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Understanding precipitation variations on various timescales and their correlations is important for assessment of flood risk and utilization of water resources. In this study, the spatial and temporal patterns of precipitation concentration in the upper reaches of the Huai River, China, were investigated using two indices: the precipitation concentration index (PCI) and the concentration index (CI) for measuring seasonality and daily heterogeneity using monthly and daily precipitation series, respectively. In particular, the trends of PCI and CI were tested by the Mann-Kendall method, and relationship among PCI, CI and percentage of precipitation contributed by the rainiest days was analyzed by the linear correlation analysis. The results show a significant seasonality of the rainfall distribution and very in homogeneous temporal distribution of the daily rainfall in the south part of the study area, especially in the three reservoirs. Positive trends in the PCI and CI were found at most stations, although none of the PCI trends were statistically significant. Daily heterogeneity of the rainfall in a year is highly correlated with the heavy rainfall amount of the 15 % rainiest days, and seasonality in rainfall distribution over a year can be partly explained by the daily rainfall heterogeneity. [ABSTRACT FROM AUTHOR]

Trend detection in hydro-climatological time series is a prime task under the context of climate changes. Rainfall is a key component of the water cycle and its variability can profoundly influence agriculture, ecosystems and water resource management. In this paper, an innovative trend analysis (ITA) method with a significant test is used for rainfall trend detection at 14 stations in the Yangtze River Delta (YRD) during 1961–2016. The trends are separately evaluated for low (<10th percentile), medium (10th–90th percentile) and high (>90th percentile) rainfall at the annual and seasonal scales. The slope and significance of the rainfall trends derived from the ITA method are compared with those from the classical trend analysis methods Theil-Sen approach and Mann-Kendall test, respectively. The ITA shows significant increasing trends at the 99% confidence level in annual rainfall at all stations. While the same significant increasing trends are identified for summer and winter, decreasing trends dominate in spring and autumn. Contrasting trends are found for extreme rainfall with strong increasing trends in high rainfall in summer and winter and decreasing trends in low rainfall in spring and autumn. The results of the ITA confirmed by the classical trend analysis methods call for more attention to the risk management of flood in extreme seasons and drought in transitional seasons across the YRD region. • Trends analysis of rainfall across the Yangtze River Delta is performed by the innovative trend analysis (ITA) method. • Separate trends in low, medium and high rainfall are quantitatively calculated based on the ITA method. • Some advantages of the ITA method to classical trend methods (Mann-Kendall test and Theil-Sen approach) are presented. • High rainfall in summer showed significant increase while low rainfall in spring and autumn exhibited decrease. [ABSTRACT FROM AUTHOR]