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A high-precision hydrodynamic model coupled with the hydrological habitat suitability model to reveal estuarine vegetation distribution 被引量:2

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摘要 In this paper,based on the finite volume method,a high-precision hydrodynamic model coupled with the habitat suitability model is established,and the computational efficiency of the coupled model is improved by a graphics processing unit(GPU)-accelerated technology.The coupled model is used to solve the problem of the non-conservation of mass that may be caused by the nearshore hydrodynamic model in the processing of wetting and drying,while avoiding the unphysical high velocities at the wetting and drying boundaries.The coupled model is applied to simulate the high-precision hydrodynamic process of the Liao River estuary(LRE)and the hydrological habitat suitability of the estuarine vegetation(Suaeda heteroptera)growing in the LRE.The simulated values of the hydrological variables(the water level,the water depth,the current velocity and direction)are highly consistent with the measured values.The root mean square errors(RMSE)of the hydrological variables are 0.10m,0.12m/s and 17.24°,respectively.Furthermore,the simulated combined suitability index(CSI)distribution of Suaeda heteroptera(S.heteroptera)matches with the distribution of S.heteroptera obtained from the high-resolution remote sensing satellite images during the same time period.The ratio of the simulated weighted usable area(WUA)of S.heteroptera to the area obtained from the remote sensing satellite images during the same period is 81.9%.This study reveals the phenomenon that the distribution of S.heteroptera in the LRE is highly correlated with the high-precision hydrodynamic processes,and provides a scientific basis and a valuable reference for the conservation and the restoration of the estuarine vegetation.
出处 《Journal of Hydrodynamics》 SCIE EI CSCD 2022年第3期451-466,共16页 水动力学研究与进展B辑(英文版)
基金 Project supported by the National Key Research and Development Program of China(Grant No.2019YFC1407700) the National Natural Science Foundation of China(Grant No.51779038).
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