长江流域资源与环境 >> 2023, Vol. 32 >> Issue (12): 2568-2580.doi: 10.11870/cjlyzyyhj202312010

• 自然资源 • 上一篇    下一篇

2000~2020年西南地区蒸散发时空变化及驱动因素探测

王永锋1,靖娟利1,2*,刘海红3


  

  1. (1.桂林理工大学测绘地理信息学院,广西 桂林 541004;2.广西高校生态时空大数据感知服务重点实验室,
    广西 桂林 541004;3.青海省基础测绘院,青海 西宁 810000)
  • 出版日期:2023-12-20 发布日期:2023-12-25

Spatio-temporal Variation of Evapotranspiration and Its Driving Factors in Southwest China from 2000 to 2020

WANG Yong-feng1,JING Juan-li1,2, LIU Hai-hong3   

  1. (1.College of Geomatics and Geoinformation, Guilin University of Technology, Guilin 541004, China;2.Guangxi University Key Laboratory of Ecological Spatiotemporal Big Data Perception, Guilin 541004, China;3.Qinghai Basic Surveying and Mapping Institute, Xining 810000, China)
  • Online:2023-12-20 Published:2023-12-25

摘要: 深入研究西南地区蒸散发(ET)时空变化特征并探索其驱动因素,对该区水资源的科学分配及合理利用具有重要意义。基于MODIS16 ET数据、同期气象数据和DEM数据,采用趋势分析法、变异系数法和地理探测器方法,分析西南地区及各地貌分区2000~2020年地表蒸散发时空变化特征及波动性,探测ET空间分异的主要影响因素。结果表明:(1)西南地区及各地貌分区年际ET总体呈波动增加趋势,广西丘陵年际ET增加速率最快。(2)西南地区多年ET均值总体呈西南和东南部高、其他地区低的空间分布格局;年际ET总体以低-较低波动区域占主导,四川盆地年际ET波动性较其他地貌分区明显;不同地貌分区年际ET呈显著增加趋势的面积占比均大于50%,若尔盖高原年际ET呈显著增加趋势的面积占比最大。(3)因子探测结果表明,降水量是西南地区ET空间分异的主导因子,解释力为57.3%;云贵高原、若尔盖高原和横断山地ET空间分异的主导因子为气候因子,其余地貌分区主导因子为植被因子。双因子交互探测结果均表现为非线性增强或双因子增强,降水量∩NDVI对西南地区ET空间分异的解释力达到64.9%;若尔盖高原ET空间分异主要受气候因子之间或高程的交互作用,其他地貌分区主要受气候因子与高程或NDVI的交互作用。研究结果揭示了西南地区蒸散发时空变化特征及其驱动因素,能为该区水资源合理利用提供科学决策。


Abstract: It is of great significance to study the spatial and temporal variation characteristics of evapotranspiration (ET) and explore its driving factors for the scientific allocation and rational utilization of water resources in southwest China. Using MODIS16 ET data, contemporaneous meteorological data and DEM data, based on trend analysis, coefficient of variation method and geographic detector method, the spatial and temporal variation and volatility of ET and the driving factors were analysed in southwest China during 2000-2020. Results showed that: (1) The interannual ET showed an increasing trend with fluctuation in southwest China and each geomorphic regions, especially in Guangxi hilly region. (2) The annual average ET was relatively higher in southwest and southeast, and relatively lower in other regions in southwest China. The interannual ET was dominated by relatively low fluctuation regions. The fluctuation was obviously in Sichuan Basin. The ratio of area where ET showing a significant increasing trend were all greater than 50% in different geomorphic regions, and the ratio in Ruoergai Plateau was the largest. (3) Factor detection results showed that precipitation was the dominant factor that influenced the spatial heterogeneity of ET in southwest China, with an explanatory power of 57.3%. Climate was the dominant factor resulting in the spatial heterogeneity of ET in Yunnan-Guizhou Plateau, Ruoergai Plateau and Hengduan Mountain, while the dominant factor was vegetation in other geomorphic regions. The dual-factor interactive detection results showed nonlinear enhancement or dual-factor enhancement in the study area. The interaction between precipitation and NDVI explained 64.9% of ET’s spatial difference in southwest China. The interaction between climatic factors and elevation in the Ruoergai Plateau, and the interaction between climatic factors and elevation or NDVI in other geomorphic regions were the dominant factors that caused the spatial differentiation of ET. The study revealed the spatio-temporal variation characteristics of evapotranspiration and the corresponding influencing factor, which could provide scientific decisions for the rational use of water resources in southwest China.

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