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Analysing trends in reference evapotranspiration and weather variables in the Tons River Basin in Central India

  • Darshana
  • Ashish Pandey
  • R. P. Pandey
Original Paper

Abstract

In this study, reference evapotranspiration (ETo) has been estimated using Penman–Monteith (PM) method on monthly time step. The monthly values have been subsequently used to estimate annual and seasonal ETo values. The trend analysis has been carried out for monthly, annual and seasonal ETo values for three meteorological stations namely Allahabad, Rewa and Satna located in the Tons River Basin in Central India. Further, the trend of weather variables that affect ETo have been examined using the Mann–Kendall test after removing the effect of significant lag-1 serial correlation from the time series using trend free-pre-whitening (TFPW) method. The magnitude of trends has been calculated using Sen’s slope estimator. Almost all the months show the significant decreasing trend in ETo values at a significance level of 1, 5 and 10 %. The significant decreasing trends were also found in annual and seasonal ETo values during the period of analysis. The magnitude of decrease in annual ETo varied from −1.75 to −8.98 mm/year. On the seasonal scale, stronger decreasing trends were identified in ETo in pre monsoon and monsoon season as compare to that of winter and post monsoon season. The significant decreasing trends were found in monthly, annual and seasonal wind speed. However, significant increase was found in annual air temperature (maximum, minimum, mean and dew point temperature) and relative humidity. Using the sensitivity analysis, maximum temperature and net solar radiation was found to be the most dominant variables which influence the rate of annual ETo over all the stations.

Keywords

Reference evapotranspiration Mann–Kendall test Trends Weather variable Sensitivity analysis Tons River Basin Madhya Pradesh India 

Notes

Acknowledgments

The authors are thankful to the Department of Science and Technology (DST), New Delhi for providing financial support during the study period. We are also thankful to anonymous reviewers for their thoughtful suggestions to improve this manuscript significantly.

References

  1. Abdelhadi AW, Hata T, Tanakamaru H, Tada A, Tariq MA (2000) Estimation of crop water requirements in arid region using Penman–Monteith equation with derived crop coefficients: a case study on Acala cotton in Sudan Gezira irrigated scheme. Agric Water Manag 45:203–214CrossRefGoogle Scholar
  2. Allen RG, Pereira LS, Raes D, Smith M (1998) Crop evapotranspiration: guidelines for computing crop requirements. FAO irrigation and drainage paper no. 56. FAO, RomeGoogle Scholar
  3. Arora M, Goel NK, Singh P (2005) Evaluation of temperature trends over India. Hydrol Sci J 50(1):81–93CrossRefGoogle Scholar
  4. Bandyopadhayay A, Bhadra A, Raghuwanshi NS, Singh R (2009) Temporal trends in estimates of reference evapotranspiration over India. J Hydrol Eng 14(5):508–518CrossRefGoogle Scholar
  5. Beven K (1979) A sensitivity analysis of the Penman-Monteith actual evapotranspiration estimates. J Hydrol 44:169–190CrossRefGoogle Scholar
  6. Burn DH, Hesch NM (2007) Trends in evaporation for the Canadian Prairies. J Hydrol 336:61–73CrossRefGoogle Scholar
  7. Chattopadhyay N, Hulme M (1997) Evaporation and potential evapotranspiration in India under conditions of recent and future climate change. Agric Forest Meteorol 87:55–73CrossRefGoogle Scholar
  8. Chen D, Gao G, Xu CY, Guo J, Ren G (2005) Comparison of the Thornthwaite method and pan data with the standard Penman-Monteith estimates of reference evapotranspiration in China. Clim Res 28:123–132CrossRefGoogle Scholar
  9. Chen S, Liu Y, Thomas A (2006) Climatic change on the Tibetan Plateau: potential evapotranspiration trends from 1961–2000. Clim Change 76(3):291–319Google Scholar
  10. Cohen S, Stahill G (1996) Contemporary climate change in the Jordan valley. J Appl Meteorol 35:1051–1058CrossRefGoogle Scholar
  11. Cohen S, Ianetz A, Stanhill G (2002) Evaporative climate changes at Bet Dagan, Israel, 1964–1998. Agric Forest Meteorol 111:83–91CrossRefGoogle Scholar
  12. Cong ZT, Yang DW (2009) Does evaporation paradox exist in China? Hydrol Earth Syst Sci 13:357–366CrossRefGoogle Scholar
  13. da Silva VPR (2004) On climate variability in Northeast of Brazil. J Arid Environ 58:575–596CrossRefGoogle Scholar
  14. Darshana, Pandey A, Gahalaut KPS, Pandey RP (2012). Spatial and temporal variability in maximum, minimum and mean air temperatures at Madhya Pradesh in central India. CR Geosci. doi: 10.1016/j.crte.2012.10.016
  15. Dash SK, Jenamani RK, Kalsi SR, Panda SK (2007) Some evidence of climate change in twentieth-century India. Clim Change 85:299–321CrossRefGoogle Scholar
  16. Dinpashoh Y, Jhajharia D, Fakheri-Fard A, Singh VP, Kahya E (2011) Trends in reference crop evapotranspiration over Iran. J Hydrol 399:422–433CrossRefGoogle Scholar
  17. Espadafor M, Lorite IJ, Gavilán P, Berengena J (2011) An analysis of the tendency of reference evapotranspiration estimates and other climate variables during the last 45 years in Southern Spain. Agric Water Manag 98:1045–1061CrossRefGoogle Scholar
  18. Gao G, Chen DL, Ren GY, Chen Y, Liao YM (2006) Spatial and temporal variations and controlling factors of potential evapotranspiration in China: 1956–2000. J Geogr Sci 16:3–12CrossRefGoogle Scholar
  19. Gavilan F, Castillo-Llanque F (2009) Estimating reference evapotranspiration with atmometers in a semiarid environment. Agric Water Manag 96:465–472CrossRefGoogle Scholar
  20. Ge G, Xu CY, Chen D, Singh VP (2012) Spatial and temporal characteristics of actual evapotranspiration over Haihe River Basin in China. Stoch Environ Res Risk Assess 26:655–669CrossRefGoogle Scholar
  21. Golubev VS, Lawrimore JH, Groisman PY, Speranskaya NA, Zhuravin SA, Menne MJ, Thomas C, Peterson TC, Malone RW (2001) Evaporation changes over the contiguous United States and the former USSR: a reassessment. Geophys Res Lett 28(13):2665–2668CrossRefGoogle Scholar
  22. Goyal RK (2004) Sensitivity of evapotranspiration to global warming: a case study of arid zone of Rajasthan (India). Agric Water Manag 69:1–11CrossRefGoogle Scholar
  23. Helsel DR (1987) Advantages of nonparametric procedures for analysis of water quality data. J Hydrol Sci 32(2):179–190CrossRefGoogle Scholar
  24. Hobbins MT, Ramîrez JA, Brown TC (2004) Trends in pan evaporation and actual evapotranspiration across the conterminous U.S.: paradoxical or complementary? Geophys Res Lett 31:L13503. doi: 10.1029/2004GL019846 CrossRefGoogle Scholar
  25. Hori ME, Ueda H (2006) Impact of global warming on the East Asian winter monsoon as revealed by nine coupled atmosphere ocean GCMs. Geophys Res Lett 33:L03713. doi: 10.1029/2005GL024961 CrossRefGoogle Scholar
  26. Ishak AM, Bray M, Remesan R, Han D (2010) Estimating reference evapotranspiration using numerical weather modelling. Hydrol Process 24:3490–3509CrossRefGoogle Scholar
  27. Jhajharia D, Dinpashoh Y, Kahya E, Singh VP, Fakheri-Fard A (2011) Trends in reference evapotranspiration in the humid region of North East India. Hydrol Process 26:421–435CrossRefGoogle Scholar
  28. Ji Y, Zhou G (2011) Important factors governing the incompatible trends of annual pan evaporation: evidence from a small scale region. Clim Change 106:303–314CrossRefGoogle Scholar
  29. Kang S, Gu B, Du T, Zhang J (2003) Crop coefficient and ratio of transpiration to evapotranspiration of winter wheat and maize in a semi-humid region. Agric Water Manag 59:239–254CrossRefGoogle Scholar
  30. Kendall MG (1975) Rank correlation methods, 4th edn. Charles Griffin, LondonGoogle Scholar
  31. Kite GW, Droogers P (2000) Comparing evapotranspiration estimates from satellites, hydrological models and field data. J Hydrol 229(1–2):3–18CrossRefGoogle Scholar
  32. Landeras G, Ortiz-Barredo A, López JJ (2008) Comparison of artificial neural network models and empirical and semi-empirical equations for daily reference evapotranspiration estimation in the Basque Country (Northern Spain). Agric Water Manag 95:553–565CrossRefGoogle Scholar
  33. Lenhart T, Eckhardt K, Fohrer N (2002) Comparison of two different approaches of sensitivity analysis. Phys Chem Earth 27:645–654CrossRefGoogle Scholar
  34. Liu B, Xu M, Henderson M, Gong W (2004) A spatial analysis of pan evaporation trends in China, 1955–2000. J Geophys Res 109:15102–15109CrossRefGoogle Scholar
  35. Lopes A, Saraiva J, Alcoforado MJ (2011) Urban boundary layer wind speed reduction in summer due to urban growth and environmental consequences in Lisbon. Environ Model Softw 26:242–243CrossRefGoogle Scholar
  36. Mann HB (1945) Non-parametric tests against trend. Econometrica 33:245–259CrossRefGoogle Scholar
  37. McCuen RH (1974) A sensitivity and error analysis of procedures used for estimating evaporation. Water Resour Bull 10:486–498CrossRefGoogle Scholar
  38. McVicar TR, Roderick ML (2010) Atmospheric science: winds of change. Nat Geosci 3(11):747–748CrossRefGoogle Scholar
  39. Pant GB, Kumar KR (1997) Climates of South Asia. Wiley, Chichester, p 320Google Scholar
  40. Peterson TC, Golubev VS, Groisman PY (1995) Evaporation losing its strength. Nature 377:687–688CrossRefGoogle Scholar
  41. Rayner DP (2007) Wind run changes: the dominant factor affecting pan evaporation trends in Australia. J Clim 20:3379–3394CrossRefGoogle Scholar
  42. Roderick ML, Farquhar GD (2004) Changes in Australian pan evaporation from 1970 to 2002. Int J Climatol 24:1077–1090CrossRefGoogle Scholar
  43. Roderick ML, Rotstayn LD, Farquhar GD, Hobbins MT (2007) On the attribution of changing pan evaporation. Geophys Res Lett 34:L17403CrossRefGoogle Scholar
  44. Sen PK (1968) Estimates of the regression coefficients based on Kendall’s tau. J Am Stat Assoc 63:1379–1389CrossRefGoogle Scholar
  45. Soltani E, Soltani A (2008) Climatic change of Khorasan, North-East of Iran, during 1950–2004. Res J Environ Sci 2(5):316–322CrossRefGoogle Scholar
  46. Song ZW, Zhang HL, Snyder RL, Anderson FE, Chen F (2010) Distribution and trends in reference evapotranspiration in the North China Plain. J Irrig Drain Eng 136(4):240–247CrossRefGoogle Scholar
  47. Tabari H, Talaee PH (2011) Recent trends of mean maximum and minimum air temperatures in the western half of Iran. Meteorol Atmos Phys 111:121–131CrossRefGoogle Scholar
  48. Tabari H, Grismer EM, Trajkovic S (2011a) Comparative analysis of 31 reference evapotranspiration methods under humid conditions. Irrig Sci. doi: 10.1007/s00271-011-0295-z Google Scholar
  49. Tabari T, Marofi S, Aeini A, Talaee PH, Mohammadi K (2011b) Trend analysis of reference evapotranspiration in the western half of Iran. Agric Forest Meteorol 151:128–136CrossRefGoogle Scholar
  50. Tebakari T, Yoshitani J, Suvanpimol C (2005) Time–space trend analysis in pan evaporation over kingdom of Thailand. J Hydrol Eng 10(3):205–215CrossRefGoogle Scholar
  51. Theil H (1950) A rank invariant method of linear and polynomial regression analysis, part 3. Neth Akad van Wettenschappen Proc 53:1397–1412Google Scholar
  52. Thomas A (2000) Spatial and temporal characteristics of potential evapotranspiration trends over China. Int J Climatol 20:381–396CrossRefGoogle Scholar
  53. Trajkovic S, Kolakovic S (2009) Wind-adjusted Turc equation for estimating reference evapotranspiration at humid European locations. Hydrol Res 40(1):45–52Google Scholar
  54. Vautard R, Cattiaux J, Yiou P, Thépaut JN, Ciais P (2010) Northern Hemisphere atmospheric stilling partly attributed to an increase in surface roughness. Nat Geosci 3:756–761CrossRefGoogle Scholar
  55. Wang W, Shao Q, Peng S, Zhang Z, Xing W, An G, Yong B (2011) Spatial and temporal characteristics of changes in precipitation during 1957–2007 in the Haihe River basin, China. Stoch Environ Res Risk Assess 25:881–895CrossRefGoogle Scholar
  56. Xu CY, Gong L, Jiang T, Chen D, Singh VP (2006) Analysis of spatial distribution and temporal trend of reference evapotranspiration and pan evaporation in Changjiang (Yangtze River) catchment. J Hydrol 27:81–93CrossRefGoogle Scholar
  57. Yang T, Chen X, Xu C-Y, Zhang Z-C (2009) Spatio-temporal changes of hydrological processes and underlying driving forces in Guizhou region, Southwest China. Stoch Environ Res Risk Assess 23:1071–1087CrossRefGoogle Scholar
  58. Yeşilırmak E (2012) Temporal changes of warm-season pan evaporation in a semi-arid Basin in Western Turkey. Stoch Environ Res Risk Assess. doi: 10.1007/s00477-012-0605-x Google Scholar
  59. Yin Y, Wu S, Chen G, Dai E (2010) Attribution analyses of potential evapotranspiration changes in China since the 1960s. Theor Appl Climatol 101:19–28CrossRefGoogle Scholar
  60. Yu PS, Yang TC, Chou CC (2002) Effects of climate change on evapotranspiration from paddy fields in southern Taiwan. Clim Change 54:165–179CrossRefGoogle Scholar
  61. Yue S, Pilon P, Phinney B, Cavadias G (2002) The influence of autocorrelation on the ability to detect trend in hydrological series. Hydrol Process 16:1807–1829CrossRefGoogle Scholar
  62. Zhang Y, Liu C, Tang Y, Yang Y (2007) Trends in pan evaporation and reference and actual evapotranspiration across the Tibetan Plateau. J Geophys Res 112:D12110. doi: 10.1029/2006JD008161 CrossRefGoogle Scholar
  63. Zhang X, Ren Y, Yin ZY, Lin Z, Zheng D (2009) Spatial and temporal variation patterns of reference evapotranspiration across the Qinghai-Tibetan Plateau during 1971–2004. J Geophys Res 114:D15105. doi: 10.1029/2009JD011753
  64. Zhang Q, Xu CY, Chen YQD, Ren LL (2011) Comparison of evopotranspiration variations between the Yellow River and Pearl River Basin, China. Stoch Environ Res Risk Assess 25:139–150CrossRefGoogle Scholar
  65. Zhang Z, Xu CY, El-Tahir MEH, Cao J, Singh VP (2012) Spatial and temporal variation of precipitation in Sudan and their possible causes during 1948–2005. Stoch Environ Res Risk Assess 26:429–441CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  1. 1.Department of Water Resources Development and ManagementIIT RoorkeeRoorkeeIndia
  2. 2.Department of Water Resources Development and ManagementIIT RoorkeeRoorkeeIndia
  3. 3.National Institute of HydrologyRoorkeeIndia

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