Memory effect of soil water regime in wet forests, Norther Europe, Latvia

Forests in hydric (wet) growing conditions are characterised by waterlogged soil conditions for a significant portion of the year with peat layer less than 30 cm. In these locations growth of most tree species is hampered due to lack of oxygen in waterlogged soil, but peat accumulation does not take place as the organic detritus is decomposed during the dry periods. These are marginal ecosystems in between wetlands and drylands and as such are sensitive to climate change. But due to their limited practical value have often been neglected by researchers.

We study the soil water regime of hydric forests constructing Hydrus-1D soil water model. The model was validated with field observations of soil water content, potential and groundwater level at three field sites in Latvia, northern Europe. The meteorological parameters for the model forcing were obtained from the E-obs data set (version v24.0e), including wind speed, relative humidity, incoming shortwave radiation, air temperature and precipitation. Model run period was from 1980 to middle of June 2021.

The model was used to explore the sensitivity of the forest water balance to the crucial parameters such as soil grain size distribution, seasonality and value of the leaf area index (LAI) and canopy surface albedo, and root system ability to compensate lack of water or waterlogged conditions in some part of the soil profile. Preliminary results indicated that there is feedback between soil aeration and transpiration. This can result in a memory effect where increased transpiration leads to soil pore water depletion, better soil aeration and further increase in transpiration and vice versa.

This work was supported by ERDF postdoctoral research project “Groundwater and soil water regime”, under climate change (No. 1.1.1.2/VIAA/3/19/524).