Skip to main content
Springer Nature Link
Log in

Wavelet entropy-based investigation into the daily precipitation variability in the Yangtze River Delta, China, with rapid urbanizations

  • Original Paper
  • Published:
Theoretical and Applied Climatology Aims and scope Submit manuscript

    We’re sorry, something doesn't seem to be working properly.

    Please try refreshing the page. If that doesn't work, please contact support so we can address the problem.

Abstract

In this paper, the daily precipitation data measured at 58 meteorological stations were used, and the spatial and temporal variability of daily precipitation and precipitation extrema in the Yangtze River Delta (YRD) during 1958–2007 was investigated using the indicator of discrete wavelet entropy; then, the urbanization effects were further analyzed. Results indicate that the daily precipitation variability in YRD, especially in the mid YRD with highly urbanized city clusters, is determined by the comprehensive impacts of atmospheric circulation, urbanizations, and the Taihu Lake. Compared with the results in 1958–1985, the variability of daily precipitation and precipitation extrema becomes more complex in 1986–2007, and daily precipitation variability is more complex in the mid YRD relative to the north and south. The precipitation extrema with bigger magnitudes show more complex variability. Urbanizations cause more complexity and fluctuations of daily precipitation in the mid YRD in 1986–2007, reflecting more uncertainty of daily precipitation variability, while the urbanization effects vary with regions and precipitation magnitudes. The variability of precipitation extrema with maximum values is mainly determined by natural atmospheric circulation but has little relationship with urbanizations; however, the variability of those precipitation extrema with general values is determined by both urbanizations and the Taihu Lake in YRD over the last three decades.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6

Similar content being viewed by others

References

  • Abramov R, Majda A, Kleeman R (2005) Information theory and predictability for low-frequency variability. J Atmos Sci 62:65–87

    Article  Google Scholar 

  • Boyer C, Chaumont D, Chartier I, Roy AG (2010) Impact of climate change on the hydrology of St. Lawrence tributaries. J Hydrol 384:65–83

    Article  Google Scholar 

  • Brunetti M, Maugeri M, Monti F, Nanni T (2006) Temperature, precipitation variability in Italy in the last two centuries from homogenised instrumental time series. Int J Climatol 26:345–381

    Article  Google Scholar 

  • Brunsell NA (2010) A multiscale information theory approach to assess spatial-temporal variability of daily precipitation. J Hydrol 385:165–172

    Article  Google Scholar 

  • Burn DH, Hag Elnur MA (2002) Detection of hydrologic trends and variability. J Hydrol 255:107–122

    Article  Google Scholar 

  • Camilloni IA, Barros VR (2003) Extreme discharge events in the Parana River and their climate forcing. J Hydrol 278:94–106

    Article  Google Scholar 

  • Carsten M, Morton C, Ralf K, Gunter M, Harry V, Frank W (2008) Modeling the water balance of a mesoscale catchment basin using remotely sensed land cover data. J Hydrol 353:322–334

    Article  Google Scholar 

  • Core Writing Team; Pachauri RK, Reisinger A, ed., (2007) Climate Change 2007: Synthesis Report, Contribution of Working Groups I, II and III to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change, IPCC

  • Chou CM (2011) Wavelet-based multi-scale entropy analysis of complex rainfall time series. Entropy 13:241–253

    Article  Google Scholar 

  • Chui LL, Shi J, Yang YM, Li GC, Fan WY (2008) Temperature change characteristics and its influence by urbanization in the Yangtze River Delta. Geogr Res 27(4):775–786 (in Chinese with English abstract)

    Google Scholar 

  • Costa M, Goldberger AL, Peng CK (2005) Multiscale entropy analysis of biological signals. Phys Rev E 71:021906

    Article  Google Scholar 

  • Du Y, Xie Z, Zeng Y, Shi Y, Wu J (2007) Impacts of urban expansion on regional temperature change in the Yangtze River Delta. J Geogr Sci 4:387–398

    Article  Google Scholar 

  • Ebrahimi N, Maasoumi E, Soofi E (1999) Ordering univariate distributions by entropy and variance. J Econom 90:317–336

    Article  Google Scholar 

  • Elsner J, Tsonis A (1993) Complexity and predictability of hourly precipitation. J Atmos Sci 50:400–405

    Article  Google Scholar 

  • Emre Cek M, Ozgoren M, Acar Savaci F (2010) Continuous time wavelet entropy of auditory evoked potentials. Comput Bio Med 40:90–96

    Article  Google Scholar 

  • Gao G, Chen DL, Xu CY, Simelton E (2007) Trend of estimated actual evapotranspiration over China during 1960–2002. J Geophys Res Atmos 112:D11120

    Article  Google Scholar 

  • Gleick PH (1989) Climate change, hydrology, and water resources. Rev Geophys 27:329–344

    Article  Google Scholar 

  • Hanson RT, Newhouse MW, Dettinger MD (2004) A methodology to assess relations between climatic variability and variations in hydrologic time series in the southwestern United States. J Hydrol 287:252–269

    Article  Google Scholar 

  • Jaynes ET (1957) Information theory and statistical mechanics. Phys Rev 106:620–630

    Article  Google Scholar 

  • Jiang T, Su BD, Wang YJ, Zhang Q, Qin YX, Shi YF (2005) Trends of temperature, precipitation and runoff in the Yangtze River basin from 1961 to 2000. Adv Clim Chang Res 1(2):65–68 (in Chinese with English abstract)

    Google Scholar 

  • Jin L, Miu QL, Zhou GX, Luo Y (1999) Analysis on climatic variation and major meteorological disasters in the Yangtze Delta in the last 45 years. J Nanjing Inst Meteorol 22(4):698–705 (in Chinese with English abstract)

    Google Scholar 

  • Jones RN, Chiew FHS, Boughton WC, Zhang L (2006) Estimating the sensitivity of mean annual runoff to climate change using selected hydrological models. Adv Water Resour 29:1419–1429

    Article  Google Scholar 

  • Kalayci S, Kahya E (2006) Assessment of streamflow variability modes in Turkey: 1964–1994. J Hydrol 324:163–177

    Article  Google Scholar 

  • Kalnay E, Cai M (2003) Impact of urbanization and land-use change on climate. Nature 423:528–531

    Article  Google Scholar 

  • Koutsoyiannis D (2005) Uncertainty, entropy, scaling and hydrological stochastics. 1. Marginal distributional properties of hydrological processes and state scaling. Hydrol Sci J 50:381–404

    Google Scholar 

  • Labat D (2005) Recent advances in wavelet analyses: part 1. A review of concepts. J Hydrol 314:275–288

    Article  Google Scholar 

  • Li ZW, Zhang YK (2008) Multi-scale entropy analysis of Mississippi River flow. Stoch Environ Res Risk Assess 22:507–512

    Article  Google Scholar 

  • Liang P, Chen BD, Chen BM (2009) Characterization of the precipitation changes in Shanghai during rainy seasons from 1873 to 2007. Resour Sci 31(5):714–721 (in Chinese with English abstract)

    Google Scholar 

  • Loukas A, Vasiliades L, Dalezios NR (2002) Potential climate change impacts on flood producing mechanisms in southern British Columbia, Canada using the CGCMA1 simulation results. J Hydrol 259:163–188

    Article  Google Scholar 

  • Maurer EP, Lettenmaier DP, Mantua NJ (2004) Variability and potential sources of predictability of North American runoff. Water Resour Res 40:W09306

    Article  Google Scholar 

  • Michaels PJ, Balling RC Jr, Vose RS, Knappenberger PC (1998) Analysis of trends in the variability of daily and monthly historical temperature measurements. Clim Res 10:27–33

    Article  Google Scholar 

  • Mishra AK, Özger M, Singh VP (2009) An entropy-based investigation into the variability of precipitation. J Hydrol 370:139–154

    Article  Google Scholar 

  • Molini A, Barbera PL, Lanza LG (2006) Correlation patterns and information flows in rainfall fields. J Hydrol 322:89–104

    Article  Google Scholar 

  • Percival DB, Walden AT (2000) Wavelet methods for time series analysis. Cambridge University Press, Cambridge

    Google Scholar 

  • Piechota TC, Dracup JA, Fovell RG (1997) Western US streamflow and atmospheric circulation patterns during El Niño–Southern Oscillation. J Hydrol 201:249–271

    Article  Google Scholar 

  • Ravines RR, Schmidt AM, Migon HS, Renno CD (2008) A joint model for rainfall–runoff: the case of Rio Grande Basin. J Hydrol 35:189–200

    Article  Google Scholar 

  • Reggiani P, Weerts AH (2008) A Bayesian approach to decision-making under uncertainty: an application to real-time forecasting in the river Rhine. J Hydrol 356:56–69

    Article  Google Scholar 

  • Sang YF, Wang D, Wu JC, Zhu QP, Wang L (2009) The relation between periods’ identification and noises in hydrologic series data. J Hydrol 368:165–177

    Article  Google Scholar 

  • Sang YF, Wang Z, Liu C (2012a) Period identification in hydrologic time series using empirical mode decomposition and maximum entropy spectral analysis. J Hydrol 424:154–164

    Article  Google Scholar 

  • Sang YF, Wang Z, Li Z, Liu C, Liu X (2012b) Investigation into the daily precipitation variability in the Yangtze River Delta, China. Hydrol Process. doi:10.1002/hyp.9202

  • Shi J, Cui LL, Zhou WJ (2008) Change trend of climatic factors in the Yangtze River Delta from 1959 to 2005. Resour Sci 30(12):1803–1808 (in Chinese with English abstract)

    Google Scholar 

  • Soofi E (1997) Information theoretic regression methods. In: Fomby T, Carter Hill R (eds) Advances in econometrics—applying maximum entropy to econometric problems, vol. 12. Jai, London

    Google Scholar 

  • Svensson C (1999) Empirical orthogonal function analysis of daily rainfall in the upper reaches of the Huai River basin, China. Theor Appl Climatol 62:147–161

    Article  Google Scholar 

  • Torrence C, Compo GP (1998) A practical guide to wavelet analysis. Bull Am Meteorol Soc 79:61–78

    Article  Google Scholar 

  • Verschuren D, Laird KR, Cumming BF (2000) Rainfall and drought in equatorial least Africa during the past 1,100 years. Science 289(5487):2068–2074

    Article  Google Scholar 

  • Wagener T, Gupta HV (2005) Model identification for hydrological forecasting under uncertainty. Stoch Environ Res Risk Assess 19:378–387

    Article  Google Scholar 

  • Wang XL, Zwiers FW (1999) Interannual variability of precipitation in an ensemble of AMIP climate simulations conducted with the CCC GCM2. J Climate 12(5):1322–1335

    Article  Google Scholar 

  • Xie ZQ, Du Y, Zeng Y, Yan ML, Zhu CY (2010) Accelerated human activities affecting the spatial pattern of temperature in the Yangtze River Delta. Quat Inter 226:112–121

    Article  Google Scholar 

  • Xu Y, Xu J, Ding J, Chen Y, Yin Y, Zhang X (2010) Impacts of urbanization on hydrology in the Yangtze River Delta, China. Water Sci Technol 62:1221–1229

    Article  Google Scholar 

  • Yarnal B, Johnson DL, Frakes BJ, Bowles GI, Pascale P (1997) The flood of '96 and its socioeconomic impacts in the Susquehanna River Basin. J Am Water Resour Assoc 33:1299–1312

    Article  Google Scholar 

  • Zhang YC (1991) Complexity and 1/f noise: a phase space approach. J Phys I Fr 1:971–977

    Article  Google Scholar 

  • Zhang Q, Liu CL, Xu CY, Xu YP, Jiang T (2006) Observed trends of annual maximum water level and streamflow during past 130 years in the Yangtze River basin, China. J Hydrol 324:255–265

    Article  Google Scholar 

  • Zhang Q, Xu CY, Zhang Z, Chen YD, Liu CL (2009) Spatial and temporal variability of precipitation over China, 1951–2005. Theor Appl Climatol 95:53–68

    Article  Google Scholar 

  • Zhang N, Gao Z, Wang X, Chen Y (2010) Modeling the impact of urbanization on the local and regional climate in Yangtze River Delta, China. Theor Appl Climatol 102:331–342

    Article  Google Scholar 

  • Zunino L, Perez DG, Garavaglia M, Rosso OA (2007) Wavelet entropy of stochastic processes. Phys A 379:503–512

    Article  Google Scholar 

Download references

Acknowledgments

The author gratefully acknowledged the most appropriate comments and suggestions given by the Editor-in-Chief, Hartmut Graßl, and the anonymous reviewers. The author also thanked Ms. Feifei Liu for her assistance in preparation of the manuscript. This project was financially supported by the National Natural Science Foundation of China (no. 40971023) and the Water Resources Public-Welfare Projects (no. 200901042 and 201201072).

Author information

Authors and Affiliations

  1. Key Laboratory of Water Cycle & Related Land Surface Processes, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, 100101, China

    Yan-Fang Sang

  2. Center for Water Resources Research, Chinese Academy of Sciences, Beijing, 100101, China

    Yan-Fang Sang

Authors
  1. Yan-Fang Sang
    View author publications

    You can also search for this author inPubMed Google Scholar

Corresponding author

Correspondence to Yan-Fang Sang.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Sang, YF. Wavelet entropy-based investigation into the daily precipitation variability in the Yangtze River Delta, China, with rapid urbanizations. Theor Appl Climatol 111, 361–370 (2013). https://doi.org/10.1007/s00704-012-0671-5

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00704-012-0671-5

Keywords