Salt marshes remove terrestrially derived nutrients en route to coasts. While these systems play a critical role in improving water quality, we still have a limited understanding of the spatiotemporal variability of biogeochemically reactive solutes and processes within salt marshes, particularly nitrogen species. To investigate this knowledge gap, we implemented a high-frequency sampling system to monitor sub-hourly nitrate (NO3) concentrations in salt marsh porewater at Elkhorn Slough in central California, USA. We instrumented three marsh positions along an elevation gradient subjected to different extents of tidal inundation, which we hypothesized would lead to varied biogeochemical characteristics and hydrological interactions. At each marsh position, we continuously monitored NO3 concentrations at depths of 10, 30, and 50 cm with subsurface water levels measured from 70 cm wells over seven deployments of ~10 days each. We quantified tidal event hysteresis between NO3 and water level to understand how NO3 concentrations and sources fluctuate across tidal cycles. There was significant differences in the NO3-subsurface water level hysteresis patterns across seasonal wet/dry periods common to Mediterranean climates. In dry periods, the NO3-subsurface water level relationship indicated that the source was likely estuarine surface water that flooded the transect during high tides. In wet periods, the NO3-subsurface water level relationship suggested the salt marsh was a source of NO3. These findings suggest that tidal and seasonal hydrologic fluxes control NO3 porewater dynamics and influence ecological processes in coastal environments.

Environmental hot spots and hot moments (HSHMs) represent rare locations and events that exert disproportionate influence over the environment. While several mechanistic models have been used to characterize HSHMs behavior at specific sites, a critical missing component of research on HSHMs has been the development of clear, conventional statistical models. In this paper, we introduced a novel stochastic framework for analyzing HSHMs and the uncertainties. This framework can easily incorporate heterogeneous features in the spatiotemporal domain and can offer inexpensive solutions for testing future scenarios. The proposed approach utilizes indicator random variables (RVs) to construct a statistical model for HSHMs. The HSHMs indicator RVs are comprised of spatial and temporal components, which can be used to represent the unique characteristics of HSHMs. We identified three categories of HSHMs and demonstrated how our statistical framework are adjusted for each category. The three categories are (1) HSHMs defined only by spatial (static) components, (2) HSHMs defined by both spatial and temporal (dynamic) components, and (3) HSHMs defined by multiple dynamic components. The representation of an HSHM through its spatial and temporal components allows researchers to relate the HSHM’s uncertainty to the uncertainty of its components. We illustrated the proposed statistical framework through several HSHM case studies covering a variety of surface, subsurface, and coupled systems.

This article is composed of a commentary about the state of ICON principles (Goldman et al. 2021) in Volcanology, Geochemistry, Petrology (VGP) and discussion on the opportunities and challenges of adopting them. VGP encompasses a broad field that addresses volcanic, magmatic, hydrothermal, geomicrobial systems and process investigations that span the physical, geochemical and biological realms, and one that is extensively supported by state-of-the-art research facilities. We suggest that an open, inclusive, collaborative and evolving model of an international coordinated network is critical to answering the most pressing challenges in VGP. In this commentary piece, we begin to discuss the elements of, challenges to, and path forward in developing such a model. For this team, ICON means collaboration, equitable access to data for the entire scientific community, and forging of partnerships that potentially contribute to more innovative ways of coordinating and sharing research. It also means bringing more equity to science, by implementing effective measures which consider access to funding, analytical equipment, resources, and mentors. More importantly, ICON to us means having important conversations around what we value in the advancement of science, perhaps exploring outside the idea of meritocracy and evaluating what individual traits can contribute to science outside what has traditionally been considered the norm.

Patterns of watershed nitrogen (N) retention and loss are shaped by how watershed biogeochemical processes retain, biogeochemically transform, and lose incoming atmospheric deposition of N. Loss patterns represented by concentration, discharge, and their associated stream exports are important indicators of watershed N retention patterns because they reveal hysteresis patterns (i.e. return to initial state) or one-way transition patterns (i.e. new steady state) that provide insight into watershed conditions driving long term stream trends. We examined the degree to which Continental U.S. (CONUS) scale deposition patterns (wet and dry atmospheric deposition), vegetation trends, and stream trends can be potential indicators of watershed N-saturation and retention conditions, and how watershed N retention and losses vary over space and time. By synthesizing changes and modalities in watershed nitrogen loss patterns based on stream data from 2200 U.S. watersheds over a 50 year record, our work characterized a new hysteresis conceptual model based on factors driving watershed N-retention and loss, including hydrology, atmospheric inputs, land-use, stream temperature, elevation, and vegetation. Our results show that atmospheric deposition and vegetation productivity groups that have strong positive or negative trends over time are associated with patterns of stream loss that uniquely indicate the stage of watershed N-saturation and reveal unique characteristics of watershed N-retention hysteresis patterns. In particular, regions with increasing atmospheric deposition and increasing vegetation health/biomass patterns have the highest N-retention capacity, become increasingly N-saturated over time, and are associated with the strongest declines in stream N exports—a pattern that is consistent across all land cover categories. In particular, the second largest factor explaining watershed N-retention was in-stream temperature and dissolved organic carbon concentration trends, while land-use explained the least amount of variability in watershed N-retention. Our CONUS scale investigation supports an updated hysteresis conceptual model of watershed N-retention and loss, providing great value to using long-term stream monitoring data as indicators of watershed N hysteresis patterns.

Agricultural managed aquifer recharge (AgMAR) is a proposed management strategy whereby surface water flows are used to intentionally flood croplands with the purpose of recharging underlying aquifers. However, legacy nitrate (NO3-) contamination in agriculturally-intensive regions poses a threat to groundwater resources under AgMAR. To address these concerns, we use a reactive transport modeling framework to better understand the effects of AgMAR management strategies (i.e., by varying the frequency, duration between flooding events, and amount of water) on N leaching to groundwater under different stratigraphic configurations and antecedent moisture conditions. In particular, we examine the potential of denitrification and nitrogen retention in deep vadose zone sediments using variable AgMAR application rates on two-dimensional representations of differently textured soils, soils with discontinuous bands/channels, and soils with preferential flow paths characteristic of typical agricultural field sites. Our results indicate that finer textured sediments, such as silt loams, alone or embedded within high flow regions, are important reducing zones providing conditions needed for denitrification. Simulation results further suggest that applying recharge water all-at-once, rather than in increments, increases denitrification within the vadose zone, but transports higher concentrations of NO3- deeper into the profile. This transport into deeper depths can be aggravated by wetter antecedent soil moisture conditions. We conclude that ideal AgMAR management strategies can be designed to enhance denitrification in the subsurface and reduce N leaching to groundwater, while specifically accounting for lithologic heterogeneity, antecedent soil moisture conditions, and depth to the water table.

Salt marshes are hotspots of nutrient processing en route to sensitive coastal environments. While our understanding of these systems has improved over the years, we still have limited knowledge of the spatiotemporal variability of critical biogeochemical processes within salt marshes. Sea-level rise will continue to force change on salt marsh functioning, highlighting the urgency of filling this knowledge gap. Our study was conducted in a central California estuary experiencing extensive marsh drowning and relative sea-level rise, making it a model system for such an investigation. Here we instrumented three marsh positions with different degrees of inundation (6.7%, 8.9%, and 11.2% of the time for the upper, middle, and lower marsh positions, respectively), providing locations with varied geochemical characteristics and hydrological interaction at the site. We continuously monitored redox potential (Eh) at depths of 0.1, 0.3, and 0.5 m, subsurface water levels (WL), and temperature at each marsh position to understand how drivers of subsurface biogeochemical processes fluctuate across tidal cycles, using wavelet analyses to explain the interactions between Eh and WL. We found that tidal forcing significantly affects biogeochemical processes by imparting controls on Eh variability, likely driving subsurface hydro-biogeochemistry of the salt marsh. Wavelet coherence showed that the Eh-WL relationship is non-linear, and their lead-lag relationship is variable. We found that precipitation events perturb Eh at depth over timescales of hours, even though WL show relatively minimal change during events. This work highlights the importance of high-frequency measurements, such as Eh, to help explain factors that govern subsurface geochemistry and hydrological processes in salt marshes.