Abstract. 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.

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 CO2 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.

The Greater Mekong Subregion is a transnational area bound together by the Mekong River basin and its immense hydropower resources, historically seen as the backbone of regional economic development. The basin is now punctuated by several dams, successful in attracting both international investors and fierce criticisms for their environmental and societal impacts. Surprisingly, no attention has been paid so far to the actual performance of these infrastructures: is hydropower supply robust with respect to the hydroclimatic variability characterizing Southeast Asia? When water availability is altered, what are the implications for power production costs and CO2 emissions? To answer these questions, we focus on the Laotian–Thai grid—the first international power‐trade infrastructure developed in the region—and use a power system model driven by a spatially distributed hydrological‐water management model. Simulation results over a 30‐year period show that production costs and carbon footprint are significantly affected by droughts, which reduce hydropower availability and increase reliance on thermoelectric resources. Regional droughts across the Mekong basin are of particular concern, as they reduce the export of cheap hydropower from Laos to Thailand. To put the analysis into a broader climate‐water‐energy context, we show that the El Niño Southern Oscillation modulates not only the summer monsoon, but also the power system behavior, shaping the relationship between hydroclimatological conditions, power production costs, and CO2 emissions. Overall, our results and models provide a knowledge basis for informing robust management strategies at the water‐energy scale and designing more sustainable power plans in the Greater Mekong Subregion.