Abstract:
Assessment of climatic variability is an
important aspect in water resources management, adaptability
and reducing impact on agriculture production due to
changing climate. The intergovernmental panel on climate
change (IPCC) in their various reports indicated that the
global temperature is increasing due to emission of greenhouse
gases, industrialization, change in lifestyle and land-use/ landcover
change. These and natural forces have contributed to
change in earth’s climate over 20th century by warming of
land and ocean surface temperature, changing in spatial and
temporal pattern of precipitation, rising in sea levels and
increase in frequency and intensity of Al Nino. Various studies
in the past have confirmed that global temperature is rising
continuously since start of industrial age that may impact
surface runoff, groundwater, availability of water, water
quality, crop production and livelihood of society. Precipitation
being the primary input in hydrological cycle needs to be
investigated for possible climate change using GCMs/RCMs or
statistical analysis. In the present study, an attempt has been
made to identify significant trends in monthly, seasonal
rainfall and different extreme rainfall indices proposed by
World Meteorological Organization (WMO) and Expert Team
on Climate Change Detection and Indices (ETCCDI)
considering suitability for Indian rainfall conditions in six rain
gauge stations namely Ambagarh, Bhanpura, Balod,
Dhamtari, Kanker and Murumsilli of upper Mahanadi
catchment. The river Mahanadi is an important river for water
resources development in Chhattisgarh State of India and
availability of water may adversely be affected due to possible
change in precipitation regime. For identification of trends,
long term rainfall data from 1960 to 2012 have been used to
compute extreme rainfall indices including maximum one-day
rainfall (RX1D), maximum 5-days rainfall (RX5D), heavy precipitation days (R7.5cm), very heavy precipitation days
(R12.5cm), moderate wet days (R75P), very wet days (R95P),
precipitation friction due to moderate wet days (R75PTOT),
precipitation friction due to very wet days (R95PTOT) and
simple daily intensity index (SDII). The Mann Kendal’s and
Spearman Rho’s test were used to identify significant trend in
extreme rainfall indices at 5 % significant level. The results of
analysis indicated that simple daily intensity index indicated no
significant trends in any rain gauge stations while rising trend
in very heavy precipitation days (R12.5cm) in most of the
station. Dhamtari and Murumsilli stations showed significant
rising trend in moderate wet days and very wet days related
extreme indices, while extreme indices series of Bhanpura and
Balod stations were found random without any significant
trend.