Preprints
https://doi.org/10.5194/egusphere-2024-1513
https://doi.org/10.5194/egusphere-2024-1513
06 Jun 2024
 | 06 Jun 2024

A rainfall-tracking travel time distribution model to quantify mixing and storage release preference in a large shallow lake by two-year stable isotopic data

Rong Mao, Xin Luo, Jiu Jimmy Jiao, Xiaoyan Shi, and Wei Xiao

Abstract. Lake Taihu is the largest eutrophic lake in China that is shallow and connected to a dense river network. Severe eutrophication is frequently observed in Lake Taihu due to excess pollutant loadings. Understanding water cycle dynamics is essential for investigating this problem. The travel time distribution (TTD), residence time distribution (RTD) and storage selection (SAS) function describing how water is stored, mixed and released in the lake provide fundamental information on water cycle dynamics. In this study, a rainfall mixing model is established and coupled with the age master equation model to estimate the time-variant TTDs and RTDs of rainwater, river water and all water in Lake Taihu based on the two-year high-resolution isotopic data. In the rainfall mixing model, a novel rainfall mixing factor is introduced to quantify the mixing of rainwater with older lake water. The estimated range of travel time varies between 2–4 months and 7–9 months, depending on lake volume. Lake Taihu shows an inverse storage effect, i.e., the release preference shifts toward younger water when lake volume is large. The results of rainfall mixing model reveal distinct patterns and control factors between the TTDs of rainwater and river water, with rainwater contributing to 15 %–25 % of outflow. Then, the SAS functions of rainwater and river water are analyzed, which are controlled by different source zones and flow patterns. Temporal variation of spatial distribution of deuterium isotope composition illustrates storage release preference is controlled by the variation of horizontal flow paths and velocities in the lake.

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Rong Mao, Xin Luo, Jiu Jimmy Jiao, Xiaoyan Shi, and Wei Xiao

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on egusphere-2024-1513', Anonymous Referee #1, 11 Jul 2024
    • AC1: 'Reply on RC1', Rong Mao, 15 Jul 2024
  • RC2: 'Comment on egusphere-2024-1513', Paolo Benettin, 19 Jul 2024
    • AC2: 'Reply on RC2', Rong Mao, 24 Jul 2024
      • EC1: 'Reply on AC2', Damien Bouffard, 30 Jul 2024
        • AC3: 'Reply on EC1', Rong Mao, 30 Jul 2024

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on egusphere-2024-1513', Anonymous Referee #1, 11 Jul 2024
    • AC1: 'Reply on RC1', Rong Mao, 15 Jul 2024
  • RC2: 'Comment on egusphere-2024-1513', Paolo Benettin, 19 Jul 2024
    • AC2: 'Reply on RC2', Rong Mao, 24 Jul 2024
      • EC1: 'Reply on AC2', Damien Bouffard, 30 Jul 2024
        • AC3: 'Reply on EC1', Rong Mao, 30 Jul 2024
Rong Mao, Xin Luo, Jiu Jimmy Jiao, Xiaoyan Shi, and Wei Xiao
Rong Mao, Xin Luo, Jiu Jimmy Jiao, Xiaoyan Shi, and Wei Xiao

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Short summary
Lake Taihu is the largest eutrophic lake in China that is shallow with a dense river network. Eutrophication is frequently observed in the lake due to excess pollutant loadings. Understanding water transport is essential for solving the problem. We developed an age-tracking rainfall mixing model to calculate residence time of rain and river water using isotope data. The variation of mixing ratio of rainwater is also estimated. The isotope data indicates the control factors of mixing in the lake.