Abstract

Understanding long-term hydroclimatic variability in the central Alps is essential when placing recent changes in precipitation and streamflow within a broader temporal context. This study reconstructs warm-season hydroclimatic variability in the central Alps using tree-ring-based hydroclimatic proxies from the Old World Drought Atlas (OWDA). Seasonal April–May–June–July–August (AMJJA) precipitation at Innsbruck, Austria, and seasonal May–June–July–August (MJJA) streamflow at the St. Jodok gauge were reconstructed using OWDA self-calibrating Palmer Drought Severity Index (scPDSI) predictors and moving-window Stepwise Linear Regression (SLR) models. Calibration windows of 30, 40, and 50 years were developed to account for temporal variability in predictor–climate relationships, and reconstruction uncertainty was quantified using multi-model ensemble bounds. An independent Deep Learning reconstruction was also developed for precipitation to provide an assessment of reconstruction skill and long-term climate trends. Specifically, the results demonstrate a robust reconstruction skill, with mean calibration R2 values of 0.65 for streamflow and 0.59 for precipitation. The streamflow reconstruction indicates that recent sustained increases represent the strongest positive anomaly in approximately 650 years, while reconstructed precipitation suggests recent decades are among the wettest sustained intervals of the last ~2000 years. Both records reveal a pronounced transition from severe late 19th-century drought conditions to persistent modern pluvial conditions. Agreement between regression and Deep Learning reconstructions supports the robustness of the identified long-term wetting trend and highlights the exceptional nature of recent hydroclimatic conditions in the central Alps.

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