प्रपत्र-5.4-उत्तराखंड हिमालय में जलवायु परिवर्तन का अध्ययन - प्राचीन वर्षा के बदलते रुझान

Abstract

The subject area of climate change is vast, but the changing pattern of rainfall is a topic within this field that deserves urgent and systematic attention, since it affects the availability of freshwater, food production and the occurrence of water related disasters triggered by extreme events. The detection of trends in rainfall is essential for the assessment of the impacts of climate variability and change on the water resources of a region. Uttarakhand is a state in the northern part of India. It is often referred to as the "Land of the Gods" due to the many holy Hindu temples and pilgrimage centres found throughout the state. Two of the most important rivers in Hinduism originate in the region, the Ganga at Gangotri and the Yamuna at Yamunotri. The state is divided into two divisions, Garhwal and Kumaon, with a total of 13 districts. Uttarakhand has a total area of 53,484 km2, of which 93% is mountainous and 65% is covered by forest. Most of the northern part of the state is covered by high Himalayan peaks and glaciers. In June 2013, several days of extremely heavy rain caused devastating floods in the region, resulting in more than 5000 people missing and presumed dead. The present study aims to determine trends in the annual, seasonal and monthly rainfall over Uttarakhand State. Long term (1901-2013) gridded daily rainfall data at 0.25 deg grid have been used. Daily rainfall data at ten grid centre locations (five each in Garhwal and Kumaon divisions) in the vicinity of Haridwar, Tehri, Uttarkashi, Rudraprayag, Joshimath, Almora, Bageshwar, Munsiyari, Pithoragarh and Rudrapur have been processed and analysed for a period of 113 years (1901-2013). Historical trends in daily rainfall have been examined using parametric (regression analysis) and non-parametric (Mann-Kendall (MK) statistics). On the basis of regression and MK test, rising and falling trend in rainfall and anomalies at various stations have been analysed. The result shows that many of these variables demonstrate statistically significant changes occurred in last eleven decades.