The Standardized Precipitation Index (SPI) is a powerful tool, requiring only precipitation data for calculating the intensity, duration, magnitude, severity and frequency of drought. Moreover, it provides helpful coverage of drought impacts on multi time scales. In this study, the SPI technique was applied to the dataset of 30 years (1986–2015) to detect drought condition in Northern Pakistan, which is a frequent drought-hit area. The coefficient of variability (CV) was used to analyze precipitation trend, while linear regression model was adopted to detect trend. The detected precipitation variability was spatially interpolated by applying the Inverse Distance Weighted (IDW) technique. It is evident from the analysis that there is great variability in precipitation pattern and trend in the study area. During the winter season, a positive trend in the precipitation variability was detected in the Himalaya and Karakorum region. In the Hindukush region, only Pattan weather station has observed a positive variability trend. In contrast to winter variability, pre-monsoon season has observed an increased variability in the Hindukush region, while the Karakorum and Himalayas regions observed a negative trend. The monsoon season has observed a decreased variation in precipitation throughout the study area except for Pattan. In post-monsoon, Skardu weather station of Himalayas, Gupis and Bunji of Karakorum region and Pattan of Hindukush region have witnessed increased precipitation variability. The meteorological stations of Karakoram and Himalaya have noticed a negative trend of precipitation variability, while in the Hindukush region, all the meteorological stations have witnessed a positive trend of variability except Saidu Sharif and Dir stations. The results of SPI also indicated a drought condition in the study area. Similarly, the SPI results of all return periods have shown a significant drought condition in the Himalayas followed by—in terms of frequency and magnitude—Karakoram and Hindukush, respectively. Based on the above findings, it is recommended that the agriculture experts should work on drought-resilient crops in order to cope up with the harsh prevalent climatic condition in Northern Pakistan.

标准化降水指数（SPI）是强大的工具，仅需要降水数据即可计算干旱的强度，持续时间，强度，严重程度和频率。此外，它在多个时间尺度上提供了干旱影响的有用报道。在这项研究中，将SPI技术应用于30年（1986-2015年）的数据集，以检测巴基斯坦北部（干旱频发的地区）的干旱情况。变异系数（CV）用于分析降水趋势，而线性回归模型用于检测趋势。通过应用反距离加权（IDW）技术在空间上对检测到的降水变化进行插值。从分析中可以明显看出，研究区的降水模式和趋势变化很大。在冬季，在喜马拉雅山和喀喇昆仑地区，降水变化呈正趋势。在欣杜库什地区，只有Pattan气象站观测到了正的变化趋势。与冬季多变性相反，季风前季节在欣杜库什地区发现了增加的变异性，而喀喇昆仑和喜马拉雅山地区则出现了消极趋势。除Pattan以外，整个研究区的季风季节降水量减少。在季风后，喜马拉雅山的Skardu气象站，喀喇昆仑地区的Gupis和Bunji以及Hindukush地区的Pattan见证了降水变化的增加。喀喇昆仑山和喜马拉雅山的气象站注意到降水变化的趋势是负面的，而在欣杜库什地区，除萨伊杜·谢里夫（Saidu Sharif）和迪尔（Dir）站外，所有气象站的变化都呈积极趋势。SPI的结果还表明研究区域处于干旱状态。同样，所有回归期的SPI结果都显示出喜马拉雅山脉出现了严重的干旱状况，其次是频率和强度，分别是Karakoram和Hindukush。基于以上发现，建议农业专家应对干旱的农作物进行工作，以应对巴基斯坦北部恶劣的普遍气候条件。所有回归期的SPI结果表明，喜马拉雅山脉出现了严重的干旱状况，其次是频率和强度，分别是Karakoram和Hindukush。基于以上发现，建议农业专家应对干旱的农作物进行工作，以应对巴基斯坦北部恶劣的普遍气候条件。所有回归期的SPI结果表明，喜马拉雅山脉出现了严重的干旱状况，其次是频率和强度，分别是Karakoram和Hindukush。基于上述发现，建议农业专家应对干旱的农作物进行工作，以应对巴基斯坦北部恶劣的普遍气候条件。