氣候變遷是二十一世紀最迫切的挑戰之一，不僅加劇了全球乾旱動態，更對永續水資源管理造成前所未有的壓力。這對台灣的水資源構成重大威脅，尤其影響農業地區——該地區的雙季作系統對水文氣候變異極為敏感。近年來，台灣遭遇的時空氣候極端事件頻率與強度日益增加，尤其是連續乾旱日數（CDD），這不僅嚴重影響水資源，更加劇水資源壓力，進而增加農田的灌溉用水需求（IWD）。因此，了解 CDD 與 IWD 的變異趨勢，對於提供水資源管理與農業規劃的關鍵資訊至關重要。 本研究採用經偏差校正的「台灣氣候變遷預測資訊與調適知識平台」CMIP6氣候預測資料，針對近期未來（2021–2050年）與遠期未來（2071–2100年），評估相較於1995–2014年基準期的連續乾旱日數未來變化。本資料集經由台灣全境六座主要氣象站的觀測資料進行驗證，並採用泰勒技能分數（TSS）及模型排名法，評估十九個 CMIP6 模型在重現歷史月累積日度（CDD）氣候學特徵方面的表現。 利用降水資料，透過曼恩–肯德爾檢驗（Mann–Kendall test）及森的斜率估計量（Sen’s slope estimator），分析台灣全境累積日度（CDD）的趨勢與變化點。未來CDD的變化是根據CMIP6在SSP1-2.6、SSP2-4.5、SSP3-7.0及SSP5-8. 5情境下的預測結果進行分析。此外，還分析了從美國國家海洋暨大氣總署（NOAA）取得的重大氣候變異性指標（包括AMO、PDO、NAO及ENSO），以評估其與CDD事件的遙相關性。 此外，本研究透過聯合國糧農組織（FAO）的AquaCrop水生產力模型，評估氣候變遷對最佳灌溉日（IWD）的影響。作為適應策略，採用「種植日期調整法」，將種植日期從原定時間提前21天起，以每7天為單位逐步延後21天，藉此找出未來氣候條件下的最佳灌溉日。 對十九個 CMIP6 模型的評估顯示，在模擬台灣地區的 CDD 方面存在明顯的季節性變異性。其中十個 TSS 值較高的模型（RM-TSS > 0.5）被認定為表現最佳的模型，並被用於建立多模型集合以進行未來預測分析。對歷史趨勢的分析揭示，台灣各地區的季節性 CDD 變異性存在顯著的空間依賴性。秋季期間，中部及南部地區的累積日度積算度（IWD）明顯以每十年增加約0.5–1.5天為特徵；而冬季期間，台灣南部則觀察到每十年約減少0.5天的溫和下降趨勢。未來預測顯示，在高排放情境（SSP3-7.0 和 SSP5-8.5）下，到 21 世紀末，乾季期間台灣全境出現延長的累積日度（CDD）現象的範圍可能擴大。特別是 SSP5-8.5 情境，顯示每十年將額外增加約 1.2 天。這些預測的增加與東亞季風系統的預期變化密切相關，特別是季節性降水模式和大氣環流動力學。相較之下，低排放情境（如 SSP1-2.6 和 SSP2-4.5）則顯示，春季 CDD 將部分恢復至基準狀態，同時春季雨帶可能持續籠罩台灣。此外，相關性分析結果顯示，大尺度大氣振盪（如 AMO、PDO 和 ENSO）與台灣特定地區春季 CDD 延長之間存在一致的關聯性。 AquaCrop 模型與觀測到的冠層覆蓋率呈現極佳的一致性（第一季 R² = 0.99，第二季 R² = 0.91），均方根誤差（RMSE）≤ 13.2%，平均絕對誤差（MAE）≤ 11.1%，這凸顯了該模型適用於在未來氣候情境下，估算跨季水稻的灌溉缺水量（IWD）。歷史模擬結果顯示，與第二作期相比，第一作期所需的灌溉用水量顯著更高，最高可達 180 毫米，對水資源造成最大負擔；而第二作期大多需要較少的補充灌溉。未來預測顯示，第一作期的灌溉用水量將大幅增加，在 SSP5-8.5 情境下，西部沿海地區的增幅最高可達 +40 毫米。此外，在台灣各區域，若將第一作期的播種日期提前14（21）天或延後21（14）天（C25/C05，可使雙季作系統達到最大的灌溉用水節省效果。在單季種植系統下，中部地區若將播種日期推遲50天，可節省80毫米灌溉用水；而在南部地區，若將播種日期推遲70天，節水量更可達150毫米。這些模式在所有情境下均一致。這些研究結果表明，監測關鍵氣候指標有助於制定春季乾旱緩解策略；同時，在台灣水資源緊缺的條件下，調整最佳播種日期有助於減輕氣候變遷對水稻灌溉用水需求的不利影響。;Climate change is one of the most pressing challenges of the 21st century， intensifying global drought dynamics and placing unprecedented strain on sustainable water resource management. It poses a significant threat to water resources in Taiwan， particularly impacting agricultural areas， where double-cropping systems are highly sensitive to hydroclimatic variability. In recent years， Taiwan has experienced increasingly frequent and intense spatiotemporal climate extremes， particularly consecutive dry days (CDD)， which strongly affect water resources and exacerbate water stress， thereby increasing irrigation water demand (IWD) in agricultural fields. Therefore， understanding the variation in CDD and IWD is essential for providing critical information for water management and agricultural planning. Bias-corrected Taiwan Climate Change Projection Information and Adaptation Knowledge Platform CMIP6 climate projections were used to assess future changes in CDD relative to the 1995–2014 baseline for the near future (2021–2050) and far future (2071–2100). The dataset was validated against observations from six major meteorological stations across Taiwan， and the performance of nineteen CMIP6 models in reproducing historical monthly CDD climatology was evaluated using the Taylor Skill Score (TSS) and model ranking methods. The Mann–Kendall test and Sen’s slope estimator were used to detect trends and change points in CDD across Taiwan using precipitation data. Future CDD changes were analyzed using CMIP6 projections under the SSP1-2.6， SSP2-4.5， SSP3-7.0， and SSP5-8.5 scenarios. In addition， major climate variability indices， including AMO， PDO， NAO， and ENSO， obtained from the National Oceanic and Atmospheric Administration， were analyzed to assess their teleconnections with CDD events. Moreover， the impacts of climate change on IWD were assessed by the Food and Agriculture Organization (FAO) AquaCrop water productivity model. As an adaptation strategy， a shifting planting-date approach， from 21 days earlier to 21 days later in seven-day increments， was applied to identify the optimal IWD for the future climate conditions. Evaluation of nineteen CMIP6 models showed clear seasonal variability in simulating CDD over Taiwan. Ten models with higher TSS (RM-TSS > 0.5) were identified as the best-performing models and utilized to develop the multi-model ensemble for future projection analyses. The analysis of historical trends reveals a pronounced spatial dependence in seasonal CDD variability across Taiwan. Increases of approximately 0.5–1.5 days per decade are evident in central and southern regions during autumn， while a modest decline of about 0.5 days per decade is observed in southern Taiwan during winter. Future projections indicate that， under high-emission scenarios (SSP3-7.0 and SSP5-8.5)， prolonged CDD is likely to become more widespread across Taiwan during the dry seasons by the end of the 21st century. The SSP5-8.5 scenario in particular indicates an additional increase of roughly 1.2 days per decade. These projected increases are closely linked to anticipated changes in the East Asian monsoon system， particularly in seasonal precipitation patterns and atmospheric circulation dynamics. In contrast， low-emission scenarios such as SSP1-2.6 and SSP2-4.5 point toward a partial recovery toward baseline spring CDD conditions， along with the potential persistence of the spring rainband over Taiwan. Furthermore， correlation results reveal a consistent relationship between large-scale atmospheric oscillations such as AMO， PDO， and ENSO and prolonged spring CDD in specific regions of Taiwan. The AquaCrop model showed excellent agreement with observed canopy cover (R² = 0.99 in season 1 and 0.91 in season 2)， with RMSE ≤ 13.2% and MAE ≤ 11.1%， highlighting its suitability for estimating IWD for inter-seasonal rice under future climate scenarios. Historical simulation results showed that the first cropping season requires substantially higher IWD compared to the second crop season， reaching up to 180 mm and imposing the greatest burden on water resources， whereas the second cropping season mostly requires less supplemental irrigation. Future projections indicated a substantial increase in IWD during the first cropping season， with rises of up to +40 mm along the western coast under the SSP5-8.5 scenarios. Furthermore， the maximum irrigation water savings for a double-cropping system can be achieved by a combination of shifting 14 (21) days earlier or 21 (14) days later for the first season (C25/C05) across different regions in Taiwan. Under a single-cropping system， 80 mm of irrigation water can be saved by shifting the planting date of 50 days later in the central region， whereas in the south this value reaches up to 150 mm by shifting the planting date of 70 days later. These patterns are consistent across all scenarios. These findings suggest that monitoring key climate indices could be able to support spring drought mitigation strategies， while adjusting optimal planting dates may help reduce the adverse impacts of climate change on rice IWD under water-stressed conditions in Taiwan.
