Variability of evapotranspiration fluxes affected by dry and wet year transitions in beech, pine and mixed stands in the lowland of northeast Germany

Abstract

Increasing climate variability, especially prolonged droughts, shapes forest water consumption and constrains vegetation growth. However, the effects of drought-induced changes on evapotranspiration (ET) fluxes vary due to species-specific differences and drought characteristics. Here, we analyzed the seasonal variations in ET in pine, beech, and mixed forest stands in northeast Germany (2012–2021) and explored the ability of a process-based ecohydrological model (EcH₂O) in reproducing the water balance components observed at three forested lysimeters. To better understand how individual climate variables control ET fluxes, we performed simulation experiments with detrended climate inputs. Multi-variable calibration showed that the model reproduced well in-situ soil moisture, seepage, and interception (EI) in the three stands. Precipitation (P) was the main driver of ET anomalies, with above-average ET in wet years and below-average ET in dry years. However, only small reductions in ET were observed during the dry year 2018. This could be attributed to high P in the previous year, i.e., P legacy effects, which led to only small reductions or even positive anomalies in ET. The beech stand, with a seasonal leaf cycle, had lower ET and interception losses compared to the pine and mixed stands, which maintain year-round foliage. This resulted in greater percolation to deeper soil layers in beech forests. These findings suggest that broadleaf species such as beech by allowing greater water transfer to groundwater, offer a distinct hydrological advantage in terms of promoting deep percolation. Our results therefore provide a process-based rationale for the strategic selection of broadleaf species in forest management to enhance groundwater recharge and promote sustainable water management. Additionally, model testing at such data-rich sites will be valuable for improving the process-consistency and reliability of other hydrological models, particularly in studies aimed at investigating the effects of different vegetation cover.