Journal of The Korean Society of Agricultural Engineers (한국농공학회논문집)

The Korean Society of Agricultural Engineers (한국농공학회)
권호 표지
DOI QR코드

DOI QR Code

Evaluation and Comparison of Meteorological Drought Index using Multi-satellite Based Precipitation Products in East Asia

다중 위성영상 기반 강우자료를 활용한 동아시아 지역의 기상학적 가뭄지수 비교 분석

  • Mun, Young-Sik (Department of Bioresources and Rural Systems Engineering, Hankyong National University) ;
  • Nam, Won-Ho (Department of Bioresources and Rural Systems Engineering, Institute of Agricultural Environmental Science, National Agricultural Water Research Center, Hankyong National University) ;
  • Kim, Taegon (Department of Bioproducts and Biosystems Engineering, University of Minnesota) ;
  • Hong, Eun-Mi (School of Natural Resources and Environmental Science, Kangwon National University) ;
  • Sur, Chanyang (Earth System Science Interdisciplinary Center, University of Maryland)
  • Received : 2019.11.04
  • Accepted : 2019.12.19
  • Published : 2020.01.31
Download PDF
⟨ Previous Next ⟩

Abstract

East Asia, which includes China, Japan, Korea, and Mongolia, is highly impacted by hydroclimate extremes such drought, flood, and typhoon recent year. In 2017, more than 18.5 million hectares of crops have been damaged in China, and Korea has suffered economic losses as a result of severe drought. Satellite-derived rainfall products are becoming more accurate as space and time resolution become increasingly higher, and provide an alternative means of estimating ground-based rainfall. In this study, we verified the availability of rainfall products by comparing widely used satellite images such as Climate Hazards Groups InfraRed Precipitation with Station (CHIRPS), Global Precipitation Climatology Centre (GPCC), and Precipitation Estimation From Remotely Sensed Information Using Artificial Neural Networks-Climate Data Record (PERSIANN-CDR) with ground stations in East Asia. Also, the satellite-based rainfall products were used to calculate the Standardized Precipitation Index (SPI). The temporal resolution is based on monthly images and compared with the past 30 years data from 1989 to 2018. The comparison between rainfall data based on each satellite image products and the data from weather station-based weather data was shown by the coefficient of determination and showed more than 0.9. Each satellite-based rainfall data was used for each grid and applied to East Asia and South Korea. As a result of SPI analysis, the RMSE values of CHIRPS were 0.57, 0.53 and 0.47, and the MAE values of 0.46, 0.43 and 0.37 were better than other satellite products. This satellite-derived rainfall estimates offers important advantages in terms of spatial coverage, timeliness and cost efficiency compared to analysis for drought assessment with ground stations.

Keywords

References

  1. Alijanian, M., G. R. Rakhshandehroo, A. Mishra, and M. Dehghani, 2019. Evaluation of remotely sensed precipitation estimates using PERSIANN-CDR and MSWEP for spatio-temporal drought assessment over Iran. Journal of Hydrology 579: 124189. doi:10.1016/j.jhydrol.2019.124189.
  2. Arkin, P. A., and P. Xie, 1994. The global precipitation climatology project: First algorithm intercomparison project. The Bulletin of the American Meteorological Society 75(3): 401-419. doi:10.1175/1520-0477(1994)075<0401:TGPCPF>2.0.CO;2.
  3. Diem, J. E., J. Hartter, S. J. Ryan, and M. W. Palace, 2014. Validation of satellite rainfall products for western Uganda. Journal of Hydrometeorogy 15(5): 2030-2038. doi:10.1175/JHM-D-13-0193.1.
  4. Edwards, D. C., and T. B. McKee, 1997. Characteristics of 20th century drought in the United States at multiple time scales. Department of Atmospheric Science, Atmospheric Science Paper No. 634, Climatology Report No. 97-2, Colorado State University.
  5. Funk, C., and J. Michaelsen, 2004. A simplified diagnostic model of orographic rainfall for enhancing satellite-based rainfall estimates in data poor regions. Journal of Applied Meteorology 43(10): 1366-1378. doi:10.1175/JAM2138.1.
  6. Funk, C. C., P. J. Peterson, M. F. Landsfeld, D. H. Pedreros, J. P. Verdin, J. D. Rowland, B. E. Romero, G. J. Husak, J. C. Michaelsen, and A. P. Verdin, 2014. A quasi-global precipitation time series for drought monitoring. U.S. Geological Survey Data Series 832. doi:10.3133/ds832.
  7. Hayes, M. J., M. D. Svoboda, D. A. Wilhite, and O. V. Vanyarkho, 1999. Monitoring the 1996 drought using the standardized precipitation index. Bulletin of the American Meteorological Society 80: 429-438. doi:10.1175/1520-0477(1999)080<0429:MTDUTS>2.0.CO;2.
  8. Hayes, M. J., O. V. Wilhelmi, and C. L. Knutson, 2004. Reducing drought risk: Bridging theory and practice. Natural Hazards Review 5(2): 106-113. doi:10.1061/(ASCE)1527-6988(2004)5:2(106).
  9. Hayes, M., M. Svoboda, N. Wall, and M. Widhalm, 2011. The lincoln declaration on drought indices: Universal meteorological drought index recommended. Bulletin of the American Meteorological Society 92: 485-488. doi:10.1175/2010BAMS3103.1.
  10. Jang, S., J. Rhee, S. Yoon, T. Lee, and K. Park, 2017. Evaluation of GPM IMERG applicability using SPI based satellite precipitation. Journal of the Korean Society of Agriculture Engineers 59(3): 29-39 (in Korean). doi:10.5389/KSAE.2017.59.3.029.
  11. Jiao, W., L. Zhang, Q. Chang, D. Fu, Y. Cen, and Q. Tong, 2016. Evaluating an enhanced vegetation condition index (VCI) based on VIUPD for drought monitoring in the continental United States. Remote Sensing 8: 224. doi:10.3390/rs8030224.
  12. Kim, H., J. Park, J. Yoo, and T. W. Kim, 2015. Assessment of drought hazard, vulnerability, and risk: A case study for administrative districts in South Korea. Journal of Hydro-environmental Research 9(1): 28-35. doi:10.1016/j.jher.2013.07.003.
  13. Korea Meteorological Administration (KMA), 2012. Development of hydro-meteorological early warning system for response to climate change. Korea Meteorological Administration, Seoul, Korea (in Korean).
  14. Kwak, J. W., S. D. Lee, Y. S. Kim, and H. S. Kim, 2013. Return period estimation of droughts using drought variables from standardized precipitation index. Journal of Korea Water Resources Association 46(8): 795-805 (in Korean). doi:10.3741/JKWRA.2013.46.8.795.
  15. Lee, H. J., W. H. Nam, D. H. Yoon, E. M. Hong, D. E. Kim, M. D. Svoboda, T. Tadesse, and B. D. Wardlow, 2019. Satellite-based evaporative stress index (ESI) as an indicator of agriculture drought in North Korea. Journal of the Korean Society of Agriculture Engineers 61(3): 1-14 (in Korean). doi:10.5389/KSAE.2019.61.3.001.
  16. Lee, J., and E. H. Lee, 2018. Evaluation of daily precipitation estimate from Integrated MultisatellitE Retrievals for GPM (IMERG) data over South Korea and East Asia. Atmosphere, Korean Meteorological Society 28(3): 273-289 (in Korean). doi:10.14191/Atmos.2018.28.3.273.
  17. McKee, T. B., N. J. Doesken, and J. Kliest, 1993. The relationship of drought frequency and duration to time scales. In Proceedings of the 8th Conference of Applied Climatology, 17-22 January, Anaheim, CA. American Meteorological Society, Boston, MA. 179-184.
  18. Mun, Y. S., W. H. Nam, M. G. Jeon, T. Kim, E. M. Hong, M. J. Hayes, and T. Tadesse, 2019. Application of meteorological drought index using Climate Hazards Group InfraRed Precipitation wigh Station (CHIRPS) based on global satellite-assisted precipitation products in Korea. Journal of the Korean Society of Agriculture Engineers 61(2): 1-11 (in Korean). doi:10.5389/KSAE.2019.61.2.001.
  19. Nam, W. H., M. J. Hayes, M. D. Svoboda, T. Tadesse, and D. A. Wilhite, 2015. Drought hazard assessment in the context of climate change for South Korea. Agricultural Water Management 160: 106-117. doi:10.1016/j.agwat.2015.06.029.
  20. Nam, W. H., E. M. Hong, J. Y. Choi, T. Kim, M. J. Hayes, and M. D. Svoboda, 2017. Assessment of the extreme 2014-2015 drought events in North Korea using weekly standardized precipitation evapotranspiration index (SPEI). Journal of the Korean Society of Agriculture Engineers 59(4): 65-74 (in Korean). doi:10.5389/KSAE.2017.59.4.065.
  21. Nam, W. H., T. Tadesse, B. D. Wardlow, M. J. Hayes, M. D. Svoboda, E. M. Hong, Y. A. Pachepsky, and M. W. Jang, 2018. Developing the vegetation drought response index for South Korea (VegDRI-SKorea) to assess the vegetation condition during drought events. International Journal of Remote Sensing 39(5): 1548-1574. doi:10.1080/01431161.2017.1407047.
  22. Novella, N. S., and W. M. Thiaw, 2013. African rainfall climatology version 2 for famine early warning systems. Journal of Applied Meteorology and Climatology 52(3): 588-606. doi:10.1175/JAMC-D-11-0238.1.
  23. Ministry of Environment (ME), 2016. Drought response assessment and limited watering guidelines (in Korean).
  24. Ministry of Environment (ME), 2018. 2013-2018 long-term drought analysis and evaluation report (in Korean).
  25. Ministry of the Interior and Safety (MOIS), 2018. Guideline for designating regular drought disaster areas (in Korean).
  26. Ministry of Land, Infrastructure and Transport (MOLIT), 1995. 1995 drought record survey report (in Korean).
  27. Ministry of Land, Infrastructure and Transport (MOLIT), 2002. 2001 drought record survey report (in Korean).
  28. Park, C. E., 2017. Spatial and temporal aspects of drought in South Korea based on standardized precipitation index (SPI) and palmer drought severity index (PDSI). Journal of Agricultural, Life and Environmental Sciences 29(3): 202-214 (in Korean). doi:10.12972/jales.20170019.
  29. Qin, Y., Z. Chen, Y. Shen, S. Zhang, and R. Shi, 2014. Evaluation of satellite rainfall estimates over the Chinese mainland. Remote Sensing 6: 11649-11672. doi:10.3390/rs61111649.
  30. Ryoo, S., and C. Yoo, 2004. A modified standardized precipitation index (MSPI) and its application. Journal of Korea Water Resources Association 37(7): 553-567 (in Korean). doi:10.3741/JKWRA.2004.37.7.553.
  31. Schneider, U., M. Ziese, A. Meyer-Christffer, P. Finger, E. Rustemeier, and A. Becker, 2016. The new portfolio of global precipitation data products of the global precipitation climatology centre suitable to assess and quantify the global water cycle and resources. Proceeding of the International Association of Hydrological Sciences 374: 29-34. doi:10.5194/piahs-374-29-2016.
  32. Shukla, S., A. McNally, G. Husak, and C. Funk, 2014. A seasonal agricultural drought forecast system for food-insecure regions of East Africa. Hydrology and Earth System Sciences 18: 3907-3921. doi:10.5194/hess-18-3907-2014.
  33. Svoboda, M., D. LeComte, M. Hayes, R. Heim, K. Gleason, J. Angel, B. Rippey, R. Tinker, M. Palecki, D. Stooksbury, D. Miskus, and S. Stephens, 2002. The drought monitor. Bulletin of the American Meteorological Society 83(8): 1181-1190. doi:10.1175/1520-0477-83.8.1181.
  34. Trenberth, K. E., J. T. Overpeck, and S. Solomon, 2004. Exploring drought and its implications for the future. Transactions American Geophysical Union 85(3): 27. doi:10.1029/2004EO030004.
  35. Wilhite, D. A., M. D. Svoboda, and M. J. Hayes, 2007. Understanding the complex impacts of drought: A key to enhancing drought mitigation and preparedness. Water Resources Management 21: 763-774. doi:10.1007/s11269-006-9076-5.
  36. World Meteorological Organization (WMO), 2014. WMO statement on the status of the global climate in 2013. World Meteorological Organization.
  37. Yun, Y. S., N. Kim, S. J. Lee, S. Park, E. Sohn, J. D. Jang, and Y. W. Lee, 2018. Inter-comparisons of satellite-based drought indices on the cropland in Korea, 2001-2017. Journal of Climate Research 13(4): 275-296 (in Korean). doi:10.14383/cri.2018.13.4.275.