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Datasets of high-resolution water level and discharge from the Saigon-Dong Nai estuary system impacted by a developing megacity, Ho Chi Minh City - Vietnam
- Source :
- Data in Brief, Vol 48, Iss , Pp 109147- (2023)
- Publication Year :
- 2023
- Publisher :
- Elsevier, 2023.
-
Abstract
- We present a new hydrological dataset collected during a field campaign in the Saigon-Dong Nai estuary system, Vietnam. These data include water level and water temperature measurements at five locations along the Saigon river and 2 locations along the Dong Nai river as well as discharge measurements from four 24-hour Acoustic Doppler Current Profiler (ADCP) campaigns at 2 locations in the Saigon river and 1 location in the Dong Nai river. Additionally, water level was barometrically compensated using air pressure measurements. Data were sampled between October 21st, 2022 and December 16th, 2022 and are provided in three processing stages namely, direct measurements as provided by the sensors (raw), barometricaly compensated measurements (pre-processed) and corrected measurements (post-processed). Even though of short duration (about 2 months), this dataset provides water level measurements at unprecedented spatial and temporal resolution in a region where data is scarce and not freely available. The synchronous logging of multiple water level sensors along river provides an opportunity to study profiles of water surface slope and upstream tidal propagation. Furthermore, the concurrent discharge measurements can be used to calibrate hydrological and/or hydraulic models of this estuary system. Additionally, the spatial resolution of this dataset is similar to the prospective measurements that the novel Surface Water and Ocean Topography (SWOT) satellite will provide. Thus, it enables the study of synthetic SWOT measurements to evaluate the future potential of the SWOT satellite over this estuary system.
Details
- Language :
- English
- ISSN :
- 23523409
- Volume :
- 48
- Issue :
- 109147-
- Database :
- Directory of Open Access Journals
- Journal :
- Data in Brief
- Publication Type :
- Academic Journal
- Accession number :
- edsdoj.5086bd95f82645e4b540bbaa8e27e8dc
- Document Type :
- article
- Full Text :
- https://doi.org/10.1016/j.dib.2023.109147