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Complexity analyses of Godavari and Krishna river streamflow using the concept of entropy

Wybrane pełne teksty z tego czasopisma
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Języki publikacji
EN
Abstrakty
EN
The hydrological regime in both the Godavari and Krishna River has been altered due to both human-induced and environmental changes. The present study utilizes the sample entropy and its more generalized approach known as multiscale entropy to investigate the temporal and spatial distribution of complexity and quantify them using SampEn values. Daily streamflow for five stations, three from Godavari River (Dhalegaon, Nowrangpur, and Polavaram), and two from Krishna River (Yadgir and K. Agraharam), was analysed for the complexity analyses. Trends in the streamflow for the selected gauging stations and their annual entropy values have also been evaluated using the Mann–Kendall test. The trend results revealed that three (Dhalegaon and Nowrangpur in Godavari basin and Yadgir in Krishna basin) out of five stations showed significant decreasing trends for both monthly and annual streamflow series. The declining trend in streamflow could be attributed to both anthropogenic (reservoir operation, increased water abstraction, etc.) and climatic (change in monsoon rainfall, temperature, etc.) factors. The most significant reduction in annual streamflow during the post-impact period was observed at Dhalegaon station in Godavari Basin (from 53,573 to 19,555 m3/s) signifying maximum alteration in annual flow regime. The entropy analysis results of streamflow showed that there was obvious spatial and temporal variation in the complexity, as indicated by the annual SampEn values. Although not profound, a negative correlation exists between the annual runoff and SampEn values (highest −0.42 at K. Agraharam) and hence a reverse correspondence exists between them. In MSE analysis, the original streamflow series increased with time scale (up to 30 days was chosen for this study), whereas entropy decreased with an increased time scale. Due to the fully operational state of the dams upstream of the gauging stations, the entropy values during the post-impact period were less the pre-impact period. The present study can be used as a scientific reference to use information science to detect hydrologic alterations in the river basins. Future studies should focus on considering both climatic and land-use changes in conjunction with the human-induced changes for more comprehensive river system disorder analysis.
Czasopismo
Rocznik
Strony
2325--2338
Opis fizyczny
Bibliogr. 77 poz.
Twórcy
  • Department of Hydrology, Indian Institute of Technology, Roorkee, India
  • Department of Hydrology, Indian Institute of Technology, Roorkee, India
Bibliografia
  • 1. Abeysingha NS, Rajapaksha URLN (2020) SPI-based spatiotemporal drought over Sri Lanka. Adv Meteorol 2020:9753279
  • 2. Aires URV, da Silva DD, Moreira MC, Ribeiro CAAS, Ribeiro CBDM (2020) The use of the normalized difference vegetation index to analyse the influence of vegetation cover changes on the streamflow in the Manhuaçu river basin Brazil. Water Resour Manag 34(6):1933–1949
  • 3. Arthington, A., 2012. Environmental flows: saving rivers in the third millennium. University of California Press, p 4.
  • 4. Arthington A, Naiman R, Mcclain M, Nilsson C (2010) Preserving the biodiversity and ecological services of rivers: new challenges and research opportunities. Freshw Biol 55:1–16
  • 5. Asfaw A, Simane B, Hassen A, Bantider A (2018) Variability and time series trend analysis of rainfall and temperature in northcentral Ethiopia: a case study in Woleka sub-basin. Weather Clim Extremes 19:29–41
  • 6. Braga AC, Alves LGA, Costa LS, Ribeiro AA, De Jesus MMA, Tateishi AA, Ribeiro HV (2016) Characterization of river flow fluctuations via horizontal visibility graphs. Phys A 444:1003–1011
  • 7. Bunn SE, Arthington AH (2002) Basic principles and ecological consequences of altered flow regimes for aquatic biodiversity. Environ Manage 30(4):492–507
  • 8. Chen F, He Q, Bakytbek E, Yu S, Zhang R (2017) Reconstruction of a long streamflow record using tree rings in the upper Kurshab River (Pamir-Alai Mountains) and its application to water resources management. Int J Water Resour Dev 33(6):976–986
  • 9. Chou CM (2012) Applying multiscale entropy to the complexity analysis of rainfall-runoff relationships. Entropy 14(5):945–957
  • 10. Chou CM (2014) Complexity analysis of rainfall and runoff time series based on sample entropy in different temporal scales. Stoch Env Res Risk Assess 28(6):1401–1408
  • 11. Costa M, Goldberger AL, Peng CK (2002) Multiscale entropy analysis of complex physiologic time series. Phys Rev Lett 89(6):068102
  • 12. Costa M, Peng CK, Goldberger AL, Hausdorff JM (2003) Multiscale entropy analysis of human gait dynamics. Phys A 330(1–2):53–60
  • 13. Costigan KH, Daniels MD (2012) Damming the prairie: human alteration of Great Plains River regimes. J Hydrol 444–445:90–99
  • 14. de Carvalho Barreto ID, Stosic T, Filho MC, Delrieux C, Singh VP, Stosic B (2020) Complexity analyses of Sao Francisco river streamflow: influence of dams and reservoirs. J Hydrol Eng 25(10):05020036
  • 15. Delgado-Bonal A, Marshak A (2019) Approximate entropy and sample entropy: a comprehensive tutorial. Entropy 21(6):541
  • 16. Fang K, Sivakumar B, Woldemeskel FM (2017) Complex networks, community structure, and catchment classification in a large-scale river basin. J Hydrol 545:478–493
  • 17. Forootan E (2019) Analysis of trends of hydrologic and climatic variables. Soil Water Res 14(3):163–171
  • 18. Gao Y, Vogel RM, Kroll CN, Poff NL, Olden JD (2009) Development of representative indicators of hydrologic alteration. J Hydrol 374(1–2):136–147
  • 19. Graf WL (2006) Downstream hydrologic and geomorphic effects of large dams on American rivers. Geomorphology 79:336–360
  • 20. Groombridge B, Jenkins MD (1998) Freshwater biodiversity: a preliminary global assessment. UNEP World Conservation Monitoring Centre
  • 21. Guzman-Vargas L, Ramírez-Rojas A, Angulo-Brown F (2008) Multiscale entropy analysis of electroseismic time series. Nat Hazard 8(4):855–860
  • 22. Han H, Hou J, Huang M, Li Z, Xu K, Zhang D, Bai G, Wang C (2020) Impact of soil and water conservation measures and precipitation on streamflow in the middle and lower reaches of the Hulu River Basin China. Catena 195:104792
  • 23. Hu M, Hua Q, Zhou H, Wu Z, Wu X (2015) The effect of dams on the larval abundance and composition of four carp species in key river systems in China. Environ Biol Fishes 98(4):1201–1205. https://doi.org/10.1007/s10641-014-0342-8
  • 24. Huang F, Li F, Zhang N, Chen Q, Qian B, Guo L, Xia Z (2017) A histogram comparison approach for assessing hydrologic regime alteration. River Res Appl 33(5):809–822
  • 25. Huang F, Xia Z, Zhang N, Zhang Y, Li J (2011) Flow-complexity analysis of the upper reaches of the Yangtze river China. J Hydrol Eng 16(11):914–919
  • 26. Jager HI, Smith BT (2008) Sustainable reservoir operation: Can we generate hydropower and preserve ecosystem values? River Res Appl 24:340–352
  • 27. Jain SK, Kumar P (2014) Environmental flows in India: towards sustainable water management. Hydrol Sci J 59(3–4):751–769
  • 28. Jiang L, Ban X, Wang X, Cai X (2014) Assessment of hydrologic alterations caused by the Three Gorges Dam in the middle and lower reaches of Yangtze River, China. Water 6(5):1419–1434. https://doi.org/10.3390/w6051419
  • 29. Jovanovic T, Mejia A, Siddique R, Gironas JA (2014) Statistical complexity in the hydrological information from urbanizing basins. AGUFM 2014:H42E
  • 30. 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 Atmos 111(D1)
  • 31. Kendall MG (1975) Rank correlation methods, book series, Charles Griffin
  • 32. Kroll CN, Croteau KE, Vogel RM (2015) Hypothesis tests for hydrologic alteration. J Hydrol 530:117–126
  • 33. Li X, Williams MW (2008) Snowmelt runoff modelling in an arid mountain watershed, Tarim basin China. Hydrological Processes 22(19):3931–3940
  • 34. Li Z, Zhang YK (2008) Multiscale entropy analysis of Mississippi River flow. Stoch Env Res Risk Assess 22(4):507–512
  • 35. Li S, Qiaofu Z, Shaohong W, Erfu D (2006) Measurement of climate complexity using sample entropy. Int J Climatol 26(15):2131–2139
  • 36. Li Z, Zheng FL, Liu WZ, Flanagan DC (2010) Spatial distribution and temporal trends of extreme temperature and precipitation events on the Loess Plateau of China during 1961–2007. Quatern Int 226(1–2):92–100
  • 37. Li J, Dong S, Liu S, Yang Z, Peng M, Zhao C (2013) Effects of cascading hydropower dams on the composition, biomass and biological integrity of phytoplankton assemblages in the middle Lancang-Mekong River. Ecol Eng 60:316–324
  • 38. Liang L, Li L, Zhang L, Li J, Li B (2008) Sensitivity of penman-monteith reference crop evapotranspiration in Tao river basin of north-eastern China. Chin Geogra Sci 18(4):340–347
  • 39. Liu C, Gao R (2017) Multiscale entropy analysis of the differential RR interval time series signal and its application in detecting congestive heart failure. Entropy 19(6):251
  • 40. Liu D, Cheng C, Fu Q, Zhang Y, Hu Y, Zhao D, Khan MI, Faiz MA (2018) Complexity measurement of precipitation series in urban areas based on particle swarm optimized multiscale entropy. Arab J Geosci 11(5):83
  • 41. Lytle DA, Poff NL (2004) Adaptation to natural flow regimes. Trends Ecol Evol 19:94–100
  • 42. Mann HB (1945) Nonparametric tests against trend. Econometrica 13(3):245–259
  • 43. Mulligan M, van Soesbergen A, Sáenz L (2020) GOODD, a global dataset of more than 38,000 georeferenced dams. Sci Data 7(1):1–8
  • 44. Nilsson C, Reidy CA, Dynesius M, Revenga C (2005) Fragmentation and flow regulation of the world’s large river systems. Science 308(5720):405–408
  • 45. Phuong DND, Tram VNQ, Nhat TT, Ly TD, Loi NK (2020) Hydro-meteorological trend analysis using the Mann-Kendall and innovative-Şen methodologies: a case study. Int J Global Warm 20(2):145–164
  • 46. Pincus SM (1991) Approximate entropy as a measure of system complexity. Proc Natl Acad Sci 88(6):2297–2301
  • 47. Poff NL, Zimmerman JK (2010) Ecological responses to altered flow regimes: a literature review to inform the science and management of environmental flows. Freshw Biol 55(1):194–205
  • 48. Poff NL, Allan JD, Bain MB, Karr JR, Prestegard BD, Richter BD, Sparks RE, Stromberg JC (1997) The natural flow regime: a paradigm for river conservation and restoration. Bioscience 47:769–784
  • 49. Porporato A, Ridolfi L (1996) Clues to the existence of deterministic chaos in river flow. Int J Mod Phys B 10(15):1821–1862
  • 50. Rego CRC, Frota HO, Gusmão MS (2013) Multifractality of Brazilian rivers. J Hydrol 495:208–215
  • 51. Richman JS, Moorman JR (2000) Physiological time-series analysis using approximate entropy and sample entropy. Am J Physiol-Heart Circ Physiol 278(6):H2039–H2049
  • 52. Richter BD, Thomas GA (2007) Restoring environmental flows by modifying dam operations. Ecol Soc 12:1–26
  • 53. Richter BD, Baumgartner JV, Powell J, Braun DP (1996) A method for assessing hydrologic alteration within ecosystems. Conserv Biol 10(4):1163–1174
  • 54. Ru HJ, Wang HJ, Zhao WH, Shen YQ, Wang Y, Zhang XK (2010) Fishes in the mainstream of the Yellow River: assemblage characteristics and historical changes. Biodivers Sci 18(2):169–174. https://doi.org/10.3724/SP.J.1003.2010.179
  • 55. Singh, R.K. and Jain, M.K., 2020. Reappraisal of hydrologic alterations in the Roanoke River basin using extended data and improved RVA method. Int J Environ Sci Technol, pp.1–24.
  • 56. Sivakumar B (2009) Nonlinear dynamics and chaos in hydrologic systems: latest developments and a look forward. Stoch Env Res Risk Assess 23(7):1027–1036
  • 57. Stanford JA, Ward JV, Liss WJ, Frissell CA, Williams RN, Lichatowich JA, Coutant CC (1996) A general protocol for restoration of regulated rivers. River Res Appl 12(4–5):391–413. https://doi.org/10.1002/(SICI)1099-1646(199607)12:4/5%3c391:AID-RRR436%3e3.0.CO;2-4
  • 58. Stosic T, Telesca L, de Souza Ferreira DV, Stosic B (2016b) Investigating anthropically induced effects in streamflow dynamics by using permutation entropy and statistical complexity analysis: a case study. J Hydrol 540:1136–1145
  • 59. Tan X, Li Y, Li X, Li J, Wang C (2012) The status of fish spawning ground in the East River with cascade dams’ duress. J Lake Sci 24(3):443–449
  • 60. Wang J, Huang J, Wu J, Han X, Lin G (2010) Ecological consequences of the Three Gorges Dam: insularization affects foraging behavior and dynamics of rodent populations. Front Ecol Environ 8(1):13–19
  • 61. Wang D, Wu J, Wang Y et al (2012) The study and application of information entropy theory in water system. Waterpower Press, Beijing, pp 31–42 (In Chinese)
  • 62. Wang W, Wang D, Singh VP, Wang Y, Wu J, Wang L, Zou X, Liu J, Zou Y, He R (2018) Optimization of rainfall networks using information entropy and temporal variability analysis. J Hydrol 559:136–155
  • 63. Wang Y, Tao Y, Sheng D, Zhou Y, Wang D, Shi X, Wu J, Ma X (2020) Quantifying the change in streamflow complexity in the Yangtze river. Environ Res 180:108833
  • 64. Watts RJ, Richter BD, Opperman JJ, Bowmer KH (2011) Dam reoperation in an era of climate change. Mar Freshw Res 62(3):321–327
  • 65. World Commission on Dams. (2000) Dams and development: a new framework for decision-making. Environ Manag Health 12:444–445
  • 66. Xavier SFA, da Silva Jale J, Stosic T, dos Santos CAC, Singh VP (2019) An application of sample entropy to precipitation in Paraíba State, Brazil. Theor Appl Climatol 136(1):429–440
  • 67. Yang SL, Zhang J, Zhu J, Smith JP, Dai SB, Gao A, Li P (2005) Impact of dams on Yangtze River sediment supply to the sea and delta intertidal wetland response. J Geophys Res Earth Surf 110(F3):247–275. https://doi.org/10.1029/2004JF000271
  • 68. Yang SL, Milliman JD, Li P, Xu K (2011) 50,000 dams later: Erosion of the Yangtze River and its delta. Global Planet Change 75(1–2):14–20. https://doi.org/10.1016/j.gloplacha.2010.09.006
  • 69. Yu M, Li Q, Lu G, Cai T, Xie W, Bai X (2013) Investigation into the impacts of the Gezhouba and the three gorges reservoirs on the flow regime of the Yangtze river. J Hydrol Eng 18(9):1098–1106
  • 70. Zhang Y, Xia J, Liang T, Shao Q (2010) Impact of water projects on river flow regimes and water quality in Huai River Basin. Water Resour Manage 24(5):889–908
  • 71. Zhang Q, Singh VP, Xu CY, Chen XH (2013) Abrupt behaviours of streamflow and sediment load variations of the Yangtze River basin. China Hydrol Process 27:444–452
  • 72. Zhang Q, Xu CY, Chen XH, Lu XX (2012a) Abrupt changes in the discharge and sediment load of the Pearl river China. Hydrol Process 26:1495–1508
  • 73. Zhang YY, Zhai XY, Shao QX, Yan ZQ (2015) Assessing temporal and spatial alterations of flow regimes in the regulated Huai river basin China. J Hydrol 529:384–397
  • 74. Zhang Q, Zhou Y, Singh VP, Chen X (2012b) The influence of dam and lakes on the Yangtze River streamflow: long-range correlation and complexity analyses. Hydrol Process 26(3):436–444
  • 75. Zhao G, Hörmann G, Fohrer N, Zhang Z, Zhai J (2010) Streamflow trends and climate variability impacts in Poyang Lake Basin, China. Water Resour Manage 24(4):689–706
  • 76. Zhou Y, Zhang Q, Li K, Chen X (2012) Hydrological effects of water reservoirs on hydrological processes in the East River (China) basin: complexity evaluations based on the multiscale entropy analysis. Hydrol Process 26(21):3253–3262
  • 77. Zhou Y, Zhang Q, Singh VP (2014) Fractal-based evaluation of the effect of water reservoirs on hydrological processes: the dams in the Yangtze River as a case study. Stoch Env Res Risk Assess 28(2):263–279
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-296496d4-e39b-4f79-9f96-d52960fbd39d
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