•Hydropower reservoirs and diversions are severely altering Mekong basin streamflow.•Dam-induced flow alteration on both mainstream and tributaries are reviewed.•Alteration assessments must consider ...hydropeaking, diversions and timing impacts.•Dams can offset or exacerbate impacts of changing climate, water use and land cover.•Observed and projected impacts must be assessed systematically and synergistically.
Hydropower production is altering the Mekong River basin’s riverine ecosystems, which contain the world’s largest inland fishery and provide food security and livelihoods to millions of people. The basin’s hydropower reservoir storage, which may rise from ∼2% of its mean annual flow in 2008 to ∼20% in 2025, is attenuating seasonal flow variability downstream of many dams with integral powerhouses and large storage reservoirs. In addition, tributary diversions for off-stream energy production are reducing downstream flows and augmenting them in recipient tributaries. To help manage tradeoffs between dam benefits (hydropower, irrigation, flood control, domestic water supply, and navigation) and their consequences for livelihoods and ecosystems, we review observed and projected impacts on river flows along both the Mekong mainstream and its tributaries. We include the effects of diversions and inter-basin transfers, which prior reviews of flow alteration in the Mekong basin have largely neglected. We also discuss the extent to which concurrent changes in climate, water demand, and land use, may offset or exacerbate hydropower-induced flow alteration. Our major recommendations for assessing hydrological impacts in the Mekong and other basins undergoing rapid hydropower development include synchronizing and integrating observational and modeling studies, improving the accuracy of reservoir water balances, evaluating multi-objective reservoir operating rules, examining hydropeaking-induced flow alteration, conducting multi-dam safety assessments, evaluating flow indicators relevant to local ecosystems and livelihoods, and considering alternative energy sources and reservoir sedimentation in long-term projections. Finally, we strongly recommend that dam impact studies consider hydrological alteration in conjunction with fish passage barriers, geomorphic changes and other contemporaneous stressors.
During the past decades, the increased impact of anthropogenic interventions on river basins has prompted hydrologists to develop various approaches for representing human–water interactions in ...large-scale hydrological and land surface models. The simulation of water reservoir storage and operations has received particular attention, owing to the ubiquitous presence of dams. Yet, little is known about (1) the effect of the representation of water reservoirs on the parameterization of hydrological models, and, therefore, (2) the risks associated with potential flaws in the calibration process. To fill in this gap, we contribute a computational framework based on the Variable Infiltration Capacity (VIC) model and a multi-objective evolutionary algorithm, which we use to calibrate VIC's parameters. An important feature of our framework is a novel variant of VIC's routing model that allows us to simulate the storage dynamics of water reservoirs. Using the upper Mekong river basin as a case study, we calibrate two instances of VIC – with and without reservoirs. We show that both model instances have the same accuracy in reproducing daily discharges (over the period 1996–2005), a result attained by the model without reservoirs by adopting a parameterization that compensates for the absence of these infrastructures. The first implication of this flawed parameter estimation stands in a poor representation of key hydrological processes, such as surface runoff, infiltration, and baseflow. To further demonstrate the risks associated with the use of such a model, we carry out a climate change impact assessment (for the period 2050–2060), for which we use precipitation and temperature data retrieved from five global circulation models (GCMs) and two Representative Concentration Pathways (RCPs 4.5 and 8.5). Results show that the two model instances (with and without reservoirs) provide different projections of the minimum, maximum, and average monthly discharges. These results are consistent across both RCPs. Overall, our study reinforces the message about the correct representation of human–water interactions in large-scale hydrological models.
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•Top ten influencing factors of groundwater salinization were identified.•The CatBoost Regression model provides the highest accuracy salinity prediction.•In the Mekong Delta, ...groundwater pumping has a strong impact on salinization processes.•Forty-eight percentage of the population is in threshold salinity areas (>250 mg/L).•Immediate actions are needed to prevent groundwater salinization.
Groundwater salinization is considered as a major environmental problem in worldwide coastal areas, influencing ecosystems and human health. However, an accurate prediction of salinity concentration in groundwater remains a challenge due to the complexity of groundwater salinization processes and its influencing factors. In this study, we evaluate state-of-the-art machine learning (ML) algorithms for predicting groundwater salinity and identify its influencing factors. We conducted a study for the coastal multi-layer aquifers of the Mekong River Delta (Vietnam), using a geodatabase of 216 groundwater samples and 14 conditioning factors. We compared the predictive performances of different ML techniques, i.e., the Random Forest Regression (RFR), the Extreme Gradient Boosting Regression (XGBR), the CatBoost Regression (CBR), and the Light Gradient Boosting Regression (LGBR) models. The model performance was assessed by using root-mean-square error (RMSE), coefficient of determination (R2), the Akaike Information Criterion (AIC), and Bayesian Information Criterion (BIC). The results show that the CBR model has the highest performance with both training (R2 = 0.999, RMSE = 29.90) and testing datasets (R2 = 0.84, RMSE = 205.96, AIC = 720.60, and BIC = 751.04). Ten of the 14 influencing factors, including the distance to saline sources, the depth of screen well, the groundwater level, the vertical hydraulic conductivity, the operation time, the well density, the extraction capacity, the thickness of the aquitard, the distance to fault, and the horizontal hydraulic conductivity are the most important factors for groundwater salinity prediction. The results provide insights for policymakers in proposing remediation and management strategies for groundwater salinity issues in the context of excessive groundwater exploitation in coastal lowland regions. Since the human-induced influencing factors have significantly influenced groundwater salinization, urgent actions should be taken into consideration to ensure sustainable groundwater management in the coastal areas of the Mekong River Delta.
Strategic dam planning and the deployment of decentralized renewable technologies are two elements of the same problem, yet normally addressed in isolation. Here, we show that an integrated view of ...the power system capacity expansion problem could have transformative effects for Southeast Asia's hydropower plans. We demonstrate that Thailand, Laos, and Cambodia have tangible opportunities for meeting projected electricity demand and CO
emission targets with less hydropower than currently planned-options range from halting the construction of all dams in the Lower Mekong to building 82% of the planned ones. The key enabling strategies for these options to succeed are solar PV and regional coordination, expressed in the form of centralized planning and cross-border power trading. The alternative expansion plans would slightly increase the cumulative costs (up to 2.4%), but substantially limit the fragmentation of additional river reaches, thereby offering more sustainable pathways for the Mekong's ecosystems and riparian people.
Abstract
Rainfall–runoff modelling is complicated due to numerous complex interactions and feedback in the water cycle among precipitation and evapotranspiration processes, and also geophysical ...characteristics. Consequently, the lack of geophysical characteristics such as soil properties leads to difficulties in developing physical and analytical models when traditional statistical methods cannot simulate rainfall–runoff accurately. Machine learning techniques with data-driven methods, which can capture the nonlinear relationship between prediction and predictors, have been rapidly developed in the last decades and have many applications in the field of water resources. This study attempts to develop a novel 1D convolutional neural network (CNN), a deep learning technique, with a ReLU activation function for rainfall–runoff modelling. The modelling paradigm includes applying two convolutional filters in parallel to separate time series, which allows for the fast processing of data and the exploitation of the correlation structure between the multivariate time series. The developed modelling framework is evaluated with measured data at Chau Doc and Can Tho hydro-meteorological stations in the Vietnamese Mekong Delta. The proposed model results are compared with simulations of long short-term memory (LSTM) and traditional models. Both CNN and LSTM have better performance than the traditional models, and the statistical performance of the CNN model is slightly better than the LSTM results. We demonstrate that the convolutional network is suitable for regression-type problems and can effectively learn dependencies in and between the series without the need for a long historical time series, is a time-efficient and easy to implement alternative to recurrent-type networks and tends to outperform linear and recurrent models.
The Soil and Water Assessment Tool (SWAT) is one of the most widely used and well-tested eco-hydrological models. However, parameter calibration, sensitivity analysis and uncertainty analysis remain ...among the most challenging tasks. Existing SWAT parameter calibration, sensitivity analysis, and uncertainty analysis tools are either commercial products or free tools with limited options. This study demonstrates an interactive graphical user interface tool in the R environment for SWAT parameter calibration, sensitivity and uncertainty analyses, and visualization, called R-SWAT. Different R functions/packages for parameter calibration, sensitivity analysis, and uncertainty analysis have been incorporated into R-SWAT. Third-party packages can be integrated into R-SWAT with minimum effort. The application of R-SWAT for a test case study demonstrates its functionalities. In general, R-SWAT (1) is a potential platform for developing and testing new sensitivity or optimization packages, and (2) promotes the understanding of hydrological processes with open-source SWAT and R.
•An R tool for SWAT parameter calibration, sensitivity analysis, and uncertainty analysis is introduced.•Integration with new sensitivity or optimization packages is streamlined.•The proposed tool enhances hydrological research with SWAT and R.
Coastal lowlands are of particular importance in providing food, shelter, and livelihoods for large populations; yet aggravating effects caused by human activities and climate change have exposed ...these areas to multiple challenges. Located in the southernmost part of the Lower Mekong Basin, the Vietnamese Mekong Delta (VMD) is adversely affected by upstream hydropower development, localised water-engineering systems (dykes), climatic factors, and sea level rise. This paper examines how these drivers shape the adaptation strategies of rural communities in the coastal areas. Using mixed sources of historical measured data, numerical modelling and qualitative data gathered in three coastal provinces (Ben Tre, Tra Vinh, and Soc Trang), we find that hydrological alterations are manipulated by various drivers with more immediate effects of the tidal systems and sea level rise in the Vietnamese East Sea. The study results suggest that while these impacts are not adequately addressed by delta-scale measures, a mixed policy approach including control and adaptation measures has been adopted to tackle saltwater intrusion on the local scale. The paper provides a holistic insight into the complex temporal-spatial dimensions of hydrological change which have distressed coastal agroecosystems and resource-dependent communities. The paper argues that while voicing concerns over transboundary hydropower impacts is essential, in situ collaborative efforts among salinity-affected jurisdictions are equally important in addressing high uncertainty and complexity of saltwater intrusion in the future.
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•Hydrological alterations in the Vietnamese Mekong Delta are manipulated by multiple drivers.•Saltwater intrusion in the study areas is largely driven by tidal systems and sea level rise of the Vietnamese East Sea.•Saltwater intrusion events place heavy pressures on coastal agroecosystems and resource-dependent communities.•The dual ‘adaptation and control’ policy has been exercised to deal with saltwater intrusion across governance scales.
The estuaries and coastal zones of the Vietnamese Mekong Delta located at the end of the Mekong Basin are susceptible to a large variety of natural threats and human interventions such as upstream ...dam construction, climate change and sea level rise. In this study, we investigated sediment dynamics and morphodynamic changes in the Mekong estuaries and coastal zone, using a well-calibrated Delft3D-4 model for a 10-years period simulation. For the first time, the impacts of different drivers were distinguished to guide future adaptation strategies and policies. Our investigations pointed out that the influences of upstream sediment reduction and large-scale sand extraction would cause substantial modifications in the subaqueous delta region. Besides human-induced impacts, modeling results also showed that the sediment volume and spatial distribution changed through the simulated period according to monsoonal variation. The influence of each driver, however, not only varied in space but also time. In the flood season, the Mekong and Bassac Rivers provided a large amount of sediment (more than 90%) that was deposited on the delta front due to coastal processes. The sediment quantity transported along the coastline changed with the monsoon and was in a dominantly south-west direction due to the northeast monsoon, especially in November, December and January. As a natural process, in the estuarine region, erosion and deposition occurred alternately, but the south-west coast region (belonging to the Ca Mau peninsula) was dominated by erosion. This is because of the formation of sand bars in front of the Bassac estuaries, which influences the capacity of sediment transportation to the south-west. Consequently, navigation capacity will reduce significantly in the estuaries and coastline erosion in the Ca Mau peninsula leads to substantial loss of houses and assets of local people. Urgent actions such as stopping sand mining or modifying dam designs are needed to sustain the delta coastline.
•A well-calibrated Delft3D model against observed and remote sensing data.•Sediment transport is strongly driven by both river discharges and monsoons.•Long-term sand bar formation diverted the direction of current sediment flows.•Human activities will lead to the severe recession of the delta.
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 11 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 10 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 water level data (Jason and Sentinel-3) 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 about 2 years and that their operations were marginally affected by the drought that occurred in the region in 2019–2020. Deciphering these operating strategies will help enrich existing monitoring tools and hydrological models, thereby supporting riparian countries in the design of more cooperative water–energy policies.
Macroscale hydrological and land surface models increasingly rely on novel streamflow routing algorithms that explicitly account for the presence of engineered water storages, which largely affect ...river basin dynamics. In this short communication, we contribute to this growing field by presenting VIC-ResOpt, a software package for the representation and optimization of water reservoirs in the routing model commonly used as a post-processor with the Variable Infiltration Capacity (VIC) hydrologic model. VIC-ResOpt comprises tools for simulating different reservoir operating approaches, optimizing operations, and exploring the sensitivity of the model output with respect to the parameterization of the operating rules. The package relies on automated scripts and optimization engines, thereby requiring minimal user effort. We demonstrate some of its functionalities in the upper portion of the Chao Phraya river basin (Thailand), which is regulated by two large dams.
•Explicit representation of water reservoirs in the VIC hydrologic model.•Simulation and optimization of both rule curves and operating rules.•Powered by state-of-the-art optimization algorithms.•VIC-ResOpt can support regional and global studies on regulated river basins.
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