Evaluation of freeze-thaw wind erosion and analysis of influencing factors on the Xizang Plateau based on the improved RWEQ
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摘要:
冻融风蚀是指气温变化导致地表结构发生变化的过程，对地表地貌的形成和土壤的性质产生重要影响。然而，青藏高原地区的特殊性和复杂性使得冻融风蚀研究尚未得到广泛关注。针对青藏高原冻融风蚀定量化分析研究相对较少，文章采用引入冻结N个因子的修正风蚀方程模型，分析2022年青藏高原冻融风蚀量的分布特征，并对青藏高原进行冻融风蚀强度分级。结果表明：（1）青藏高原冻融风蚀模数为8.90×108～4.95×105 t/（km2·a），冻融风蚀总量为2.87×1013 t，冻融风蚀总面积2.41×106 km2；（2）青藏高原轻度以下冻融风蚀占全部冻融风蚀面积的84.26%，说明青藏高原冻融风蚀以轻微和轻度为主；（3）5个因子的显著性检验结果均为显著，对青藏高原冻融风蚀模数影响程度排序为气象因子>土壤结皮因子>土壤可蚀性因子>地表粗糙度因子>植被覆盖度因子。研究不仅为青藏高原地区的环境保护和可持续发展提供了基础资料和实践参考，而且通过模型的应用，还为其他具有类似气候和地理特征的地区在冻融风蚀研究方面提供了多元方法和经验。
Abstract:Freeze-thaw wind erosion refers to the process in which temperature fluctuations cause changes in the surface structure, significantly impacting on the formation of surface landform and soil properties. However, due to the particularity and complexity of the Xizang Plateau, the study of freeze-thaw wind erosion has not received widespread attention. Due to the relative scarcity of quantitative studies on the freeze-thaw wind erosion on the Xizang Plateau, this study utilizes a Revised Wind Erosion Equation (RWEQ) that incorporates a freezing N-factor to analyze the distribution characteristics of freeze-thaw wind erosion on the Xizang Plateau in 2022. The study also categorizes the intensity of freeze-thaw wind erosion across the Xizang Plateau. The results indicate: (1) The freeze-thaw wind erosion modulus on the Qinghai- Xizang Plateau ranges from 8.90×108 to 4.95×105 (t·km−2·a−1), with a total erosion amount of 2.87×1013 t and a total affected area of 2.41×10 km2; (2) Moderate or greater freeze-thaw wind erosion accounts for 84.26% of the total affected area, indicating that light and mild erosion are predominant. (3) The significance tests of the five factors were all significant, and the influence of the freezing-thawing wind erosion modulus on the Qinghai-Xizang Plateau was ranked as meteorological factors > soil crust factors > soil erodibility factors > surface roughness factors>vegetation coverage factors. This study not only provides foundational data and practical references for environmental protection and sustainable development in the Qinghai-Xizang Plateau, but also offers a diverse range of methods and experiences for studying freeze-thaw wind erosion in other regions with similar climatic and geographical characteristics through the application of the model.
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Key words:
- modified wind erosion model /
- Xizang Plateau /
- freeze-thaw wind erosion /
- freezing factor
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表 1 数据引用来源
Table 1. Data citation sources
数据 数据来源 数据精度 单位 青藏高原矢量边界 中国科学院资源环境科学与数据中心 青藏高原气象站点 中国科学院资源环境科学与数据中心 降雨数据 中国科学院资源环境科学与数据中心 日 mm 风速数据 中国科学院资源环境科学与数据中心 日 m·s-1 蒸散发量数据 时空三极环境大数据平台 月 mm 雪盖数据 中国科学院资源环境科学与数据中心 日 mm 地表温度数据 欧洲中期天气预报中心 日 °C 土壤数据 国家冰川冻土沙漠科学中心 土地利用数据 Zenodo平台 1 km 数字高程模型数据 中国科学院资源环境科学与数据中心 1 km 归一化植被指数 地球资源数据云平台 a 
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表 2 研究区冻融风蚀强度分级
Table 2. Classification of freeze-thaw wind erosion intensity on the study area
等级 轻微 轻度 中度 强烈 极强烈 剧烈 分级标准
/（t·km−2·a−1）<2 2～25 25～50 50～80 80～150 >150 分布面积/km2 1388638 645200 149399 111901 74017 44472 面积占比/% 57.53 26.73 6.19 4.64 3.07 1.84
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表 3 137Cs核素示踪实验值与模型模拟值对比
Table 3. Comparison of experimental values from the 137Cs nuclide tracer and the model simulation values
样点编码 S1 S3 S4 S5 S6 S7 实验值/（t·km−2·a−1） 8414 6943 2262 3068 2020 4759 改进模型计算结果
/（t·km−2·a−1）9447 4725 2387 3083 2103 4819 传统模型计算结果
/（t·km−2·a−1）10167 5896 1823 2110 1531 3290
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表 4 个变量间的相关性
Table 4. Correlations between variables
$ SL $ $ WF $ $ EF $ $ SCF $ $ {K}' $ $ C $ 冻融风蚀模数 1 −0.027 −0.013 0.020 0.007 0.007 气象因子 −0.027 1 0.007 0.052 0.053 −0.072 土壤可蚀性因子 −0.013 0.007 1 0.188 0.024 −0.033 土壤结皮因子 0.020 0.052 0.188 1 0.045 0 地表粗糙度因子 0.007 0.053 0.024 0.045 1 −0.062 植被覆盖度因子 0.007 −0.072 −0.033 0.000 −0.062 1
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表 5 变量的显著性及共线性
Table 5. Significance and collinearity of variables
皮尔逊
相关性显著性 95%置信区间 共线性统计 下限 上限 容差 VIF $ SL-WF $ 0.027 0.001 −0.029 −0.025 0.981 1.019 $ SL-EF $ 0.013 0.001 −0.011 −0.015 0.309 3.233 $ SL-SCF $ 0.020 0.001 0.018 0.022 0.309 3.231 $ SL-K' $ 0.007 0.001 0.005 0.009 0.987 1.014 $ SL-C $ 0.007 0.001 0.005 0.009 0.989 1.011
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表 6 回归系数
Table 6. Regression coefficients
模型 未标准化系数 标准化系数 $ t $ 显著性 β 标准误差 β 常量 3.246 0.029 113.648 0.000 $ WF $ −0.012 0.000 −0.028 −28.883 0.001 $ EF $ −0.762 0.043 −0.017 −17.528 0.001 $ SCF $ 0.499 0.020 0.024 24.415 0.001 $ {K}' $ 0.152 0.018 0.008 8.527 0.001 $ C $ 0.094 0.018 0.005 5.120 0.001
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