Snowpack, surface energy balance, and soil hydrology in cold regions: Integration of process-based modelling and multi-source data
Thesis event information
Date and time of the thesis defence
Place of the thesis defence
University of Oulu, OP Auditorium L10
Topic of the dissertation
Snowpack, surface energy balance, and soil hydrology in cold regions: Integration of process-based modelling and multi-source data
Doctoral candidate
Master of Science Jari-Pekka Nousu
Faculty and unit
University of Oulu Graduate School, Faculty of Technology, Water, Energy and Environmental Engineering
Subject of study
Environmental engineering
Opponent
Associate Professor Nick Rutter, Northumbria University
Custos
Associate Professor Hannu Marttila, University of Oulu
Predictive models and measurements reveal key hydrological processes and challenges in modelling
This doctoral dissertation combines predictive models and comprehensive measurement data in hydrological research, improving the accuracy of snow cover and soil moisture predictions. The study also offers new methods for understanding hydrological processes in cold regions.
In his doctoral dissertation, Jari-Pekka Nousu studied the processes related to snow cover, surface energy balance, and soil hydrology, as well as the challenges of modelling these processes in cold regions. The thesis consists of three separate studies that provide new solutions and recommendations for combining measurements and models, as well as improving the reliability of predictive models.
In the first study, Nousu examined the interactions between snow cover, vegetation, and atmosphere in boreal and subarctic environments. The results showed significant uncertainties in predicting the energy balance of snow cover and that different modelling methods have a substantial impact on the energy balance of forest ecosystems and snow cover. These findings are important for understanding atmospheric and hydrological processes and, for example, improving snowmelt and weather prediction models.
In the second study, Nousu applied statistical methods and historical data to correct errors in automatic snow forecasts in the French Alps and the Pyrenees. The method significantly improved the accuracy of snow forecasts, which is particularly crucial for avalanche prediction in mountainous areas.
The third study focused on soil hydrology in a northern Finnish catchment area. Nousu investigated the temporal and spatial variation of soil moisture using hydrological models, field measurements, and satellite-based estimates. The study revealed that groundwater flow significantly influences surface soil moisture. This insight is crucial for understanding hydrological and ecological processes. It can also aid in predicting drought risks and greenhouse gas emissions in cold regions.
The predictive models developed and tested in the thesis support the forecasting of avalanches, hydrology, and energy fluxes between soil, snow cover, vegetation, and the atmosphere. The research enhances our understanding of atmospheric and hydrological processes in cold regions, laying the foundation for environmental research under changing conditions.
In his doctoral dissertation, Jari-Pekka Nousu studied the processes related to snow cover, surface energy balance, and soil hydrology, as well as the challenges of modelling these processes in cold regions. The thesis consists of three separate studies that provide new solutions and recommendations for combining measurements and models, as well as improving the reliability of predictive models.
In the first study, Nousu examined the interactions between snow cover, vegetation, and atmosphere in boreal and subarctic environments. The results showed significant uncertainties in predicting the energy balance of snow cover and that different modelling methods have a substantial impact on the energy balance of forest ecosystems and snow cover. These findings are important for understanding atmospheric and hydrological processes and, for example, improving snowmelt and weather prediction models.
In the second study, Nousu applied statistical methods and historical data to correct errors in automatic snow forecasts in the French Alps and the Pyrenees. The method significantly improved the accuracy of snow forecasts, which is particularly crucial for avalanche prediction in mountainous areas.
The third study focused on soil hydrology in a northern Finnish catchment area. Nousu investigated the temporal and spatial variation of soil moisture using hydrological models, field measurements, and satellite-based estimates. The study revealed that groundwater flow significantly influences surface soil moisture. This insight is crucial for understanding hydrological and ecological processes. It can also aid in predicting drought risks and greenhouse gas emissions in cold regions.
The predictive models developed and tested in the thesis support the forecasting of avalanches, hydrology, and energy fluxes between soil, snow cover, vegetation, and the atmosphere. The research enhances our understanding of atmospheric and hydrological processes in cold regions, laying the foundation for environmental research under changing conditions.
Last updated: 21.10.2024