Hydrology and Carbon Flux Interconnections in a Hemiboreal Forest: Impacts of Heatwaves in Järvselja, Estonia

Understanding the coupling between hydrological dynamics and carbon sequestration is critical for predicting hemiboreal forest resilience to climate extremes. This study investigates water–carbon interactions in the Järvselja forest (Estonia) through a multi-objective hybrid modeling framework. We integrated long-term (2014–2025) eddy covariance flux measurements and daily meteorological data with a coupled architecture combining the process-based GR4J-Cemaneige model and a Long Short-Term Memory (LSTM) network. To validate the physical consistency of the deep learning component, we employed Support Vector Regression (SVR) diagnostic probes to map LSTM internal cell states against ERA5 soil moisture reanalysis data and in situ water table measurements. The combined LSTM + GR4J-Cemaneige model outperformed standalone approaches in the calibrated Reola catchment (NSE = 0.887), so by assuming hydrological similarity the hybrid model was regionalized to the streamflow ungauged Kalli basin. An in silico interpretability probe validated that the LSTM implicitly encoded physically meaningful soil moisture dynamics (r>0.9) without explicit training data. The analysis revealed that the 2018 heatwave triggered a synchronous collapse in water availability and carbon uptake, shifting the ecosystem from a robust sink to a net source. A significant legacy effect was observed, with carbon sequestration capacity lagging behind hydrological recovery for two years. The results of this paper substantiate the influence of climate warming on hemiboreal forests, demonstrating its implications for soil hydrology and the availability of water to sustain photosynthesis.