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Anthropogenic climate change and associated increasing nutrient loading to coasts will worsen coastal eutrophication on a global scale. Basin Head is a coastal lagoon located in northeastern Prince Edward Island, Canada, with a federally protected ecosystem. Nitrate-nitrogen (NO3-N) is conveyed from agricultural fields in the watershed to the eutrophic lagoon via intertidal groundwater springs and groundwater-dominated tributaries. A field program focused on four main tributaries that discharge into the lagoon was conducted to measure year-round NO3-N loading. These measurements were used to calibrate a SWAT+ hydrologic model capable of simulating hydrologic and NO3-N loads to the lagoon. Several climate change scenarios incorporating different agricultural best management practices (BMPs) were simulated to better understand potential future NO3-N loading dynamics. Results indicate that all climate change scenarios produced increased annual NO3-N loading to the lagoon when comparing historical (1990-2020) to end of century time periods (2070-2100); however, only one climate scenario (MRI-ESM2-0 SSP5-8.5) resulted in a statistically significant (p-value <0.05) increase. Enlarged buffer strips and delayed tillage BMP simulations produced small (0%-8%) effects on loading, while changing the crop rotation from potato-barley-clover to potato-soybean-barley yielded a small reduction in NO3-N loading between the historical period and the end of the century (26%-33%). Modeling revealed changes in seasonal loading dynamics under climate change where NO3-N loads remained more consistent throughout the year as opposed to current conditions where the dominant load is in the spring. An increase in baseflow contributions to streamflow was also noted under climate change, with the largest change occurring in the winter (e.g., up to a five-fold increase in February). These findings have direct implications for coastal management in groundwater-dominated agricultural watersheds in a changing climate. [ABSTRACT FROM AUTHOR]

Mountains have a critical role in freshwater supply for downstream populations. As the climate changes, groundwater stored in mountains may help buffer the impacts to declining water resources caused by decreased snowpack and glacier recession. However, given the scarcity of groundwater observation wells in mountain regions, it remains unclear how mountain groundwater is being impacted by climate change across ecoregions. This study quantifies temporal trends in mountain groundwater levels and explores how various climatic, physiographic and anthropogenic factors affect these trends. We compiled data from 171 public groundwater observation wells within mountain regions across Canada and the United States, for which at least 20 years of monthly data is available. The Mann‐Kendall test for monotonic trend revealed that 54% of these wells have statistically significant temporal trends (p < 0.05) over the period of record, of which 69% were negative and therefore indicating overall declining groundwater storage. Wells in the western mountain ranges showed stronger trends (both positive and negative) than the eastern mountain ranges, and higher elevation wells showed fewer negative trends than the low elevation (<400 m asl) wells (p < 0.05). Correlation, Kruskal‐Wallis tests, stepwise multiple linear regression and random forest regression were used to identify factors controlling groundwater trends. Statistical analysis revealed that lower‐elevation mountain regions with higher average annual temperatures and lower average annual precipitation have the greatest declines in groundwater storage under climate change. Trends in temperature and precipitation, and ecoregion were also important predictors on groundwater level trends, highlighting geographic differences in how mountain wells are responding to climate change. Furthermore, sedimentary bedrock aquifers showed markedly more negative trends than crystalline bedrock aquifers. The findings demonstrate that the impact of climate change on mountain water resources extends to the subsurface, with important implications for global water resources. [ABSTRACT FROM AUTHOR]

Oceanic storms can strongly disturb the physical and biogeochemical conditions of transitional coastal waters. Impacts of extreme oceanic storms on coastal ecosystems have received limited attention worldwide, with no studies at higher latitudes (> 45°) where tropical cyclones have usually abated. This study investigates the combined impacts from marine and atmospheric forcing on a coastal lagoon in Prince Edward Island, Canada, during and after Extratropical Cyclone Fiona in September 2022. Physical (water levels and temperature) and biogeochemical (dissolved oxygen [DO], electrical conductivity, pH, nitrate–nitrogen concentrations, total suspended solids [TSS]) datasets from the lagoon and the watershed's tributaries, groundwater springs, and piezometers were used to assess ecosystem disturbance and recovery timelines following the storm. Fiona resulted in a 1.6 m storm surge into the lagoon that elevated water temperatures by up to 6°C, disturbed the density‐dependent stratification of salinity and temperature, and reduced the diel amplitude of DO, indicating a reduction in plant respiration due to ecosystem disturbance. The freshwater tributaries revealed sharp changes in flow (30‐fold increase), nitrate–nitrogen (NO3‐N) concentrations and loading (70‐fold increase), and TSS loading (40‐fold increase) to the lagoon during and immediately following the storm. The lagoon rapidly recovered (hours) from the hydraulic disturbance of the storm surge, but elevated nutrient levels persisted for months. The intensity and frequency of extratropical cyclones is projected to increase in the Northwest Atlantic, making field‐based studies of cyclone impacts on coastal waters critical for understanding future coastal ecosystem disturbance and recovery periods relative to the timing of future storms. [ABSTRACT FROM AUTHOR]

Water flow through catchments sustains ecosystems and human activity, shapes landscapes, and links climate to the outermost layers of the solid Earth. The profound importance of water moving between the atmosphere and aquifers has led to efforts to develop and maintain coupled models of surface water and groundwater. However, developing inputs to these models is usually time-consuming and requires extensive knowledge of software engineering, often prohibiting their use by many researchers and water managers, and thus reducing these models' potential to promote science-driven decision-making in an era of global change and increasing water-resource stress. In response to this need, we have developed GSFLOW-GRASS, a straightforward set of open-source tools that develops inputs for and runs GSFLOW, the U.S. Geological Survey's coupled groundwater-surface-water flow model. As inputs, GSFLOW-GRASS requires at a minimum a digital elevation model, a precipitation and temperature record, and estimates of channel parameters and hydraulic conductivity. GSFLOW-GRASS is written in Python as a set of (1) GRASS GIS extensions, (2) input-file-builder scripts, and (3) visualization scripts. We developed a set of custom GRASS GIS commands that generate "hydrologic response units" for surface water, discretized topologically as sub-basins of the tributary network; build the MODFLOW grid; and add necessary attributes to each of these geospatial units. These GIS outputs are interpreted by a second set of Python scripts, which link them to hydrologic variables, build inputs to GSFLOW, and run GSFLOW. Lastly, GSFLOW output files are used to produce figures and time-lapse movies of simulation results using a third set of post-processing Python scripts. We demonstrate the broad applicability of these tools to diverse settings through examples based on: the high Peruvian Andes, the Channel Islands of California, and the formerly-glaciated Upper Mississippi valley in Minnesota. [ABSTRACT FROM AUTHOR]