Influence of Different Sample Well Densities and Interpolation Methods on the Spatial Distribution of Groundwater Quality

被引：0
|
作者：
Sun, Feng [1 ]
Lu, Hongjian [1 ]
Mao, Meng [2 ]
Guo, Rui [1 ]
Ruan, Qiongyao [1 ]
机构：
[1] Information Center, Hydrology and Water Resources Monitoring and Forecasting Center, The Ministry of Water Resources of the People’s Republic of China, Beijing,100053, China
[2] College of Land Science and Technology, China Agricultural University, Key Laboratory of Arable Land Conservation (North China), MARA, Technology Innovation Center of Land Engineering, MNR, Beijing,100193, China
来源：
Yingyong Jichu yu Gongcheng Kexue Xuebao/Journal of Basic Science and Engineering | / 32卷 / 04期
关键词：
Base function - Groundwater quality assessment - Interpolation accuracy - Interpolation method - Inverse distance weighted - Kriging - Radial base function - Radial basis - Sample well density - Spatial interpolation;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
37
引用
收藏
页码：1067 / 1079
相关论文
共 50 条
  • [1] An indoor environmental quality distribution map based on spatial interpolation methods
    Choi, Heeju
    Kim, Hakpyeong
    Yeom, Seungkeun
    Hong, Taehoon
    Jeong, Kwangbok
    Lee, Jaewook
    [J]. BUILDING AND ENVIRONMENT, 2022, 213
  • [2] Comparison Quality of Interpolation Methods to Estimate Spatial Distribution of Soil Moisture Content
    Tuncay, Tulay
    [J]. COMMUNICATIONS IN SOIL SCIENCE AND PLANT ANALYSIS, 2021, 52 (04) : 353 - 374
  • [3] Hydrogeochemical characteristics and spatial distribution of groundwater quality in Arusha well fields, Northern Tanzania
    Nyamboge Chacha
    Karoli N. Njau
    George V. Lugomela
    Alfred N. N. Muzuka
    [J]. Applied Water Science, 2018, 8
  • [4] Hydrogeochemical characteristics and spatial distribution of groundwater quality in Arusha well fields, Northern Tanzania
    Chacha, Nyamboge
    Njau, Karoli N.
    Lugomela, George V.
    Muzuka, Alfred N. N.
    [J]. APPLIED WATER SCIENCE, 2018, 8 (04)
  • [5] Influence of spatial structure on accuracy of interpolation methods
    Kravchenko, AN
    [J]. SOIL SCIENCE SOCIETY OF AMERICA JOURNAL, 2003, 67 (05) : 1564 - 1571
  • [6] Use of neural networks and spatial interpolation to predict groundwater quality
    Sunayana
    Kalawapudi, Komal
    Dube, Ojaswikrishna
    Sharma, Renuka
    [J]. ENVIRONMENT DEVELOPMENT AND SUSTAINABILITY, 2020, 22 (04) : 2801 - 2816
  • [7] Use of neural networks and spatial interpolation to predict groundwater quality
    Komal Sunayana
    Ojaswikrishna Kalawapudi
    Renuka Dube
    [J]. Environment, Development and Sustainability, 2020, 22 : 2801 - 2816
  • [8] Dataset characteristics influence the performance of different interpolation methods for soil salinity spatial mapping
    Mahmood Fazeli Sangani
    Davood Namdar Khojasteh
    Gary Owens
    [J]. Environmental Monitoring and Assessment, 2019, 191
  • [9] Dataset characteristics influence the performance of different interpolation methods for soil salinity spatial mapping
    Sangani, Mahmood Fazeli
    Khojasteh, Davood Namdar
    Owens, Gary
    [J]. ENVIRONMENTAL MONITORING AND ASSESSMENT, 2019, 191 (11)
  • [10] Spatial interpolation methods and geostatistics for mapping groundwater contamination in a coastal area
    Vetrimurugan Elumalai
    K. Brindha
    Bongani Sithole
    Elango Lakshmanan
    [J]. Environmental Science and Pollution Research, 2017, 24 : 11601 - 11617
12345