TitleNS45A-0321 - Characterization of reservoir ice phenology using an automatic detection algorithm based on Sentinel-2A
Session Start2022-12-15 14:45:00 CST
Session End2022-12-15 18:15:00 CST
LocationMcCormick Place, Poster Hall, Hall - A
AuthorDoris
Presentation TypeIn Person Poster
AbstractIn cold regions, the longevity of lake and reservoir ice cover is reduced by rising global temperatures, with significant impacts on aquatic ecosystems. For example, the early break-up of the ice cover leads to an accelerated development of summer stratification and higher surface temperatures, which can result in lower dissolved oxygen concentrations in the water and more sustained evaporative losses. In order to diagnose these present and future changes, it is useful to employ modeling. While physically based lake models can be a good alternative for this purpose, they are generally too demanding in terms of input data to be deployed on a large scale in cold regions, which are therefore often difficult to access and with limited in situ monitoring. While lake ice has been studied for a long time, reservoir ice is rather poorly documented and differs from lake ice by significant water level fluctuations and outflows required for turbining. The objective of this study is to explore a simple and large-scale approach to model the ice cover duration of reservoirs in cold regions. The ice cover duration is estimated from satellite images, using an automated Sentinel-2A image processing algorithm that differentiates ice from water on the Google Earth Engine platform. The algorithm is applied to 479 northern hemisphere hydroelectric reservoirs from the Global Reservoirs and Dams (GRanD v1.3) database that are located north of the January 0�C isotherm. This allows for the creation of an entirely new database of phenology dates (ice-on and ice-off) associated with hydroelectric reservoirs from 2018 to 2021. These phenology dates, in combination with air temperature data from weather stations and/or reanalysis (ERA5-Land), are then used to model the ice cover duration of these reservoirs using the Stefan equation, which is based on daily air temperatures. Various parameters influencing ice formation are explored such as accumulated freezing degree days, climatic zones and reservoir morphometric parameters. A multivariate statistical study correlating physical and morphometric reservoir parameters with phenology dates is also performed. Finally, an ice thickness measurement campaign conducted during the winter of 2021-2022 at the Romaine-2 reservoir in Quebec provided a smaller-scale and more detailed application of the methodology.