IDEAS home Printed from https://ideas.repec.org/a/eee/agiwat/v213y2019icp580-593.html
   My bibliography  Save this article

Spatial distribution of soil moisture estimates using a multiple linear regression model and Korean geostationary satellite (COMS) data

Author

Listed:
  • Lee, Yonggwan
  • Jung, Chunggil
  • Kim, Seongjoon

Abstract

This study attempts to estimate the spatial distribution of the soil moisture (SM) in South Korea (99,260 km2) from January 2013 to May 2015 using a multiple linear regression (MLR) model with data from the Korean multipurpose geostationary Communication, Ocean and Meteorological Satellite (COMS), and land surface temperature (LST) data. The normalized distribution vegetation index (NDVI) from the moderate-resolution imaging spectroradiometer (MODIS) on board the Terra satellite was used to reflect the vegetation variations. Observed precipitation data measured by automatic weather stations (AWSs) operated by the Korea Meteorological Administration (KMA) were collected, and SM data were collected from 38 stations operated by various institutions. The regression coefficients of the MLR model were estimated seasonally considering five days of preceding precipitation. The p-values of all regression coefficients were below 0.05, and all coefficients of determination (R2) ranged from 0.17 to 0.63. Specifically, the R2 of loam in the summer was the highest at 0.63, and most of the R2 values were 0.4 or higher. The results of the SM regression showed that the overall R2 was higher than 0.4 and that the root mean square error (RMSE) was less than 5% at all but a few stations. A time series analysis of the simulated SM revealed that the observed SM data ranged from 0 to 20% for sand, 10 to 30% for loam, 20 to 40% for clay and 30 to 50% for silt. The simulated SM followed the volatility of the observed data in most of the soils. The spatial distribution of the simulated SM showed the same trends with the observed data on the monthly spatial precipitation map. Consequently, the estimated map of the soil moisture index (SMI) can be used to better understand the severity of drought and the variability in the SM.

Suggested Citation

  • Lee, Yonggwan & Jung, Chunggil & Kim, Seongjoon, 2019. "Spatial distribution of soil moisture estimates using a multiple linear regression model and Korean geostationary satellite (COMS) data," Agricultural Water Management, Elsevier, vol. 213(C), pages 580-593.
    • Handle: RePEc:eee:agiwat:v:213:y:2019:i:c:p:580-593
    DOI: 10.1016/j.agwat.2018.09.004
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378377418313568
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.agwat.2018.09.004?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Nam, Won-Ho & Hong, Eun-Mi & Choi, Jin-Yong, 2015. "Has climate change already affected the spatial distribution and temporal trends of reference evapotranspiration in South Korea?," Agricultural Water Management, Elsevier, vol. 150(C), pages 129-138.
    2. Baik, Jongjin & Choi, Minha, 2015. "Evaluation of geostationary satellite (COMS) based Priestley–Taylor evapotranspiration," Agricultural Water Management, Elsevier, vol. 159(C), pages 77-91.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Wan, Wei & Liu, Zhong & Li, Kejiang & Wang, Guiman & Wu, Hanqing & Wang, Qingyun, 2021. "Drought monitoring of the maize planting areas in Northeast and North China Plain," Agricultural Water Management, Elsevier, vol. 245(C).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Hu, Xuhua & Chen, Mengting & Liu, Dong & Li, Dan & Jin, Li & Liu, Shaohui & Cui, Yuanlai & Dong, Bin & Khan, Shahbaz & Luo, Yufeng, 2021. "Reference evapotranspiration change in Heilongjiang Province, China from 1951 to 2018: The role of climate change and rice area expansion," Agricultural Water Management, Elsevier, vol. 253(C).
    2. Zihan Liu & Dong Jing & Yu Han & Jingxin Yu & Tiangang Lu & Lili Zhangzhong, 2022. "Spatiotemporal Distribution Characteristics and Influencing Factors Analysis of Reference Evapotranspiration in Beijing–Tianjin–Hebei Region from 1990 to 2019 under Climate Change," Sustainability, MDPI, vol. 14(10), pages 1-22, May.
    3. Nam, Won-Ho & Hayes, Michael J. & Svoboda, Mark D. & Tadesse, Tsegaye & Wilhite, Donald A., 2015. "Drought hazard assessment in the context of climate change for South Korea," Agricultural Water Management, Elsevier, vol. 160(C), pages 106-117.
    4. Hong, Eun-Mi & Nam, Won-Ho & Choi, Jin-Yong & Pachepsky, Yakov A., 2016. "Projected irrigation requirements for upland crops using soil moisture model under climate change in South Korea," Agricultural Water Management, Elsevier, vol. 165(C), pages 163-180.
    5. Baik, Jongjin & Choi, Minha, 2015. "Evaluation of geostationary satellite (COMS) based Priestley–Taylor evapotranspiration," Agricultural Water Management, Elsevier, vol. 159(C), pages 77-91.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:agiwat:v:213:y:2019:i:c:p:580-593. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/agwat .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.