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Seasonal drought ensemble predictions based on multiple climate models in the upper Han River Basin, China

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Abstract

An experimental seasonal drought forecasting system is developed based on 29-year (1982–2010) seasonal meteorological hindcasts generated by the climate models from the North American Multi-Model Ensemble (NMME) project. This system made use of a bias correction and spatial downscaling method, and a distributed time-variant gain model (DTVGM) hydrologic model. DTVGM was calibrated using observed daily hydrological data and its streamflow simulations achieved Nash–Sutcliffe efficiency values of 0.727 and 0.724 during calibration (1978–1995) and validation (1996–2005) periods, respectively, at the Danjiangkou reservoir station. The experimental seasonal drought forecasting system (known as NMME-DTVGM) is used to generate seasonal drought forecasts. The forecasts were evaluated against the reference forecasts (i.e., persistence forecast and climatological forecast). The NMME-DTVGM drought forecasts have higher detectability and accuracy and lower false alarm rate than the reference forecasts at different lead times (from 1 to 4 months) during the cold-dry season. No apparent advantage is shown in drought predictions during spring and summer seasons because of a long memory of the initial conditions in spring and a lower predictive skill for precipitation in summer. Overall, the NMME-based seasonal drought forecasting system has meaningful skill in predicting drought several months in advance, which can provide critical information for drought preparedness and response planning as well as the sustainable practice of water resource conservation over the basin.

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References

  • Ahmed KF (2011) Bias Correction and Downscaling of climate model outputs required for impact assessments of climate change in the US northeast. Master’s Theses pp212. http://digitalcommons.uconn.edu/gs_theses/212

  • Arnold JG, Williams JR, Srinivasan R (1997) Model theory of SWAT. USDA. Agricultural Research Service Grassland. Soil and Water Research Laboratory, USA

    Google Scholar 

  • Becker E, van den Dool H, Zhang Q (2014) Predictability and forecast skill in NMME. J Climate 27:5891–5906. doi:10.1175/JCLI-D-13-00597.1

    Article  Google Scholar 

  • Caffrey P, Farmer A (2014) A review of Downscaling methods for climate change projections. Tetra Tech ARD

  • Day GN (1985) Extended streamflow forecasting using NWSRFS. J Water Resour Plann Manage Div Am Soc Civ Eng 111:157–170. doi:10.1061/(ASCE)0733-9496(1985)111:2(157)

    Article  Google Scholar 

  • DelSole T, Nattala J, Tippett MK (2014) Skill improvement from increased ensemble size and model diversity. Geophys Res Lett 41:7331–7342. doi:10.1002/2014GL060133

    Article  Google Scholar 

  • Garen DC (1992) Improved techniques in regression-based streamflow volume forecasting. J Water Resour Plann Manage 118:654–670. doi:10.1061/(ASCE)0733-9496(1992)

    Article  Google Scholar 

  • Huggins LF, Monke EJ (1966) The mathematical simulation of the hydrology of small watersheds. Technical Report No. 1. Purdue University Water Resource Research Center, West Lafayette

    Google Scholar 

  • Jin R, Guo H (1993) Water resources assessment in the water source areas of the Middle Route of the South to North Water Transfer Project and water quantity analysis in the Danjiangkou Reservoir. Yangzte River 24:7–12

    Google Scholar 

  • Kirtman BP, Min D, Infanti JM, Kinter JL, Paulino DA, Zhang Q, van den Dool H, Saha S, Pena Mendez M, Becker E, Peng P, Tripp P, Huang J, DeWitt DG, Tippett MK, Barnston AG, Li S, Rosati A, Schubert SD, Rienecker M, Suarez M, Li ZE, Marshak J, Lim Y.-K, Tribbia J, Pegion K, Merryfield WJ, Denis B, Wood EF (2014) The North American Multi-Model Ensemble (NMME): Phase-1 seasonal to interannual prediction, phase-2 toward developing intra-seasonal prediction. Bull Am Meteorol Soc 95:585–601. doi:10.1175/BAMS-D-12-00050.1

    Article  Google Scholar 

  • Li S, Zhang Q (2012) Basin ecosystem management in the Upper Han River for the South to North Water Division Project, China. J Environ Anal Toxicol S3:002. doi:10.4172/2161-0525.S3-002

    Article  Google Scholar 

  • Li S, Gu S, Liu W, Han H, Zhang Q (2008) Water quality in relation to land use and land cover in the upper Han River Basin, China. Catena 75:216–222

    Article  Google Scholar 

  • Li S, Liu W, Gu S, Cheng X, Xu Z, Zhang Q (2009) Spatio-temporal dynamics of nutrients in the upper Han River basin, China. J Hazard Mat 162(2–3):1340–1346. doi:10.1016/j.jhazmat.2008.06.059

    Article  Google Scholar 

  • Luo L, Wood EF (2007) Monitoring and predicting the 2007 US drought. J Geophys Res 34:L22702. doi:10.1029/2007GL031673

    Article  Google Scholar 

  • Luo L, Wood EF (2008) Use of Bayesian merging techniques in a multimodel seasonal hydrologic ensemble prediction system for the eastern United States. J Hydrometeor 9:866–884. doi:10.1175/2008JHM980.1

    Article  Google Scholar 

  • Luo L, Wood EF, Pan M (2007) Bayesian merging of multiple climate model forecasts for seasonal hydrological predictions. J Geophys Res 112:D10102. doi:10.1029/2006JD007655

    Article  Google Scholar 

  • Ma F, Yuan X, Ye A (2015) Seasonal drought predictability and forecast skill over China. J Geophys Res 120(16):8264–8275. doi:10.1002/2015JD023185

    Article  Google Scholar 

  • Ma F, Ye A, Deng X, Zhou Z, Liu X, Duan Q, Xu J, Miao C, Di Z, Gong W (2016) Evaluating the skill of NMME seasonal precipitation ensemble predictions for 17 hydroclimatic regions in continental China. Int J Climatol 26:132–144. doi:10.1002/joc.4333

    Article  Google Scholar 

  • Meng C, Yin SY (2012) Study on precipitation change and drought prediction in upper reaches of Hanjiang River during the last 50 years. Res Agri Modern 33(1):125–128

    Google Scholar 

  • Mo K, Lettenmaier DP (2014) Hydrologic prediction over the conterminous United States using the National Multi-Model Ensemble. J Hydrometeor 15:1457–1472. doi:10.1175/JHM-D-13-0197.1

    Article  Google Scholar 

  • Pagano T, Garen D, Sorooshian S (2004) Evaluation of official western U.S. seasonal water supply outlooks, 1922–2002. J Hydrometeor 5:896–909. doi:10.1175/1525-7541(2004)005<0896:EOOWUS>2.0.CO;2

    Article  Google Scholar 

  • Pereira L, Pereira A, Allen R, Alves I (1999) Evapotranspiration: concepts and future trend. J Irrig Drain Eng 4:45–51. doi:10.1061/(ASCE)0733-9437(1999)

    Article  Google Scholar 

  • Ren L, Yin S, Peng W (2013) Statistics and causes of historical drought disasters in upper reaches of Hanjiang River. Bull Soil Water Conserv 33(1):129–371

    Google Scholar 

  • Sheffield J, Goteti G, Wen F, Wood EF (2004) A simulated soil moisture based drought analysis for the United States. J Geophys Res 109:D24108. doi:10.1029/2004JD005182

    Article  Google Scholar 

  • Sheffield J, Wood EF, Chaney N, Guan K, Sadri S, Yuan X, Olang L, Amani A, Ali A, Demuth S, Ogallo L (2014) A drought monitoring and forecasting system for sub-Sahara African water resources and food security. Bull Amer Meteor Soc 95:861–882. doi:10.1175/BAMS-D-12-00124.1

    Article  Google Scholar 

  • Shen D, Liu C (1998) Effects of different scales of MR-SNWTP on the down stream of the Danjiang Kou reservoir. Acta Geographica Sinica 53:341–348

    Google Scholar 

  • Shukla S, Lettenmaier DP (2011) Seasonal hydrologic prediction in the United States: Understanding the role of initial hydrologic conditions and seasonal climate forecast skill. Hydrol Earth Syst Sci 15:3529–3538. doi:10.5194/hess-15-3529-2011

    Article  Google Scholar 

  • Shukla S, Sheffield J, Wood EF, Lettenmaier DP (2013) On the sources of global land surface hydrologic predictability. Hydrol Earth Syst Sci 17:2781–2796. doi:10.5194/hess-17-2781-2013

    Article  Google Scholar 

  • Su B, Kundzewicz ZW, Jiang T (2008) Simulation of extreme precipitation over the Yangtze River Basin using Wakeby distribution. Theor Appl Climatol 96:209–219. doi:10.1007/s00704-008-0025-5

    Article  Google Scholar 

  • Tao X, Chen H, Xu C (2015) Characteristics of drought variations in Hanjiang Basin in 1961–2014 based on SPI/SPEI. Journal of Water Resources Research 4(5):404–415. doi:10.12677/JWRR.2015.45050

    Article  Google Scholar 

  • Van den Hurk B, Bouwer LM, Buontempo C, Döscher R, Ercin E, Hananel C, Hunink JE, Kjellström E, Klein B, Manez M, Pappenberger F, Pouget L, Ramos M-H, Ward PJ, Weerts AH, Wijngaard JB (2016) Improving predictions and management of hydrological extremes through climate services. Climate Services 1: 6–11. doi:10.1016/j.cliser.2016.01.001

    Article  Google Scholar 

  • Wang A, Lettenmaier DP, Sheffield J (2011) Soil moisture drought in China, 1950–2006. J Climate 24:3257–3271. doi:10.1175/2011JCLI3733.1

    Article  Google Scholar 

  • Wilks DS (2011) Statistical methods in the atmospheric sciences. 3rd edn. Academic Press, Salt Lake City

    Google Scholar 

  • Wood AW, Maurer EP, Kumar A, Lettenmaier DP (2002) Long-range experimental hydrologic forecasting for the eastern United States. J Geophys Res 107(D20):6–15. doi:10.1029/2001JD000659(ACL 6–1–ACL)

    Article  Google Scholar 

  • Wood AW, Lettenmaier DP (2006) A test bed for new seasonal hydrologic forecasting approaches in the western United States. Bull Am Meteor Soc 87:1699–1712. doi:10.1175/BAMS-87-12-1699

    Article  Google Scholar 

  • Wood AW, Leung LR, Sridhar V, Lettenmaier DP (2004) Hydrologic implications of dynamical and statistical approaches to downscaling climate model outputs. Clim Change 62(1–3):189–216. doi:10.1023/B:CLIM.0000013685.99609.9e

    Article  Google Scholar 

  • Wood EF, et al. (2011), Hyperresolution global land surface modeling: Meeting a grand challenge for monitoring Earth’s terrestrial water. Water Resour Res 47:W05301, doi:10.1029/2010WR010090

    Article  Google Scholar 

  • Xia J, Wang G, Lv A (2003) A research on distributed time variant gain modeling. Acta Geographica Sinica 58(5):789–796. doi:10.11821/xb200305019

    Article  Google Scholar 

  • Xia J, Wang G, Tan G, Huang GH (2005) Development of distributed time-variant gain model for nonlinear hydrological systems. Sci China Series D: Earth Sci 48(6):713–723. doi:10.1360/03yd0183

    Article  Google Scholar 

  • Xiao M, Zhang Q, Singh VP, Chen X (2016) Probabilistic forecasting of seasonal drought behaviors in the Huai River basin, China. Theore Appl Climatol. doi:10.1007/s00704-016-1733-x

    Article  Google Scholar 

  • Xu Y (1998) An analysis of climatic cause for dry and rainless Han River basin during 1997. Hubei Meteorological (2):12–14 (in Chinese)

  • Yang Y, Zhou N, Guo X, Hu Q (1997) The hydrology characteristics analysis of HanJiang up-streams. Hydrology 2:54–56

    Google Scholar 

  • Ye A, Xia J, Wang GS, Wang XN (2005) Drainage network extraction and subcatchment delineation based on digital elevation model. J Hydraul Eng 36(5):531–537 (Chinese)

    Google Scholar 

  • Ye A, Duan Q, Zeng H, Li L, Wang C (2010) A distributed time-variant gain hydrological model based on remote sensing. J Resour Ecol 1(3):222–230. doi:10.3969/j.issn.1674-764x.2010.03.005

    Article  Google Scholar 

  • Ye A, Duan Q, Xu J (2014) A review of hydrological ensemble forecast and case study. China Water Power Press, Beijing (Chinese)

    Google Scholar 

  • Yuan X (2016) An experimental seasonal hydrological forecasting system over the Yellow River basin-Part II: The added value from climate forecast models. Hydrol Earth Syst Sci 20:2453–2466. doi:10.5194/hess-20-2453-2016

    Article  Google Scholar 

  • Yuan X, Wood EF (2012) On the clustering of climate models in ensemble seasonal forecasting. Geophys Res Lett 39:L18701. doi:10.1029/2012GL052735

    Article  Google Scholar 

  • Yuan X, Wood EF, Roundy JK, Pan M (2013) CFSv2-based seasonal hydroclimatic forecasts over conterminous United States. J Climate 26:4828–4847. doi:10.1175/JCLI-D-12-00683.1

    Article  Google Scholar 

  • Yuan X, Roundy JK, Wood EF, Sheffield J (2015a) Seasonal forecasting of global hydrologic extremes: system development and evaluation over GEWEX Basins. Bull Am Meteor Soc 96:1895–1912. doi:10.1175/BAMS-D-14-00003.1

    Article  Google Scholar 

  • Yuan X, Wood EF, Ma Z (2015b) A review on climate-model-based seasonal hydrologic forecasting: physical understanding and system development. Wiley Interdisciplinary Reviews: Water 2(5): 523–536.doi:10.1002/wat2.1088

    Article  Google Scholar 

  • Yuan X, Ma F, Wang L, Zheng Z, Ma Z, Ye A, Peng S (2016) An experimental seasonal hydrological forecasting system over the Yellow River basin-Part I: Understanding the role of initial hydrological conditions. Hydrol Earth Syst Sci 20:2437–2451. doi:10.5194/hess-20-2437-2016

    Article  Google Scholar 

  • Zhai J, Su B, Krysanova V, Vetter T, Gao C, Jiang T (2010) Spatial variation and trends in PDSI and SPI indices and their relation to streamflow in 10 large regions of China. J Climate 23:649–663. doi:10.1175/2009JCLI2968.1

    Article  Google Scholar 

  • Zhang Q (2005) The South-to-North Water Diversion (SNWD) Project. Front Ecol Environ 3(2):75–76. doi:10.2307/3868512

    Article  Google Scholar 

Download references

Acknowledgements

This study was supported by the Natural Science Foundation of China (No. 41475093), the Intergovernmental Key International S&T Innovation Cooperation Program (No. 2016YFE0102400) and the State Key Laboratory of Severe Weather Open Research Program (No. 2015LASW-A05).

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Correspondence to Aizhong Ye.

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This paper is a contribution to the special collection on the North American Multi-Model Ensemble (NMME) seasonal prediction experiment. The special collection focuses on documenting the use of the NMME system database for research ranging from predictability studies, to multi-model prediction evaluation and diagnostics, to emerging applications of climate predictability for subseasonal to seasonal predictions.This special issue is coordinated by Annarita Mariotti (NOAA), Heather Archambault (NOAA), Jin Huang (NOAA), Ben Kirtman (University of Miami) and Gabriele Villarini (University of Iowa).

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Ma, F., Ye, A. & Duan, Q. Seasonal drought ensemble predictions based on multiple climate models in the upper Han River Basin, China. Clim Dyn 53, 7447–7460 (2019). https://doi.org/10.1007/s00382-017-3577-1

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