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Widespread observations of ecohydrological separation are interpreted by suggesting that water flowing through highly conductive soil pores resists mixing with matrix storage over periods of days to months (i.e., two ‘water worlds’ exist). These interpretations imply that heterogeneous flow can produce ecohydrological separation in soils, yet little mechanistic evidence exists to explain this phenomenon. We quantified the separation between mobile water moving through preferential flow paths versus less mobile water remaining in the soil matrix after free‐drainage to identify the amount of preferential flow necessary to maintain a two water world's scenario. Soil columns of varying macropore structure were subjected to simulated rainfall of increasing rainfall intensity (26 mm h−1, 60 mm h−1, and 110 mm h−1) whose stable isotope signatures oscillated around known baseline values. Prior to rainfall, soil matrix water δ2H nearly matched the known value used to initially wet the pore space whereas soil δ18O deviated from this value by up to 3.4‰, suggesting that soils may strongly fractionate 18O. All treatments had up to 100% mixing between rain and matrix water under the lowest (26 mm h−1) and medium (60 mm h−1) rainfall intensities. The highest rainfall intensity (110 mm h−1), however, reduced mixing of rain and matrix water for all treatments and produced significantly different preferential flow estimates between columns with intact soil structure compared to columns with reduced soil structure. Further, artificially limiting exchange between preferential flow paths and matrix water reduced bypass flow under the most intense rainfall. We show that (1) precipitation offset metrics such as lc‐excess and d‐excess may yield questionable interpretations when used to identify ecohydrological separation, (2) distinct domain separation may require extreme rainfall intensities and (3) domain exchange is an important component of macropore flow.

Preferential flow reduces water residence times and allows rapid transport of pollutants such as organic contaminants. Thus, preferential flow is considered to reduce the influence of soil matrix-solute interactions during solute transport. While this claim may be true when rainfall directly follows solute application, forcing rapid chemical and physical disequilibrium, it has been perpetuated as a general feature of solute transport—regardless of the magnitude preferential flow. A small number of studies have alternatively shown that preferential transport of strongly sorbing solutes is reduced when solutes have time to diffuse and equilibrate within the soil matrix. Here we expand this inference by allowing solute sorption equilibrium to occur and exploring how physiochemical properties affect solute transport across a vast range of preferential flow. We applied deuterium-labeled rainfall to field plots containing manure spiked with eight common antibiotics with a range of affinity for the soil after 7 days of equilibration with the soil matrix and quantified preferential flow and solute transport using 48 soil pore water samplers spread along a hillslope. Based on > 700 measurements, our data showed that solute transport to lysimeters was similar—regardless of antibiotic affinity for soil—when preferential flow represented less than 15% of the total water flow. When preferential flow exceeded 15%, however, concentrations were higher for compounds with relatively low affinity for soil. We provide evidence that (1) bypassing water flow can select for compounds that are more easily released from the soil matrix, and (2) this phenomenon becomes more evident as the magnitude of preferential flow increases. We argue that considering the natural spectrum preferential flow as an explanatory variable to gauge the influence of soil matrix-solute interactions may improve parsimonious transport models.

Compared to surface application, manure subsurface injection reduces surface runoff of nutrients, antibiotic resistant microorganisms, and emerging contaminants. Less is known regarding the impact of both manure application methods on surface transport of antibiotic resistance genes (ARGs) in manure-amended fields. We applied liquid dairy manure to field plots by surface application and subsurface injection and simulated rainfall on the first or seventh day following application. The ARG richness, relative abundance (normalized to 16s rRNA), and ARG profiles in soil and surface runoff were monitored using shotgun metagenomic sequencing. Within 1 day of manure application, compared to unamended soils, soils treated with manure had 32.5–70.5% greater ARG richness and higher relative abundances of sulfonamide (6.5–129%) and tetracycline (752–3766%) resistance genes (p ≤ 0.05). On day 7, soil ARG profiles in the surface-applied plots were similar to, whereas subsurface injection profiles were different from, that of the unamended soils. Forty-six days after manure application, the soil ARG profiles in manure injection slits were 37% more diverse than that of the unamended plots. The abundance of manure-associated ARGs were lower in surface runoff from manure subsurface injected plots and carried a lower resistome risk score in comparison to surface-applied plots. This study demonstrated, for the first time, that although manure subsurface injection reduces ARGs in the runoff, it can create potential long-term hotspots for elevated ARGs within injection slits.

Land application of manure, while beneficial to soil health and plant growth, can lead to an overabundance of nutrients and introduction of emerging contaminants into agricultural fields. Compared with surface application of manure, subsurface injection has been shown to reduce nutrients and antibiotics in surface runoff. However, less is known about the influence of subsurface injection on the transport and persistence of antibiotic‐resistant microorganisms. We simulated rainfall to field plots at two sites (one in Virginia and one in Pennsylvania) 1 or 7 d after liquid dairy manure surface and subsurface application (56 Mg ha–1) and monitored the abundance of culturable antibiotic‐resistant fecal coliform bacteria (ARFCB) in surface runoff and soils for 45 d. We performed these tests at both sites in spring 2018 and repeated the test at the Virginia site in fall 2019. Manure subsurface injection, compared with surface application, resulted in less ARFCB in surface runoff, and this reduction was greater at Day 1 after application compared with Day 7. The reductions of ARFCB in surface runoff because of manure subsurface injection were 2.5–593 times at the Virginia site in spring 2018 and fall 2019 and 4–5 times at the Pennsylvania site in spring 2018. The ARFCB were only detectable in the 0‐to‐5‐cm soil depth within 14 d of manure surface application but remained detectable in the injection slits of manure subsurface‐injected plots even at Day 45. This study demonstrated that subsurface injection can significantly reduce surface runoff of ARFCB from manure‐applied fields.

The soil water retention curve (SWRC) is essential for assessing water flow and solute transport in unsaturated media. The van Genuchten (VG) model is widely used to describe the SWRC; however, estimation of its effective hydraulic parameters is often prone to error, especially when data exist for only a limited range of matric potential. We developed a Metropolis-Hastings algorithm of the Markov chain Monte Carlo (MH-MCMC) approach using R to estimate VG parameters, which produces a numerical estimate of the joint posterior distribution of model parameters, including fully-quantified uncertainties. When VG model parameters were obtained using complete range of soil water content (SWC) data (i.e., from saturation to oven dryness), the MH-MCMC approach returned similar accuracy as the widely used non-linear curve-fitting program RETC (RETention Curve), but avoiding non-convergence issues. When VG model parameters were obtained using 5 SWC data measured at matric potential of around −60, −100, −200, −500, and −15,000 cm, the MH-MCMC approach was more robust than the RETC program. The performance of MH-MCMC are generally good (R2 > 0.95) for all 8 soils, whereas the RETC underperformed for coarse-textured soils. The MH-MCMC approach was used to obtain VG model parameters for all 1871 soils in the National Cooperative Soil Characterization dataset with SWC measured at matric potentials of −60 cm, −100 cm, −330 cm, and −15,000 cm; the results showed that the simulated SWC by MH-MCMC model were highly consistent with the measured SWC at corresponding matric potential. Altogether, our new MH-MCMC approach to solving the VG model is more robust to limited coverage of soil matric potential when compared to the RETC procedures, making it an effective alternative to traditional water retention solvers. We developed an MH-MCMC code in R for solving VG model parameters, which can be found at the GitHub repository.

<p>Organic contaminants such as antibiotics are being applied to soils in increasing loads. These chemicals can be rapidly transported via preferential flow, making it important to understand and quantify soil-solute interactions under bypass flow conditions. In this study we applied deuterium-labeled rainfall to field plots containing manure spiked with eight common antibiotics, and collected pore water samples from 48 suction cups spread along a hillslope. In total we collected more than 700 measurements across the eight antibiotics. Our results indicated that solute transport to lysimeters was similar between antibiotics when preferential flow was less than 15%. When preferential flow exceeded 15%, however, compounds with relatively low affinity for soil were sampled in higher concentrations, suggesting that preferential flow mobilizes compounds that are more easily released from the soil matrix. Our findings show that extensive preferential flow can enhance, rather than reduce, the influence of chemical properties. These data provide new insight into how flow heterogeneity affects pollutant mobility in soils and can be used to build more accurate process-based transport models.</p>