<script type="text/javascript">
<!--
document.write('<div id="oa_widget"></div>');
document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=undefined&type=result"></script>');
-->
</script>
doi: 10.31223/x5dk9d
Monitoring inland water levels is crucial for understanding hydrological processes to climate change impact leading to policy implementation. Satellite altimetry has proved to be an excellent technique to precisely measure water levels of rivers, lakes, and other inland water bodies. The ATL13 product of ICESat-2 space-borne LiDAR is solely dedicated to inland water bodies. The water surface heights were derived from ICESat-2's strong beams, and performance was assessed with respect to reservoir gauge observations. Statistical measurements were used to understand the agreement (R2= 0.99, %RMSE=0.08) among the datasets. An R2 value of 0.99 was observed between ICESat-2 derived water level anomaly and the reservoir storage anomaly. This study provides a unique opportunity to utilize the ATL13 data product to study reservoir water level variation and estimate the reservoir's storage. The methodology can also be helpful to understand the reservoir storage variation in a data-sparse region.
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 0 | |
popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |