Viet Nam2026Monitoring flow variability in the lower Mekong River using multi-temporal remote sensing data
[Tên tác giả]
[Đơn vị công tác]
- Published in
- [Tên tạp chí hoặc hội nghị]
- Year
- 2026
- DOI
- 10.48550/clmv.2026.001
- Original language
- Tiếng Việt
- Topic
- Mekong water resources
- Published by
- [Đơn vị công tác]
Abstract
This study uses multi-temporal satellite imagery to analyse flow variability in the lower Mekong River during 2015–2025. Results show a marked shift in seasonal flow patterns compared with the historical hydrological cycle. The study proposes a monitoring framework combining remote sensing and ground stations to improve early warning reliability.
Background
Flow variability in the lower Mekong River is increasingly shaped by the combined effects of climate change and upstream water resource development, creating an urgent need for a monitoring system with broad spatial coverage and frequent updates.
Conventional monitoring based on ground station networks, while accurate, is limited in spatial density, particularly in cross-border areas where data sharing remains constrained.
Methods
The study uses a time series of optical and radar satellite imagery collected from 2015 to 2025, combined with water-level data from river gauging stations to build a model estimating inundation area and flow over time.
The analytical approach includes atmospheric correction of satellite imagery, extraction of surface water indices, and cross-validation against ground-truth data at selected points to assess model accuracy.
Key findings
Results show that the flood season in the lower reaches tends to arrive later and with greater variability compared with the hydrological cycle observed before 2015, consistent with reported changes in upstream reservoir operations.
The combined remote sensing and ground station model achieved notably higher accuracy in estimating inundation area than either data source used alone.
Policy recommendations
The study recommends that Mekong basin management agencies establish a mechanism for real-time sharing of remote sensing and gauging station data among countries, as a basis for a shared early warning system.
It also recommends investing in upgrading satellite data processing capacity at national agencies to reduce dependence on external data sources and analysis.