4.7 Article

Nonlinear causal analysis reveals an effective water level regulation approach for phytoplankton blooms controlling in reservoirs

期刊

SCIENCE OF THE TOTAL ENVIRONMENT
卷 806, 期 -, 页码 -

出版社

ELSEVIER
DOI: 10.1016/j.scitotenv.2021.150948

关键词

Causal relationship; Hydrological disturbance; Nonlinear dynamical system; Phytoplankton bloom; Reservoir

资金

  1. National Natural Science Foundation of China [31670534]
  2. Chinese Academy of Sciences [KFJ-SWYW0036]

向作者/读者索取更多资源

This study investigates the nonlinear causal relationship between water level fluctuation (WLF) and phytoplankton biomass using empirical dynamic modeling (EDM). It found that the water level change in the past 24 hours has the strongest causal effect on daily dynamics of phytoplankton biomass with a 2-day time lag. The rise and fall of water level both significantly impact phytoplankton blooms, with rising water level having a more substantial effect overall.
Reservoirs are a rapidly increasing water body providing water supply, irrigation, and many other benefits for human societies globally. However, due to changes in hydrological conditions, building reservoirs tends to bring adverse effects such as eutrophication and phytoplankton blooms, reducing the ecosystem service values. This study focuses on using the empirical dynamic modeling (EDM), an emerging approach for nonlinear analysis, to investigate the nonlinear causal relationship of water level fluctuation (WLF) on phytoplankton biomass and then develop a quantitative model guiding effective phytoplankton blooms controlling based on water level regulations in reservoirs. Specifically, with 9-year continued daily observed data in the Three Gorges Reservoir, we examined the causal effects of different WLF parameters on the dynamics of phytoplankton blooms for the first time. We found that the water level change in the past 24 h (AWL) has the strongest causal effect on the daily dynamics of phytoplankton biomass among all WLF parameters (AWL, |AWL|, and the water level), with a time lag of 2 days. Moreover, EDM revealed a nonlinear relationship between AWL and daily dynamics of phytoplankton biomass and achieved a successful prediction for the chlorophyll a concentration 2-day ahead. Further scenario analyses found that both the rise and fall of water level will significantly reduce the chlorophyll a concentration when phytoplankton blooms occur. Nevertheless, on the whole, the rising water level has a more substantial effect on phytoplankton blooms than falling the water level. This result reveals that regulating AWL is a simple and effective approach in controlling phytoplankton blooms in reservoirs. Our study reported the nonlinear causal effect of AWL on the dynamics of chlorophyll a and provided a quantitative approach guiding effective phytoplankton blooms controlling based on the water level regulation, which might have a broad application in algal blooms controlling in reservoirs and similar waterbodies. (c) 2021 Elsevier B.V. All rights reserved.

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