The ongoing and proposed construction of large-scale hydropower dams in the Mekong river basin is a subject of intense debate and growing international concern due to the unprecedented and potentially irreversible impacts these dams are likely to have on the hydrological, agricultural, and ecological systems across the basin. Studies have shown that some of the dams built in the tributaries and the main stem of the upper Mekong have already caused basin-wide impacts by altering the magnitude and seasonality of flows, blocking sediment transport, affecting fisheries and livelihoods of downstream inhabitants, and changing the flood pulse to the Tonle Sap Lake. There are hundreds of additional dams planned for the near future that would result in further changes, potentially causing permanent damage to the highly productive agricultural systems and fisheries, as well as the riverine and floodplain ecosystems. Several studies have examined the potential impacts of existing and planned dams but the integrated effects of the dams when combined with the adverse hydrologic consequences of climate change remain largely unknown. Here, we provide a detailed review of the existing literature on the changes in climate, land use, and dam construction and the resulting impacts on hydrological, agricultural, and ecological systems across the Mekong. The review provides a basis to better understand the effects of climate change and accelerating human water management activities on the coupled hydrological-agricultural-ecological systems, and identifies existing challenges to study the region’s Water, Energy, and Food (WEF) nexus with emphasis on the influence of future dams and projected climate change. In the last section, we synthesize the results and highlight the urgent need to develop integrated models to holistically study the coupled natural-human systems across the basin that account for the impacts of climate change and water infrastructure development. This review provides a framework for future research in the Mekong, including studies that integrate hydrological, agricultural, and ecological modeling systems.

The Mekong River Basin (MRB) is one of the significant river basins in the world. For political and economic reasons, it has remained mostly in its natural condition. However, with population increases and rapid industrial growth in the Mekong region, the river has recently become a hotbed of hydropower development projects. This study evaluated these changing hydrological conditions, primarily driven by climate as well as land use and land cover change between 1992 and 2015 and into the future. A 3% increase in croplands and a 1–2% decrease in grasslands, shrublands, and forests was evident in the basin. Similarly, an increase in temperature of 1–6 °C and in precipitation of 15% was projected for 2015–2099. These natural and climate-induced changes were incorporated into two hydrological models to evaluate impacts on water budget components, particularly streamflow. Wet season flows increased by up to 10%; no significant change in dry season flows under natural conditions was evident. Anomaly in streamflows due to climate change was present in the Chiang Saen and Luang Prabang, and the remaining flow stations showed up to a 5% increase. A coefficient of variation <1 suggested no major difference in flows between the pre- and post-development of hydropower projects. The results suggested an increasing trend in streamflow without the effect of dams, while the inclusion of a few major dams resulted in decreased river streamflow of 6% to 15% possibly due to irrigation diversions and climate change. However, these estimates fall within the range of uncertainties in natural climate variability and hydrological parameter estimations. This study offers insights into the relationship between biophysical and anthropogenic factors and highlights that management of the Mekong River is critical to optimally manage increased wet season flows and decreased dry season flows and handle irrigation diversions to meet the demand for food and energy production.

Short-term drought forecasting is helpful for establishing drought mitigation plans and for managing risks that often ensue in water resource systems. Additionally, hydrologic modeling using high-resolution spatial and temporal data is used to simulate the land surface water and energy fluxes, including runoff, baseflow, and soil moisture, which are useful for drought forecasting. In this study, the Soil and Water Assessment Tool (SWAT) and Variable Infiltration Capacity (VIC) models are used for short-term drought forecasting in the contiguous United States (CONUS), as many areas in this region are frequently affected by varying drought intensities. Weekly-to-seasonal meteorological inputs are provided by the Climate Prediction Center (CPC) for the retrospective period (January 2012 to July 2017) and Climate Forecasting System version 2 (CFS v2) for the forecasting period (August 2017 to April 2018), and these inputs are used to estimate agricultural and groundwater drought conditions. For drought assessment, three drought indices, namely, the Standardized Soil Moisture index (SSI), the Multivariate Standardized Drought Index (MSDI), and the Standardized Baseflow index (SBI), were analyzed. The accuracy of the forecasting results was verified using several a performance measure (Drought area agreement (%); DA). Generally, eight weeks of lead time forecasting showed good drought predictability from both the SWAT and VIC models for the MSDI simulations (62% for SWAT and 64% for VIC for all drought categories). However, the DA values for eight weeks lead time forecasting for SSI were 23% (SWAT) and 10% (VIC) and 7% (SWAT) and 7% (VIC) for the SBI, respectively. In addition, the accuracies of drought predictions remarkably decreased after eight weeks, and the average DA values were 36% for SWAT and 38% for VIC due to an increase in the uncertainties associated with meteorological variables in CFS v2 products. For example, there are increases in the total number of grids where the absolute values of monthly differences between CFSv2 and CPC observations exceed 20 mm and 1 °C during the forecasting period. Additionally, drought forecasting using only one variable (i.e., SSI and SBI) showed low prediction performances even for the first eight weeks. The results of this study provide insights into drought forecasting methods and provide a better understanding to plan for timely water resource management decisions.

The Congo Basin, home to the world’s second-largest tropical rainforest, plays a pivotal role in regulating global climate through carbon sequestration, rainfall recycling, and temperature regulation. However, the acceleration of the land-use changes—driven by agriculture, logging, mining, and urbanization—is eroding these vital ecosystem services. This chapter examines potential feedbacks between land-use change and climate, focusing on how deforestation and degradation disrupt biogeophysical processes and amplify the regional and global climate risks. Using observational evidence and modeling approaches, we show that continued forest loss could transform the Congo Basin from a net carbon sink to a carbon source, exacerbate extreme events such as droughts and floods, and destabilize regional rainfall systems. Future scenarios indicate that deforestation could reduce rainfall by up to 10% and raise surface temperatures by about 0.7 °C by mid-century (~2050). Unfortunately, these impacts extend beyond central Africa and influence tropical circulation and global climate stability. To safeguard the Congo Basin’s ecological integrity and climate functions, urgent action is required—through integrated land-use planning, forest conservation, climate-smart agriculture, and robust governance. The chapter underscores that the Congo Basin is both a frontline victim of global change and a critical lever for achieving climate resilience worldwide.