A snow quality assessment tool based on new techniques and sámi knowledge (Snow4all)
|Coordinator||Stockholms universitet - Institutionen för naturgeografi|
|Funding from Vinnova||SEK 2 910 000|
|Project duration||November 2017 - December 2020|
Purpose and goal
Our main aim is to develop new methods tp access information on snow quality and assess the impact of changed snow conditions on ecosystems using Sami knowledge. We will develop and test a physical snow-model which simulates ice layers in the snowpack (WP1). Collect data in the field for calibration and validation of model and UAV derived data (WP2). We will develop Unmanned Aerial Vehicle (UAV) methods to measure different snow properties (WP3) and implement snow process representations in the SMHI hydrological modelling system (WP4) and develop a prototype snow-forecasting tool.
Expected results and effects
The results provided in this project will support sustainable management of the rapidly changing environment in northern Sweden. This is because information on snow conditions will allow a more sustainable reindeer grazing which keeps ecosystems in balance.
Planned approach and implementation
We will use a snow-model to simulate present and future snow using regional climate model data (WP1). We will use weather data to validate the model results together with results from manual snow surveys (WP2). We will develop methodologies to measure snow attributes with UAV platforms carrying different types of sensors to investigate the potential to measure changes in snow conditions (WP3). SMHI computational- and data infrastructures for hydrological forecasting will be used to develop a prototype tool for analysis and forecasting of snow conditions in the case study areas (WP4).