[1]ZHANG Shanhong,BAI Hongying,QI Guizeng,et al.Spatial Simulation of Active Accumulated Temperature≥10℃in Qinling-Daba Mountains Based on Anusplin and Multiple Linear Regression Model[J].Research of Soil and Water Conservation,2022,29(01):184-189+196.
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Research of Soil and Water Conservation[ISSN 1005-3409/CN 61-1272/P] Volume:
29
Number of periods:
2022 01
Page number:
184-189+196
Column:
Public date:
2022-02-20
- Title:
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Spatial Simulation of Active Accumulated Temperature≥10℃in Qinling-Daba Mountains Based on Anusplin and Multiple Linear Regression Model
- Author(s):
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ZHANG Shanhong1,2,3, BAI Hongying1,3, QI Guizeng1,3, LIANG Jia4, ZHAO Ting1,3
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(1.College of Urban and Environmental Sciences, Northwest University, Xi'an 710127, China; 2.College of Urban, Rural Planning and Architectural Engineering, Shangluo University, Shangluo, Shaanxi 726000, China; 3.Key Laboratory of Shaanxi Surface System and Environmental Carrying Capacity, Northwest University, Xi'an 710127, China; 4.Shaanxi Meteorological Service Center, Xi'an 710014, China)
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- Keywords:
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Anusplin; active accumulated temperature; multiple linear regression model; spatial simulation; Qinling-Daba Mountains
- CLC:
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P467
- DOI:
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- Abstract:
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To obtain accurate and fast spatial accumulated temperature data in mountainous regions, two methods, high-precision meteorological interpolation software Anusplin and multiple linear regression model, were used to simulate the spatial distribution of accumulated temperature ≥10℃ in mountainous areas in order to provide solutions for the spatial distribution of accumulated temperature in mountainous areas. The Qinling-Daba Mountains with large topographic relief was taken as the study area. Based on Anusplin and multiple linear regression interpolation methods separately, 30 m resolution spatial distribution of actively accumulated temperature ≥10℃(AAT10)was simulated by combining with DEM and the daily meteorological observation data from 69 meteorological stations in the research and surrounding 22 meteorological stations during 1960—2019. The interpolation accuracy of Anusplin and multiple linear regression were compared, and the applicability of the two methods in complex mountainous areas is evaluated through verifying the measured data of reserved meteorological stations. The results show that both two interpolation methods are suitable for spatial simulation of active accumulated temperature ≥10℃(AAT10)in Qinling-Daba mountains, but the Anusplin has slightly higher accuracy than the multiple linear regression interpolation methods. In other words, the spatial interpolation method based on Anusplin can more realistically reflect the spatial distribution of the accumulated temperature, and can better simulate the high-precision accumulated temperature data of complex mountainous areas, which provides a new method for the spatial simulation of active accumulated temperature in the mountainous area.