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Abstract Accurate groundwater representation in land surface models (LSMs) is vital for water and energy cycle studies, water resource assessments, and climate projections. Yet, many LSMs do not consider key processes including lateral groundwater flow and aquifer pumping, especially at the global scale. This study simulates these processes using an enhanced version of the Community Land Model (CLM5) and evaluates their roles at three spatial resolutions (0.5°, 0.25°, 0.1°). Results show that lateral flow strongly modulates water table depth and capillary rise at all resolutions. The magnitude of mean lateral flow increases from 25 mm/year at 0.5° to 36 mm/year at 0.25°, and 52 mm/year at 0.1° resolution, with pumping inducing lateral flow even at 0.5° (∼50 km), a typical grid size in global LSMs. Further, lateral flow alters runoff in regions with high recharge and shallow water table (e.g., eastern North America and Amazon basin), and soil moisture and ET in regions with comparatively low recharge and deeper water table (e.g., western North America, central Asia, and Australia) through enhanced capillary rise. Runoff alteration by lateral flow increases substantially with resolution, from a maximum of 15 mm/month at 0.5° to 20 mm/month and 25 mm/month at 0.25° and 0.1°, respectively; the impact of resolution on soil moisture and ET is less pronounced. While the model does not fully capture deeper water tables—warranting further enhancements—it provides valuable insights on how lateral groundwater flow impacts land surface processes, highlighting the importance of lateral groundwater flow and pumping in global LSMs. 

Abstract Characterizing the impact of human actions on terrestrial water fluxes and storages at multi‐basin, continental, and global scales has long been on the agenda of scientists engaged in climate science, hydrology, and water resources systems analysis. This need has resulted in a variety of modeling efforts focused on the representation of water infrastructure operations. Yet, the representation of human‐water interactions in large‐scale hydrological models is still relatively crude, fragmented across models, and often achieved at coarse resolutions (10–100 km) that cannot capture local water management decisions. In this commentary, we argue that the concomitance of four drivers and innovations is poised to change the status quo: “hyper‐resolution” hydrological models (0.1–1 km), multi‐sector modeling, satellite missions able to monitor the outcome of human actions, and machine learning are creating a fertile environment for human‐water research to flourish. We then outline four challenges that chart future research in hydrological modeling: (a) creating hyper‐resolution global data sets of water management practices, (b) improving the characterization of anthropogenic interventions on water quantity, stream temperature, and sediment transport, (c) improving model calibration and diagnostic evaluation, and (d) reducing the computational requirements associated with the successful exploration of these challenges. Overcoming them will require addressing modeling, computational, and data development needs that cut across the hydrology community, thereby requiring a major communal effort. 

Abstract. Flow regimes in major global river systems are undergoing rapid alterations due to unprecedented stress from climate change and human activities. The Mekong River basin (MRB) was, until recently, among the last major global rivers relatively unaltered by humans, but this has been changing alarmingly in the last decade due to booming dam construction. Numerous studies have examined the MRB's flood pulse and its alterations in recent years. However, a mechanistic quantification at the basin scale attributing these changes to either climatic or human drivers is lacking. Here, we present the first results of the basin-wide changes in natural hydrological regimes in the MRB over the past 8 decades and the impacts of dams in recent decades by examining 83 years (1940–2022) of river regime characteristics simulated by a river–floodplain hydrodynamic model that includes 126 major dams in the MRB. Results indicate that, while the Mekong River's flow has shown substantial decadal trends and variabilities, the operation of dams in recent years has been causing a fundamental shift in the seasonal volume and timing of river flow and extreme hydrological conditions. Even though the dam-induced impacts have been small so far and most pronounced in areas directly downstream of major dams, dams are intensifying the natural variations in the Mekong's mainstream wet-season flow. Further, the additional 65 dams commissioned since 2010 have exacerbated drought conditions by substantially delaying the MRB's wet-season onset, especially in recent years (e.g., 2019 and 2020), when the natural wet-season durations are already shorter than in normal years. Further, dams have shifted by up to 20 % of the mainstream annual volume between the dry and wet seasons in recent years. While this has a minimal impact on the MRB's annual flow volume, the flood occurrence in many major areas of Tonlé Sap and the Mekong Delta has been largely altered. This study provides critical insights into the long-term hydrological variabilities and impacts of dams on the Mekong River's flow regimes, which can help improve water resource management in light of intensifying hydrological extremes. 

Abstract The Mekong River basin (MRB) is a transboundary basin that supports livelihoods of over 70 million inhabitants and diverse terrestrial-aquatic ecosystems. This critical lifeline for people and ecosystems is under transformation due to climatic stressors and human activities (e.g., land use change and dam construction). Thus, there is an urgent need to better understand the changing hydrological and ecological systems in the MRB and develop improved adaptation strategies. This, however, is hampered partly by lack of sufficient, reliable, and accessible observational data across the basin. Here, we fill this long-standing gap for MRB by synthesizing climate, hydrological, ecological, and socioeconomic data from various disparate sources. The data— including groundwater records digitized from the literature—provide crucial insights into surface water systems, groundwater dynamics, land use patterns, and socioeconomic changes. The analyses presented also shed light on uncertainties associated with various datasets and the most appropriate choices. These datasets are expected to advance socio-hydrological research and inform science-based management decisions and policymaking for sustainable food-energy-water, livelihood, and ecological systems in the MRB. 

Various climate, hydro-meteorological, ecological, and socio-economic datasets are synthesized and made available for the Mekong River Basin. The sources of each dataset are also mentioned in the associated readme file. Dam attribute data, inundation data, and Cambodia census data can be made available upon request to the authors.