This study aims to construct two hedging policies based on current storage and two auxiliary factors (past storage trend and future standardized streamflow index (SSI) and compare the effects on reservoir performance in terms of shortage characteristics (maximum single-period shortage ratio, total shortage ratio, average water shortage per shortage period, and risk) during droughts. The proposed approach is applied to the Nanhua Reservoir located in southern Taiwan. The results reveal that Model S (demand-based rule curves associated with fuzzified storage) efficiently improves shortage characteristics during droughts and outperforms Model C (current operation). Further improvements are obtained by incorporating past storage trends (Model STs: Model S with different periods of past storage trends) and future SSIs (Model SHs: Model S with different time-scale SSIs) into Model S. Exactly known SSIs in Model SHs derive optimistic hedging policies that have fewer less-than-1 rationing coefficients and significantly reduce shortage duration and total deficits. In contrast, Model STs lack future inflow information and lead to conservative hedging policies, which have early hedging and effectively decrease the maximum single-period water shortage. The effects of past storage trends and future SSIs on shortage characteristics decrease with longer periods since models with short-term information effectively capture the inherent variations and derive more effective hedging policies. According to the overall objective, Model SHs generally outperform Model STs, models with short-term information outperform the long-term models, and all the proposed optimization models outperform the current operation.

将具有不同时标SSI的模型S转换为模型S。模型SH中确切已知的SSI会得出乐观的对冲策略，其配给系数小于1，并显着减少了短缺持续时间和总赤字。相比之下，模型ST缺乏未来的流入信息，并导致采取保守的套期保值政策，这些政策可以尽早进行套期保值，并有效地减少了最大的单期缺水量。过去的存储趋势和未来的SSI对短缺特征的影响随着时间的延长而降低，因为具有短期信息的模型可以有效地捕获固有变化并得出更有效的对冲政策。根据总体目标，模型SH总体上优于模型ST，具有短期信息的模型优于长期模型，