Observed trends and changes in daily temperature and precipitation extremes over the Koshi river basin 1975–2010

Abstract

ABSTRACT:The Koshi river basin is a sub-basin of the Ganges shared among China, Nepal, and India. The river system has a high potential for investment in hydropower development and for irrigation in downstream areas. The upper part of the basin contains a substantial reserve of freshwater in the form of snow and glaciers. Climate variability, climate change, and climate extremes might impact on these reserves, and in turn impact on systems that support livelihoods, such as agriculture, biodiversity and related ecosystem services. Climatological variability and trends over the Koshi river basin were studied using RClimDex. Daily temperature data (20 stations) and precipitation data (50 stations) from 1975 to 2010 were used in the analysis. The results show that the frequency and intensity of weather extremes are increasing. The daily maximum temperature (TXx) increased by 0.1 ∘ C decade −1 on average between 1975 and 2010 and the minimum (TNn) by 0.3 ∘ C decade −1 . The number of warm nights increased at all stations. Most of the extreme temperature indices showed a consistently different pattern in the mountains than in the Indo-Gangetic plains, although not all results were statistically significant. The warm days (TX90p), warm nights (TN90p), warm spell duration (WSDI), and diurnal temperature range (DTR) increased at most of the mountain stations; whereas monthly maximum and minimum values of daily maximum temperature, TX90p, cool nights (TN10p), WSDI, cold spell duration indicator (CSDI), DTR decreased at the stations in the Indo-Gangetic plains, while the number of cold days increased. There was an increase in total annual rainfall and rainfall intensity, although no clear long-term linear trend, whereas the number of consecutive dry days increased at almost all stations. The results indicate that the risk of extreme climate events over the basin is increasing, which will increase people's vulnerability and has strong policy implications.

Rising Precipitation Extremes across Nepal

“…In line with the stationwise trends, field significance trends are also statistically significant for all the sub-regions, except for CH. This finding is consistent with previous studies of Shrestha et al [32] and Sigdel and Ma [104] over Koshi basin of Nepal. A similar increase in CDD has also been reported for the Songhu River basin in China [108] and across Bangladesh [109], as CDD is mostly related to the large-scale weather systems rather than localized systems [68].…”

“…Positive trends in RX1day and RX5day are field significant over the WM, CL and CH regions, while negative trends are field significant over the CM region and RX1day decrease is additionally field significant over the EM region. Such a pattern of change in RX1day is consistent with the previous studies [32,104] that also report a decreasing trend of RX1day from most of the stations, where such a trend is particularly significant above 100 m (asl) within the Koshi River basin-a basin spanning mainly over the eastern and partially over the central region of our study area.…”

“…The spatial pattern of trend changes in PRCPTOT is quite similar to that of the monsoonal precipitation as it dominates (about 80% of) the total annual precipitation in Nepal. Decreasing PRCPTOT over the eastern region that covers most of the Koshi River basin within Nepal is consistent with the reports of significant precipitation decrease over the Koshi River basin during the 1994-2013 period [50] and over the middle mountains and hills during the 1975-2010 period [32]. Based on the coarse resolution Global Precipitation Climatology Project (GPCP) dataset, Yao et al [113] have also provided evidence of decreasing precipitation over all the Himalayas and an increase in the eastern Pamir regions during 1979-2010. factors besides precipitation.…”

“…Unlike significant decreasing trends in PRCPTOT over EM, EL and CL regions, in accord with Shrestha et al [32], SDII features a significant increasing trend. An increase in SDII over such regions is mainly due to the higher decrease in WD than in PRCPTOT (Figure 9b).…”

“…Since precipitation extremes are more localized and can be smoothed over when limited gauge data is interpolated [30], employing APHRODITE may have significantly affected the computation of extreme statistics as it hardly incorporates any real observations from the early 1950s west of Kathmandu [31]. Recently, analyzing the extreme precipitation indices only within the Koshi River basin in eastern Nepal for the 1975-2010 period, Shrestha et al [32] have reported an overall increase in the precipitation total and intensity, though such trends were statistically insignificant. These discordant findings of changes in the precipitation extremes over Nepal may be attributed to employing varying datasets, analyzing different time periods, and focusing on distinct study regions, hence lacking a countrywide picture.…”