place in many areas, often focusing on phosphorous (P) load limitations. But the
spread of non-nitrogen-fixing cyanobacteria (e.g., Microcystis, as in our case study
of Lake Taihu) and the influence of climatic variables (mainly temperature and
solar radiation) on bloom formation have introduced new factors, which need to be
taken into account when setting up management strategies aimed at reducing the
impact of HABs [12, 13].
The integration of remote sensing information about changes in both the aquatic
and terrestrial compartments can provide new insights into the assessment of inland
water bodies and coastal areas ecosystems. The objective of this chapter is to
demonstrate the capabilities of remote sensing in providing multi-temporal information for water color and water quality (e.g., bio-optical parameters) as well as for
environmental drivers of water quality threats, such as HABs. Specifically, the
chapter focuses on HABs in Lake Taihu (China) to demonstrate the potential of
remote sensing for integrated assessment of watershed dynamics.
2 Study Area
The Lake Taihu watershed is located in one of the most important developing areas
of China and has experienced enormous changes in land use and land cover over the
past three decades. From 1990 to 2010, the population of Taihu watershed has more
than doubled, and economic growth brought along an increasing number of industries. The GDP of the area has seen a sharp increase, from 847 billion Yuan (RMB)
in 1998 to 2,662 billion Yuan (RMB) in 2007 [2].
The Taihu watershed occupies the southern part of Jiangsu Province (Sunan),
part of Zhejiang Province and Shanghai Municipality (Fig. 1). The Eastern China
lake region (around 36,900 km
2 ), along the course of the lower Yangtze River, is
currently one of the most densely populated areas in the world and therefore subject
to significant anthropogenic pressures. More than 150 million people live in the
three provinces of this region, Anhui, Jiangsu, and Shanghai, where a large part of
national GDP is produced through industrial and agricultural activities. The local
per capita GDP is three times the national average and the population density
(averaging 600 per km
2
) is seven times higher than national average.
This region contains one of the most abundant surface water resources in China.
Hundreds of large and small lakes exist in the region, but most have undergone
significant eutrophication over the past three decades. Lake Taihu is the largest and
most endangered lake in the region, suffering from high nutrient loads and eutrophic condition, low water level, and frequent problems of massive anoxia and algal
blooms. These issues jeopardize basic ecosystem services for local population and
water resources for drinking water supplies, agriculture, fishing, fish farming, and
aquaculture.
High water levels in Lake Taihu generally occur during late August to
September, at the end of monsoon season, while low levels occur during November
to May (winter and spring), the dry season. Lake sediment cores have shown that
Using Remote Sensing to Assess the Impact of Human Activities on Water. . .
87
spread of non-nitrogen-fixing cyanobacteria (e.g., Microcystis, as in our case study
of Lake Taihu) and the influence of climatic variables (mainly temperature and
solar radiation) on bloom formation have introduced new factors, which need to be
taken into account when setting up management strategies aimed at reducing the
impact of HABs [12, 13].
The integration of remote sensing information about changes in both the aquatic
and terrestrial compartments can provide new insights into the assessment of inland
water bodies and coastal areas ecosystems. The objective of this chapter is to
demonstrate the capabilities of remote sensing in providing multi-temporal information for water color and water quality (e.g., bio-optical parameters) as well as for
environmental drivers of water quality threats, such as HABs. Specifically, the
chapter focuses on HABs in Lake Taihu (China) to demonstrate the potential of
remote sensing for integrated assessment of watershed dynamics.
2 Study Area
The Lake Taihu watershed is located in one of the most important developing areas
of China and has experienced enormous changes in land use and land cover over the
past three decades. From 1990 to 2010, the population of Taihu watershed has more
than doubled, and economic growth brought along an increasing number of industries. The GDP of the area has seen a sharp increase, from 847 billion Yuan (RMB)
in 1998 to 2,662 billion Yuan (RMB) in 2007 [2].
The Taihu watershed occupies the southern part of Jiangsu Province (Sunan),
part of Zhejiang Province and Shanghai Municipality (Fig. 1). The Eastern China
lake region (around 36,900 km
2 ), along the course of the lower Yangtze River, is
currently one of the most densely populated areas in the world and therefore subject
to significant anthropogenic pressures. More than 150 million people live in the
three provinces of this region, Anhui, Jiangsu, and Shanghai, where a large part of
national GDP is produced through industrial and agricultural activities. The local
per capita GDP is three times the national average and the population density
(averaging 600 per km
2
) is seven times higher than national average.
This region contains one of the most abundant surface water resources in China.
Hundreds of large and small lakes exist in the region, but most have undergone
significant eutrophication over the past three decades. Lake Taihu is the largest and
most endangered lake in the region, suffering from high nutrient loads and eutrophic condition, low water level, and frequent problems of massive anoxia and algal
blooms. These issues jeopardize basic ecosystem services for local population and
water resources for drinking water supplies, agriculture, fishing, fish farming, and
aquaculture.
High water levels in Lake Taihu generally occur during late August to
September, at the end of monsoon season, while low levels occur during November
to May (winter and spring), the dry season. Lake sediment cores have shown that
Using Remote Sensing to Assess the Impact of Human Activities on Water. . .
87