Browsing by Author "Tyystjärvi, Vilna"

Soil moisture influences various environmental and climatological processes and is an important part of the hydrological cycle. The processes influencing its spatial and temporal variation are complex and linked with each other as well as influenced by soil moisture itself which makes observing them challenging. This is especially true in cold regions where soil moisture has shown strong fine scale variation and influences numerous ecosystem processes. To test different hypotheses related to soil moisture and to simulate its variation, several hydrological process-based models have been developed. Understanding how these models differ from each other and how they describe soil moisture is crucial in order to use them effectively. For this study, three process-based models representing varying model approaches and answering different research questions were chosen and used to simulate the spatial and temporal variation of soil moisture in a small study area in northwestern Finland. JSBACH is a global-scale land surface model that simulates various geophysical and geochemical processes over land and in the boundary layer between land surface and the atmosphere. SpaFHy is a catchment scale hydrological model developed to simulate water balance and evapotranspiration in boreal forests. Ecohydrotools is a hydrological model used to study fine scale spatial variation in soil hydrology. The model results show clear similarities as well as differences when compared with each other and with field measurements of soil moisture. The strongest similarities are in distinguishing wetter and drier areas in the study area, although the actual moisture content estimations vary between the models. All models show difficulties in simulating finer scale spatial variation, particularly in drier areas. Temporal variation shows more similarities between the models, although there are also clear discrepancies with measurements and the models. These simulations show that there are several things influencing a model’s capability to simulate soil moisture variation. Varying data requirements, included processes as well as model design and purpose all influence the results, leading to varying estimations of soil moisture. Improving model predictions in cold environments requires better understanding of the underlying processes as well as more detailed information on the environmental variables influencing soil moisture.