scholarly journals Satellite observations reveal thirteen years of reservoir filling strategies, operating rules, and hydrological alterations in the Upper Mekong River Basin

2021 ◽  
Author(s):  
Dung Trung Vu ◽  
Thanh Duc Dang ◽  
Stefano Galelli ◽  
Faisal Hossain

Abstract. The current situation in the Lancang–Mekong River Basin is emblematic of the issues faced by many transboundary basins around the world: riparian countries prioritize national water-energy policies and provide limited information on how major infrastructures are operated. In turn, such infrastructures and their management become a source of controversy. Here, we turn our attention to the Upper Mekong River, or Lancang, where a system of eleven mainstream dams controls about 55 % of the annual flow to Northern Thailand and Laos. Yet, assessing their actual impact is a challenging task because of the chronic lack of data on reservoir storage and dam release decisions. To overcome this challenge, we focus on the ten largest reservoirs and leverage satellite observations to infer 13-year time series of monthly storage variations. Specifically, we use area-storage curves (derived from a Digital Elevation Model) and time series of water surface area, which we estimate from Landsat images through a novel algorithm that removes the effects of clouds and other disturbances. We also use satellite radar altimetry data (Jason) to validate the results obtained from satellite imagery. Our results describe the evolution of the hydropower system and highlight the pivotal role played by Xiaowan and Nuozhadu reservoirs, which make up to ~85 % of the total system's storage in the Lancang River Basin. We show that these two reservoirs were filled in only two years, and that their operations did not change in response to the drought that occurred in the region in 2019–2020. Deciphering these operating strategies could help enrich existing monitoring tools and hydrological models, thereby supporting riparian countries in the design of more cooperative water-energy policies.

2019 ◽  
Vol 12 (1) ◽  
pp. 18
Author(s):  
Hok Sum Fok ◽  
Linghao Zhou ◽  
Yongxin Liu ◽  
Zhongtian Ma ◽  
Yutong Chen

Surface runoff (R), which is another expression for river water discharge of a river basin, is a critical measurement for regional water cycles. Over the past two decades, river water discharge has been widely investigated, which is based on remotely sensed hydraulic and hydrological variables as well as indices. This study aims to demonstrate the potential of upstream global positioning system (GPS) vertical displacement (VD) and its standardization to statistically derive R time series, which has not been reported in recent literature. The correlation between the in situ R at estuaries and averaged GPS-VD and its standardization in the river basin upstream on a monthly temporal scale of the Mekong River Basin (MRB) is examined. It was found that the reconstructed R time series from the latter agrees with and yields a similar performance to that from the terrestrial water storage based on gravimetric satellite (i.e., Gravity Recovery and Climate Experiment (GRACE)) and traditional remote sensing data. The reconstructed R time series from the standardized GPS-VD was found to have a 2–7% accuracy increase against those without standardization. On the other hand, it is comparable to data that are obtained by the Palmer drought severity index (PDSI). Similar accuracies are exhibited by the estimated R when externally validated through another station location with in situ time series. The comparison of the estimated R at the entrance of river delta against that at the estuaries indicates a 1–3% relative error induced by the residual ocean tidal effect at the estuary. The reconstructed R from the standardized GPS-VD yields the lowest total relative error of less than 9% when accounting for the main upstream area of the MRB. The remaining errors may be the result of the combined effect of the proposed methodology, remaining environmental signals in the data time series, and potential time lag (less than a month) between the upstream MRB and estuary.


2021 ◽  
Vol 13 (23) ◽  
pp. 4831
Author(s):  
Senlin Tang ◽  
Hong Wang ◽  
Yao Feng ◽  
Qinghua Liu ◽  
Tingting Wang ◽  
...  

Terrestrial water storage (TWS) is a critical variable in the global hydrological cycle. The TWS estimates derived from the Gravity Recovery and Climate Experiment (GRACE) allow us to better understand water exchanges between the atmosphere, land surface, sea, and glaciers. However, missing historical (pre-2002) GRACE data limit their further application. In this study, we developed a random forest (RF) model to reconstruct the monthly terrestrial water storage anomaly (TWSA) time series using Global Land Data Assimilation System (GLDAS) and Climatic Research Unit (CRU) data for the Lancang-Mekong River basin. The results show that the RF-built TWSA time series agrees well with the GRACE TWSA time series for 2003–2014, showing that correlation coefficients (R) of 0.97 and 0.90 at the basin and grid scales, respectively, which demonstrates the reliability of the RF model. Furthermore, this method is used to reconstruct the historical TWSA time series for 1980–2002. Moreover, the discharge can be obtained by subtracting the evapotranspiration (ET) and RF-built terrestrial water storage change (TWSC) from the precipitation. The comparison between the discharge calculated from the water balance method and the observed discharge showed significant consistency, with a correlation coefficient of 0.89 for 2003–2014 but a slightly lower correlation coefficient (0.86) for 1980–2002. The methods and findings in this study can provide an effective means of reconstructing the TWSA and discharge time series in basins with sparse hydrological data.


2017 ◽  
Vol 14 (3) ◽  
pp. 39-48 ◽  
Author(s):  
Faisal Hossain ◽  
Safat Sikder ◽  
Nishan Biswas ◽  
Matthew Bonnema ◽  
Hyongki Lee ◽  
...  

2018 ◽  
Vol 564 ◽  
pp. 559-573 ◽  
Author(s):  
Ibrahim Nourein Mohammed ◽  
John D. Bolten ◽  
Raghavan Srinivasan ◽  
Venkat Lakshmi

2021 ◽  
Vol 765 ◽  
pp. 144494
Author(s):  
He Chen ◽  
Junguo Liu ◽  
Ganquan Mao ◽  
Zifeng Wang ◽  
Zhenzhong Zeng ◽  
...  

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