Optimization of suspended particulate transport parameters from measured concentration profiles with a new analytical model
Journal article
Zhang, Shaotong, Zhao, Zixi, Wu, Jinran, Perrochet, Pierre, Wang, You-Gan, Li, Guangxue and Li, Sanzhong. (2024). Optimization of suspended particulate transport parameters from measured concentration profiles with a new analytical model. Water Research. 254, pp. 1-11. https://doi.org/10.1016/j.watres.2024.121407
Authors | Zhang, Shaotong, Zhao, Zixi, Wu, Jinran, Perrochet, Pierre, Wang, You-Gan, Li, Guangxue and Li, Sanzhong |
---|---|
Abstract | 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 |
Keywords | Erosion rate; Settling velocity ; Eddy diffusivity ; Unsteady 1DV model ; Nonlinear least squares fitting ; Yellow River Delta |
Year | 01 Jan 2024 |
Journal | Water Research |
Journal citation | 254, pp. 1-11 |
Publisher | Elsevier Ltd. (UK) - Pergamon Press |
ISSN | 0043-1354 |
Digital Object Identifier (DOI) | https://doi.org/10.1016/j.watres.2024.121407 |
Web address (URL) | https://www.sciencedirect.com/science/article/pii/S0043135424003099?via%3Dihub |
Open access | Published as non-open access |
Research or scholarly | Research |
Page range | 1-11 |
Publisher's version | License All rights reserved File Access Level Controlled |
Output status | Published |
Publication dates | |
Online | 01 Mar 2024 |
Publication process dates | |
Accepted | 29 Feb 2024 |
Deposited | 05 Sep 2024 |
Supplemental file | License All rights reserved File Access Level Controlled |
Additional information | © 2024 Elsevier Ltd. |
All rights reserved. | |
Place of publication | United Kingdom |
https://acuresearchbank.acu.edu.au/item/90y02/optimization-of-suspended-particulate-transport-parameters-from-measured-concentration-profiles-with-a-new-analytical-model
Restricted files
Publisher's version
Supplemental file
17
total views0
total downloads4
views this month0
downloads this month