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[1]Ma Jun,Han Lei,Zhou Peng,et al.Simulation of Robinia pseudoacacia Canopy Interception Based on Modified Gash Model and Neural Network Model[J].Research of Soil and Water Conservation,2024,31(04):188-196.[doi:10.13869/j.cnki.rswc.2024.04.012]

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Simulation of Robinia pseudoacacia Canopy Interception Based on Modified Gash Model and Neural Network Model

Research of Soil and Water Conservation[ISSN 1005-3409/CN 61-1272/P] Volume: 31 Number of periods: 2024 04 Page number: 188-196 Column: Public date: 2024-06-30

Title:: Simulation of Robinia pseudoacacia Canopy Interception Based on Modified Gash Model and Neural Network Model

Author(s):: Ma Jun¹, Han Lei^2,3,4, Zhou Peng¹, Liu Lili^2,3,4, Wang Nana^2,3,4, Ma Yunlei^2,3,4; (1.College of Forestry and Prataculture, Ningxia University, Yinchuan 750021, China; 2.School of Geography and Planning, Ningxia University, Yinchuan 750021, China; 3.China-Arab Joint International Research Laboratory for Featured Resources and Environmental Governance in Arid Regions, Yinchuan 750021, China; 4.Key Laboratory of Resource Evaluation and Environmental Regulation in Arid Region of Ningxia, Yinchuan 750021, China)

Keywords:: canopy interception; modified Gash model; neural network model; sparrow search algorithm; Robinia pseudoacacia

CLC:: S792.26; S715.2

DOI:: 10.13869/j.cnki.rswc.2024.04.012

Abstract:: [Objective]The aims of this study are to compare and analyze the applicability of modified Gash model and neural network model in simulating and predicting canopy interception of artificial forest to reveal the canopy interception and its response process of Robinia pseudoacacia in arid area, and to provide scientific basis for further understanding of forest eco-hydrological process and its regulation mechanism. [Method]Robinia pseudoacacia plantation in the east of the Yellow River of Ningxia was taken as the research object, the stemflow and throughfall were observed and the canopy interception was calculated. The modified Gash model and neural network model were used to simulate the canopy interception of Robinia pseudoacacia forest. [Result](1)The throughfall, stemflow and canopy interception of Robinia pseudoacacia plantation in the study area were 154.19 mm, 5.61 mm and 16.5 mm, respectively, and the thresholds for throughfall and stemflow were 1.37 mm and 2.17 mm, respectively.(2)Both the Gash modified model and the optimized neural network model could better simulate the canopy interception of Robinia pseudoacacia. The absolute error, mean square error, root mean square error and mean absolute percentage error of the Gash modified model were 0.20%, 0.06%, 0.24% and 52.43%, respectively. The fitting accuracy of the simulation results reached 83%. Compared with the Gash modified model, the mean square error of the BP neural network algorithm model(SSA-BP)optimized by the sparrow search algorithm was reduced by 61.48%, the mean absolute error was reduced by 40.39%, the root mean square error was reduced by 37.93%, the mean absolute percentage error was reduced by 50.52%, and the coefficient of determination was increased by 1.2%. [Conclusion]In the simulation study of canopy interception, the BP neural network model with sparrow search algorithm has a good reliability, which can effectively reduce the simulation error and improve the prediction accuracy of the model.

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Last Update: 2024-06-30