor watershed dynamics as a whole, especially in conjunction with in situ environmental data.
Using Remote Sensing to Assess the Impact of Human Activities on Water Quality: Case Study of Lake Taihu, China
Paolo Villa;
2015
Abstract
An integrated assessment of water quality stressors at watershed scale is the basis for timely and effective management actions. The capacity of remote sensing to deliver spatial and temporal information about fundamental environmental dynamics makes it an ideal tool for determining the causes of water quality deterioration. This chapter focuses on harmful algal blooms in Lake Taihu (China), as a case study, demonstrating the potential of remote sensing for integrated assessment of watershed dynamics. The temporal and spatial variability of the conditions in Lake Taihu and its watershed were derived from satellite data to produce a monthly time series of algal bloom coverage, aquatic vegetation extent, and land cover from 2000 to 2013. Environmental features related to nutrient loading, climate conditions, and agricultural practices were also used to analyze the driving forces of algal blooms. Two distinct temporal patterns were identified. Prior to 2006, bloom initiation date was sensitive to agricultural activities (winter crop productivity and nutrient loading). After 2006-2007, an inversion of this relationship was observed, suggesting nutrient saturation with a shift to other watershed scale stressors, mainly climate related. After 2009, a return to pre-2006 conditions was shown. These results demonstrate how remote sensing can be used to monitor watershed dynamics as a whole, especially in conjunction with in situ environmental data.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
