Remote Sensing Monitoring Method for Groundwater Level on Aeolian Desertification Area

被引:5
|
作者
Chen Siming [1 ,2 ]
Aidi, Huo [1 ,2 ]
Wenke, Guan [3 ]
机构
[1] Changan Univ, Minist Educ, Key Lab Subsurface Hydrol & Ecol Effects Arid Reg, Xian, Shaanxi, Peoples R China
[2] Changan Univ, Sch Water & Environm, Xian 710054, Shaanxi, Peoples R China
[3] Xinjiang Acad Forestry, Afforestat Desert Control Res Inst, Urumqi, Peoples R China
基金
中国国家自然科学基金; 国家重点研发计划;
关键词
Aeolian areas; MODIS image data; groundwater level; monitoring Model; Xinjiang; WATER; MODEL;
D O I
10.3103/S1063455X20060090
中图分类号
O69 [应用化学];
学科分类号
081704 ;
摘要
Groundwater is one of the most important natural resources. Regional groundwater depth is an important parameter for understanding groundwater resources and maintaining sustainable development of water resources and environment. The middle reaches of the Tarim River in Xinjiang are the most primitive and well-preserved place in the world, which provides valuable resources in studying the response mechanism of surface vegetation to the groundwater level. The ecological environment of Tarim River Basin has been deteriorating, and Populuseuphratica forest has died, which is directly related to the decrease of water inflow and groundwater level around the Tarim River. To obtain the spatial distribution of the groundwater level, this study uses the MODIS satellite remote sensing image data and the remote sensing-mathematical-model of a fusion science research methods, based on the field investigation of the groundwater level, soil moisture, and other supporting information on Aeolian desertification area in the middle reaches of Tarim River in Xinjiang. Through the experimental equation of the soil moisture and groundwater level, a simple and effective remote sensing method was proposed. This method is used to evaluate the spatial distribution of groundwater level based on the MODIS image data when there is capillary supply in the soil. This model was field-proven on the desertification area in the middle reaches of Tarim River. The results indicate that the correlation coefficient between the inversion of groundwater depth and the measured groundwater level is 0.89, which are realistic with small errors. So it is feasible to monitor and assess the spatial distribution of groundwater table depth in desertification areas with a large groundwater depth of 6 m or less. This study is helpful to provide critical area for the ecological environment monitoring and restoration, and ultimately serve the sustainable development of water and environment.
引用
收藏
页码:522 / 529
页数:8
相关论文
共 50 条
  • [31] Remote sensing monitoring and impact assessment of mining disturbance in mining area with high undergroundwater level
    Xiao W.
    Chen W.
    He T.
    Zhao Y.
    Hu Z.
    Meitan Xuebao/Journal of the China Coal Society, 2022, 47 (02): : 922 - 933
  • [32] Remote sensing of desertification and study of temporal variability of aeolian deposits in parts of the Arabian Desert for sustainable development in an arid environment
    Rajendran, Sankaran
    Al Kuwari, Hamad Al Saad
    Sadooni, Fadhil N.
    Nasir, Sobhi
    Govil, Himanshu
    Ghrefat, Habes
    ENVIRONMENTAL RESEARCH, 2023, 232
  • [33] Monitoring the severity of degradation and desertification by remote sensing (case study: Hamoun International Wetland)
    Zolfaghari, Farhad
    Azarnivand, Hossein
    Khosravi, Hasan
    Zehtabian, Gholamreza
    Sigaroudi, Shahram Khalighi
    FRONTIERS IN ENVIRONMENTAL SCIENCE, 2022, 10
  • [34] Vegetation monitoring in shendong mining area by remote sensing
    Liu, Ying
    Yue, Hui
    International Journal of Signal Processing, Image Processing and Pattern Recognition, 2015, 8 (06) : 135 - 144
  • [35] A novel integrated approach for monitoring drought stress in an aeolian desertification area using Vegetation Drought Status Index
    Zhao, Zhixin
    Liu, Qi
    Huo, Aidi
    Cheng, Yuxiang
    Guan, Wenke
    EL-Sayed Abuarab, Mohamed
    Mokhtar, Ali
    Elbeltagi, Ahmed
    WATER SUPPLY, 2023, 23 (02) : 738 - 748
  • [36] Impact of mining industries on the groundwater level fluctuation in Singrauli coalfield area by using remote sensing and GIS, India
    Sonkar, Ashwani Kumar
    Varshney, Ramita
    Ahmed, Shah Izhar
    Vishwakarma, Ashish Kumar
    Jamal, Aarif
    ENVIRONMENTAL QUALITY MANAGEMENT, 2023, 33 (01) : 311 - 325
  • [37] AN AUTOMATIC METHOD FOR FLOODED AREA EXTRACTION BASED ON LEVEL SET METHOD USING REMOTE SENSING DATA
    Liu, Yang
    Dai, Qin
    Liu, Jianbo
    2014 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS), 2014, : 2142 - 2145
  • [38] The use of remote sensing for desertification studies: A review
    Rivera-Marin, Daniela
    Dash, Jadunandan
    Ogutu, Booker
    JOURNAL OF ARID ENVIRONMENTS, 2022, 206
  • [39] REMOTE SENSING OF AEOLIAN DUST PRODUCTION AND DISTRIBUTION
    White, Kevin
    DESERTIFICATION AND RISK ANALYSIS USING HIGH AND MEDIUM RESOLUTION SATELLITE DATA, 2009, : 59 - 69