No abstract

This paper, therefore, attempts to study temporal variation in temperature over Junagadh (Saurashtra Region) of Gujarat, India, India, during the period 1980-2011. The long-term change in temperature has been evaluated by Mann-Kendall rank statistics and linear trend. An important aspect of the present study is the significant cooling trend in mean annual temperature, which is more predominant during winter season. The summer season also shows significant cooling trend due to slightly decrease in Tmax. This cooling trend in Junagadh (Saurashtra Region) Gujarat, India temperature is supported by studies conducted by other researchers (Rupa Kumar and Hingane, 1988). These authors studied the temperature for Junagadh (Saurashtra region) Gujarat, India during the period 1980-2007 and observed a cooling trend, but not significant at any level. Against this background, in the present study, temperature data during the period 1980-2011 have been studied. The result indicates significant slightly decrease in winter temperature at 0.01 level. This suggests that the last decade has witnessed a phenomenal epoch in temperature series, leading to a decreasing trend from non-significant to significant. Contrary to this, the monsoon season shows warming trend. This may be due to significant increase in the low cloud amount during this season. We are still a long way from understanding the complex interaction of many physical processes that determine the evolution of climate.

The reliability of estimates of reference evapotranspiration (ET0) using pan evaporation (Epan) depends on the accurate determination of pan coefficients (Kpan). Six ET0 models were evaluated for their usefulness using 33-year climatological dataset of a semi-arid region of the Gujarat state of India. The equations compared include Cuenca (1989), Allen and Pruitt (1991), Snyder (1992), Modified Snyder (Grismer et al., 2002), Orang (1998), and Pereira et al. (1995). The ET0 data, calculated using daily Kpan values from these equations, were compared to the Food and Agricultural Organization (FAO)-Penman-Monteith (FAO56-PM) method as a reference. Based on the visual comparison as well as from the statistical criteria, ET0 values computed using Modified Snyder and Orang model have very close agreement with the FAO56-PM method for daily, monthly, and annual estimates as compared to other approaches. The sequential performances of the explored models was found as: Modified Snyder (Eqn. 5) > Orang (Eqn. 6) > Cuenca Eqn. (2) > Allen & Pruitt (Eqn. 3) > Snyder (Eqn. 4) > Pereira et al. (Eqn. 7) model. Therefore, the Modified Snyder model (Grismer et al., 2002) could be recommended as the best model for ET0 computations under these prevailing climatic conditions for a semi arid region.

Trend analysis has become one of the most important issues in hydro-meteorological variables study due to climate change and the focus given to it in the recent past from the scientific community. In this study, long-term trends of rainfall are analyzed in eight stations located in semi-arid central Gujarat region, India by considering time series data of 116 years (1901-2016). Discrete wavelet transform (DWT) as a dyadic arrangement of continuous wavelet transformation combined with the widely applied and acknowledged Mann-Kendall (MK) trend analysis method were applied for analysis of trend and dominant periodicities in rainfall time series at monthly, annual and monsoonal time scales. Initially, rainfall time series applied in this study were decomposed using DWT to generate sub-time series at high and low frequencies, before applying the MK trend test. Further, the Sequential Mann-Kendall (SQMK) test was also applied to find out the trend changing points. The result showed that at the monthly annual and monsoon time scales, the trends in rainfall were significantly decreasing in most of the station. The 4-month and 8-month components were found as dominant at the monthly time series and the 2-year and 4-year component were found as dominant at the monsoon time series, whereas the 2-year components were observed as dominant in the annual time scale.