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

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 ETₒvalues. The trend analysis has been carried out for monthly, annual and seasonal ETₒvalues fo...

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Veröffentlicht in:Stochastic environmental research and risk assessment 2013-08, Vol.27 (6), p.1407-1421
Hauptverfasser: Darshana, Pandey, Ashish, Pandey, R. P
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Sprache:eng
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Zusammenfassung: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 ETₒvalues. The trend analysis has been carried out for monthly, annual and seasonal ETₒvalues 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 ETₒhave 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 ETₒvalues at a significance level of 1, 5 and 10 %. The significant decreasing trends were also found in annual and seasonal ETₒvalues during the period of analysis. The magnitude of decrease in annual ETₒvaried from −1.75 to −8.98 mm/year. On the seasonal scale, stronger decreasing trends were identified in ETₒin 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 ETₒover all the stations.
ISSN:1436-3240
1436-3259
DOI:10.1007/s00477-012-0677-7