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2022 , Vol. 45 >Issue 2: 370 - 378

DOI: https://doi.org/10.12118/j.issn.1000–6060.2021.228

气候与水文

近50 a新疆风蚀气候侵蚀力迁移特征及影响因素研究

  • 王雅琴 ,
  • 杨海梅 ,
  • 范文波 ,
  • 许忠宇 ,
  • 乔长录
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  • 1.石河子大学水利建筑工程学院,新疆 石河子 832000
    2.石河子大学现代节水灌溉兵团重点实验室,新疆 石河子 832000
    3.石河子大学理学院,新疆 石河子 832000
王雅琴（1997-）,女,硕士研究生,主要从事区域土壤风蚀研究. E-mail: 1565266581@qq.com

收稿日期: 2021-05-17

  修回日期: 2021-07-08

  网络出版日期: 2022-04-02

基金资助

国家自然科学基金项目(51569028);国家自然科学基金项目(51769030);国家自然科学基金项目资助(41761064)

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Migration characteristics of wind erosion climate erosivity and its influencing factors in Xinjiang in recent 50 years

  • Yaqin WANG ,
  • Haimei YANG ,
  • Wenbo FAN ,
  • Zhongyu XU ,
  • Changlu QIAO
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  • 1. College of Water & Architecture Engineering, Shihezi University, Shihezi 832000, Xinjiang, China
    2. Key Laboratory of Modern Water-saving Irrigation of Xinjiang Production & Construction Group, Shihezi University, Shihezi 832000, Xinjiang, China
    3. College of Science, Shihezi University, Shihezi 832000, Xinjiang, China

Received date: 2021-05-17

  Revised date: 2021-07-08

  Online published: 2022-04-02

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摘要

以1969—2019年新疆维吾尔自治区62个气象站点的逐日气象资料为数据基础,探究气象因子变化对风蚀气候侵蚀力的影响;运用地理加权回归模型及重心迁移模型,从时空尺度上分析新疆风蚀气候侵蚀力重心迁移规律;结合有效敏感性指数和有效影响面积（EIA）等指标,定量描述风蚀气候侵蚀力对各气象因子的敏感程度,从区域尺度上分析新疆不同区域影响风蚀气候侵蚀力的主导因子差异性。结果表明：近50 a风蚀气候侵蚀力的重心迁移范围主要分布在南疆、北疆和东疆交界处,年际与月际迁移方向均呈现西北—东南—西北的往复迁移特征,春夏季来临之际重心由西北向东南方向迁移,寒冷季节临近时则向西北回迁。气候因子对风蚀气候侵蚀力的影响程度表现为风速>气温>降水量>相对湿度。近30 a来风速、平均气温、相对湿度及降水量对风蚀气候侵蚀力的EIA分别减少了124598.15 km2、51891.28 km2、11287.12 km2、18627.12 km2。区域上,北疆阿勒泰地区风蚀气候侵蚀力主要受相对湿度及降水量的影响,南疆西南部地区风蚀气候侵蚀力主要受风速和平均气温的影响,东疆地区风蚀气候侵蚀力主要受风速的影响。研究结果可为新疆地区土壤风蚀灾害的防治及评估提供区域性的差异化理论指导,同时为土壤风蚀的大尺度驱动力研究提供新的研究视角。

关键词： 风蚀气候侵蚀力; 气候变化; 重心迁移; 地理加权回归; 新疆

本文引用格式

王雅琴 , 杨海梅 , 范文波 , 许忠宇 , 乔长录 . 近50 a新疆风蚀气候侵蚀力迁移特征及影响因素研究[J]. 干旱区地理, 2022 , 45(2) : 370 -378 . DOI: 10.12118/j.issn.1000–6060.2021.228

Abstract

Based on daily meteorological data of 62 meteorological stations in Xinjiang, China from 1969 to 2019, this study investigated the influence of meteorological factors on wind erosion climatic erosivity. Geographically weighted regression and gravity center migration models were used to analyze the gravity center migration law of wind erosion climatic erosivity in Xinjiang from the spatial and temporal scales. Combined with the effective sensitivity index and effective affected area, the sensitivity degree of wind erosion climatic erosivity to various meteorological factors was quantitatively described. The dominant factors of wind erosion climatic erosivity in different regions of Xinjiang were analyzed. The results showed that the center of gravity of wind erosion for the past 50 years is mainly located at the junction of the north-south and east boundaries. The migration directions of inter-annual and inter-month show a northwest-southeast-northwest cycle. The center of gravity of wind erosion moves from the northwest to the southeast at the onset of the spring and summer and then moves back to the northwest when the cold season approaches. The degree of influence of climatic factors on wind erosion climatic erosivity is shown as wind speed>air temperature>precipitation>relative humidity. In the past 30 years, the effective influence of wind speed, mean air temperature, humidity, and precipitation on wind erosion has decreased by 124598.15 km2, 51891.28 km2, 11287.12 km2, and 18627.12 km2, respectively. Regionally, the wind erosion climatic erosivity is mainly influenced by relative humidity and precipitation in the Altai Prefecture of north Xinjiang. Wind speed and temperature are the main factors influencing wind erosion climatic erosivity in the southwest of southern Xinjiang. Wind erosion climatic erosivity in eastern Xinjiang is affected only by wind speed. The research results can provide regionally differentiated theoretical guidance for preventing and assessing soil wind erosion disasters in Xinjiang. It can also provide new research perspectives for studying large-scale driving forces of soil wind erosion.

Key words： wind erosion climate erosivity; climate change; center of gravity migration; geographically weighted regression; Xinjiang

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