Abstract
Climate change is a main driving force that affects the hydrological cycle, leading to an increase in natural hazards. Among these natural hazards, drought is one of the most destructive and becomes more complex considering climate change. Therefore, it is necessary to investigate the effect of climate change on different types of drought. In this study, we examined the propagation probability of meteorological drought into hydrological drought using a probabilistic graphical model across South Korea. We performed correlation analyses among meteorological drought represented by Standardized Precipitation Index (SPI) and Standardized Precipitation Evapotranspiration Index (SPEI) and hydrological drought by Standardized Runoff Index (SRI) on different time scales. Drought characteristics were examined under a baseline period, RCP 4.5, and 8.5 climate change scenarios, and the results illustrated that drought characteristics varied spatially. On average, drought severity of SPI increased in P1 (2011–2040) and then deceased in P2 (2041–2070) and P3 (2071–2099) under RCP 4.5, whereas drought severity also increased in P1 under RCP 8.5. However, average drought severity of SPEI increased in P3, whereas that of SRI showed a decreasing trend for all the periods. Finally, propagation occurrence probabilities of different states of meteorological drought resulting in different states of hydrological drought were examined under climate change scenarios. The average propagation probability of extreme state of meteorological drought resulting in moderate and severe condition of hydrological drought increased by 13% and 2%, respectively, under RCP 4.5; while average propagation probability of extreme state of meteorological drought resulting in severe and extreme conditions of hydrological drought increased by 1.5% and 84%, respectively, under RCP 8.5. We concluded that propagation probability of meteorological drought into hydrological drought increased significantly under climate change. These findings will be helpful for early mitigation of hydrological drought.
Similar content being viewed by others
References
Dai A (2012) Increasing drought under global warming in observations and models. Nat Clim Chang 3:52–58. https://doi.org/10.1038/nclimate1633
Eum HI, Cannon AJ (2017) Intercomparison of projected changes in climate extremes for South Korea: application of trend preserving statistical downscaling methods to the CMIP5 ensemble. Int J Climatol 37(8):3381–3397. https://doi.org/10.1002/joc.4924
Ghosh S, Mujumdar PP (2007) Nonparametric methods for modeling GCM and scenario uncertainty in drought assessment. Water Resour Res 43(7):W07405
Hao ZC, Hao FH, Singh VP, Ouyang W, Cheng HG (2017) An integrated package for drought monitoring, prediction and analysis to aid drought modeling and assessment. Environ Model Softw 91:199–209. https://doi.org/10.1016/j.envsoft.2017.02.008
Huang SZ, Li P, Huang Q, Leng GY, Hou BB, Ma L (2017) The propagation from meteorological to hydrological drought and its potential influence factors. J Hydrol 547:184–195. https://doi.org/10.1016/j.jhydrol.2017.01.041
Intergovernmental Panel on Climate Change (IPCC) (2013) Summary for policymakers. Climate change 2013. The science of climate change. Contribution of Working Group I to the fifth assessment report of the intergovernmental panel on climate change
Lee JH, Kim CJ (2013) A multimodel assessment of the climate change effect on the drought severity–duration–frequency relationship. Hydrol Process 27(19):2800–2813. https://doi.org/10.1002/hyp.9390
Lee H, Im ES, Bae DH (2019) A comparative assessment of climate change impacts on drought over Korea based on multiple climate projections and multiple drought indices. Clim Dyn. https://doi.org/10.1007/s00382-018-4588-2
McKee TB, Doesken NJ, Kleist J (1993) The relationship of drought frequency and duration to time scales. In: Proceedings of the 8th conference on applied climatology. Anaheim, pp 179–184
Melo DDCD, Wendland E (2016) Hydrological system time lag responses to meteorological shifts. RBRH 21(4):766–776. https://doi.org/10.1590/2318-0331.011616083
Mishra V, Cherkauer KA, Shukla S (2010) Assessment of drought due to historic climate variability and projected future climate change in the midwestern United States. J Hydrometeorol 11(1):46–68. https://doi.org/10.1175/2009JHM1156.1
Orlowsky B, Seneviratne SI (2013) Elusive drought: uncertainty in observed trends and short-and long-term CMIP5 projections. Hydrol Earth Syst Sci 17:1765–1781. https://doi.org/10.5194/hess-17-1765-2013
Ouyang F, Zhu Y, Fu G, Lü H, Zhang A, Yu Z, Chen X (2015) Impacts of climate change under CMIP5 RCP scenarios on streamflow in the Huangnizhuang catchment. Stoch Env Res Risk Assess 29(7):1781–1795. https://doi.org/10.1007/s00477-014-1018-9
Palmer WC (1965) Meteorological drought. US Department of Commerce, Weather Bureau, Research Paper No. 45, p 58
Rhee J, Cho J (2016) Future changes in drought characteristics: regional analysis for South Korea under CMIP5 projections. J Hydrometeorol 17:437–451. https://doi.org/10.1175/JHM-D-15-0027.1
Sattar MN, Kim TW (2018) Probabilistic characteristics of lag time between meteorological and hydrological droughts using a Bayesian model. Terr Atmos Ocean Sci 29:1–12. https://doi.org/10.3319/TAO.2018.07.01.01
Shin JY, Chen S, Lee JH, Kim TW (2018a) Investigation of drought propagation in South Korea using drought index and conditional probability. Terr Atmos Ocean Sci 29:231–241. https://doi.org/10.3319/TAO.2017.08.23.01
Shin Y, Lee Y, Choi J, Park JS (2018b) Integration of max-stable processes and Bayesian model averaging to predict extreme climatic events in multi-model ensembles. Stoch Env Res Risk Assess 33(1):47–57. https://doi.org/10.1007/s00477-018-1629-7
Shukla S, Wood AW (2008) Use of a standardized runoff index for characterizing hydrologic drought. Geophys Res Lett 35(2):L02405. https://doi.org/10.1029/2007GL032487
Stagge JH, Tallaksen LM, Gudmundsson L, Van Loon AF, Stahl K (2015) Candidate distributions for climatological drought indices (SPI and SPEI). Int J Climatol 35(13):4027–4040. https://doi.org/10.1002/joc.4267
Tsakiris G, Vangelis H (2005) Establishing a drought index incorporating evapotranspiration. Eur Water 9(10):3–11
Van Loon AF, Van Lanen HAJ (2012) A process-based typology of hydrological drought. Hydrol Earth Syst Sci 16:1915–1946. https://doi.org/10.5194/hessd-8-11413-2011
Van-Rooy MP (1965) A rainfall anomaly index (RAI) independent of time and space. Notos 14:43–48
Vicente-Serrano SM, Beguería S, López-Moreno JI (2010) A multiscalar drought index sensitive to global warming: the standardized precipitation evapotranspiration index. J Clim 23:1696–1718. https://doi.org/10.1175/2009jcli2909.1
Wang W, Ertsen MW, Svoboda MD, Hafeez M (2016a) Propagation of drought: from meteorological drought to agricultural and hydrological drought. Adv Meteorol. https://doi.org/10.1155/2016/6547209
Wang X, Yang T, Li X, Shi P, Zhou X (2016b) Spatio-temporal changes of precipitation and temperature over the Pearl River basin based on CMIP5 multi-model ensemble. Stoch Env Res Risk Assess 31(5):1077–1089. https://doi.org/10.1007/s00477-016-1286-7
Wilhite DA, Glantz MH (1985) Understanding the drought phenomenon: the role of definitions. Water Int 10(3):111–120. https://doi.org/10.1080/02508068508686328
Wu J, Miao C, Zheng H, Duan Q, Lei X, Li H (2018) Meteorological and hydrological drought on the Loess Plateau, China: evolutionary characteristics, impact, and propagation. J Geophys Res Atmosp 123(20):11–569. https://doi.org/10.1029/2018JD029145
Xu K, Wu C, Hu BX (2018) Projected changes of temperature extremes over nine major basins in China based on the CMIP5 multimodel ensembles. Stoch Env Res Risk Assess 33(1):321–339. https://doi.org/10.1007/s00477-018-1569-2
Yu Z, Gu H, Wang J, Xia J, Lu B (2017) Effect of projected climate change on the hydrological regime of the Yangtze River Basin, China. Stoch Env Res Risk Assess 32(1):1–16. https://doi.org/10.1007/s00477-017-1391-2
Yuan X, Zhang M, Wang L (2016) Understanding and seasonal forecasting of hydrological drought in the anthropocene. Hydrol Earth Syst Sci Dis. https://doi.org/10.5194/hess-2016-592
Zhao L, Lyu A, Wu J, Hayes M, Tang Z, He B, Liu J, Liu M (2014) Impact of meteorological drought on streamflow drought in Jinghe River Basin of China. Chin Geogr Sci 24:694–705. https://doi.org/10.1007/s11769-014-0726-x
Zhensheng Y, Yuguo D (1990) Climate statistics. Meteorological Press, Beijing (in Chinese)
Acknowledgements
This study was supported by the Korea Environmental Industry & Technology Institute (KEITI) through Advanced Water Management Research Program, funded by Korean Ministry of Environment (Grant 79616). The first author would like to thank to the Higher Education Commission (HEC) and Government of Pakistan for the scholarship under the project “HRD Initiative-MS leading to Ph.D. program of faculty development for UESTPS, Phase-1, and Batch-V for Hanyang University, South Korea”.
Author information
Authors and Affiliations
Corresponding author
Additional information
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Electronic supplementary material
Below is the link to the electronic supplementary material.
Rights and permissions
About this article
Cite this article
Jehanzaib, M., Sattar, M.N., Lee, JH. et al. Investigating effect of climate change on drought propagation from meteorological to hydrological drought using multi-model ensemble projections. Stoch Environ Res Risk Assess 34, 7–21 (2020). https://doi.org/10.1007/s00477-019-01760-5
Published:
Issue Date:
DOI: https://doi.org/10.1007/s00477-019-01760-5