Abstract
A reliable understanding of propagation from meteorological to hydrological drought is necessary for accurate forecasting of hydrological droughts. Our current understanding of drought propagation is limited because the characteristics of each drought and the lag time between droughts are uneven due to spatial variability in underlying conditions and climatic variables. The objective of this study is to identify the probabilistic relationship between lag time and the occurrence of different classes of hydrological drought in South Korea while considering propagation factors and using a Bayesian network model. The results show that the propagation rate varied from 27% to 60% and the maximum value of the lag time was projected to be 4 to 10 weeks. For moderate intensity of meteorological drought, the occurrence probability of lag time was high and decreased when the intensity changed to severe and extreme. In addition, the probability for each class of hydrological drought intensity varied with space and increased as the intensity of propagated meteorological drought class changed from moderate to extreme. The observed probabilistic characteristics of hydrological drought may be useful in decision-making strategies for mitigating water shortage.
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References
Barker L, Hannaford J, Chiverton A, Svensson C (2016) From meteorological to hydrological drought using standardised indicators. Hydrol Earth Syst Sci 20:2483–2505. https://doi.org/10.5194/hess-20-2483-2016
Cancelliere A, Salas JD (2010) Drought probabilities and return period for annual streamflows series. J Hydrol 391:77–89. https://doi.org/10.1016/j.jhydrol.2010.07.008
Chang H, Kwon W-T (2007) Spatial variations of summer precipitation trends in South Korea, 1973–2005. Environ Res Lett 2:045012. https://doi.org/10.1088/1748-9326/2/4/045012
Edossa DC, Babel MS, Gupta AD (2010) Drought analysis in the Awash river basin, Ethiopia. Water Resour Manag 24:1441–1460. https://doi.org/10.1007/s11269-009-9508-0
Huang S, Huang Q, Chang J, Leng G, Xing L (2015) The response of agricultural drought to meteorological drought and the influencing factors: A case study in the Wei River Basin. China Agricultural Water Management 159:45–54. https://doi.org/10.1016/j.agwat.2015.05.023
Huang S, Li P, Huang Q, Leng G, Hou B, 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
Kim CJ, Park MJ, Lee JH (2014) Analysis of climate change impacts on the spatial and frequency patterns of drought using a potential drought hazard mapping approach. Int J Climatol 34:61–80. https://doi.org/10.1002/joc.3666
Kim D-W, Byun H-R, Choi K-S, Oh S-B (2011) A spatiotemporal analysis of historical droughts in Korea. J Appl Meteorol Climatol 50:1895–1912. https://doi.org/10.1175/2011JAMC2664.1
Leng G, Tang Q, Rayburg S (2015) Climate change impacts on meteorological, agricultural and hydrological droughts in China. Glob Planet Chang 126:23–34. https://doi.org/10.1016/j.gloplacha.2015.01.003
López-Moreno J, Vicente-Serrano S, Zabalza J, Beguería S, Lorenzo-Lacruz J, Azorin-Molina C, Morán-Tejeda E (2013) Hydrological response to climate variability at different time scales: A study in the Ebro basin. J Hydrol 477:175–188. https://doi.org/10.1016/j.jhydrol.2012.11.028
Lorenzo-Lacruz J, Morán-Tejeda E, Vicente-Serrano S, López-Moreno J (2013) Streamflow droughts in the Iberian Peninsula between 1945 and 2005: spatial and temporal patterns. Hydrol Earth Syst Sci 17:119–134. https://doi.org/10.5194/hess-17-119-2013
Maeng SJ, Azam M, Kim HS, Hwang JH (2017) Analysis of changes in spatio-temporal patterns of drought across South Korea. Water 9:679. https://doi.org/10.3390/w9090679
Mishra A, Singh V, Desai V (2009) Drought characterization: a probabilistic approach. Stoch Env Res Risk A 23:41–55. https://doi.org/10.1007/s00477-007-0194-2
Mishra V, Cherkauer KA (2010) Retrospective droughts in the crop growing season: Implications to corn and soybean yield in the midwestern United States. Agric For Meteorol 150:1030–1045. https://doi.org/10.1016/j.agrformet.2010.04.002
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 11:46–68. https://doi.org/10.1175/2009JHM1156.1
Mo KC (2008) Model-based drought indices over the United States. J Hydrometeorol 9:1212–1230. https://doi.org/10.1175/2008JHM1002.1
Paik K, Kim JH, Kim HS, Lee DR (2005) A conceptual rainfall-runoff model considering seasonal variation. Hydrol Process 19:3837–3850. https://doi.org/10.1002/hyp.5984
Salas JD, Fu C, Cancelliere A, Dustin D, Bode D, Pineda A, Vincent E (2005) Characterizing the severity and risk of drought in the Poudre River, Colorado. J Water Resour Plan Manag 131:383–393. https://doi.org/10.1061/(ASCE)0733-9496(2005)131:5(383)
Sattar MN, Kim T-W (2018) Probabilistic characteristics of lag time between meteorological and hydrological droughts using a Bayesian model. Terrestrial. Atmospheric and Oceanic Sciences (TAO) 29:1–12. https://doi.org/10.3319/TAO.2018.07.01.01
Sen Roy S, Balling RC (2004) Trends in extreme daily precipitation indices in India. Int J Climatol 24:457–466. https://doi.org/10.1002/joc.995
Serinaldi F, Bonaccorso B, Cancelliere A, Grimaldi S (2009) Probabilistic characterization of drought properties through copulas. Physics and Chemistry of the Earth, Parts A/B/C 34:596–605. https://doi.org/10.1016/j.pce.2008.09.004
Shin JY, Ajmal M, Yoo J (2016) Kim T-W (2016) A Bayesian network-based probabilistic framework for drought forecasting and outlook. Adv Meteorol. https://doi.org/10.1155/2016/9472605
Song S, Singh VP (2010a) Frequency analysis of droughts using the Plackett copula and parameter estimation by genetic algorithm. Stoch Env Res Risk A 24:783–805. https://doi.org/10.1007/s00477-010-0364-5
Song S, Singh VP (2010b) Meta-elliptical copulas for drought frequency analysis of periodic hydrologic data. Stoch Env Res Risk A 24:425–444. https://doi.org/10.1007/s00477-009-0331-1
Tabrizi AA, Khalili D, Kamgar-Haghighi AA, Zand-Parsa S (2010) Utilization of time-based meteorological droughts to investigate occurrence of streamflow droughts. Water Resour Manag 24:4287–4306. https://doi.org/10.1007/s11269-010-9659-z
Tallaksen LM, Van Lanen HA (2004) Hydrological drought: processes and estimation methods for streamflow and groundwater. Elsevier, Amsterdam
Van Loon A, Van Huijgevoort M, Van Lanen H (2012) Evaluation of drought propagation in an ensemble mean of large-scale hydrological models. Hydrol Earth Syst Sci 16:4057–4078. https://doi.org/10.5194/hess-16-4057-2012
Van Loon AF (2015) Hydrological drought explained. WIREs Water 2:359–392. https://doi.org/10.1002/wat2.1085
Wong G, Van Lanen H, Torfs P (2013) Probabilistic analysis of hydrological drought characteristics using meteorological drought. Hydrol Sci J 58:253–270. https://doi.org/10.1080/02626667.2012.753147
Wu J, Chen X, Gao L, Yao H, Chen Y, Liu M (2016) Response of hydrological drought to meteorological drought under the influence of large reservoir. Adv Meteorol. https://doi.org/10.1155/2016/2197142
Wu J, Chen X, Yao H, Gao L, Chen Y, Liu M (2017) Non-linear relationship of hydrological drought responding to meteorological drought and impact of a large reservoir. J Hydrol 551:495–507. https://doi.org/10.1016/j.jhydrol.2017.06.029
Yoo J, Kwon H-H, Kim T-W, Ahn J-H (2012) Drought frequency analysis using cluster analysis and bivariate probability distribution. J Hydrol 420:102–111. https://doi.org/10.1016/j.jhydrol.2011.11.046
Yoo J, Kwon HH, So BJ, Rajagopalan B, Kim TW (2015) Identifying the role of typhoons as drought busters in South Korea based on hidden Markov chain models. Geophys Res Lett 42:2797–2804. https://doi.org/10.1002/2015GL063753
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
Zhao L, Wu J, Fang J (2016) Robust response of streamflow drought to different timescales of meteorological drought in Xiangjiang River Basin of China. Adv Meteorol. https://doi.org/10.1155/2016/1634787
Acknowledgements
This work was supported by the Korea Agency for Infrastructure Technology Advancement (KAIA) grant, which was funded by the Ministry of Land, Infrastructure and Transport (Grant 18AWMP-B083066-05). The authors would like to acknowledge the Higher Education Commission (HEC) of Pakistan for granting a scholarship to Muhammad Nouman Sattar to pursue his PhD degree.
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Sattar, M.N., Lee, JY., Shin, JY. et al. Probabilistic Characteristics of Drought Propagation from Meteorological to Hydrological Drought in South Korea. Water Resour Manage 33, 2439–2452 (2019). https://doi.org/10.1007/s11269-019-02278-9
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DOI: https://doi.org/10.1007/s11269-019-02278-9