In recent decades, climate change and other anthropogenic activities have substantially affected groundwater systems worldwide. These impacts include changes in groundwater recharge, discharge, flow, storage, and distribution. Climate-induced shifts are evident in altered recharge rates, greater groundwater contribution to streamflow in glacierized catchments, and enhanced groundwater flow in permafrost areas. Direct anthropogenic changes include groundwater withdrawal and injection, regional flow regime modification, water table and storage alterations, and redistribution of embedded groundwater in foods globally. Notably, groundwater extraction contributes to sea level rise, increasing the risk of groundwater inundation in coastal areas. The role of groundwater in the global water cycle is becoming more dynamic and complex. Quantifying these changes is essential to ensure sustainable supply of fresh groundwater resources for people and ecosystems.

CH₄ emissions from inland water are highly uncertain in the current global CH₄ budget, especially for rivers and streams due to sparse measurements and the uncertainty of measurements caused by turbulent water flow. A previous study has revealed that vertical hydrologic exchange flow (VHEF) is the main regulator of CH₄ emissions from riverbed sediments. However, to what extent the understanding obtained from the plot‐scale can be extended to the reach scale and basin scale remains unknown. To address this challenge, we developed a process‐based model to estimate CH₄ flux at the air‐water interface using the attributes available in the national hydrography data set. It calculates the annual mean flux of VHEF, CH₄ production in sediments, and CH₄ transport in the river channel in a sequential manner. Model performance is evaluated by CH₄ efflux observed at the Hanford reach of the Columbia River. We show that reach‐wise sediment hydrologic and biogeochemical conditions estimated from the national hydrography data set could serve as a good indicator of CH₄ emissions from rivers. Aerobic methane oxidation and export to the downstream are the dominant ways of total CH₄ loss for the large lowland river. The hotspots of CH₄ emissions are likely to be at the reaches with fine sediments and slow channel velocity. This study demonstrates the possibility of quantifying CH₄ emissions at the reach scale and the modeling framework has the potential to be extended to the basin scale to improve estimates of CH₄ emissions from lotic inland water.

Regional scale transport models are needed to support the long‐term evaluation of groundwater quality and to develop management strategies aiming to prevent serious groundwater degradation. The purpose of this study is to evaluate the capacity of a previously developed upscaling approach to adequately describe the main solute transport processes, including the capture of late‐time tails under changing boundary conditions. Potential factors that impact the performance of upscaling methods, including temporal variations in mass transfer rates and mass distributions, were investigated. Advective‐dispersive contaminant transport in a 3‐D heterogeneous domain was simulated and used as a reference solution. The equivalent transport under homogeneous flow conditions was then evaluated by applying the multirate mass transfer (MRMT) model. The random walk particle tracking method was used to solve the solute transport for heterogeneous and homogeneous MRMT scenarios under steady state and transient conditions. The results indicate that the MRMT model can capture the tails satisfactorily for plumes transported with ambient steady state flow fields at all studied scales using the same parameters. However, when the boundary conditions change in either local, plume, or regional scale, the mass transfer model calibrated for transport under steady state conditions cannot accurately reproduce the tailings observed for the heterogeneous scenario. The deteriorating impacts of transient boundary conditions on the upscaled model are more significant for regions where the flow fields are dramatically affected, which highlights the poor applicability of the MRMT approach for complex field settings. This finding also has implications for the suitability of other potential upscaling approaches.