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Persistence expressed by hurst exponent (H) is estimated for streamflow 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.
Wydawca
Czasopismo
Rocznik
Tom
Strony
1373--1383
Opis fizyczny
Bibliogr. 25 poz.
Twórcy
autor
- TKM College of Engineering, Kollam 691005, India
autor
- Center of Excellence in Hydroinformatics Faculty of Civil Engineering, University of Tabriz, Tabriz, Iran
autor
- TKM College of Engineering, Kollam 691005, India
autor
- TKM College of Engineering, Kollam 691005, India
autor
- TKM College of Engineering, Kollam 691005, India
autor
- TKM College of Engineering, Kollam 691005, India
Bibliografia
- 1. 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
- 2. 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
- 3. 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
- 4. 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
- 5. 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
- 6. Bassingthwaighte JB, Raymond GM (1995) Evaluation of the dispersional analysis method for fractal time series. Ann Biomed Eng 23(4):491–505
- 7. 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
- 8. 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
- 9. 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
- 10. 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
- 11. Dey P, Mujumdar PP (2018) Multiscale evolution of persistence of rainfall and Streamflow. Adv Wat Resour 121:285–330
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- 13. 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
- 14. 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
- 15. Hirpa FA, Gebremichael M, Over TM (2010) River flow fluctuation analysis: effect of watershed area. Wat Resour Res. https://doi.org/10.1029/2009WR009000
- 16. Hurst HE (1951) Long-term storage capacity of reservoirs. Trans Am Soc Civil Eng 116:770–799
- 17. 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
- 18. 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
- 19. 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
- 20. 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
- 21. 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
- 22. Taqqu MS, Teverovsky V, Willinger W (1995) Estimators for long-range dependence: an empirical study. Fractals 3:785–788
- 23. 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
- 24. Villarini G, Wasko C (2021) Humans, climate and streamflow. Nat Clim Chang 11:725–726
- 25. 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
Uwagi
PL
Opracowanie rekordu ze środków MEiN, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2022-2023).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-fa60a66a-3dde-4334-8cd9-076316ecadd7