Multi-scale soil moisture data and process-based modeling reveal the importance of lateral groundwater flow in a subarctic catchment
Year: 2024
Type: article
Abstract: Soil moisture plays a key role in soil nutrient and carbon cycling; plant productivity; and energy, water, and greenhouse gas exchanges between the land and the atmosphere. The knowledge on drivers of spatiotemporal soil moisture dynamics in subarctic landscapes is limited. In this study, we used the Spatial Forest Hydrology (SpaFHy) model, in situ soil moisture data, and Sentinel-1 synthetic aperture radar (SAR)-based soil moisture estimates to explore spatiotemporal controls of soil moisture in a subarctic headwater catchment in northwestern Finland. The role of groundwater dynamics and lateral flow in soil moisture was studied through three groundwater model conceptualizations: (i) omission of groundwater storage and lateral flow, (ii) conceptual TOPMODEL approach based on topographic wetness index, and (iii) explicit 2D lateral groundwater flow. The model simulations were compared against continuous point soil moisture measurements, distributed manual measurements, and novel SAR-based soil moisture estimates available at high spatial and temporal resolutions. Based on model scenarios and model–data comparisons, we assessed when and where the lateral groundwater flow shapes shallow soil moisture and under which conditions soil moisture variability is driven more by local ecohydrology, i.e., the balance of infiltration, drainage, and evapotranspiration. The choice of groundwater flow model was shown to have a strong impact on modeled soil moisture dynamics within the catchment. All model conceptualizations captured the observed soil moisture dynamics in the upland forests, but accounting for the lateral groundwater flow was necessary to reproduce the saturated conditions common in the peatlands and occasionally in lowland forest grid cells. We further highlight the potential of integrating multi-scale observations with land surface and hydrological models. The results have implications for ecohydrological and biogeochemical processes, as well as for modeling hydrology and Earth system feedbacks in subarctic and boreal environments.
Language: English
Subfield: Environmental Engineering
Field: Environmental Science
Domain: Physical Sciences
SDGs: Life on land, Climate action
Open Access status: gold
Estimated APC paid: $1,993
Awards: G1733659723, G4311023376, G495187929, Correcting a bias undermining the global importance of snowmelt (SNOMLT), Precision nutrient management - a tool for mitigation of climate change and environmental loading in boreal forestry, Building a multi-physics model to explore forest snow feedbacks to the atmosphere and terrestrial systems, G7295091557, G8135058772, LS-HYDRO: From forest structure to hydrological function – merging dense Earth Observation data and process-models
OpenAlex ID: W4403734950