A least-squares collocation approach to densifying river level from multi-mission satellite altimetry; Case study Mackenzie River basin

Measuring river water level is essential for the global freshwater system monitoring, water resource management, hydrological model development, and climate change assessment. Despite its importance, the number of in-situ gauges has decreased over the recent decades. Moreover, many of the river systems are monitored either sparsely or not long enough to investigate their long-term evolution. Satellite altimetry is a unique technique that has enabled quantifying river levels for more than 25 years. Single mission altimetric water level time series can be obtained at the intersection of the satellite ground tracks and the river. For operational hydrology, however, single mission satellite altimetry is limited in its spatial and temporal sampling governed by the orbit configuration. This study proposes a framework to estimate the long-term sub-monthly river water level over the entire river using Least-Squares Collocation (LSC) by benefiting from multi-mission altimetric water levels (both interleaved and repeat orbit missions). The proposed method allows us to obtain dense water level observations both in time and space.  We present the results over the Mackenzie River basin, located in Canada, and validate against in-situ data.