Unraveling Temporal Complexities in Lake Science through Sediment Records and Process-Based Models 

The expected alterations in nutrient levels and climate conditions are projected to significantly reduce oxygen concentrations in numerous stratified lakes globally. Nevertheless, the exact duration, timing, and consequences on lake oxygen over decadal to centennial scales remain uncertain due to the limited availability of long-term monitoring data. In this study, we introduce an innovative model-data assimilation approach that integrates 150 years of limnological and paleolimnological data to assess the human-induced impact and future outlook of dissolved oxygen (DO) conditions in the renowned Lake Geneva under various climate scenarios. Pluri-decadal series of limnological data monthly collected by the French Observatoire des LAcs (OLA database) were used to calibrate and validate the model. In addition, model outputs were further validated with published paleolimnological records for the past 170 years. Results of the calibration procedure show that the GLM-AED2 model accurately predicts the magnitude and seasonal dynamics of the state variables with goodness-of-fit metrics under the literature range (e.g. RMSE = 0.96 mg L–1 and RRMSE = 25% for dissolved oxygen; RMSE = 6.53 ug L–1 and RRMSE = 37% for chlorophyll-a, both in the epilimnion). Our analysis reveals that over centennial timescales, it was eutrophication combined with reduced winter mixing that initiated prolonged and severe bottom-water hypoxia. Conversely, examining the recent years and projecting forward to 2100, climate change is poised to be the primary driver of hypoxia in Lake Geneva and analogous lakes, even with decreased phosphorus concentrations. Our results strongly advocate for the necessity of reducing local phosphorus inputs in stratified lakes to avert deoxygenation. However, it is essential to acknowledge that doing so may also limit lake productivity due to nutrient availability.