and turbidity as the main driving factors for the formation of short-term phytoplankton blooms, while longer-term algal biomass dynamics were mostly correlated with the level of nutrients available.
In 2007, an extraordinary algal bloom event occurred in Lake Taihu. It was
preceded by an anomalously mild winter season, which resulted in favorable
conditions for overwintering of phytoplankton biomass and cyanobacterial blooms
[17]. The 2007 bloom led to a drinking water shortage for more than one million
people when HABs caused temporary closure of water treatment facilities in
northern Lake Taihu. This event further raised the awareness of public authorities
to the elevated environmental and human costs of HABs [22].
In this framework, remote sensing approaches were developed to map algal
bloom spatial–temporal dynamics and their relation with environmental variables,
to better understand those phenomena and mitigate their effects [2, 13, 23, 24]. A
retrospective analysis by remote sensing and in situ measured data, focusing on
bloom duration and dating back to 1987, was carried out by Duan et al. [2,
25]. Their study showed three distinct trends: from 1987 to 1997, blooms occurred
later each year, while from 1997 to 2007 the trend was reversed, with blooms
starting earlier each year, and after the 2007 bloom event, initiation occurred later
each year. Bloom initiation date was found to correlate well with winter temperature minima and TN:TP ratios [23].
More recently, black water blooms, occurring in particular conditions of dissolved
organic matter and phytoplankton combination in water column, and favored during
springtime conditions in the macrophyte-dominated areas of the lake’s hypereutrophic bays, were studied using remote sensing [25]. From this preliminary
study, the authors conclude that this phenomenon and its connection with
cyanobacteria and other algal blooming events needs to be further investigated.
Eutrophication and algal blooms have been partially attributed to climatic
influences, such as the increasing temperature, and anthropogenic influences such
as nutrient loading, but quantitative exploration of the main drivers has not been
performed on a watershed scale. An integrated assessment of water quality stressors
is fundamental to understand the relationship between land use, human activities,
and ecosystem degradation, with the ultimate goal of promoting a more sustainable
lake environment.
3 Remote Sensing of Lake Taihu Watershed
3.1 Dataset and Derived Features
In our study, the relationship between human activities and water quality of Lake
Taihu was investigated through remote sensing to better understand the links
between driving forces and dynamics of algal blooms. This was achieved by
using low to mid-resolution multi-temporal and multi-seasonal satellite images
Using Remote Sensing to Assess the Impact of Human Activities on Water. . .
89
In 2007, an extraordinary algal bloom event occurred in Lake Taihu. It was
preceded by an anomalously mild winter season, which resulted in favorable
conditions for overwintering of phytoplankton biomass and cyanobacterial blooms
[17]. The 2007 bloom led to a drinking water shortage for more than one million
people when HABs caused temporary closure of water treatment facilities in
northern Lake Taihu. This event further raised the awareness of public authorities
to the elevated environmental and human costs of HABs [22].
In this framework, remote sensing approaches were developed to map algal
bloom spatial–temporal dynamics and their relation with environmental variables,
to better understand those phenomena and mitigate their effects [2, 13, 23, 24]. A
retrospective analysis by remote sensing and in situ measured data, focusing on
bloom duration and dating back to 1987, was carried out by Duan et al. [2,
25]. Their study showed three distinct trends: from 1987 to 1997, blooms occurred
later each year, while from 1997 to 2007 the trend was reversed, with blooms
starting earlier each year, and after the 2007 bloom event, initiation occurred later
each year. Bloom initiation date was found to correlate well with winter temperature minima and TN:TP ratios [23].
More recently, black water blooms, occurring in particular conditions of dissolved
organic matter and phytoplankton combination in water column, and favored during
springtime conditions in the macrophyte-dominated areas of the lake’s hypereutrophic bays, were studied using remote sensing [25]. From this preliminary
study, the authors conclude that this phenomenon and its connection with
cyanobacteria and other algal blooming events needs to be further investigated.
Eutrophication and algal blooms have been partially attributed to climatic
influences, such as the increasing temperature, and anthropogenic influences such
as nutrient loading, but quantitative exploration of the main drivers has not been
performed on a watershed scale. An integrated assessment of water quality stressors
is fundamental to understand the relationship between land use, human activities,
and ecosystem degradation, with the ultimate goal of promoting a more sustainable
lake environment.
3 Remote Sensing of Lake Taihu Watershed
3.1 Dataset and Derived Features
In our study, the relationship between human activities and water quality of Lake
Taihu was investigated through remote sensing to better understand the links
between driving forces and dynamics of algal blooms. This was achieved by
using low to mid-resolution multi-temporal and multi-seasonal satellite images
Using Remote Sensing to Assess the Impact of Human Activities on Water. . .
89