干旱区研究 ›› 2021, Vol. 38 ›› Issue (4): 939-949.doi: 10.13866/j.azr.2021.04.05

• 水资源及其利用 • 上一篇    下一篇

基于CSLE模型的天山北坡中段山区水力侵蚀时空变化特征及影响因素研究

常梦迪1,2(),王新军1,2(),李娜1,2,闫立男1,2,马克1,2,李菊艳3   

  1. 1.新疆农业大学草业与环境科学学院,新疆 乌鲁木齐 830052
    2.新疆土壤与植物生态过程重点实验室,新疆 乌鲁木齐 830052
    3.新疆维吾尔自治区水土保持生态环境监测总站,新疆 乌鲁木齐 830000
  • 收稿日期:2020-11-16 修回日期:2021-01-25 出版日期:2021-07-15 发布日期:2021-08-03
  • 通讯作者: 王新军
  • 作者简介:常梦迪(1996-),女,硕士研究生,主要从事水土流失监测与评估、地理信息系统及遥感应用研究. E-mail: 1761316194@qq.com
  • 基金资助:
    新疆维吾尔自治区财政专项“天山北坡典型区水土流失与经济发展关系研究”(213031002)

Study on temporal and spatial variation characteristics and influencing factors of hydraulic erosion in the middle of the northern slope of Tianshan Mountains based on CSLE model

CHANG Mengdi1,2(),WANG Xinjun1,2(),LI Na1,2,YAN Linan1,2,MA Ke1,2,LI Juyan3   

  1. 1. College of Grassland and Environment Sciences, Xinjiang Agricultural University, Urumqi 830052, Xinjiang, China
    2. Xinjiang Key Laboratory of Soil and Plant Ecological Processes, Urumqi 830052, Xinjiang, China
    3. General Station Soil and Water Conservation and Ecological Environment Monitoring of Xinjiang, Urumqi 830000, Xinjiang, China
  • Received:2020-11-16 Revised:2021-01-25 Online:2021-07-15 Published:2021-08-03
  • Contact: Xinjun WANG

摘要:

掌握天山北坡土壤水蚀分异的空间规律及其驱动力,对生态预警和土壤侵蚀防治具有重要意义,为天山北坡区域生态环境的综合治理提供理论依据和数据支持。以天山北坡中段山区为例,基于中国土壤流失方程(Chinese Soil Loss Equation,CSLE),采用野外调研、地理信息系统、数理统计和地理探测器等方法,定量分析2000—2018年研究区土壤水力侵蚀的时空格局特征(面积,强度和地理分布),借助地理探测器探究降雨、地形、土壤、植被对土壤水力侵蚀强度的内在驱动力。结果表明:(1) 2000—2018年天山北坡中段山区土壤水力侵蚀强度主要以微度、轻度侵蚀为主,分别占总面积的32.34%~40.87%、33.36%~43.01%。近20 a的微度、轻度侵蚀的面积均呈下降趋势(-26.70 km2·a-1、-77.47 km2·a-1),而其他侵蚀强度的面积均呈上升趋势(22.10~30.96 km2·a-1),总体上土壤水力侵蚀强度处于增加趋势。(2) 整体土壤侵蚀模数呈乌鲁木齐市>昌吉市>阜康市>呼图壁县>玛纳斯县>沙湾县>石河子市。天山北坡中段山区侵蚀强度的空间分布与降雨、地形、土壤、植被密切相关,土壤类型为棕钙土、草毡土、栗钙土,植被覆盖度小于15%、坡度大于15°和降雨量在400~450 mm范围内的地区为高风险侵蚀区域。(3) 分异性的大小由因子探测器中q值来度量,其q值越大,该影响因素对土壤侵蚀空间分布的解释力越强,呈降雨(0.49)>土壤类型(0.17)>坡度(0.11)>植被覆盖度(0.10)。不同影响因素通过交互作用明显增强土壤侵蚀空间异质性,及植被覆盖度与降雨因子的耦合作用,q值增幅极大,确定土壤侵蚀重点治理区域对全面土壤侵蚀防治具有重要意义。

关键词: 天山北坡, 水力侵蚀, CSLE模型, 时空格局, 地理探测器, 影响因素

Abstract:

It is of great significance to ecological early warning and soil erosion prevention on mastering the spatial law and driving force of soil water erosion differentiation on the northern slope of Tianshan Mountains, which could provide theoretical basis and data support for comprehensive management of regional ecological environment on the northern slope of Tianshan Mountains. Taking the mountainous area in the middle of the northern slope of Tianshan Mountains as an example, the temporal and spatial pattern characteristics (area, intensity and geographical distribution) of soil hydraulic erosion in the study area from 2000 to 2018 were quantitatively analyzed by means of field investigation, geographic information system, mathematical statistics and geographic detectors, and the internal driving forces of rainfall, topography, soil and vegetation on soil hydraulic erosion intensity were explored by means of geographic detectors based on the Chinese soil loss equation (CSLE). The results showed that: (1) From 2000 to 2018, the intensity of soil hydraulic erosion in the middle of the northern slope of Tianshan Mountains was mainly slight erosion and mild erosion, accounting for 32.34%-40.87% and 33.36%-43.01% of the total area respectively. In recent 20 years, the area of slight and light erosion had a downward trend (-26.70, -77.47 km2·a-1), while the area of other erosion intensities had an upward trend (22.10-30.96 km2·a-1), and the overall soil hydraulic erosion intensity was in an increasing trend. (2) The overall soil erosion modulus was Urumqi > Changji City > Fukang City > Hutubi County > Manas County > Shawan County > Shihezi City. The spatial distribution of erosion intensity in the middle of the northern slope of the Tianshan Mountains was closely related to rainfall, topography, soil, and vegetation. The soil types were brown calcareous soil, grass felt soil, and chestnut soil. The area with vegetation coverage less than 15%, slope greater than 15° and rainfall in the range of 400-450 mm was a high-risk erosion area. (3) The magnitude of the differentiation was measured by the q value in the factor detector. The greater the q value, the stronger the explanatory power of the influencing factor to the spatial distribution of soil erosion, the rainfall (0.49) > soil type (0.17) > slope (0.11) > vegetation coverage (0.10). Different influencing factors obviously enhanced the spatial heterogeneity of soil erosion through interaction, and the coupling effect of vegetation coverage and rainfall factors made the q value increase greatly. It is of great significance to determine the key control areas of soil erosion for comprehensive soil erosion prevention and control.

Key words: northern slope of Tianshan Mountains, hydraulic erosion, CSLE model, temporal and spatial pattern, geographic detector, influencing factors