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Optimization of suspended particulate transport parameters from measured concentration profiles with a new analytical model.
Zhang, Shaotong; Zhao, Zixi; Wu, Jinran; Perrochet, Pierre; Wang, You-Gan; Li, Guangxue; Li, Sanzhong.
Affiliation
  • Zhang S; Frontiers Science Center for Deep Ocean Multispheres and Earth System; Key Lab of Submarine Geosciences and Prospecting Techniques, MOE; College of Marine Geosciences Ocean University of China, Qingdao 266100, China. Electronic address: shaotong.zhang@ouc.edu.cn.
  • Zhao Z; Frontiers Science Center for Deep Ocean Multispheres and Earth System; Key Lab of Submarine Geosciences and Prospecting Techniques, MOE; College of Marine Geosciences Ocean University of China, Qingdao 266100, China.
  • Wu J; Institute for Positive Psychology and Education, Australian Catholic University, Brisbane, QLD 4014, Australia.
  • Perrochet P; Center for Hydrogeology and Geothermics, University of Neuchatel, Neuchatel 2000, Switzerland.
  • Wang YG; School of Mathematics and Physics, The University of Queensland, Brisbane, QLD 4067, Australia.
  • Li G; Frontiers Science Center for Deep Ocean Multispheres and Earth System; Key Lab of Submarine Geosciences and Prospecting Techniques, MOE; College of Marine Geosciences Ocean University of China, Qingdao 266100, China.
  • Li S; Frontiers Science Center for Deep Ocean Multispheres and Earth System; Key Lab of Submarine Geosciences and Prospecting Techniques, MOE; College of Marine Geosciences Ocean University of China, Qingdao 266100, China; Laboratory for Marine Mineral Resources, Qingdao National Laboratory for Marine Sci
Water Res ; 254: 121407, 2024 May 01.
Article in En | MEDLINE | ID: mdl-38442609
ABSTRACT
The water body's suspended concentration reflects many coastal environmental indicators, which is important for predicting ecological hazards. The modeling of any concentration in water requires solving the settling-diffusion equation (SDE), and the values of several key input parameters therein (settling velocity ws, eddy diffusivity Ds, and erosion rates p(t)) directly determine the prediction performance. The time-consuming large-scale simulations would benefit if the parameter values could be estimated through available observations in the target sea area. The present work proposes a new optimization method for synchronously estimating the three parameters from limited concentration observations. First, an analytical solution to the one-dimensional vertical (1DV) SDE for suspended concentrations in an unsteady scenario is derived. Second, the near bottom suspended sediment concentration (SSC) profiles are measured with high-resolution observation. Third, the key parameters are optimized through the best fit of the measured SSC profiles and those modeled with the unsteady solution. Nonlinear least square fitting (NLSF) is introduced to judge the best fits automatically. The high-resolution concentration measurements in a specially-designed cylindrical tank experiment using the Yellow River Delta sediments test the proposed method. The method performs well in the initial period of turbulence generation when sediment resuspension is significant. It optimizes p(t), ws, and Ds with reasonable values and uniqueness of their combination. The proposed theory is a practical tool for quickly estimating key substance transport parameters from limited observations; it also has the potential to construct local parametric models to benefit the 3D modeling of coastal substance transport. Although the present work takes SSC as an example, it can be extended to any suspended particulate concentration in the water.
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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Water / Geologic Sediments Language: En Journal: Water Res / Water res / Water research Year: 2024 Type: Article

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Water / Geologic Sediments Language: En Journal: Water Res / Water res / Water research Year: 2024 Type: Article