Flood scaling theory is important for flood predictions in data-scarce regions but is often applied to quantile-based floods that have no physical mechanisms. In this study, we propose a framework for flood prediction in data-scarce regions by event-based flood scaling. After analyzing the factors controlling the flood scaling, flood events are first simulated by a hydrological model with different areally averaged rainfall events and curve number (CN) values as inputs, and the peak discharge of each subcatchment is obtained. Then, the flood scaling is analyzed according to the simulated peak discharge and subcatchment area. Accordingly, the relationship curves between the scaling exponent and the two explanatory factors (rainfall intensity and CN) can be drawn. Assuming that the flood and the corresponding rainfall event have the same frequency, the scaling exponent with a specific flood frequency can be interpolated from these curves.

洪水定标理论对于数据稀缺地区的洪水预测很重要，但通常应用于没有物理机制的基于分位数的洪水。在这项研究中，我们提出了一个基于事件的洪水标度在数据稀缺地区进行洪水预报的框架。在分析了控制洪水泛滥的因素之后，首先使用水文模型模拟洪水事件，以不同的区域平均降雨事件和曲线数（CN）值作为输入，并获得每个子汇水面积的峰值流量。然后，根据模拟的峰值流量和子汇水面积分析洪水的规模。因此，可以绘制比例指数和两个解释性因素（降雨强度和CN）之间的关系曲线。假设洪水和相应的降雨事件具有相同的频率，