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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. 

Abstract Reactive Transport Models (RTMs) are essential tools for understanding and predicting intertwined ecohydrological and biogeochemical processes on land and in rivers. While traditional RTMs have focused primarily on subsurface processes, recent watershed‐scale RTMs have integrated ecohydrological and biogeochemical interactions between surface and subsurface. These emergent, watershed‐scale RTMs are often spatially explicit and require extensive data, computational power, and computational expertise. There is however a pressing need to create parsimonious models that require minimal data and are accessible to scientists with limited computational background. To that end, we have developed BioRT‐HBV 1.0, a watershed‐scale, hydro‐biogeochemical RTM that builds upon the widely used, bucket‐type HBV model known for its simplicity and minimal data requirements. BioRT‐HBV uses the conceptual structure and hydrology output of HBV to simulate processes including advective solute transport and biogeochemical reactions that depend on reaction thermodynamics and kinetics. These reactions include, for example, chemical weathering, soil respiration, and nutrient transformation. The model uses time series of weather (air temperature, precipitation, and potential evapotranspiration) and initial biogeochemical conditions of subsurface water, soils, and rocks as input, and output times series of reaction rates and solute concentrations in subsurface waters and rivers. This paper presents the model structure and governing equations and demonstrates its utility with examples simulating carbon and nitrogen processes in a headwater catchment. As shown in the examples, BioRT‐HBV can be used to illuminate the dynamics of biogeochemical reactions in the invisible, arduous‐to‐measure subsurface, and their influence on the observed stream or river chemistry and solute export. With its parsimonious structure and easy‐to‐use graphical user interface, BioRT‐HBV can be a useful research tool for users without in‐depth computational training. It can additionally serve as an educational tool that promotes pollination of ideas across disciplines and foster a diverse, equal, and inclusive user community. 

Abstract Dissolved organic and inorganic carbon (DOC and DIC) influence water quality, ecosystem health, and carbon cycling. Dissolved carbon species are produced by biogeochemical reactions and laterally exported to streams via distinct shallow and deep subsurface flow paths. These processes are arduous to measure and challenge the quantification of global carbon cycles. Here we ask: when, where, and how much is dissolved carbon produced in and laterally exported from the subsurface to streams? We used a catchment‐scale reactive transport model, BioRT‐HBV, with hydrometeorology and stream carbon data to illuminate the “invisible” subsurface processes at Sleepers River, a carbonate‐based catchment in Vermont, United States. Results depict a conceptual model where DOC is produced mostly in shallow soils (3.7 ± 0.6 g/m²/yr) and in summer at peak root and microbial respiration. DOC is flushed from soils to the stream (1.0 ± 0.2 g/m²/yr) especially during snowmelt and storms. A large fraction of DOC (2.5 ± 0.2 g/m²/yr) percolates to the deeper subsurface, fueling deep respiration to generate DIC. DIC is exported predominantly from the deeper subsurface (7.1 ± 0.4 g/m²/yr, compared to 1.3 ± 0.3 g/m²/yr from shallow soils). Deep respiration reduces DOC and increases DIC concentrations at depth, leading to commonly observed DOC flushing (increasing concentrations with discharge) and DIC dilution patterns (decreasing concentrations with discharge). Surprisingly, respiration processes generate more DIC than weathering in this carbonate‐based catchment. These findings underscore the importance of vertical connectivity between the shallow and deep subsurface, highlighting the overlooked role of deep carbon processing and export.