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Groundwater discharge to rivers takes many forms, including preferential groundwater discharge points (PDPs) along riverbanks that are exposed at low flows, with multi-scale impacts on aquatic habitat and water quality. The physical controls on the spatial distribution of PDPs along riverbanks are not well-defined, rendering their prediction and representation in models challenging. To investigate the local riverbank sediment controls on PDP occurrence, we tested drone-based and handheld thermal infrared to efficiently map PDP locations along two mainstem rivers. Early in the study, we found drone imaging was better suited to locating tributary and stormwater inflows, which created relatively large water surface thermal anomalies in winter, compared to PDPs that often occurred at the sub-meter scale and beneath riparian tree canopy. Therefore, we primarily used handheld thermal infrared imaging from watercraft to map PDPs and larger seepage faces along 12-km of the fifth-order Housatonic River in Massachusetts, USA and 26-km of the Farmington River in Connecticut, USA. Overall, we mapped 31 riverbank PDPs along the Housatonic reach that meanders through lower permeability soils, and 104 PDPs along the Farmington reach that cuts through sandier sediments. Riverbank soil parameters extracted at PDP locations from the Soil Survey Geographic (SSURGO) database did not differ substantially from average bank soils along either reach, although the Farmington riverbank soils were on average 5× more permeable than Housatonic riverbank soils, likely contributing to the higher observed prevalence of PDPs. Dissolved oxygen measured in discharge water at these same PDPs varied widely, but showed no relation to measured sand, clay, or organic matter content in surficial soils indicating a lack of substantial near-surface aerobic reaction. The PDP locations were investigated for the presence of secondary bank structures, and commonly co-occurred with riparian tree root masses indicating the importance of localized physical controls on the spatial distribution of riverbank PDPs. 

River networks regulate carbon and nutrient exchange between continents, atmosphere, and oceans. However, contributions of riverine processing are poorly constrained at continental scales. Scaling relationships of cumulative biogeochemical function with watershed size (allometric scaling) provide an approach for quantifying the contributions of fluvial networks in the Earth system. Here we show that allometric scaling of cumulative riverine function with watershed area ranges from linear to superlinear, with scaling exponents constrained by network shape, hydrological conditions, and biogeochemical process rates. Allometric scaling is superlinear for processes that are largely independent of substrate concentration (e.g., gross primary production) due to superlinear scaling of river network surface area with watershed area. Allometric scaling for typically substrate-limited processes (e.g., denitrification) is linear in river networks with high biogeochemical activity or low river discharge but becomes increasingly superlinear under lower biogeochemical activity or high discharge, conditions that are widely prevalent in river networks. The frequent occurrence of superlinear scaling indicates that biogeochemical activity in large rivers contributes disproportionately to the function of river networks in the Earth system.

 

Groundwater is critical for maintaining stream baseflow and thermal stability; however, the influence of groundwater on streamflow has been difficult to evaluate at broad spatial scales. Techniques such as baseflow separation necessitate streamflow records and do not directly indicate whether groundwater inflow may be sourced from more dynamic shallow flowpaths. We present a web tool applicationPASTA(Paired Air and Stream Temperature Analysis;https://cuahsi.shinyapps.io/pasta/) that capitalizes on increased public stream temperature data availability and large‐scale, gridded climate observations to provide new and efficient insights regarding relative groundwater influence on streams.PASTAanalyzes paired air and stream water temperature signals to evaluate spatiotemporal patterns in stream thermal sensitivity and relative groundwater influence, including inference regarding the dominant source groundwater depth (shallow or deep (i.e., approximately >6 m depth)). The tool is linked to publicly available stream temperature datasets and accepts user‐uploaded datasets. As local air temperature is not often monitored, PASTA pulls daily air temperature data from the comprehensive Daymet products when directly measured data are unavailable, allowing the repurposing of existing stream temperature data. After data are selected or uploaded, the tool (a) fits sinusoidal curves of daily stream and air temperatures by year (water or calendar) to indicate groundwater influence characteristics and (b) performs linear regressions for stream versus air temperatures to indicate stream thermal sensitivity. Results are exported in ASCII file format, creating an efficient and approachable analysis tool for the adoption of newly developed heat tracing analysis from stream reach to landscape scales.

 

Mean annual temperature and mean annual precipitation drive much of the variation in productivity across Earth's terrestrial ecosystems but do not explain variation in gross primary productivity (GPP) or ecosystem respiration (ER) in flowing waters. We document substantial variation in the magnitude and seasonality of GPP and ER across 222 US rivers. In contrast to their terrestrial counterparts, most river ecosystems respire far more carbon than they fix and have less pronounced and consistent seasonality in their metabolic rates. We find that variation in annual solar energy inputs and stability of flows are the primary drivers of GPP and ER across rivers. A classification schema based on these drivers advances river science and informs management. 

Groundwater discharge generates streamflow and influences stream thermal regimes. However, the water quality and thermal buffering capacity of groundwater depends on the aquifer source-depth. Here, we pair multi-year air and stream temperature signals to categorize 1729 sites across the continental United States as having major dam influence, shallow or deep groundwater signatures, or lack of pronounced groundwater (atmospheric) signatures. Approximately 40% of non-dam stream sites have substantial groundwater contributions as indicated by characteristic paired air and stream temperature signal metrics. Streams with shallow groundwater signatures account for half of all groundwater signature sites and show reduced baseflow and a higher proportion of warming trends compared to sites with deep groundwater signatures. These findings align with theory that shallow groundwater is more vulnerable to temperature increase and depletion. Streams with atmospheric signatures tend to drain watersheds with low slope and greater human disturbance, indicating reduced stream-groundwater connectivity in populated valley settings.

 

Hypoxia in coastal waters and lakes is widely recognized as a detrimental environmental issue, yet we lack a comparable understanding of hypoxia in rivers. We investigated controls on hypoxia using 118 million paired observations of dissolved oxygen (DO) concentration and water temperature in over 125,000 locations in rivers from 93 countries. We found hypoxia (DO < 2 mg L⁻¹) in 12.6% of all river sites across 53 countries, but no consistent trend in prevalence since 1950. High‐frequency data reveal a 3‐h median duration of hypoxic events which are most likely to initiate at night. River attributes were better predictors of riverine hypoxia occurrence than watershed land cover, topography, and climate characteristics. Hypoxia was more likely to occur in warmer, smaller, and lower‐gradient rivers, particularly those draining urban or wetland land cover. Our findings suggest that riverine hypoxia and the resulting impacts on ecosystems may be more pervasive than previously assumed.

 

To assess the distribution, frequency, and global extent of riverine hypoxia, we compiled 118 million paired dissolved oxygen (DO) and water temperature measurements from 125,158 unique locations in rivers in 93 countries and territories across the globe. The dataset also includes site characteristics derived from StreamCat, the National Hydrography and HydroAtlas datasets and proximal land cover derived from MODIS-based IGBP land cover types compiled using Google Earth Engine (GEE).