DOI QR코드

DOI QR Code

SPI 및 SDI 기반의 Seasonal ARIMA 모형을 활용한 가뭄예측 - 충주댐, 보령댐 유역을 대상으로 -

Short Term Drought Forecasting using Seasonal ARIMA Model Based on SPI and SDI - For Chungju Dam and Boryeong Dam Watersheds -

  • Yoon, Yeongsun (Geum RiverSurvey Division, Korea institute of Hydrological Survey) ;
  • Lee, Yonggwan (Dept. of Civil, Environmental, and Plant Engineering, Konkuk University) ;
  • Lee, Jiwan (Dept. of Civil, Environmental, and Plant Engineering, Konkuk University) ;
  • Kim, Seongjoon (School of Civil and Environmental Engineering, Konkuk University)
  • 투고 : 2018.03.14
  • 심사 : 2018.11.06
  • 발행 : 2019.01.31

초록

In this study, the SPI (Standardized Precipitation Index) of meteorological drought and SDI (Streamflow Drought Index) of hydrological drought for 1, 3, 6, 9, and 12 months duration were estimated to analyse the characteristics of drought using rainfall and dam inflow data for Chungju dam ($6,661.8km^2$) with 31 years (1986-2016) and Boryeong dam ($163.6km^2$) watershed with 19 years (1998-2016) respectively. Using the estimated SPI and SDI, the drought forecasting was conducted using seasonal autoregressive integrated moving average (SARIMA) model for the 5 durations. For 2016 drought, the SARIMA had a good results for 3 and 6 months. For the 3 months SARIMA forecasting of SPI and SDI, the correlation coefficient of SPI3, SPI6, SPI12, SDI1, and SDI6 at Chungju Dam showed 0.960, 0.990, 0.999, 0.868, and 0.846, respectively. Also, for same duration forecasting of SPI and SDI at Boryeong Dam, the correlation coefficient of SPI3, SPI6, SDI3, SDI6, and SDI12 showed 0.999, 0.994, 0.999, 0.880, and 0.992, respectively. The SARIMA model showed the possibility to provide the future short-term SPI meteorological drought and the resulting SDI hydrological drought.

키워드

NGHHCI_2019_v61n1_61_f0001.png 이미지

Fig. 1 Flow chart of the study

NGHHCI_2019_v61n1_61_f0002.png 이미지

Fig. 2 SPI and SDI values from 1986 to 2016 at Chungju Dam watershed

NGHHCI_2019_v61n1_61_f0003.png 이미지

Fig. 3 SPI and SDI values from 1998 to 2016 at Boryeong Dam watershed

NGHHCI_2019_v61n1_61_f0004.png 이미지

Fig. 4 Comparison of SARIMA results of SPI and SDI series at Chungju dam watershed (2016)

NGHHCI_2019_v61n1_61_f0005.png 이미지

Fig. 5 Comparison of SARIMA results of SPI and SDI series at Boryeong dam watershed (2016)

Table 1 Classification Range of Drought Condition for SPI value

NGHHCI_2019_v61n1_61_t0001.png 이미지

Table 2 Classification Range of Drought Condition for SDI value

NGHHCI_2019_v61n1_61_t0002.png 이미지

Table 3 Test results of Augmented Dickey-Fuller (ADF) about SPI and SDI at Chungju Dam and Boryeong Dam watershed

NGHHCI_2019_v61n1_61_t0003.png 이미지

Table 4 Selection of optimal SARIMA model through Akaike’s Information Criterion (AIC) and SBC (Schwartz Bayesian Criterion) for Chungju Dam and Boryeong Dam watershed

NGHHCI_2019_v61n1_61_t0004.png 이미지

Table 5 Statistical analysis results for SPI, SDI series using SARIMAat Chungju Dam and Boryeong Dam watershed

NGHHCI_2019_v61n1_61_t0005.png 이미지

Table 6 Correlation analysis between observed and predicted values of SPI and SDI series using SARIMA model (2016, Chungju Dam)

NGHHCI_2019_v61n1_61_t0006.png 이미지

Table 7 Correlation analysis between observed and predicted values of SPI and SDI series using SARIMA model (2016, Boryeong Dam)

NGHHCI_2019_v61n1_61_t0007.png 이미지

참고문헌

  1. Ahn, S. R., S. H. Kim, S. W. Yoon, and S. J. Kim, 2013. Evaluation of suspended solids and eutrophication in Chunghu lake using CE-QUAL-W2. Journal of Korea Water Resources Association 46(11): 1115-1128 (in Korean). doi:10.3741/JKWRA.2013.46.11.1115.
  2. Alam, N. M., S. K. Sarkar, C. Jana, A. Raizada, D. Mandal, R. Kaushal, N. K. Sharma, P. K. Mishra, and G. C. Sharma, 2016. Forecasting meteorological drought for a typical drought affected area in India using stochastic models. Journal of the Indian Society of Agricultural Statistics 70(1): 71-81.
  3. Baier, W., 1969. Concepts of soil moisture availability and their effect on soil moisture estimates from a meteorological budget. Agricultural Meteorology 6(3): 165-178. doi:10.1016/0002-1571(69)90002-8.
  4. Box, G. E. P., and G. M. Jenkins, 1976. Time Series Analysis Forecasting and Control, Holden-Day, San Francisco.
  5. Cho, S. I., and J. S. Choi, 2005. A Monte Carlo experiment of the power of augmented Dickey-Fuller Unit Root Test. Journal of The Korean Official Statistics 10(1): 165-188 (in Korean).
  6. Choi, Y. J., 2017. Analysis of Boryeong Dam diversion tunnel operation effects. Master Thesis, Ajou University, Republic of Korea (in Korean).
  7. 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.
  8. Granger, C. W., and P. Newbold, 1974. Spurious regressions in econometrics. Journal of econometrics 2(2): 111-120. https://doi.org/10.1016/0304-4076(74)90034-7
  9. Hisdal, H., and L. M. Tallaksen, 2003. Estimation of regional meteorological and hydrological drought characteristics: a case study for Denmark. Journal of Hydrology 281(3): 230-247. doi:10.1016/S0022-1694(03)00233-6.
  10. Kim, S. J., and J. W. Lee, 2017. A brief review on utilization of standard precipitation index (SPI). Water for future 50(6): 41-49.
  11. Kim, S. H., and E. S. Chung, 2017. Peak drought index analysis of cheongmicheon watershed using meteorological and hydrological drought index. J. Korea Water Resour. Assoc. 50(1): 65-73 (in Korean). doi:10.3741/JKWRA.2017.50.1.65.
  12. Kwon, H. J., H. J. Park, D. O. Hong, and S. J. Kim, 2006. A study on semi-distributed hydrologic drought assessment modifying SWSI. Journal of Korea Water Resources Association 39(8): 645-658. doi:10.3741/JKWRA.2006.39.8.645.
  13. Lee, J. W., Y. G. Lee, and S. J. Kim, 2017. The possibility of drought espression by late march dryness in rice paddy areas using terra MODIS NDVI. Journal of the Korean Association of Geographic Information Studies 20(3): 27-41. doi:10.11108/kagis.2017.20.3.027.
  14. Lee, J. W., J. U. Kim, C. G. Jung, and S. J. Kim, 2018. Forecasting of monthly agricultural reservoir storage rate using multiple linear regression. Journal of the Korean Association of Geographic Information Studies in press. doi:10.11108/kagis.2018.21.3.019.
  15. Liu, L., Y. Hong, C. N. Bednarczyk, B. Yong, M. A. Shafer, R. Riley, and J. E. Hocker, 2012. Hydroclimatological drought analyses and projections using meteorological and hydrological drought indices: a case study in Blue River Basin, Oklahoma. Water Resources Management 26(10): 2761-2779. doi:10.1007/s11269-012-0044-y.
  16. Lloyd‐Hughes, B., and M. A. Saunders, 2002. A drought climatology for Europe. International Journal of Climatology 22(13): 1571-1592. doi:10.1002/joc.846.
  17. McKee, T. B., N. J. Doesken, and J. Kleist, 1993. The relationship of drought frequency and duration to time scales. In Proceedings of the 8th Conference on Applied Climatology 17(22): 179-183.
  18. Nalbantis, I., 2008. Evaluation of a hydrological drought index. European Water 23(24): 67-77.
  19. Nalbantis, I., and G. Tsakiris, 2009. Assessment of hydrological drought revisited. Water Resources Management 23(5): 881-897. doi:10.1007/s11269-008-9305-1.
  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 Agricultural Engineers 59(4): 65-74. doi:10.5389/KSAE.2017.59.4.065.
  21. Nam, W. H., M. J. Hayes, D. A. Wilhite, and M. D. Svoboda, 2015. Projection of temporal trends on drought characteristics using the standardized precipitation evapotranspiration index (SPEI) in South Korea. Journal of the Korean Society of Agricultural Engineers 57(1): 37-45. doi:10.5389/KSAE.2015.57.1.037.
  22. Oh, T. S., Y. I. Moon, S. S. Kim, and G. S. Park, 2011. Frequency analysis of meteorologic drought indices using boundary Kernel Density function. Journal of the Korean Society of Civil Engineers 31(2B): 87-98. doi:10.12652/Ksce.2011.31.2B.087.
  23. Park, M. J., H. J. Shin, Y. D. Choi, J. Y. Park, and S. J. Kim, 2011. Development of a hydrological drought index considering water availability. Journal of the Korean Society of Agricultural Engineers 53(6): 165-170. doi:10.5389/KSAE.2011.53.6.165.
  24. Shin, C. H., and S. H. Jeong, 2011. A study on application of ARIMA and Neural Networks for time series forecasting of prot traffic. Journal of Navigation and Port Research 35(1): 83-91 (in Korean). doi:10.5394/KINPR.2011.35.1.83.
  25. Tabari, H., H. Abghari, and P. Hosseinzadeh Talaee, 2012. Temporal trends and spatial characteristics of drought and rainfall in arid and semiarid regions of Iran. Hydrological Processes 26(22): 3351-3361. doi:10.1002/hyp.8460.
  26. Tigkas, D., H. Vangelis, and G. Tsakiris, 2012. Drought and climatic change impact on streamflow in small watersheds. Science of the Total Environment 440: 33-41. doi:10.1016/j.scitotenv.2012.08.035.
  27. Vicente-Serrano, S. M., S. Begueria, and J. I. Lopez-Moreno, 2010. A multiscalar drought index sensitive to global warming: the standardized precipitation evapotranspiration index. Journal of Climate 23(7): 1696-1718. doi:10.1175/2009JCLI2909.1.