Abstract Stochastic rainfall models have been widely used for hydrological modelling and climate change impact studies, the accuracy of which can substantially affect the reliability of water resources planning, hydraulic structure design and flood and drought risk assessment. The primary objective of this study is to develop a stochastic daily rainfall model through coupling a Markov chain model with a rainfall event model (SDRM-MCREM) to simultaneously preserve the statistical properties of rainfall time series and rainfall events. The newly developed model is applied to the Qu River basin, East China and its performance is evaluated at catchment scale. Results demonstrate that SDRM-MCREM shows a good performance in reproducing most of the rainfall time-series statistics (i.e. rainfall percentiles, average monthly and annual rainfall, inter-monthly rainfall variability and extreme rainfall) and rainfall event characteristics (i.e. distributions of wet and dry spells, occurrence frequency of different rainfall event classes, temporal rainfall patterns and their occurrence frequency in different rainfall event classes). The statistics of average runoff and extreme runoff are also well preserved by using the SDRM-MCREM simulations as input of hydrological modelling except that the interannual variability of rainfall and runoff is slightly underestimated. Moreover, SDRM-MCREM shows a great potential to be used for flood and drought risk assessment in reproducing the exceedance probabilities of high flows (e.g. annual maximum 1-day, 3-day and 5-day mean runoff) and low flows (e.g. annual minimum 7-day, 30-day and 90-day mean runoff).

中文翻译：

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一种新的随机日降雨模型的开发和水文气象评估：马尔可夫链与降雨事件模型的耦合

摘要 随机降雨模型已广泛用于水文建模和气候变化影响研究，其准确性对水资源规划、水工结构设计和水旱灾害风险评估的可靠性产生重大影响。本研究的主要目标是通过将马尔可夫链模型与降雨事件模型 (SDRM-MCREM) 耦合来开发随机日降雨模型，以同时保留降雨时间序列和降雨事件的统计特性。新开发的模型应用于华东曲河流域，并在流域尺度上评估其性能。结果表明，SDRM-MCREM 在再现大部分降雨时间序列统计数据（即降雨百分位数、平均月和年降雨量、月间降雨变率和极端降雨）和降雨事件特征（即干湿期的分布、不同降雨事件类别的发生频率、时间降雨模式及其在不同降雨事件类别中的发生频率）。通过使用 SDRM-MCREM 模拟作为水文建模的输入，平均径流和极端径流的统计数据也得到了很好的保留，只是降雨和径流的年际变化略有低估。此外，SDRM-MCREM 在再现高流量（例如年最大 1 天、3 天和 5 天平均径流）和低流量（例如每年7 天、30 天和 90 天平均径流）。