Considerable biases in precipitation simulations in climate models have required the adoption of delta-change approaches to construct future precipitation scenarios for hydrological climate change impact studies. However, different delta-change methods yield different future precipitation scenarios that might significantly affect the projected future streamflow. To assess these effects, two delta-change methods were compared: the simple delta-change (SDC) method with a constant scaling factor and the quantile-quantile delta-change (QQDC) method with a quantile mapping-based non-uniform delta factor. The Xinanjiang (XAJ) hydrological model was applied using historical climatic data and two future precipitation scenarios for streamflow simulations in the Pearl River basin, China. The results show that the two delta-change methods have significant influences on future precipitation and streamflow projections, and these impacts become more distinct at finer and extreme event time scales. For instance, the QQDC method projects the 20-year daily maximum precipitation to be 8.1–98.6% higher than the SDC method. Consequently, the XAJ model with the QQDC future precipitation produces the 20-year daily maximum streamflow to be approximately 7.0–65.0% higher than that using the SDC precipitation. It implies that future precipitation transformation methods are a source of uncertainty, affecting future discharge projections. Such uncertainty should be considered in water resources management and flood control strategies for future climate change adaptations.

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