Spatial Distribution of Extreme Precipitation Events and Its Trend in Nepal

Dibas Shrestha¹, Shankar Sharma¹, Kalpana Hamal^{2, 3}, Umair Khan Jadoon^{3, 4} and Binod Dawadi^{1, 5,}

¹Central Department of Hydrology and Meteorology, Tribhuvan University, Kirtipur Nepal

²International Center for Climate and Environment Sciences, Institute of Atmospheric Physics, Chinese Academy of Sciences, P.O. Box 9804, Beijing 100029, China

³University of Chinese Academy of Sciences, Beijing 100049, China

⁴Key laboratory of Continental Collision and Plateau Uplift, Institute of Tibetan Plateau Research, Chinese Academy of Sciences, Beijing 100101, China

⁵Kathmandu Centre for Research and Education, Chinese Academy of Sciences-Tribhuvan University, Kathmandu, Nepal

Cite this paper:
Dibas Shrestha, Shankar Sharma, Kalpana Hamal, Umair Khan Jadoon and Binod Dawadi. Spatial Distribution of Extreme Precipitation Events and Its Trend in Nepal. Applied Ecology and Environmental Sciences. 2021; 9(1):58-66. doi: 10.12691/aees-9-1-8

Abstract

The mountainous country with complex topography and climatic conditions over Nepal, the Tropical Rainfall Measuring Mission (TRMM-3B42), were evaluated for monitoring extreme precipitation events using 142-gauge observation from January 1998 to December 2018. Several extreme precipitation indices based on daily timescale data were selected for evaluation. Detection skills, spatial distribution, and trends in extreme precipitation were also investigated. TRMM product moderately capture (POD>70%) the true precipitation events (Probability of Detection) at most of the station. Although, TRMM product shows higher (FAR>40%) false precipitation events (False Alarm Ratio) however, it accurately captures (ACC>80%) the precipitation and no-precipitation events (Accuracy) over the country. Based on five different extreme precipitation indices; heavy precipitation events (R10mm), extreme precipitation events (R25mm), 7 Consecutive Dry Days (CDD), 7 Consecutive Wet Days (CWD), and one-day maximum precipitation (Rx1day), it was observed that the TRMM product can reproduce the spatial distribution of heavy and extreme precipitation events however, it tends to underestimate (overestimate) the frequency of R25mm and CDD (R10mm and CWD spells). Further, increasing (decreasing) trend of dry (wet) spells are observed in both datasets (observed and TRMM) during the study period. The highest Rx1day (about 500 mm/day) was observed during 2014 and 2017; differently, TRMM product shows during 2008 with the highest Rx1day about 300 mm/day. This study provides accuracy of TRMM product to represent the spatio-temporal distribution of extreme precipitation events and its recent trends in Nepal, which is of great significance to hydro-meteorological application. In general, the TRMM product is a good alternative to monitoring extreme precipitation events in Nepal; however, there is still space for further improvement in rainfall retrieval algorithms, especially in high-elevation areas.

Keywords:
precipitation Nepal spatial pattern TRMM extreme events

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