Skip to main content

On the detection and attribution of streamflow persistence of rivers in Peninsular India

Abstract

Persistence expressed by hurst exponent (H) is estimated for streamflows of 122 stations in the basins of Peninsular India by three methods at different aggregation scales (daily, monthly mean, monthly and annual maximum). Mean H values indicated long term persistence (LTP) and the data of more than 70% stations showed LTP for other temporal resolutions. H displayed negative correlation with time series length, mean annual and specific mean discharges, while no significant correlation with catchment area. Positive dependence was found between persistence of streamflow and different climatic attributes (rainfall; maximum, mean and minimum temperature) for daily and annual maximum datasets.

This is a preview of subscription content, access via your institution.

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

Data availability

The data that support the findings of this study are available on request from the corresponding author.

References

  • Adarsh S, Nagesh Kumar D, Deepthi B, Gayathri G, Aswathy SS, Bhagyasree S (2019) Multifractal characterization of meteorological drought in India using detrended fluctuation analysis. Int J Climatol 39(11):4234–4255

    Article  Google Scholar 

  • Adarsh S, Nourani V, Archana DS, Dharan DS (2020a) Multifractal description of rainfall fields over India. J Hydrol. https://doi.org/10.1016/j.jhydrol.2020.124913

    Article  Google Scholar 

  • Adarsh S, Dharan DS, Nandhu AR, Anand Vishnu B, Mohan VK, Watorek M (2020b) Multifractal description of streamflow and suspended sediment concentration data from Indian river basins. Acta Geophys 68:519–535

    Article  Google Scholar 

  • Adarsh S, Chavan SR, Ali M, Archana DS, Dharan DS, Khan MI (2021) Spatiotemporal variability of multifractal properties of fine resolution daily gridded rainfall fields over India. Nat Hazards. https://doi.org/10.1007/s11069-021-04523-0

    Article  Google Scholar 

  • Alves da Silva AS, Cunha Filho M, Simoes Cezar Menezes R, Stosic T, Stosic B (2020) Trends and persistence of dry-wet conditions in northeast Brazil. Atmosphere 11(10):1134

    Article  Google Scholar 

  • Bassingthwaighte JB, Raymond GM (1995) Evaluation of the dispersional analysis method for fractal time series. Ann Biomed Eng 23(4):491–505

    Article  Google Scholar 

  • Caccia DC, Percival D, Cannon MJ, Raymond G, Bassingthwaighte JB (1997) Analyzing exact fractal time series: evaluating dispersional analysis and rescaled range methods. Physica A Stat Mech Appl 246(3–4):609–632

    Article  Google Scholar 

  • Chakraborty S, Chattopadhyay S (2021) Exploring the Indian summer monsoon rainfall through multifractal detrended fluctuation analysis and the principle of entropy maximization. Earth Sci Inform 14(3):1571–1577

    Article  Google Scholar 

  • Chandrasekaran C, Poomalai P, Saminathan B, Suthanthiravel S, Sundaram K, Hakkim FFA (2019) An investigation on the relationship between the Hurst exponent and the predictability of a rainfall time series. Meteorol Appl 16(3):511–519

    Google Scholar 

  • Chiverton A, Hannaford J, Holman I, Corstanje R, Prudhomme C, Bloomfield J, Hess TM (2015) Which catchment characteristics control the temporal dependence structure of daily river flows? Hydrol Process 29(6):1353–1369

    Article  Google Scholar 

  • Dey P, Mujumdar PP (2018) Multiscale evolution of persistence of rainfall and Streamflow. Adv Wat Resour 121:285–330

    Article  Google Scholar 

  • Drożdż S, Minati L, Oświȩcimka P, Stanuszek M, Wątorek M, (2019) Signatures of the crypto-currency market decoupling from the Forex. Fut Internet 11(7):154

    Article  Google Scholar 

  • Ghosh S, Mujumdar PP (2007) Nonparametric methods for modeling GCM and scenario uncertainty in drought assessment. Water Resour Res 43:W07405. https://doi.org/10.1029/2006WR005351

    Article  Google Scholar 

  • Harman CJ, Troch PA, Sivapalan M (2011) Functional model of water balance variability at the catchment scale: 2 Elasticity of fast and slow runoff components to precipitation change in the continental United States. Wat Resour Res 47(2):4

    Article  Google Scholar 

  • Hirpa FA, Gebremichael M, Over TM (2010) River flow fluctuation analysis: effect of watershed area. Wat Resour Res. https://doi.org/10.1029/2009WR009000

    Article  Google Scholar 

  • Hurst HE (1951) Long-term storage capacity of reservoirs. Trans Am Soc Civil Eng 116:770–799

    Article  Google Scholar 

  • Kantelhardt JW, Koscielny-Bunde E, Rybski D, Braun P, Bunde A, Havlin S (2006) Long-term persistence and multifractality of precipitation and river runoff records. J Geophys Res 111:D01106. https://doi.org/10.1029/2005JD005881

    Article  Google Scholar 

  • López-Lambraño AA, Fuentes C, López-Ramos AA, Mata-Ramírez J, López-Lambraño M (2018) Spatial and temporal hurst exponent variability of rainfall series based on the climatological distribution in a semiarid region in Mexico. Atmósfera 31(3):199–219

    Article  Google Scholar 

  • Markonis Y, Moustakis Y, Nasika C, Sychova P, Dimitriadis P, Hanel M, Maca P, Papalexiou SM (2018) Global estimation of long-term persistence in annual river runoff. Adv Wat Resour 113:1–12

    Article  Google Scholar 

  • Pal S, Dutta S, Nasrin T, Chattopadhyay S (2020) Hurst exponent approach through rescaled range analysis to study the time series of summer monsoon rainfall over northeast India. Theoret Appl Climatol 142(1):581–587

    Article  Google Scholar 

  • Szolgayova E, Laaha G, Blöschl G, Bucher C (2014) Factors influencing long range dependence in streamflow of European rivers. Hydrol Process 28(4):1573–1586

    Article  Google Scholar 

  • Taqqu MS, Teverovsky V, Willinger W (1995) Estimators for long-range dependence: an empirical study. Fractals 3:785–788

    Article  Google Scholar 

  • Tong S, Li X, Zhang J, Bao Y, Bao Y, Na L, Si A (2019) Spatial and temporal variability in extreme temperature and precipitation events in InnerMongolia (China) during 1960–2017. Sci Tot Environ 649:75–89

    Article  Google Scholar 

  • Villarini G, Wasko C (2021) Humans, climate and streamflow. Nat Clim Chang 11:725–726

    Article  Google Scholar 

  • Xu X, Yang D, Sivapalan M (2011) Assessing the impact of climate variability on catchment water balance and vegetation cover. Hydrol Earth Syst Sci Discuss 8:6291–6632

    Google Scholar 

Download references

Funding

No funding was received for performing this research work.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Sankaran Adarsh.

Ethics declarations

Conflict of interest

Authors declare that there is no conflict of interest.

Additional information

Edited by Dr. Michael Nones (CO-EDITOR-IN-CHIEF).

Supplementary Information

Below is the link to the electronic supplementary material.

Supplementary file1 (DOCX 849 KB)

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Adarsh, S., Nourani, V., Johnson, A. et al. On the detection and attribution of streamflow persistence of rivers in Peninsular India. Acta Geophys. 70, 1373–1383 (2022). https://doi.org/10.1007/s11600-022-00800-z

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11600-022-00800-z

Keywords

  • Hurst exponent
  • Persistence
  • Correlation
  • Catchment attributes
  • Climatic attributes