Developing a Formula to Estimate Precipitation at Ungauged Location and Analysis of Rainfall Pattern: Case Study for Rastra Bank Chowk, Pokhara, Nepal

K. Basnet, Kabita Poudel
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Abstract

Pokhara receives the second highest amount of rainfall in the country, according to Department of Hydrology and Meteorology. The rainfall distribution within this small region is random. The precipitation in Pokhara is measured from limited rain gauge stations. For understanding the spatial variation, it is necessary to access the daily rainfall data at the gauged as well as ungauged stations.  In view of this problem, this study is aimed at developing the formula to estimate the rainfall value at an ungauged station, Rastrabank Chowk Pokhara using the calibration and validation method. For this purpose, the daily rainfall data of the sample station was measured using standard rain gauge for a period of four months from May 13, 2020 to September 15, 2020. The analysis of the spatial distribution and variation of daily rainfall at meteorological stations as well as sample station was done to select the data for the development of the formula. Calibration and validation of formula was performed for equal period using the statistical indices NSE, R2 and PBIAS. Calibration was performed using rainfall data of available meteorological stations of Pokhara in the first two consecutive months. From the numerous hit and trial procedures, the equation developed with rainfall data of Airport and Malepatan stations comprising of three constant values were obtained with the highest NSE and R2. PBIAS value was then calculated for maximum NSE and R2. In the next phase, validation of the equation for other two months (14 July- 15 September,2020) was performed to obtain maximum possible value of NSE and R2 and a smaller value of PBIAS. The equation was obtained with 0.980 NSE, 0.980 R2 and 6.437 % PBIAS value which indicated good agreement between observed and predicted rainfall value. Spatial rainfall pattern analysis using SURFER model demonstrated that there was a homogenous distribution of rainfall in Malepatan, Airport and sample stations. The temporal trend showed that the month July of 2020 had a higher amount of precipitation at Pokhara valley. From the HYSPLIT model, it was observed that the rainfall events in Pokhara valley was due to westerlies dominance. This study would provide the rainfall estimation techniques and hence would significantly contribute to meteorological investigations and water resource planning.
建立一个估算未测量地点降水的公式和降雨模式分析:以尼泊尔博卡拉Rastra Bank Chowk为例
据水文和气象部门称,博卡拉的降雨量在全国排名第二。这个小区域内的降雨分布是随机的。博卡拉的降水是由有限的雨量站测量的。为了了解其空间变化,有必要获取测量站和非测量站的日降雨量数据。鉴于这一问题,本研究旨在利用校准和验证方法,建立Rastrabank Chowk Pokhara非计量站雨量值的估算公式。为此,使用标准雨量计测量了样本站2020年5月13日至2020年9月15日4个月的日降雨量数据。通过对各气象站和样站日降水量的空间分布和变化分析,为公式的编制选择数据。采用统计指标NSE、R2和PBIAS对公式进行等期校正和验证。利用博卡拉现有气象站连续头两个月的雨量资料进行校正。从大量的hit和trial程序中,利用Airport和Malepatan站的降雨数据建立的方程由三个常量组成,具有最高的NSE和R2。然后计算最大NSE和R2的PBIAS值。在下一阶段,对另外两个月(2020年7月14日至9月15日)的方程进行验证,以获得NSE和R2的最大可能值以及较小的PBIAS值。NSE为0.980,R2为0.980,PBIAS值为6.437%,表明观测值与预测值吻合较好。基于SURFER模型的空间降雨格局分析表明,马勒巴滩、机场和样站降水分布均匀。时间变化趋势表明,2020年7月博卡拉河谷降水偏多。从HYSPLIT模式观察到,博卡拉河谷的降雨事件是由西风带主导的。这项研究将提供降雨估算技术,因此将对气象调查和水资源规划作出重大贡献。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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