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Inferring causal impacts of extreme water-level drawdowns on lake water clarity using long-term monitoring data.
Nakanishi, Kosuke; Yokomizo, Hiroyuki; Fukaya, Keiichi; Kadoya, Taku; Matsuzaki, Shin-Ichiro S; Nishihiro, Jun; Kohzu, Ayato; Hayashi, Takehiko I.
Affiliation
  • Nakanishi K; Health and Environmental Risk Division, National Institute for Environmental Studies, 16-2 Onogawa, Tsukuba, Ibaraki 305-8506, Japan. Electronic address: nakanishi.kosuke@nies.go.jp.
  • Yokomizo H; Health and Environmental Risk Division, National Institute for Environmental Studies, 16-2 Onogawa, Tsukuba, Ibaraki 305-8506, Japan.
  • Fukaya K; Biodiversity Division, National Institute for Environmental Studies, 16-2 Onogawa, Tsukuba, Ibaraki 305-8506, Japan.
  • Kadoya T; Biodiversity Division, National Institute for Environmental Studies, 16-2 Onogawa, Tsukuba, Ibaraki 305-8506, Japan.
  • Matsuzaki SS; Biodiversity Division, National Institute for Environmental Studies, 16-2 Onogawa, Tsukuba, Ibaraki 305-8506, Japan.
  • Nishihiro J; Center for Climate Change Adaptation, National Institute for Environmental Studies, 16-2 Onogawa, Tsukuba, Ibaraki 305-8506, Japan.
  • Kohzu A; Regional Environment Conservation Division, National Institute for Environmental Studies, 16-2 Onogawa, Tsukuba, Ibaraki 305-8506, Japan.
  • Hayashi TI; Social Systems Division, National Institute for Environmental Studies, 16-2 Onogawa, Tsukuba, Ibaraki 305-8506, Japan.
Sci Total Environ ; 838(Pt 2): 156088, 2022 Sep 10.
Article in En | MEDLINE | ID: mdl-35605866
Although long-term ecosystem monitoring provides essential knowledge for practicing ecosystem management, analyses of the causal effects of ecological impacts from large-scale observational data are still in an early stage of development. We used causal impact analysis (CIA)-a synthetic control method that enables estimation of causal impacts from unrepeated, long-term observational data-to evaluate the causal impacts of extreme water-level drawdowns during summer on subsequent water quality. We used more than 100 years of transparency and water level monitoring data from Lake Biwa, Japan. The results of the CIA showed that the most extreme drawdown in recorded history, which occurred in 1994, had a significant positive effect on transparency (a maximum increase of 1.75 m on average over the following year) in the north basin of the lake. The extreme drawdown in 1939 was also shown to be a trigger for an increase in transparency in the north basin, whereas that in 1984 had no significant effects on transparency. In the south basin, contrary to the pattern in the north basin, the extreme drawdown had a significant negative effect on transparency shortly after the extreme drawdown. These different impacts of the extreme drawdowns were considered to be affected by the timing and magnitude of the extreme drawdowns and the depths of the basins. Our approach of inferring the causal impacts of past events on ecosystems will be helpful in implementing water-level management for ecosystem management and improving water quality in lakes.
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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Water Quality / Lakes / Environmental Monitoring Type of study: Prognostic_studies Country/Region as subject: Asia Language: En Journal: Sci Total Environ Year: 2022 Type: Article

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Water Quality / Lakes / Environmental Monitoring Type of study: Prognostic_studies Country/Region as subject: Asia Language: En Journal: Sci Total Environ Year: 2022 Type: Article