Suggestion of Classification Method for Agricultural Drought Using Groundwater Level Change

Chan-Duck Jeong; Byung-Sun Lee; Gyu-Sang Lee; Jun-Kyum Kim; Sung-Ho Song

doi:doi:10.11648/j.wros.20221101.12

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Suggestion of Classification Method for Agricultural Drought Using Groundwater Level Change

Chan-Duck Jeong, Byung-Sun Lee, Gyu-Sang Lee, Jun-Kyum Kim, Sung-Ho Song

Published in Journal of Water Resources and Ocean Science (Volume 11, Issue 1)

Received: 17 February 2022 Accepted: 14 March 2022 Published: 23 March 2022

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Abstract

Since weather factors such as precipitation and temperature etc. show repeated patterns every year, it can be said that future changes can be predicted by analyzing past weather data. Therefore, when a drought occurs, the groundwater level is also lowered, so it can be seen that a change in the groundwater level can represent a drought. Like precipitation, groundwater level changes also have a high correlation with drought, so many researchers use SGI (standardized groundwater level index) to which the SPI (standardized precipitation index) method is applied to evaluate the severity of drought and predict trends. However, these approaches have the limitations to indicate the real groundwater system because the drought grades for the entire area are defined with the observation data of a single monitoring well without surrounding influences. When analyzing groundwater level fluctuations to understand the correlation with drought, it is necessary to calculate and apply the actual groundwater level that reflects groundwater use interference. Therefore, in this study, based on the long-term groundwater level data at 162 monitoring well installed before 2015 in Korea, the characteristics of groundwater level changes were analyzed and compared with the period of agricultural drought over the past five years. From the results, it can be confirmed that agricultural drought in regions is classified using the percentile of the SPI method by conducting a frequency analysis that the current groundwater level increase or decrease compared to the past average groundwater level.

Published in	Journal of Water Resources and Ocean Science (Volume 11, Issue 1)
DOI	10.11648/j.wros.20221101.12
Page(s)	14-29
Creative Commons	This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.
Copyright	Copyright © The Author(s), 2022. Published by Science Publishing Group

Keywords

Groundwater Level, SPI, SGI, Agricultural Drought

References

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[2]	Edwards, D. C., and T. B. McKee, (1997). Characteristics of 20th century drought in the United States at multiple time scales. Climatology Report No. 97-2, Colorado State Univ., Ft. Collins, CO.
[3]	Hoque, M. A., Hoque, M. M and Ahmed, K., 2007, “Declining Ground water Level and Aquifer Dewatering in Dhaka Metropolitan Area, Bangladesh: Causes and Quantification”, Hydrogeology Journal, Vol. 15, pp. 1523-1534.
[4]	Hyung Jin Shin, Hae Do Kim, Jae Nam Lee, Dae Eui Kim, Mun Sung Kang, 2019, Sensitivity of Precipitation and Storage Capacity Caused by Climate Changes in Agricultural Reservoir, Korea Water Resources Association, Academic presentation materials.
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[6]	Kim, G. B., Yun, H. H. and Kim, D. H., 2006, Relationship Between Standardized Precipitation Index and Groundwater Levels: A Proposal for Establishment of Drought Index Wells, J. Soil and Groundwater Environment, 11 (3), pp. 31-42.
[7]	Kim, H. J., Lee, J. Y., Jeon, W. H., and Lee, K. K., 2016, Groundwater environment in Seoul, Republic of Korea. In: Groundwater Environment in Asian Cities, (S. Shrestha, V. P. Pandey, B. R. Shivakoti, & S. Thatikonda, eds.). Butterworth Heinemann, Oxford, UK. pp. 413–449.
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[9]	Lee J. J., Kang, S. U., Jeong, J. H., Chun, G. I., 2018, Development of groundwater level monitoring and forecasting technique for drought analysis (I); Groundwater drought monitoring using standardized groundwater level index (SGI), J. Korea Water Resour. Assoc. Vol. 51 (11), pp. 1011-1020.
[10]	Lee, H. G., Jeon, W. H., Yun, S. W., Kwon, K. D., and Lee, J. Y., 2017, Comparative study of variation of groundwater and dam storage from 1996-2015 in Korea, Journal of the Geological Society of Korea, pp. 715-726.
[11]	Lee, J. J., Kang, S. U., Kim, T. H., and Chun, G. I., 2018, Development of groundwater level monitoring and forecasting technique for drought analysis (II) - Groundwater drought forecasting Using SPI, SGI and ANN, Journal of Korea Water Resources Association, v. 51 n. 11, pp. 1021-1029.
[12]	Lee, J. N., Shin, H. J., Lee, J. J, and Kang, M. S., 2019, Utilization evaluation of water level data for agricultural reservoir flood analysis, Korea Water Resources Association academic presentation material, p. 393.
[13]	McKee, T. B., N. J. Doesken, and J. Kleist, 1993, The relationship of drought frequency and duration of time scales. Eighth Conference on Applied Climatology, American Meteorological Society, Jan. 17-23, Anaheim CA, pp. 179-186.
[14]	Song, S. H., 2018, Assessment of drought effects on groundwater system in rural area using Standardized Groundwater level Index (SGI), J. Soil Groundwater Environ. Vol. 23 (3), pp. 1-9.
[15]	Song, S. H., Ahn, J. G., Lee, B. S., and Goo, M. H., 2017, Development of agricultural drought evaluation technology based on ICT-based real-time analysis of groundwater level, Korea Rural Research Institute.
[16]	Song, S. H., Lee, G. S., Jeong, C. D., and Myoung, W. H., 2019, Estimation of potential water supply for agricultural water demand based on time-series groundwater level data in Jeju Island, Korea Rural Research Institute, pp. 64-67.
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APA Style

Chan-Duck Jeong, Byung-Sun Lee, Gyu-Sang Lee, Jun-Kyum Kim, Sung-Ho Song. (2022). Suggestion of Classification Method for Agricultural Drought Using Groundwater Level Change. Journal of Water Resources and Ocean Science, 11(1), 14-29. https://doi.org/10.11648/j.wros.20221101.12

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ACS Style

Chan-Duck Jeong; Byung-Sun Lee; Gyu-Sang Lee; Jun-Kyum Kim; Sung-Ho Song. Suggestion of Classification Method for Agricultural Drought Using Groundwater Level Change. J. Water Resour. Ocean Sci. 2022, 11(1), 14-29. doi: 10.11648/j.wros.20221101.12

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AMA Style

Chan-Duck Jeong, Byung-Sun Lee, Gyu-Sang Lee, Jun-Kyum Kim, Sung-Ho Song. Suggestion of Classification Method for Agricultural Drought Using Groundwater Level Change. J Water Resour Ocean Sci. 2022;11(1):14-29. doi: 10.11648/j.wros.20221101.12

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@article{10.11648/j.wros.20221101.12,
  author = {Chan-Duck Jeong and Byung-Sun Lee and Gyu-Sang Lee and Jun-Kyum Kim and Sung-Ho Song},
  title = {Suggestion of Classification Method for Agricultural Drought Using Groundwater Level Change},
  journal = {Journal of Water Resources and Ocean Science},
  volume = {11},
  number = {1},
  pages = {14-29},
  doi = {10.11648/j.wros.20221101.12},
  url = {https://doi.org/10.11648/j.wros.20221101.12},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.wros.20221101.12},
  abstract = {Since weather factors such as precipitation and temperature etc. show repeated patterns every year, it can be said that future changes can be predicted by analyzing past weather data. Therefore, when a drought occurs, the groundwater level is also lowered, so it can be seen that a change in the groundwater level can represent a drought. Like precipitation, groundwater level changes also have a high correlation with drought, so many researchers use SGI (standardized groundwater level index) to which the SPI (standardized precipitation index) method is applied to evaluate the severity of drought and predict trends. However, these approaches have the limitations to indicate the real groundwater system because the drought grades for the entire area are defined with the observation data of a single monitoring well without surrounding influences. When analyzing groundwater level fluctuations to understand the correlation with drought, it is necessary to calculate and apply the actual groundwater level that reflects groundwater use interference. Therefore, in this study, based on the long-term groundwater level data at 162 monitoring well installed before 2015 in Korea, the characteristics of groundwater level changes were analyzed and compared with the period of agricultural drought over the past five years. From the results, it can be confirmed that agricultural drought in regions is classified using the percentile of the SPI method by conducting a frequency analysis that the current groundwater level increase or decrease compared to the past average groundwater level.},
 year = {2022}
}

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TY  - JOUR
T1  - Suggestion of Classification Method for Agricultural Drought Using Groundwater Level Change
AU  - Chan-Duck Jeong
AU  - Byung-Sun Lee
AU  - Gyu-Sang Lee
AU  - Jun-Kyum Kim
AU  - Sung-Ho Song
Y1  - 2022/03/23
PY  - 2022
N1  - https://doi.org/10.11648/j.wros.20221101.12
DO  - 10.11648/j.wros.20221101.12
T2  - Journal of Water Resources and Ocean Science
JF  - Journal of Water Resources and Ocean Science
JO  - Journal of Water Resources and Ocean Science
SP  - 14
EP  - 29
PB  - Science Publishing Group
SN  - 2328-7993
UR  - https://doi.org/10.11648/j.wros.20221101.12
AB  - Since weather factors such as precipitation and temperature etc. show repeated patterns every year, it can be said that future changes can be predicted by analyzing past weather data. Therefore, when a drought occurs, the groundwater level is also lowered, so it can be seen that a change in the groundwater level can represent a drought. Like precipitation, groundwater level changes also have a high correlation with drought, so many researchers use SGI (standardized groundwater level index) to which the SPI (standardized precipitation index) method is applied to evaluate the severity of drought and predict trends. However, these approaches have the limitations to indicate the real groundwater system because the drought grades for the entire area are defined with the observation data of a single monitoring well without surrounding influences. When analyzing groundwater level fluctuations to understand the correlation with drought, it is necessary to calculate and apply the actual groundwater level that reflects groundwater use interference. Therefore, in this study, based on the long-term groundwater level data at 162 monitoring well installed before 2015 in Korea, the characteristics of groundwater level changes were analyzed and compared with the period of agricultural drought over the past five years. From the results, it can be confirmed that agricultural drought in regions is classified using the percentile of the SPI method by conducting a frequency analysis that the current groundwater level increase or decrease compared to the past average groundwater level.
VL  - 11
IS  - 1
ER  -

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Author Information

Chan-Duck Jeong

Future Rural & Fishing Village Research Lab, Rural Research Institute, Korea Rural Community Corporation, Jeollanamdo Naju City, Korea
Byung-Sun Lee

Future Rural & Fishing Village Research Lab, Rural Research Institute, Korea Rural Community Corporation, Jeollanamdo Naju City, Korea
Gyu-Sang Lee

Future Rural & Fishing Village Research Lab, Rural Research Institute, Korea Rural Community Corporation, Jeollanamdo Naju City, Korea
Jun-Kyum Kim

Future Rural & Fishing Village Research Lab, Rural Research Institute, Korea Rural Community Corporation, Jeollanamdo Naju City, Korea
Sung-Ho Song

Future Rural & Fishing Village Research Lab, Rural Research Institute, Korea Rural Community Corporation, Jeollanamdo Naju City, Korea

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APA Style

Chan-Duck Jeong, Byung-Sun Lee, Gyu-Sang Lee, Jun-Kyum Kim, Sung-Ho Song. (2022). Suggestion of Classification Method for Agricultural Drought Using Groundwater Level Change. Journal of Water Resources and Ocean Science, 11(1), 14-29. https://doi.org/10.11648/j.wros.20221101.12

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ACS Style

Chan-Duck Jeong; Byung-Sun Lee; Gyu-Sang Lee; Jun-Kyum Kim; Sung-Ho Song. Suggestion of Classification Method for Agricultural Drought Using Groundwater Level Change. J. Water Resour. Ocean Sci. 2022, 11(1), 14-29. doi: 10.11648/j.wros.20221101.12

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AMA Style

Chan-Duck Jeong, Byung-Sun Lee, Gyu-Sang Lee, Jun-Kyum Kim, Sung-Ho Song. Suggestion of Classification Method for Agricultural Drought Using Groundwater Level Change. J Water Resour Ocean Sci. 2022;11(1):14-29. doi: 10.11648/j.wros.20221101.12

Copy | Download

@article{10.11648/j.wros.20221101.12,
  author = {Chan-Duck Jeong and Byung-Sun Lee and Gyu-Sang Lee and Jun-Kyum Kim and Sung-Ho Song},
  title = {Suggestion of Classification Method for Agricultural Drought Using Groundwater Level Change},
  journal = {Journal of Water Resources and Ocean Science},
  volume = {11},
  number = {1},
  pages = {14-29},
  doi = {10.11648/j.wros.20221101.12},
  url = {https://doi.org/10.11648/j.wros.20221101.12},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.wros.20221101.12},
  abstract = {Since weather factors such as precipitation and temperature etc. show repeated patterns every year, it can be said that future changes can be predicted by analyzing past weather data. Therefore, when a drought occurs, the groundwater level is also lowered, so it can be seen that a change in the groundwater level can represent a drought. Like precipitation, groundwater level changes also have a high correlation with drought, so many researchers use SGI (standardized groundwater level index) to which the SPI (standardized precipitation index) method is applied to evaluate the severity of drought and predict trends. However, these approaches have the limitations to indicate the real groundwater system because the drought grades for the entire area are defined with the observation data of a single monitoring well without surrounding influences. When analyzing groundwater level fluctuations to understand the correlation with drought, it is necessary to calculate and apply the actual groundwater level that reflects groundwater use interference. Therefore, in this study, based on the long-term groundwater level data at 162 monitoring well installed before 2015 in Korea, the characteristics of groundwater level changes were analyzed and compared with the period of agricultural drought over the past five years. From the results, it can be confirmed that agricultural drought in regions is classified using the percentile of the SPI method by conducting a frequency analysis that the current groundwater level increase or decrease compared to the past average groundwater level.},
 year = {2022}
}

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TY  - JOUR
T1  - Suggestion of Classification Method for Agricultural Drought Using Groundwater Level Change
AU  - Chan-Duck Jeong
AU  - Byung-Sun Lee
AU  - Gyu-Sang Lee
AU  - Jun-Kyum Kim
AU  - Sung-Ho Song
Y1  - 2022/03/23
PY  - 2022
N1  - https://doi.org/10.11648/j.wros.20221101.12
DO  - 10.11648/j.wros.20221101.12
T2  - Journal of Water Resources and Ocean Science
JF  - Journal of Water Resources and Ocean Science
JO  - Journal of Water Resources and Ocean Science
SP  - 14
EP  - 29
PB  - Science Publishing Group
SN  - 2328-7993
UR  - https://doi.org/10.11648/j.wros.20221101.12
AB  - Since weather factors such as precipitation and temperature etc. show repeated patterns every year, it can be said that future changes can be predicted by analyzing past weather data. Therefore, when a drought occurs, the groundwater level is also lowered, so it can be seen that a change in the groundwater level can represent a drought. Like precipitation, groundwater level changes also have a high correlation with drought, so many researchers use SGI (standardized groundwater level index) to which the SPI (standardized precipitation index) method is applied to evaluate the severity of drought and predict trends. However, these approaches have the limitations to indicate the real groundwater system because the drought grades for the entire area are defined with the observation data of a single monitoring well without surrounding influences. When analyzing groundwater level fluctuations to understand the correlation with drought, it is necessary to calculate and apply the actual groundwater level that reflects groundwater use interference. Therefore, in this study, based on the long-term groundwater level data at 162 monitoring well installed before 2015 in Korea, the characteristics of groundwater level changes were analyzed and compared with the period of agricultural drought over the past five years. From the results, it can be confirmed that agricultural drought in regions is classified using the percentile of the SPI method by conducting a frequency analysis that the current groundwater level increase or decrease compared to the past average groundwater level.
VL  - 11
IS  - 1
ER  -

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