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This repository contains the input data for SAS and nitrate transport modeling and the model results that can be used to reproduce the water age and nitrate reactive transport results presented in Sha et al. Coupled hydrologic and biogeochemical responses of nitrate export in a tile-drained agricultural watershed revealed by SAS functions and nitrate isotopes. 

Indirect nitrous oxide (N2O) emissions from streams and rivers are a poorly constrained term in the global N2O budget. Current models of riverine N2O emissions place a strong focus on denitrification in groundwater and riverine environments as a dominant source of riverine N2O, but do not explicitly consider direct N2O input from terrestrial ecosystems. Here, we combine N2O isotope measurements and spatial stream network modeling to show that terrestrial-aquatic interactions, driven by changing hydrologic connectivity, control the sources and dynamics of riverine N2O in a mesoscale river network within the U.S. Corn Belt. We find that N2O produced from nitrification constituted a substantial fraction (i.e., > 30%) of riverine N2O across the entire river network. The delivery of soil-produced N2O to streams was identified as a key mechanism for the high nitrification contribution and potentially accounted for more than 40% of the total riverine emission. This revealed large terrestrial N2O input implies an important climate-N2O feedback mechanism that may enhance riverine N2O emissions under a wetter and warmer climate. Inadequate representation of hydrologic connectivity in observations and modeling of riverine N2O emissions may result in significant underestimations. 

The combination of high nitrogen (N) inputs on tile‐drained agricultural watersheds contributes to excessive nitrate loss to surface‐ and groundwater systems. This study combined water age modeling based on StorAge Selection functions and nitrate isotopic analysis to examine the underlying mechanisms driving nitrate export in an intensively tile‐drained mesoscale watershed typical of the U.S. Upper Midwest. The water age modeling revealed a pronounced inverse storage effect and strong young water preference under high‐flow conditions, emphasizing evolving water mixing behavior driven by groundwater fluctuation and tile drain activation. Integrating nitrate concentration‐isotope‐discharge relationships with water age dynamics disentangled the interactions between flow path variations and subsurface N cycling in shaping seasonally variable nitrate export regimes at the watershed scale. Based on these results, a simple transit time‐based and isotope‐aided nitrate transport model was developed to estimate the timescales of watershed‐scale nitrate reactive transport. Model results demonstrated variable nitrate source availability and a wetness dependence for denitrification, indicating that interannual nitrate chemostasis is driven by coupled and proportional responses of soil nitrate production, denitrification, and flow path activation to varying antecedent wetness conditions. These findings suggest that intensively tile‐drained Midwestern agricultural watersheds function as both N transporters and transformers and may respond to large‐scale mitigation efforts within a relatively short timeframe. Collectively, the results of this study demonstrate the potential of integrated water age modeling and nitrate isotopic analysis to advance the understanding of macroscale principles governing coupled watershed hydrologic and N biogeochemical functions. 

Abstract Accurately quantifying and predicting the reactive transport of nitrate () in hydrologic systems continues to be a challenge, due to the complex hydrological and biogeochemical interactions that underlie this transport. Recent advances related to time‐variant water age have led to a new method that probes water mixing and selection behaviors using StorAge Selection (SAS) functions. In this study, SAS functions were applied to investigate storage, water selection behaviors, and export regimes in a tile‐drained corn‐soybean field. The natural abundance stable nitrogen and oxygen isotopes of tile drainage were also measured to provide constraints on biogeochemical transformations. The SAS functions, calibrated using chloride measurements at tile drain outlets, revealed a strong young water preference during tile discharge generation. The use of a time‐variant SAS function for tile discharge generated unique water age dynamics that reveal an inverse storage effect driven by the activation of preferential flow paths and mechanically explain the observed variations in isotopes. Combining the water age estimates with isotope fingerprinting shed new light on export dynamics at the tile‐drain scale, where a large mixing volume and the lack of a strong vertical contrast in concentration resulted in chemostatic export regimes. For the first time, isotopes were embedded into a water age‐based transport model to model reactive transport under transient conditions. The results of this modeling study provided a proof‐of‐concept for the potential of coupling water age modeling with isotope analysis to elucidate the mechanisms driving reactive transport. 

Abstract The response of highly productive croplands at northern mid-latitudes to climate change is a primary source of uncertainty in the global carbon cycle, and a concern for future food production. We present a decadal time series (2007 to 2019) of hourly CO 2 concentration measured at a very tall tower in the United States Corn Belt. Analyses of this record, with other long-term data in the region, reveal that warming has had a positive impact on net CO 2 uptake during the early crop growth stage, but has reduced net CO 2 uptake in both croplands and natural ecosystems during the peak growing season. Future increase in summer temperature is projected to reduce annual CO 2 sequestration in the Corn Belt by 10–20%. These findings highlight the dynamic control of warming on cropland CO 2 exchange and crop yields and challenge the paradigm that warming will continue to favor CO 2 sequestration in northern mid-latitude ecosystems.