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ABSTRACT The importance of subsurface water dynamics, such as water storage and flow partitioning, is well recognised. Yet, our understanding of their drivers and links to streamflow generation has remained elusive, especially in small headwater streams that are often data‐limited but crucial for downstream water quantity and quality. Large‐scale analyses have focused on streamflow characteristics across rivers with varying drainage areas, often overlooking the subsurface water dynamics that shape streamflow behaviour. Here we ask the question:What are the climate and landscape characteristics that regulate subsurface dynamic storage, flow path partitioning, and dynamics of streamflow generation in headwater streams?To answer this question, we used streamflow data and a widely‐used hydrological model (HBV) for 15 headwater catchments across the contiguous United States. Results show that climate characteristics such as aridity and precipitation phase (snow or rain) and land attributes such as topography and soil texture are key drivers of streamflow generation dynamics. In particular, steeper slopes generally promoted more streamflow, regardless of aridity. Streams in flat, rainy sites (< 30% precipitation as snow) with finer soils exhibited flashier regimes than those in snowy sites (> 30% precipitation as snow) or sites with coarse soils and deeper flow paths. In snowy sites, less weathered, thinner soils promoted shallower flow paths such that discharge was more sensitive to changes in storage, but snow dampened streamflow flashiness overall. Results here indicate that land characteristics such as steepness and soil texture modify subsurface water storage and shallow and deep flow partitioning, ultimately regulating streamflow response to climate forcing. As climate change increases uncertainty in water availability, understanding the interacting climate and landscape features that regulate streamflow will be essential to predict hydrological shifts in headwater catchments and improve water resources management. 

We used spatial data from previously mapped preferential groundwater discharges throughout the Farmington River watershed in Connecticut and Massachusetts (https://doi.org/10.5066/P915E8JY) to guide water sample collection at known locations of groundwater discharging to surface water. In 2017 and 2019 - 2021, samples were collected during general river baseflow conditions (July ? November, less than 30.9 cms mean daily discharge (USGS gage 01189995, statistics 2010-2022) when the riverbank discharge points were exposed. We collected a suite of dissolved constituents and stable isotopes of water directly in the shallow saturated sediments of active points of discharge, and coincident stream chemical samples were also collected adjacent to locations of groundwater discharge. Data collected includes nutrients (NO3, NH4, Cl, SO4, PO4, dissolved organic carbon (DOC), and total nitrogen (TN)), greenhouse gases (CO2, CH4, and N2O), dissolved gases (N2, dissolved oxygen (DO)), conductivity, sediment characteristics, temperature, and spatial information. This dataset includes 2 main files: 1) Farmington_Chemistry_2017_2021.csv contains attribute information for each biogeochemical constituent collected at preferential groundwater discharges along the Farmington River network. 2)Farmington_Temporal_Cl_Rn_Iso_2020.csv contain attribute information for source characteristic data (Chloride, Radon, Isotope) collected at locations of repeat sampling at 5 groundwater seep faces along the Farmington River (Alsop and Rainbow Island). 

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.