Impact of paddy irrigation levels on floods and water use in the Mekong River basin

Using the Global Land Surface Satellite (GLASS) leaf area index (LAI), the actual evapotranspiration (ETa) and available water resources in the Mekong River Basin were estimated with the Remote Sensing-Based Vegetation Interface Processes Model (VIP-RS). The relative contributions of climate variables and vegetation greening to ETa were estimated with numerical experiments. The results show that the average ETa in the entire basin increased at a rate of 1.16 mm year−2 from 1980 to 2012 (36.7% of the area met the 95% significance level). Vegetation greening contributed 54.1% of the annual ETa trend, slightly higher than that of climate change. The contributions of air temperature, precipitation and the LAI were positive, whereas contributions of solar radiation and vapor pressure were negative. The effects of water supply and energy availability were equivalent on the variation of ETa throughout most of the basin, except the upper reach and downstream Mekong Delta. In the upper reach, climate warming played a critical role in the ETa variability, while the warming effect was offset by reduced solar radiation in the Mekong Delta (an energy-limited region). For the entire basin, the available water resources showed an increasing trend due to intensified precipitation; however, in downstream areas, additional pressure on available water resources is exerted due to cropland expansion with enhanced agricultural water consumption. The results provide scientific basis for practices of integrated catchment management and water resources allocation.

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Error Correction of Multi-Source Weighted-Ensemble Precipitation (MSWEP) over the Lancang-Mekong River Basin

Remote Sensing ◽

10.3390/rs13020312 ◽

2021 ◽

Vol 13 (2) ◽

pp. 312

Author(s):

Xiongpeng Tang ◽

Jianyun Zhang ◽

Guoqing Wang ◽

Gebdang Biangbalbe Ruben ◽

Zhenxin Bao ◽

...

Keyword(s):

Error Correction ◽

River Basin ◽

Regional Scale ◽

Mekong River ◽

Precipitation Data ◽

Climate Data ◽

Hydrological Simulation ◽

Mekong River Basin ◽

Precipitation Estimation ◽

Simulation Results

The demand for accurate long-term precipitation data is increasing, especially in the Lancang-Mekong River Basin (LMRB), where ground-based data are mostly unavailable and inaccessible in a timely manner. Remote sensing and reanalysis quantitative precipitation products provide unprecedented observations to support water-related research, but these products are inevitably subject to errors. In this study, we propose a novel error correction framework that combines products from various institutions. The NASA Modern-Era Retrospective Analysis for Research and Applications (AgMERRA), the Asian Precipitation Highly-Resolved Observational Data Integration Towards Evaluation of Water Resources (APHRODITE), the Climate Hazards group InfraRed Precipitation with Stations (CHIRPS), the Multi-Source Weighted-Ensemble Precipitation Version 1.0 (MSWEP), and the Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks-Climate Data Records (PERSIANN) were used. Ground-based precipitation data from 1998 to 2007 were used to select precipitation products for correction, and the remaining 1979–1997 and 2008–2014 observe data were used for validation. The resulting precipitation products MSWEP-QM derived from quantile mapping (QM) and MSWEP-LS derived from linear scaling (LS) are evaluated by statistical indicators and hydrological simulation across the LMRB. Results show that the MSWEP-QM and MSWEP-LS can better capture major annual precipitation centers, have excellent simulation results, and reduce the mean BIAS and mean absolute BIAS at most gauges across the LMRB. The two corrected products presented in this study constitute improved climatological precipitation data sources, both time and space, outperforming the five raw gridded precipitation products. Among the two corrected products, in terms of mean BIAS, MSWEP-LS was slightly better than MSWEP-QM at grid-scale, point scale, and regional scale, and it also had better simulation results at all stations except Strung Treng. During the validation period, the average absolute value BIAS of MSWEP-LS and MSWEP-QM decreased by 3.51% and 3.4%, respectively. Therefore, we recommend that MSWEP-LS be used for water-related scientific research in the LMRB.

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River Levels Derived with CryoSat-2 SAR Data Classification—A Case Study in the Mekong River Basin

Remote Sensing ◽

10.3390/rs9121238 ◽

2017 ◽

Vol 9 (12) ◽

pp. 1238 ◽

Cited By ~ 13

Author(s):

Eva Boergens ◽

Karina Nielsen ◽

Ole Andersen ◽

Denise Dettmering ◽

Florian Seitz

Keyword(s):

River Basin ◽

Data Classification ◽

Mekong River ◽

Mekong River Basin ◽

Sar Data

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The Politics of Regional Governance in the Mekong River Basin

Global Change Peace & Security ◽

10.1080/0951274032000044522 ◽

2003 ◽

Vol 15 (1) ◽

pp. 59-76 ◽

Cited By ~ 12

Author(s):

Blake D. Ratner

Keyword(s):

River Basin ◽

Regional Governance ◽

Mekong River ◽

Mekong River Basin

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