Abstract Understanding temporal and spatial changes in precipitation has far-reaching implications for watershed development and risk assessment under global climate change. In our study, temporal and spatial variability in precipitation concentration (PC) in Central Asia (CA) from 1980 to 2017, measured with the precipitation concentration index (PCI) and Gini Coefficient (GC), was analyzed using interpolated precipitation from the Climate Prediction Center (CPC) and National Centers for Environmental Prediction (NCEP). The results showed that: (1) interpolated precipitation increased significantly, with significant mutations (P

中文翻译：

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中亚主要流域降水浓度和趋势及其潜在驱动因素调查

摘要 了解降水的时空变化对全球气候变化下的流域发展和风险评估具有深远的意义。在我们的研究中，1980 年至 2017 年中亚 (CA) 降水浓度 (PC) 的时空变异性，使用降水浓度指数 (PCI) 和基尼系数 (GC) 测量，使用来自气候预测的插值降水进行分析中心 (CPC) 和国家环境预测中心 (NCEP)。结果表明：（1）插值降水显着增加，突变显着（P