Automated Water Level Monitoring at the Continental Scale from ICESat-2 Photons

Of the approximately 6700 lakes and reservoirs larger than 1 km2 in the Contiguous United States (CONUS), only ~430 (~6%) are actively gaged by the United States Geological Survey (USGS) or their partners and are available for download through the National Water Information System database. Remote sensing analysis provides a means to fill in these data gaps in order to glean a better understanding of the spatiotemporal water level changes across the CONUS. This study takes advantage of two-plus years of NASA’s ICESat-2 (IS-2) ATLAS photon data (ATL03 products) in order to derive water level changes for ~6200 overlapping lakes and reservoirs (>1 km2) in the CONUS. Interactive visualizations of large spatial datasets are becoming more commonplace as data volumes for new Earth observing sensors have markedly increased in recent years. We present such a visualization created from an automated cluster computing workflow that utilizes tens of billions of ATLAS photons which derives water level changes for all of the overlapping lakes and reservoirs in the CONUS. Furthermore, users of this interactive website can download segmented and clustered IS-2 ATL03 photons for each individual waterbody so that they may run their own analysis. We examine ~19,000 IS-2 derived water level changes that are spatially and temporally coincident with water level changes from USGS gages and find high agreement with our results as compared to the in situ gage data. The mean squared error (MSE) and the mean absolute error (MAE) between these two products are 1 cm and 6 cm, respectively.

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Global Estimation and Assessment of Monthly Lake/Reservoir Water Level Changes Using ICESat-2 ATL13 Products

Remote Sensing ◽

10.3390/rs13142744 ◽

2021 ◽

Vol 13 (14) ◽

pp. 2744

Author(s):

Nan Xu ◽

Huiying Zheng ◽

Yue Ma ◽

Jian Yang ◽

Xinyuan Liu ◽

...

Keyword(s):

Water Level ◽

The United States ◽

Water Levels ◽

Reservoir Water ◽

Reservoir Water Level ◽

Inland Water ◽

Water Level Changes ◽

Global Estimation ◽

Water Surfaces ◽

Lakes And Reservoirs

Accurate and detailed information on lake/reservoir water levels and temporal changes around the globe is urgently required for water resource management and related studies. The traditional satellite radar altimeters normally monitor water level changes of large lakes and reservoirs (i.e., greater than 1 km2) around the world. Fortunately, the recent Ice, Cloud, and land Elevation Satellite-2 (ICESat-2) makes it possible to monitor water level changes for some small lakes and reservoirs (i.e., less than 1 km2). ICESat-2 ATL13 products provide observations of inland water surface heights, which are suitable for water level estimation at a global scale. In this study, ICESat-2 ATL13 products were used to conduct a global estimation and assessment of lake/reservoir water level changes. We produced monthly water levels for 13,843 lakes and reservoirs with areas greater than 0.1 km2 and all-season ATL13 products across the globe, in which 2257 targets are smaller than 1 km2. In total, the average valid number of months covered by ICESat-2 is 5.41 months and only 204 of 13,843 lakes and reservoirs have water levels in all the months in 2019. In situ water level data from 21 gauge stations across the United States and 12 gauge stations across Australia were collected to assess the monthly lake/reservoir water levels, which exhibited a high accuracy (RMSE = 0.08 m, r = 0.999). According to comparisons between the monthly water levels and changes from ATL08 products in another study and ATL13 products in this study, we found that both products can accurately estimate the monthly water level of lakes and reservoirs, but water levels derived from ATL13 products exhibited a higher accuracy compared with water levels derived from ATL08 products (RMSE = 0.28 m, r = 0.999). In general, the ATL13 product is more convenient because the HydroLAKES mask of inland water bodies, the orthometric height (with respect to the EGM2008 geoid) of water surfaces, and several data quality parameters specific to water surfaces were involved in the ATL13 product.

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