氣候變遷加劇極端氣候事件，影響水文循環並凸顯理解水文記憶的重要性，水文記憶意指水文狀態對未來行為的影響。透過多尺度量化分析水文記憶與遲滯特性，說明水文系統內隱藏的動態規律，進而提升極端事件預測能力。本研究以臺灣44個集水區超過30年的水文資料為基礎，結合統計指標、碎形理論、集水區遺忘曲線與遲滯迴圈方法，不僅探討單一水文分量之記憶性，更分析各分量間的遲滯關係及作用機制。自相關分析結果顯示，降水與流量分別具有2至4個月及3至5個月的記憶時間，且呈現非穩態性，有助於深入了解內部結構。複合碎形去趨勢波動分析指出，流量呈現顯著長期正向持續性，有明顯多尺度差異，及以小波動事件主導的特徵，降水則偏向短期正向持續波動，事件尺度較一致，顯示降水長期波動結構相對單一。由集水區遺忘曲線顯示臺灣僅25%的集水區具顯著水文記憶，主要集中於西南部，水文記憶現象最顯著約35天，持續影響最久可達到50天，記憶特徵多出現在面積小於500 km²且基流指數較低的集水區，與坡度和降雨強度等因子無顯著關聯。遲滯迴圈分析顯示降水–流量和降水–地下儲水量多為逆時針迴圈，顯示降水普遍先於其餘水文反應，遲滯指數絕對值多介於0.3至0.6，反應輸入與反應間的時間差異；而地下儲水量–流量在中西部普遍為順時針迴圈，表現出由流量補注地下水的方向，並伴隨顯著的正值殘差，代表事件後仍有延續性反應。這些結果指出中西部地區降水後流量迅速上升但地下水補注遲滯，增加洪水風險。北部及東北部山區則由地下水補注河川流量，具有較佳的緩衝機制與恢復能力。研究結果證實臺灣集水區水文系統具有多尺度複雜性，透過量化水文記憶，更精準掌握極端水文事件之遲滯反應與作用機制，並作為未來水資源管理及水文預測的重要參考。

Climate change intensifies extreme climate events, significantly affecting the hydrological cycle and highlighting the importance of understanding hydrological memory. Hydrological memory refers to how past hydrological states influence future responses. Quantifying memory and hysteresis characteristics at multiple scales can reveal hidden dynamics within hydrological systems, thereby improving the prediction of extreme events. This study analyzes over 30 years of hydrological data from 44 catchments across Taiwan, integrating statistical indicators, fractal theory, the catchment forgetting curve (CFC), and hysteresis loop analyses. It examines memory within individual hydrological components and the hysteresis relationships among these components. Autocorrelation analyses indicate effective memory durations of approximately 2–4 months for precipitation and 3–5 months for streamflow, both exhibiting non-stationary behavior, thus providing insights into internal hydrological structures. Multifractal detrended fluctuation analysis (MFDFA) demonstrates that streamflow exhibits significant long-term positive persistence, clear multi-scale variability, and dominance by small-magnitude events. In contrast, precipitation shows short-term positive persistence with more uniform event scales, indicating relatively simpler long-term fluctuation patterns. The catchment forgetting curve analysis reveals that only 25% of Taiwan’s catchments exhibit significant hydrological memory, mainly located in the southwestern region. The strongest memory effects typically last about 35 days, with persistence extending up to 50 days. Memory characteristics commonly appear in catchments smaller than 500 km² and with lower baseflow indices, but are not significantly correlated with slope or precipitation intensity. Hysteresis loop analyses show mainly anticlockwise loops for precipitation–streamflow and precipitation–groundwater storage, indicating precipitation generally precedes other hydrological responses. The absolute hysteresis indices mostly range between 0.3 and 0.6, reflecting the temporal lag between inputs and responses. Conversely, groundwater storage–streamflow relationships in central and western regions typically show clockwise hysteresis loops, suggesting streamflow contributes to groundwater recharge, accompanied by significant positive residual values, indicating persistent post-event responses. These findings suggest that, following precipitation, streamflow rapidly increases in central and western Taiwan, while groundwater recharge exhibits notable hysteresis, thus increasing flood risk. In contrast, northern and northeastern mountainous regions exhibit effective groundwater contributions to streamflow, providing better buffering mechanisms and recovery capacities. Overall, results confirm the multi-scale complexity of Taiwan's catchment hydrological systems. Quantifying hydrological memory enhances understanding of hysteresis effects during extreme hydrological events, providing critical references for water resource management and hydrological forecasting.

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