Long-Term Water Surface Area Monitoring and Derived Water Level Using Synthetic Aperture Radar (SAR) at Altevatn, a Medium-Sized Arctic Lake

• Published in: Remote Sensing
• Main Authors: Hannah Vickers, Eirik Malnes, Kjell-Arild Høgda
• Format: Text
• Language: English
• Published: Multidisciplinary Digital Publishing Institute 2019
• Subjects: unsupervised clustering; synthetic aperture radar; lake water extent; Sentinel-1; long-term monitoring; hypsometry; Arctic; Norway; Arctic Lake; Asar; Northern Norway
• Online Access: https://doi.org/10.3390/rs11232780

Monitoring water storage in lakes and reservoirs is critical to water resource management, especially in a changing climate. Satellite microwave remote sensing offers a weather and light-independent solution for mapping water cover over large scales. We have used 13 years of synthetic aperture radar (SAR) data from three different sensors (Sentinel-1, RADARSAT-2, and Envisat advanced synthetic aperture radar (ASAR)) to develop a method for mapping surface water cover and thereby estimating the lake water extent (LWE). The method uses the unsupervised K-means clustering algorithm together with specific post-processing techniques to create binary maps of the water area. We have specifically tested and validated the method at Altevatn, a medium-sized arctic lake in Northern Norway, by using in-situ measurements of the water level. The multi-sensor SAR LWE time series were used in conjunction with the water level measurements to derive the lake hypsometry while at the same time quantifying the accuracy of our method. For Altevatn lake we estimated LWE with a root mean squared error (RMSE) of 0.89 km2 or 1.4% of the mean LWE, while the inferred lake water level (LWL) was associated with an RMSE of 0.40 m, or 2.5% of the maximum annual variation. We foresee that there is potential to further develop the algorithm by generalizing its use to other lakes worldwide and automating the process such that near real-time monitoring of LWE may be possible.