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Understanding Seasonal Water Clarity Dynamics of Lake Dahuchi from In Situ and Remote Sensing Data

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  • Guofeng Wu
  • Jan Leeuw
  • Yaolin Liu

Abstract

Obtaining, analyzing and understanding the seasonal dynamics of water clarity is of importance for understanding and managing lakes and sustaining their ecosystem services. This study aimed to explore the seasonal dynamics of water clarity and to analyze how water level, wind velocity and total precipitation influence this dynamics in Lake Dahuchi, China. The Secchi disk depths recorded in the field and derived from Moderate Resolution Imaging Spectroradiometer (MODIS) images together demonstrated a seasonal pattern of water clarity, which was lower in winter and spring, increased in April or May to reach the highest values in summer, upon which it gradually declined from September onward. Piecewise linear regression analysis between water clarity and water level showed that water level could explain 70% of the variation of the logarithm of Secchi disk depth. The water clarity of Lake Dahuchi was primarily controlled by suspended sediment, while the seasonal variation of water level induced different sediment resuspension, thus we concluded that the water clarity seasonal dynamics of Lake Dahuchi was mainly regulated by seasonal variation of water level. Copyright Springer Science+Business Media B.V. 2009

Suggested Citation

  • Guofeng Wu & Jan Leeuw & Yaolin Liu, 2009. "Understanding Seasonal Water Clarity Dynamics of Lake Dahuchi from In Situ and Remote Sensing Data," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 23(9), pages 1849-1861, July.
    • Handle: RePEc:spr:waterr:v:23:y:2009:i:9:p:1849-1861
    DOI: 10.1007/s11269-008-9356-3
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    Citations

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    Cited by:

    1. Min-Cheng Tu & Patricia Smith & Anthony M Filippi, 2018. "Hybrid forward-selection method-based water-quality estimation via combining Landsat TM, ETM+, and OLI/TIRS images and ancillary environmental data," PLOS ONE, Public Library of Science, vol. 13(7), pages 1-23, July.
    2. Claudia Giardino & Mariano Bresciani & Paolo Villa & Angiolo Martinelli, 2010. "Application of Remote Sensing in Water Resource Management: The Case Study of Lake Trasimeno, Italy," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 24(14), pages 3885-3899, November.
    3. Yipeng Liao & Yun Li & Jingxiang Shu & Zhiyong Wan & Benyou Jia & Ziwu Fan, 2021. "Water Transparency Prediction of Plain Urban River Network: A Case Study of Yangtze River Delta in China," Sustainability, MDPI, vol. 13(13), pages 1-15, July.
    4. R. Fernandez & M. Bonansea & M. Marques, 2014. "Monitoring Turbid Plume Behavior from Landsat Imagery," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 28(10), pages 3255-3269, August.
    5. Xian Guan & Jonathan Li & William Booty, 2011. "Monitoring Lake Simcoe Water Clarity Using Landsat-5 TM Images," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 25(8), pages 2015-2033, June.

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