Regional assessment for the occurrence probability of wind erosion based on the joint probability density function of air density and wind speed

被引:0
|
作者
Liang, Yushi [1 ,2 ]
Shen, Yaping [3 ]
Zhang, Zeyu [1 ]
Ji, Xiaodong [1 ]
Zhang, Mulan [4 ]
Li, Yiran [5 ]
Wang, Yu [2 ]
Xue, Xinyue [1 ]
机构
[1] Beijing Forestry Univ, Sch Soil & Water Conservat, Beijing 100083, Peoples R China
[2] Jilin Agr Univ, Coll Resources & Environm, Key Lab Straw Comprehens Utilizat & Black Soil Con, Minist Educ, Changchun 130118, Peoples R China
[3] Southwest Jiaotong Univ, Fac Geosci & Environm Engn, Chengdu 611756, Peoples R China
[4] Chinese Acad Sci, Inst Atmospher Phys, Beijing 100029, Peoples R China
[5] Southwest Forestry Univ, Coll Ecol & Environm, Kunming 650224, Peoples R China
基金
中国国家自然科学基金;
关键词
Air density; Threshold wind velocity; Joint probability density function; Random forest model; Occurrence probability of wind erosion; Land desertification; THRESHOLD FRICTION VELOCITY; SANDY LAND AREA; DUST EMISSION; AEOLIAN TRANSPORT; SIZE CHARACTERISTICS; ENERGY ASSESSMENT; SOIL-MOISTURE; CHINA; DESERTIFICATION; DISTRIBUTIONS;
D O I
10.1016/j.catena.2024.108213
中图分类号
P [天文学、地球科学];
学科分类号
07 ;
摘要
The importance of air density variations in aeolian sand movement investigations is currently attracting widespread consideration. For this purpose, the spatial distribution characteristics of threshold wind velocity under the influence of air density are determined. To better understand the occurrence conditions of wind erosion events at different spatiotemporal scales, the present paper regards the air density metric as a bridge linking wind speed distribution and threshold wind velocity, reveals the coupling relationship between air density and wind speed by introducing the statistical distribution function method of probabilistic statistical thoughts, and accomplishes the scaling up of wind speed distribution parameters according to the random forest algorithm, achieving a comprehensive evaluation of the regional overall level of wind erosion events. The results demonstrate that the mean threshold wind velocity value in the study area is 4.29 m/s, displaying a decreasing pattern with higher values in the west and lower values in the east. The mean occurrence probability of the wind erosion value is 7.92 %, with regions exceeding 12 % basically located in the central and eastern parts of the Hunshandake Sandy Land, which means that the total annual cumulative time of wind erosion in these areas is expected to approach 1.5 months. This study can contribute to the development of a systematic assessment framework of wind erosion potential risks at the regional scale. It will provide crucial information and new insights for wind erosion process research, thereby offering a theoretical basis and technical reference for a full understanding of land desertification evolution patterns.
引用
收藏
页数:22
相关论文
共 50 条
  • [31] Estimating wind speed probability distribution using kernel density method
    Qin, Zhilong
    Li, Wenyuan
    Xiong, Xiaofu
    ELECTRIC POWER SYSTEMS RESEARCH, 2011, 81 (12) : 2139 - 2146
  • [32] Estimating wind speed probability distribution by diffusion-based kernel density method
    Xu, Xiaoyuan
    Yan, Zheng
    Xu, Shaolun
    ELECTRIC POWER SYSTEMS RESEARCH, 2015, 121 : 28 - 37
  • [33] Wind Speed Probability Distribution Based on Adaptive Bandwidth Kernel Density Estimation Model for Wind Farm Application
    Chau, Tin Trung
    Nguyen, Thu Thi Hoai
    Nguyen, Linh
    Do, Ton Duc
    WIND ENERGY, 2025, 28 (02)
  • [34] Approximation of two-peak wind speed probability density function with mixed weibull distribution
    Wang, Songyan
    Yu, Jilai
    Dianli Xitong Zidonghua/Automation of Electric Power Systems, 2010, 34 (06): : 89 - 93
  • [35] A novel method for studying the wind speed probability distribution and estimating the average wind energy density
    Wang, Lingzhi
    Zhang, Xinbo
    ENGINEERING RESEARCH EXPRESS, 2024, 6 (02):
  • [36] Wind speed probability distribution estimation and wind energy assessment
    Wang, Jianzhou
    Hu, Jianming
    Ma, Kailiang
    RENEWABLE & SUSTAINABLE ENERGY REVIEWS, 2016, 60 : 881 - 899
  • [37] Estimation of wind speed probability density function using a mixture of two truncated normal distributions
    Mazzeo, Domenico
    Oliveti, Giuseppe
    Labonia, Ester
    RENEWABLE ENERGY, 2018, 115 : 1260 - 1280
  • [38] A Novel Multiobjective Formulation for Optimal Wind Speed Modeling via a Mixture Probability Density Function
    Diaaeldin, Ibrahim Mohamed
    Attia, Mahmoud A.
    Khamees, Amr K.
    Omar, Othman A. M.
    Badr, Ahmed O.
    MATHEMATICS, 2023, 11 (06)
  • [39] Joint probability distributions for wave height, wind setup and wind speed
    Van Gelder, PHAJM
    Vrijling, JK
    Van Haaren, DH
    Coastal Engineering 2004, Vols 1-4, 2005, : 1032 - 1046
  • [40] The joint scalar probability density function
    Jones, WP
    CLOSURE STRATEGIES FOR TURBULENT AND TRANSITIONAL FLOWS, 2002, : 582 - 625