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.
Having accurate and ample data on rains is the sole golden input for deciding ultimate success of any progressive efforts towards natural resource management. Ultimate conquest of any pertinent schemes on developing and managing watersheds, canals, commands, irrigation net-works, soil-erosion, soil-conservation, drylands, forests, pastures, livestock, land use changes and many ecology-based errands; is entirely governs by the precision, relevancy and quality of rainfall data. Even the ending success of present days smart hydrologic models, modelling entirely remains regulated by the precision & relevance of rainfall data used therein. Most commonly available rain data happens to be daily rain values. However, for precise planning at microscale, we need to have its finer sub-daily temporal distribution. Rainfall disaggregation is a newly emerging applied option where utilities of advanced stochastic architecture is utilized across the globe to offer desired location specific and even rainy day specific best possible temporal disaggregated outcomes. Present paper offers some of the crisped outcomes from a detailed study performed in Gujarat. The predictive ability of one of the most popular BLRP model in this regard is shared by incorporating its basic architecture followed by its predictive performances on randomised sample rainy days covering 6 explicit locations in middle Gujarat region of western India. Preliminary findings reported herein will serve as a food for thought for smarter ways of managing water, land, watersheds and ecology. The BLRP model for rainfall disaggregation has the potential to improve the accuracy of rainfall estimates, facilitate efficient water management, improve hydrological modeling, facilitate climate change analysis, and be cost-effective.
: Climatic change is one of the most important issues of present times, therefore, world-wide interest in global warming and climate change has led to numerous trend detection studies. Anthropogenic interference in the environment is one of the greatest causes of the process of climatic change in several regions of the world. This study focuses on the variability and trends of the mean annual, seasonal and monthly surface air temperature in Junagadh (Saurashtra region) of Gujarat, during the period 1980-2011. This study investigated monthly, seasonal and annual climatic variability in Junagadh (Saurashtra region) of Gujarat based on mean maximum, mean minimum and mean air temperatures. One of the main results of this study was the confirmation of a significant warming trend in average temperatures in Junagadh (Saurashtra region) of Gujarat. Analysis of maximum and minimum temperatures revealed a warming trend for the annual and all seasonal series. The warming trend for the summer and winter seasons was statistically significant at P < 0.01 level with a rate of increase of 0.006 C/year and less 0.055C/year. The air temperature time series were analyzed, so that the variability and trends can be described.
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