Long-term change of total suspended matter in a deep-valley reservoir with HJ-1A/B: implications for reservoir management

Yibo Zhang, Kun Shi, Yunlin Zhang, Max ​Moreno Madrinan, Guangwei Zhu, Yongqiang Zhou, Xiaolong Yao

Research output: Contribution to journalArticle

Abstract

The valley reservoirs service as a critical resource for society by providing drinking water, power generation, recreation, and maintaining biodiversity. Management and assessment of the water environment in valley reservoirs are urgent due to the recent eutrophication and water quality deterioration. As an essential component of the water body, total suspended matter (TSM) hinder the light availability to underwater and then affect the photosynthesis of aquatic ecosystem. We used long-term HJ-1A/B dataset to track TSM variation and elucidating the driving mechanism of valley reservoirs. Taking a typical deep-valley reservoir (Xin’anjing Reservoir) as our case study, we constructed a TSM model with satisfactory performance (R2, NRMSE, and MRE values are 0.85, 18.57%, and 20%) and further derived the spatial-temporal variation from 2009 to 2017. On an intra-annual scale, the TSM concentration exhibited a significant increase from 2.13 ± 1.10 mg L−1 in 2009 to 3.94 ± 0.82 mg L−1 in 2017. On a seasonal scale, the TSM concentration in the entire reservoir was higher in the summer (3.36 ± 1.54 mg L−1) and autumn (2.74 ± 0.82 mg L−1) than in the spring (1.84 ± 1.27 mg L−1) and winter (1.44 ± 2.12 mg L−1). On a monthly scale, the highest and lowest mean TSM value occurred in June (4.66 ± 0.45 mg L−1) and January (0.67 ± 1.50 mg L−1), and the monthly mean TSM value increased from January to June, then dropped from June to December. Combing HJ-1A/B-derived TSM, climatological data, basin dynamic, and morphology of the reservoir, we elucidated the driving mechanism of TSM variation. The annual increase of TSM from long-term HJ-1A/B data indicated that the water quality of Xin’anjiang Reservoir was decreasing. The annual increase of phytoplankton jointed with an increase of built-up land and decrease of forest land in the basin may partially be responsible for the increasing trend in TSM. This study suggested that combining the long-term remote sensing data and in situ data could provide insight into the driving mechanism of water quality dynamic and improve current management efforts for local environmental management.

Original languageEnglish (US)
JournalEnvironmental Science and Pollution Research
DOIs
StateAccepted/In press - Jan 1 2018

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Reservoir management
Petroleum reservoirs
Water Quality
long-term change
Water quality
valley
Eutrophication
Water power
Phytoplankton
Recreation
Aquatic ecosystems
Environmental management
Photosynthesis
Water
Body Water
Biodiversity
Potable water
Drinking Water
Power generation
Ecosystem

Keywords

  • Dynamic
  • Land cover change
  • Rainfall
  • Suspended matter
  • Valley reservoirs

ASJC Scopus subject areas

  • Environmental Chemistry
  • Pollution
  • Health, Toxicology and Mutagenesis

Cite this

Long-term change of total suspended matter in a deep-valley reservoir with HJ-1A/B : implications for reservoir management. / Zhang, Yibo; Shi, Kun; Zhang, Yunlin; ​Moreno Madrinan, Max; Zhu, Guangwei; Zhou, Yongqiang; Yao, Xiaolong.

In: Environmental Science and Pollution Research, 01.01.2018.

Research output: Contribution to journalArticle

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abstract = "The valley reservoirs service as a critical resource for society by providing drinking water, power generation, recreation, and maintaining biodiversity. Management and assessment of the water environment in valley reservoirs are urgent due to the recent eutrophication and water quality deterioration. As an essential component of the water body, total suspended matter (TSM) hinder the light availability to underwater and then affect the photosynthesis of aquatic ecosystem. We used long-term HJ-1A/B dataset to track TSM variation and elucidating the driving mechanism of valley reservoirs. Taking a typical deep-valley reservoir (Xin’anjing Reservoir) as our case study, we constructed a TSM model with satisfactory performance (R2, NRMSE, and MRE values are 0.85, 18.57{\%}, and 20{\%}) and further derived the spatial-temporal variation from 2009 to 2017. On an intra-annual scale, the TSM concentration exhibited a significant increase from 2.13 ± 1.10 mg L−1 in 2009 to 3.94 ± 0.82 mg L−1 in 2017. On a seasonal scale, the TSM concentration in the entire reservoir was higher in the summer (3.36 ± 1.54 mg L−1) and autumn (2.74 ± 0.82 mg L−1) than in the spring (1.84 ± 1.27 mg L−1) and winter (1.44 ± 2.12 mg L−1). On a monthly scale, the highest and lowest mean TSM value occurred in June (4.66 ± 0.45 mg L−1) and January (0.67 ± 1.50 mg L−1), and the monthly mean TSM value increased from January to June, then dropped from June to December. Combing HJ-1A/B-derived TSM, climatological data, basin dynamic, and morphology of the reservoir, we elucidated the driving mechanism of TSM variation. The annual increase of TSM from long-term HJ-1A/B data indicated that the water quality of Xin’anjiang Reservoir was decreasing. The annual increase of phytoplankton jointed with an increase of built-up land and decrease of forest land in the basin may partially be responsible for the increasing trend in TSM. This study suggested that combining the long-term remote sensing data and in situ data could provide insight into the driving mechanism of water quality dynamic and improve current management efforts for local environmental management.",
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AU - ​Moreno Madrinan, Max

AU - Zhu, Guangwei

AU - Zhou, Yongqiang

AU - Yao, Xiaolong

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