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Seasonality shift and streamfow fow variability trends in central India

Wybrane pełne teksty z tego czasopisma
Identyfikatory
Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
A better understanding of intra/inter-annual streamfow variability and trends enables more efective water resources planning and management for current and future needs. This paper investigates the variability and trends of streamfow data from fve stations (i.e. Ashti, Chindnar, Pathgudem, Polavaram, and Tekra) in Godavari river basin, India. The streamfow data were obtained from the Indian Central Water Commission and cover more than 30 years of mean daily records (i.e. 1972–2011). The streamfow data were statistically assessed using Gamma, Generalised Extreme Value and Normal distributions to under stand the probability distribution features of data at inter-annual time-scale. Quantifable changes in observed streamfow data were identifed by Sen’s slope method. Two other nonparametric, Mann–Kendall and Innovative Trend Analysis methods were also applied to validate fndings from Sen’s slope trend analysis. The mean fow discharge for each month (i.e. January to December), seasonal variation (i.e. Spring, Summer, Autumn, and Winter) as well as an annual mean, annual maximum and minimum fows were analysed for each station. The results show that three stations (i.e. Ashti, Tekra, and Polavaram) demonstrate an increasing trend, notably during Winter and Spring. In contrast, two other stations (i.e. Pathgudem, Chindnar) revealed a decreasing trend almost at all seasons. A signifcant decreasing trend was observed at all station over Summer and Autumn seasons. Notably, all stations showed a decreasing trend in maximum fows; remarkably, Tekra station revealed the highest decreasing magnitude. Signifcant decrease in minimum fows was observed in two stations only, Chindnar and Pathgudem. Findings resulted from this study might be useful for water managers and decision-makers to propose more sustainable water management recommendations and practices.
Czasopismo
Rocznik
Strony
1461--1475
Opis fizyczny
Bibliogr. 66 poz.
Twórcy
autor
  • CERIS, Instituto Superior Técnico, Universidade de Lisboa, Lisbon, Portugal
autor
  • College of Hydraulic and Environmental Engineering, China Three Gorges University, Yichang 443002, China
  • Department of Petroleum, Koya Technical Institute, Erbil Polytechnic University, Erbil, Kurdistan 44001, Iraq
  • Environmental Quality, Atmospheric Science and Climate Change Research Group, Ton Duc Thang University, Ho Chi Minh City, Vietnam
  • Faculty of Environment and Labour Safety, Ton Duc Thang University, Ho Chi Minh City, Vietnam
  • Group of Mathematical Modelling and Numerical Simulation (GMMNS), National University of Engineering (UNI), Lima, Peru
autor
  • Department of Hydrology, Indian Institute of Technology Roorkee, Roorkee, India
autor
  • Punjab Agricultural University, Regional Research Station, Bathinda- 151001, Punjab, India
  • Institute of Research and Development, Duy Tan University, Danang 550000, Vietnam
  • Faculty of Environmental and Chemical Engineering, Duy Tan University, Danang 550000, Vietnam
autor
  • Department of Hydrology, Indian Institute of Technology Roorkee, Roorkee, India
  • Ho Chi Minh City University of Technology (HUTECH) 475A, Dien Bien Phu, Ward 25, Binh Thanh District, Ho Chi Minh City, Vietnam
autor
  • Ho Chi Minh City University of Technology (HUTECH) 475A, Dien Bien Phu, Ward 25, Binh Thanh District, Ho Chi Minh City, Vietnam
autor
  • College of Hydraulic and Environmental Engineering, China Three Gorges University, Yichang 443002, China
  • Hubei Provincial Collaborative Innovation Center for Water Security, Wuhan 430070, Chin
Bibliografia
  • 1. Abghari H, Tabari H, Hosseinzadeh Talaee P (2013) River flow trends in the west of Iran during the past 40 years: impact of precipitation variability. Global Planet Change 101:52–60. https://doi.org/10.1016/j.gloplacha.2012.12.003
  • 2. Adamowski K, Liang G-C, Patry GG (1998) Annual maxima and partial duration flood series analysis by parametric and non-parametric methods. Hydrol Process 12:1685–1699
  • 3. Ahmed K, Shahid S, Chung E-S, Ismail T, Wang X-J (2017) Spatial distribution of secular trends in annual and seasonal precipitation over. Pak Clim Res 74:95–107
  • 4. Ali R, Chunju Z, Yihon Z, Nawaz N (2018) The challenges of water resources availability and development in Huai River Basin, China. Curr J Appl Sci Technol 25:1–13. https://doi.org/10.9734/cjast/2017/38191
  • 5. Ali R, Ismael A, Heryansyah A, Nawaz N (2019a) Long term historic changes in the flow of lesser zab river, iraq. Hydrology 6:22
  • 6. Ali R, Kuriqi A, Abubaker S, Kisi O (2019b) Hydrologic alteration at the upper and middle part of the Yangtze river, China: towards sustainable water resource management under increasing water exploitation. Sustainability 11:5176
  • 7. Ali R, Kuriqi A, Abubaker S, Kisi O (2019c) Hydrologic alteration at the upper and middle part of the Yangtze River, China: towards sustainable water resource management under increasing water exploitation. Sustainability. https://doi.org/10.3390/su11195176
  • 8. Ali R, Kuriqi A, Abubaker S, Kisi O (2019d) Long-term trends and seasonality detection of the observed flow in Yangtze River using Mann–Kendall and Sen’s innovative trend method. Water 11:1855
  • 9. Ali R, Kuriqi A, Kisi O (2020) Human–environment natural disasters interconnection in China: a review. Climate. https://doi.org/10.3390/cli8040048
  • 10. Allan RP, Liepert BG (2010) Anticipated changes in the global atmospheric water cycle. Environ Res Lett 5:025201
  • 11. Ardıçlıoğlu M, Kuriqi A (2019) Calibration of channel roughness in intermittent rivers using HEC-RAS model: case of Sarimsakli creek, Turkey. SN Appl Sci. https://doi.org/10.1007/s42452-019-1141-9
  • 12. Ay M, Kisi O (2014) Investigation of trend analysis of monthly total precipitation by an innovative method. Theor Appl Climatol 120:617–629. https://doi.org/10.1007/s00704-014-1198-8
  • 13. Brunetti M, Caloiero T, Coscarelli R, Gullà G, Nanni T, Simolo C (2012) Precipitation variability and change in the Calabria region (Italy) from a high resolution daily dataset. Int J Climatol 32:57–73
  • 14. Caloiero T, Coscarelli R, Ferrari E (2018) Application of the innovative trend analysis method for the trend analysis of rainfall anomalies in southern Italy. Water Resour Manag 32:4971–4983. https://doi.org/10.1007/s11269-018-2117-z
  • 15. Chandole V, Joshi GS, Rana SC (2019) Spatio-temporal trend detection of hydro-meteorological parameters for climate change assessment in Lower Tapi river basin of Gujarat state, India. J Atmos Sol Terr Phys 195:105130
  • 16. Chaturvedi RK, Joshi J, Jayaraman M, Bala G, Ravindranath N (2012) Multi-model climate change projections for India under representative concentration pathways. Curr Sci 103:791–802
  • 17. Cui L, Wang L, Lai Z, Tian Q, Liu W, Li J (2017) Innovative trend analysis of annual and seasonal air temperature and rainfall in the Yangtze River Basin, China during 1960–2015. J Atmos Sol Terr Phys 164:48–59
  • 18. Demir V, Kisi O (2016) Comparison of Mann–Kendall and innovative trend method (Şen trend) for monthly total precipitation (Middle Black Sea Region, Turkey)
  • 19. Deshpande N, Kothawale D, Kulkarni A (2016) Changes in climate extremes over major river basins of India. Int J Climatol 36:4548–4559
  • 20. Falkenmark M (2010) The greatest water problem: the inability to link environmental security, water security and food security. Int J Water Resour Dev 17:539–554. https://doi.org/10.1080/07900620120094073
  • 21. Galeati G (1990) A comparison of parametric and non-parametric methods for runoff forecasting. Hydrol Sci J 35:79–94. https://doi.org/10.1080/02626669009492406
  • 22. Gao C, Liu L, Ma D, He K, Xu Y-P (2019) Assessing responses of hydrological processes to climate change over the southeastern Tibetan Plateau based on resampling of future climate scenarios. Sci Total Environ 664:737–752
  • 23. Grimaldi S, Petroselli A, Salvadori G, De Michele C (2016) Catchment compatibility via copulas: a non-parametric study of the dependence structures of hydrological responses. Adv Water Resour 90:116–133. https://doi.org/10.1016/j.advwatres.2016.02.003
  • 24. Güçlü YS, Dabanlı İ, Şişman E, Şen Z (2019) Air quality (AQ) identification by innovative trend diagram and AQ index combinations in Istanbul megacity. Atmos Pollut Res 10:88–96. https://doi.org/10.1016/j.apr.2018.06.011
  • 25. Gupta V, Jain MK (2018) Investigation of multi-model spatiotemporal mesoscale drought projections over India under climate change scenario. J Hydrol 567:489–509
  • 26. Gupta V, Jain MK (2020) Impact of ENSO, global warming, and land surface elevation on extreme precipitation in India. J Hydrol Eng 25:05019032
  • 27. Hansen J, Sato M, Ruedy R, Lo K, Lea DW, Medina-Elizade M (2006) Global temperature change. PNAS 103:14288–14293
  • 28. Hollert H (2013) Processes and environmental quality in the Yangtze River system. Springer, Berlin
  • 29. IPCC (2018) Global warming of 1.5°C. An IPCC special report on the impacts of global warming of 1.5°C above pre-industrial levels and related global greenhouse gas emission pathways, in the context of strengthening the global response to the threat of climate change, sustainable development, and efforts to eradicate poverty. Intergovernmental Panel on Climate Change, Geneva, Switzerland
  • 30. Jena PP, Chatterjee C, Pradhan G, Mishra A (2014) Are recent frequent high floods in Mahanadi basin in eastern India due to increase in extreme rainfalls? J Hydrol 517:847–862
  • 31. Kale GD, Kumar DN (2018) Trend detection analysis of seasonal rainfall of homogeneous regions and all India, prepared by using individual month rainfall values. Water Conserv Sci Eng 3:129–138
  • 32. Kang H, Sridhar V (2017) Combined statistical and spatially distributed hydrological model for evaluating future drought indices in Virginia. J Hydrol Reg Stud 12:253–272
  • 33. Khan N, Shahid S, Chung ES, Kim S, Ali R (2019a) Influence of surface water bodies on the land surface temperature of Bangladesh. Sustainability. https://doi.org/10.3390/su11236754
  • 34. Khan N, Shahid S, Ismail T, Ahmed K, Nawaz N (2019b) Trends in heat wave related indices in Pakistan. Stoch Environ Res Risk Assess 33:287–302
  • 35. Khan N, Shahid S, Ahmed K, Wang X, Ali R, Ismail T, Nawaz N (2020) Selection of GCMs for the projection of spatial distribution of heat waves in Pakistan. Atmos Res. https://doi.org/10.1016/j.atmosres.2019.104688
  • 36. Krishnakumar K, Rao GP, Gopakumar C (2009) Rainfall trends in twentieth century over Kerala, India. Atmos Environ 43:1940–1944
  • 37. Kuriqi A, Koçileri G, Ardiçlioğlu M (2019a) Potential of Meyer-Peter and Müller approach for estimation of bed-load sediment transport under different hydraulic regimes. Model Earth Syst Environ 6:129–137. https://doi.org/10.1007/s40808-019-00665-0
  • 38. Kuriqi A, Pinheiro AN, Sordo-Ward A, Garrote L (2019b) Flow regime aspects in determining environmental flows and maximising energy production at run-of-river hydropower plants. Appl Energy. https://doi.org/10.1016/j.apenergy.2019.113980
  • 39. Kuriqi A, Pinheiro AN, Sordo-Ward A, Garrote L (2019c) Influence of hydrologically based environmental flow methods on flow alteration and energy production in a run-of-river hydropower plant. J Clean Prod 232:1028–1042. https://doi.org/10.1016/j.jclepro.2019.05.358
  • 40. Mittal N, Bhave AG, Mishra A, Singh R (2015) Impact of human intervention and climate change on natural flow regime. Water Resour Manag 30:685–699. https://doi.org/10.1007/s11269-015-1185-6
  • 41. Naresh Kumar M, Murthy C, Sesha Sai M, Roy P (2012) Spatiotemporal analysis of meteorological drought variability in the Indian region using standardized precipitation index. Meteorol Appl 19:256–264
  • 42. Noor M, Ismail T, Chung E-S, Shahid S, Sung JH (2018) Uncertainty in rainfall intensity duration frequency curves of peninsular Malaysia under changing climate scenarios. Water 10:1750
  • 43. Othman Ali R, Chunju Z, Yihon Z, Imran Azam M (2018a) The effects of human activities, climatic conditions and land-use factors on water resources development in huai river basin northeast china. Int J Hydrol. https://doi.org/10.15406/ijh.2018.02.00059
  • 44. Othman Ali R, Chunjua Z, Yihona Z, Ping L, Heryansyaha A, Nawaz N (2018b) Impact of climatic change on water resources in Huia river basin, China. Int J Eng Technol. https://doi.org/10.14419/ijet.v7i4.15788
  • 45. Öztopal A, Şen Z (2017) Innovative trend methodology applications to precipitation records in Turkey. Water Resour Manag 31:727–737
  • 46. Pahl-Wostl C (2019) Governance of the water-energy-food security nexus: a multi-level coordination challenge. Environ Sci Policy 92:356–367. https://doi.org/10.1016/j.envsci.2017.07.017
  • 47. Piniewski M, Marcinkowski P, Kundzewicz ZW (2018) Trend detection in river flow indices in Poland. Acta Geophys 66:347–360
  • 48. Pradhan U, Wu Y, Shirodkar P, Zhang J, Zhang G (2014) Multi-proxy evidence for compositional change of organic matter in the largest tropical (peninsular) river basin of India. J Hydrol 519:999–1009
  • 49. Rajamani L (2009) India and climate change: what india wants, needs, and needs to do. India Rev 8:340–374. https://doi.org/10.1080/14736480903116842
  • 50. Razavi S, Vogel R (2018) Prewhitening of hydroclimatic time series? Implications for inferred change and variability across time scales. J Hydrol 557:109–115
  • 51. Sa’adi Z, Shahid S, Ismail T, Chung E-S, Wang X-J (2019) Trends analysis of rainfall and rainfall extremes in Sarawak, Malaysia using modified Mann–Kendall test. Meteorol Atmos Phys 131:263–277
  • 52. Sediqi MN et al (2019a) Spatio-temporal pattern in the changes in availability and sustainability of water resources in Afghanistan. Sustainability 11:5836
  • 53. Sediqi MN et al (2019b) Spatio-temporal pattern in the changes in availability and sustainability of water resources in Afghanistan. Sustainability. https://doi.org/10.3390/su11205836
  • 54. Sen P (1968) Estimates of the regression coefficient based on Kendall’s Tau. J Am Stat Assoc 63:1379–1389
  • 55. Şen Z (2012) Innovative trend analysis methodology. J Hydrol Eng 17:1042–1046
  • 56. Şen Z (2015) Innovative trend significance test and applications. Theor Appl Climatol 127:939–947. https://doi.org/10.1007/s00704-015-1681-x
  • 57. Sen Roy S, Balling RC (2007) Diurnal variations in summer season precipitation in India. Int J Climatol 27:969–976. https://doi.org/10.1002/joc.1458
  • 58. Sengupta A, Rajeevan M (2013) Uncertainty quantification and reliability analysis of CMIP5 projections for the Indian summer monsoon. Curr Sci 105:1692–1703
  • 59. Sharma PJ, Patel PL (2018) Rainfall trends over the past century for tropical climatic region in western India. EPiC Ser Eng 3:1935–1944
  • 60. Sharma S, Saha AK (2017) Statistical analysis of rainfall trends over Damodar River basin, India. Arab J Geosci 10:319
  • 61. Singh V, Sharma A, Goyal MK (2019) Projection of hydro-climatological changes over eastern Himalayan catchment by the evaluation of RegCM4 RCM and CMIP5 GCM models. Hydrol Res 50:117–137
  • 62. Sonali P, Kumar DN (2013) Review of trend detection methods and their application to detect temperature changes in India. J Hydrol 476:212–227
  • 63. Timbadiya P, Mirajkar A, Patel P, Porey P (2013) Identification of trend and probability distribution for time series of annual peak flow in Tapi Basin, India. ISH J Hydraul Eng 19:11–20
  • 64. Yue S, Wang C (2004) The Mann–Kendall test modified by effective sample size to detect trend in serially correlated hydrological series. Water Resour Manag 18:201–218
  • 65. Yue S, Pilon P, Cavadias G (2002) Power of the Mann–Kendall and Spearman’s rho tests for detecting monotonic trends in hydrological series. J Hydrol 259:254–271
  • 66. Zhang Q, Xu C-Y, Zhang Z, Chen YD, Liu C-l, Lin H (2008) Spatial and temporal variability of precipitation maxima during 1960–2005 in the Yangtze River basin and possible association with large-scale circulation. J Hydrol 353:215–227
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-6058c226-3d01-42c4-9c6d-a7d2d6efa7b7
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