Accurate soil depth mapping is vital for hydrological and ecological insights, yet traditional methods remain laborious. We integrated ground-penetrating radar (GPR) with a Transformer-based deep learning model to enhance predictions in a steep forested catchment. Using datasets comprising point-scale soil measurements and GPR transects (128 auger, 550 GPR, 678 combined points), we benchmarked the Transformer against neural networks (ANN, DNN) and machine learning models (random forest, support vector machine) under two variable strategies: all variables and Boruta-based selection. The Transformer outperformed all models across datasets and strategies, even with limited auger data. GPR data combined with all variables yielded superior predictions over Boruta-selected variables, indicating features deemed less critical in traditional models retain predictive value in Transformers. Notably, GPR integration revealed significant soil depth reductions at footslopes-undetectable with auger data alone. These findings demonstrate the enhanced accuracy of coupling GPR with Transformer models for soil depth mapping in complex terrains.

Wetlands are crucial components of many landscapes, offering numerous hydrologic and biochemical ecosystem services such as flood control, groundwater recharge, water quality enhancement, and climate change mitigation. However, their complex interactions with hydrology and biogeochemistry are often oversimplified in existing watershed-scale models. This study addresses these limitations by developing SWAT-WetQual, a coupled modeling framework that integrates the Soil and Water Assessment Tool (SWAT) with the Wetland Water Quality (WetQual) model, to simulate nutrient, sediment, and carbon dynamics within wetlands at watershed scales. The SWAT-WetQual enhances the representation of internal wetland processes, incorporating key mechanisms, such as denitrification, volatilization, and mineralization across water column and aerobic and anerobic soil layers, surpassing the limitations of the default SWAT wetland module. The SWAT-WetQual framework was validated through comparisons with a loose-coupling approach and applied to the Greensboro watershed, a wetland-rich basin in the mid-Atlantic U.S. Results demonstrate that wetlands significantly reduce pollutant loads by retaining 74% of sediment, 19% of total nitrogen (TN), and 13% of total organic carbon (TOC) inputs into the wetlands in the case-study watershed. Comparison to a no wetland scenario further highlighted the cumulative watershed benefits of wetlands including the downstream reduction in annual sediment load by 12% (from 3,471 to 3,055 tons/yr), 68% for nitrate (from 412 to 131 tons/yr), and 24% for TOC (2,281 to 1,725 tons/yr). These reductions were most pronounced during high-flow periods and agricultural activity seasons, highlighting wetlands’ critical role in improving water quality to downstream. By enabling more accurate assessment of wetland functions at watershed scales, the SWAT-WetQual model offers a valuable tool for researchers, watershed planners, and decision-makers to better understand the cumulative effects of wetlands on watershed-scale water quality.

Large amounts of poultry litter, which is a mixture of manure and bedding material, are produced by the expanding poultry industry in the southeastern United States and are applied to pasture lands as an organic fertilizer. In addition to essential plant nutrients-nitrogen, phosphorus, and potassium (N-P-K)-poultry litter contains other nutrients and metals. However, information on the leaching potential of these metals from no-till pasture soils is scarce. This study addresses this critical gap by quantifying the subsurface loss of several metals (i.e., aluminum [Al], boron [B], calcium [Ca], magnesium [Mg], manganese [Mn], sodium [Na], and zinc [Zn]) following poultry litter application to tall fescue pastures, and evaluating the role of preferential flow paths in enhancing their mobility through the soil. A rainfall simulation was conducted on 12 undisturbed soil columns (150-mm diameter and 500-mm length) collected from a field at the Sand Mountain Research and Extension Center in Alabama, USA. Poultry litter was surface broadcasted at the application rate of 0 (control) and 5 Mg ha-1 (treatment). Leachate metal concentrations were measured and bromide breakthrough curves (BTCs) were analyzed to assess the degree of preferential flow. A sequential extraction procedure for soil and poultry litter samples was used for identifying metals in the following seven categorized fractions: soluble, exchangeable, bound to carbonates, bound to amorphous oxides, bound to crystalline oxides, bound to organic matter, and residual. Shapes of the BTCs and other solute transport parameters, such as early breakthrough and immobile pore-water fraction (ranging from 0.31 to 0.80), provided direct evidence of preferential flow in the studied columns. The flow-weighted mean concentrations of Al, B, Na, and Zn in the leachate were significantly higher in the treatment columns than those in the control columns (e.g., Al: 0.82-3.33 mg L-1, Zn: 0.03-0.16 mg L-1, Na: 4-7.8 mg L-1). However, poultry litter had no significant effect on metal leaching, except for Na. Eluted total metal loadings in the treatment columns varied in the following order: Ca > Mg > Na > Al > Zn > Mn > B. Although the leaching losses of certain metals did not significantly increase with poultry litter application in this study, their accumulation in the soil raises concerns. Despite not posing an immediate threat, the potential for soil contamination and the subsequent accelerated subsurface transport of these metals due to continued loading warrants further investigation. These findings have important implications for the safe and sustainable management of poultry litter in pasture soils.

This study investigated the potential shift in future climate including its extremes across the Chesapeake Bay watershed, a region in northeastern United States that is vulnerable to climate change. Using downscaled and bias-corrected projections from 13 CMIP6 Global Climate Models (GCMs) under four Shared Socioeconomic Pathways (SSP126, SSP245, SSP370, SSP585), we analyzed the changes in annual and seasonal precipitation and temperature patterns as well as the change in extreme climate through the evaluation of 20 climate indices.Results reveal a consistent warming trend across all scenarios until the mid-twenty-first century, after which outcomes diverge according to emission pathways. Seasonal assessments showed that average summer temperature will rise substantially in the watershed, especially under the high emissions scenario, accompanied by an increased frequency of heatwaves, tropical nights, and summer days. Concurrently, cold extremes, such as frost and icing days, are projected to decline, especially in northern parts of the watershed. The region is expected to see a decline in icing days by close to 73

Forests serve as crucial carbon sinks, yet quantifying carbon cycle processes within forested watersheds is challenging due to inherent complexities, including multiple carbon pools and variability. Dissolved organic carbon (DOC) transport from forests significantly impacts drinking water quality since it interacts with chlorine to form disinfection byproducts. Although the Soil and Water Assessment Tool-Carbon (SWAT-C) has been widely used to understand carbon fluxes at the watershed scale, the model has been primarily evaluated in non-forested watersheds and loading to aquatic systems, often overlooking terrestrial carbon fluxes from forested regions within watersheds of interests. This study assessed the applicability of SWAT-C in simulating carbon fluxes in both terrestrial and aquatic systems in the forested Big Creek watershed located in the south-central United States (U.S.), which also serves as a drinking water source, and analyzed dominant pathways of DOC transport across the landscape. Additionally, three management scenarios (i.e., forest conversion, raking in forests, and adjusting biomass harvest in croplands) aimed at reducing DOC transport were evaluated. Calibration efforts using remotely sensed as well as datasets demonstrated the proficiency of SWAT-C in simulating both terrestrial and aquatic carbon fluxes in forest-dominated regions. Results emphasize the importance of initializing and calibrating the parameters of dominant land use/cover types to enhance model performance in simulating carbon fluxes. The study found that all evaluated management scenarios can reduce DOC transport into streams, with the conversion of the dominant loblolly pine forests to restored longleaf pine forests achieving a 40% reduction in forest-derived DOC yields. These findings offer valuable insights for watershed-scale carbon cycling modeling and inform management strategies in forest-dominant watersheds to mitigate DOC yields.

Preferential flow via soil macropores can enhance phosphorus (P) loss in leachate. The application of animal manure can further exacerbate P losses in leachate in various forms. Limited work has been done to quantify colloidal-facilitated-P loss in leachate as a function of manure type. Therefore, the goal of this study was to determine the impact of three manure types, namely, poultry litter, swine lagoon effluent, and dairy manure, on P leaching in various forms using column-based rainfall simulation experiments. Intact-undisturbed soil columns were collected from a pasture field located in Alabama, USA. The overall experimental design included four treatments with two replications each (poultry litter (solid) at rate 1, poultry litter (solid) at rate 2, dairy manure (semi-solid), and swine lagoon effluent (liquid) and unamended control). The bromide breakthrough curves showed evidence of preferential flow. The flow-weighted mean total P concentrations for treatment columns ranged from 5.4 to 6 mg L- 1, 6.22 to 12.18 mg L- 1, 0.95 to 1.42 mg L- 1, and 0.29 to 1.1 mg L- 1 for columns treated with solid poultry litter at rate 1, solid poultry litter at rate 2, swine lagoon effluent, and dairy manure, respectively. Colloidal P accounted for 5 to 49 % of the total P leaching from the treatment columns. Therefore, the results of this study show that colloidal-facilitated migration of P can be significant and should be considered when elucidating P transport in agricultural systems fertilized with animal manure.

With the increasing trend of greenhouse gases in the atmosphere, by 2052 the temperature is expected to rise by 1.5 °C from the Pre-industrial Period, affecting future extreme rainfall events. This necessitates quantifying extreme hydrologic events to plan and design hydrologic and hydraulic structures using rainfall Intensity-Duration-Frequency (IDF) curves to adapt to future climate scenarios. This study developed future projected IDF curves for the Southeast United States using disaggregated sub-hourly (15-, 30-, and 45-min) monthly maximum rainfall from 2030 to 2059 using five climate models under the Representative Concentration Pathway 8.5 scenario. A computationally efficient feed-forward back-propagation Artificial Neural Network (ANN)-based approach was found to be significantly superior for disaggregating rainfall to a stochastic model with an average Nash–Sutcliffe efficiency (NSE) ranging from 0.67 to 0.84. The study found that there is an increasing rate of future projected annual maximum rainfall intensities in the range of 7% to 36% with reference to the historical period. The spatial variation in future projected extreme rainfall depths showed that the Gulf-Atlantic coast and the Appalachian Mountains are expected to receive more extreme rainfalls.

Abstract Repeated broiler litter application on agricultural lands can cause nutrient enrichment of subsurface effluent, especially with the existence of preferential flow through soil macropores. Previous studies quantifying soil macropores have not attempted to establish a connection of soil macropore characteristics with the subsurface nutrient (nitrogen [N] and phosphorus [P]) losses, across different topographical locations in the field. This study investigated the effect of broiler litter application and preferential flow on subsurface nutrient transport (N and P) at different topographical positions (upslope, midslope, and downslope) in a no‐till pasture field located in Alabama, USA. Twelve intact soil columns (150 mm id and 500 mm length) were used, and the nutrient leaching measurements from laboratory experiments were linked to soil macropore characteristics quantified using X‐ray computed tomography image analysis and solute transport modeling. Treatments included surface broadcast broiler litter (5 Mg ha−1, on dry basis) and unamended control. Leachates were analyzed for dissolved reactive P (DRP), total P (TP), and nitrate + nitrite‐N (NO3− + NO2−–N). The bromide breakthrough curves provided evidence of preferential flow in all columns. Litter application significantly increased leachate P concentrations, and average TP and DRP concentrations were significantly higher in the leachate from upslope columns compared to those at downslope location. The NO3−–N concentrations in leachate exceeded the US EPA drinking water standard of 10 mg L−1 in all the treatment columns. The highest flow‐weighted mean concentrations of TP and DRP, at 2.7 and 2.5 mg L−1, respectively, were recorded in the upslope columns. Soil physicochemical properties and nutrient leaching losses varied substantially across topographical positions, indicating a need for variable litter application rates to reduce P build‐up and subsequent leaching in vulnerable locations within the field. The relevance of the effect of topographic position on nutrient leaching found in this study should be further tested by investigating a wider range of slopes and soil types in pastures.

Integration of novel compounds into biological processes holds significant potential for modifying or expanding existing cellular functions. However, the cellular uptake of these compounds is often hindered by selectively permeable membranes. We present a novel bacterial transport system that has been rationally designed to address this challenge. Our approach utilizes a highly promiscuous sulfonate membrane transporter, which allows the passage of cargo molecules attached as amides to a sulfobutanoate transport vector molecule into the cytoplasm of the cell. These cargoes can then be unloaded from the sulfobutanoyl amides using an engineered variant of the enzyme γ-glutamyl transferase, which hydrolyzes the amide bond and releases the cargo molecule within the cell. Here, we provide evidence for the broad substrate specificity of both components of the system by evaluating a panel of structurally diverse sulfobutanoyl amides. Furthermore, we successfully implement the synthetic uptake system in vivo and showcase its functionality by importing an impermeant non-canonical amino acid.

A detailed understanding of variation in soil moisture is needed for developing precision irrigation strategies that can maximize crop production while minimizing consumptive water use. The overarching aim of the study was to optimize the representative location for precision water management with the integration of unsupervised learning and temporal stability analyses. The hypothesis for this objective was that a zone-specific representative sensor location can be determined for variable rate irrigation management in the field. The study was conducted in Tennessee Valley Region of Northern Alabama, USA. The study found that each zone in the field can be represented with a temporally stable location to determine the average zone-specific soil moisture using the concept of unsupervised learning for management zone delineation and temporal stability in soil moisture, which showed that the zone-specific irrigation can be scheduled during the growing season. Farmers can use the dry, wet, and temporally stable locations for establishing the best irrigation scheduling to increase water-use efficiency during the growing season.

Study region: Lower Apalachicola-Chattahoochee-Flint (ACF) River Basin of southeastern United States Study focus: The threats of climate change on the surface- and groundwater resources of the lower ACF River Basin of southeastern U.S. is an important concern for the long-term ecological as well as agricultural sustainability. This study developed a coupled SWAT-MODFLOW for the study region and evaluated the impacts of climate change projected under RCP4.5 and RCP8.5 emissions scenarios. New hydrological insights into the region: Evaluation of simulated streamflow and groundwater levels showed that SWAT-MODFLOW can adequately replicate the hydrology of a karstic watershed such as that present in the study domain even without the incorporation of conduit flows/karst features. Comparison to baseline conditions indicates a shift in the monthly streamflow pattern in the region with a reduction from April to June and increases in the rest of the year under future climate. The region will also likely see an increase in low-flow as well as high-flow events, thus increasing streamflow variability in the region. More frequent low flow conditions in the future can lead to increased drying of ephemeral streams threatening the ecological sustainability of the region due to habitat loss. This, along with the projected reduction in groundwater levels can lead to increased stress on water resources of the region for irrigation, thus threatening the agriculture sustainability and increasing water conflict between the neighboring states.

Millimeter-wave applications above Ka-band have become increasingly important for the defense sector. With the overcrowded spectrum at lower microwave frequencies, more systems are demanding the use of spectrum space at V-, and W-band with wider bandwidth. Gallium-Nitride (GaN) has intrinsic capability to enable its high-frequency performance, allowing the capability for solid-state technology for high-power millimeter wave applications [1]. In order to address the DoD needs and to provide a technology platform, BAE Systems is developing a “Scaled GaN HEMT Technology” that offers the required gain and power added efficiency at V- and W-band applications while still providing sufficient output power density. This paper describes the results from BAE Systems on-going efforts on 90 nm GaN Technology development. Maturation of the 90 nm GaN process, is one of the next key objectives within the BAE Systems foundry.

The El Niño Southern Oscillation (ENSO) is a cyclical ocean-atmosphere warming and cooling phenomenon centered in the Pacific Ocean near the Earth‘s equator West of Peru. ENSO exhibits strong teleconnections (relationships to other climate, environmental, or natural phenomena typically over large distances) around the world. For example, ENSO linkages to precipitation, groundwater, and streamflow in the United States have already been studied (Kousky et al., 1984; Mitra et al., 2014; Singh et al., 2021), and there are several others not cited here for brevity. While ENSO teleconnections to environmental variables such as precipitation is a relatively well-studied subject, there has been little investigation of the characteristics of precipitation (e.g., intensity, duration, frequency, etc.). One aspect of precipitation that has not been studied with relation to ENSO or any other climate oscillation is that of rainfall erosivity. Rainfall erosivity refers to the capacity of rainfall to cause erosion. It is represented with a numerical index called the erosion index (EI), which was first discovered by Wischmeier & Smith (1958) and Wischmeier (1959). This numerical index is calculated as the product of a storm‘s total kinetic energy (E) and maximum 30-minute intensity (I30) both of which have been found to be significantly related to ENSO in the Southeast United States (McGehee, 2016). ENSO teleconnections to rainfall erosivity in the contiguous United States (CONUS) are still mostly unknown, though they are expected to be of varying regional significance throughout CONUS and around the globe. 3,400 precipitation gauges across CONUS and some of its non-contiguous states and territories were used to calculate erosion indices over the period 1970-2013 (McGehee et al., 2022) and compared to ENSO 3.4 sea surface temperatures (SSTs) for the same time period. A recently developed joint-rank fit (JRFit) statistical procedure (Kloke et al., 2009), which has been found to be more powerful and robust for cluster-correlated analyses (Singh et al., 2018), was selected to test significance and estimate means of ENSO phases. ENSO teleconnections to erosivity were evaluated for both unfilled and filled time series using both 1-month and 3-month aggregation for the analysis. Results for this analysis will be presented at the meeting and could have important implications for soil conservation in the United States and erosion prediction models and technologies based on the Universal Soil Loss Equation (USLE).

Rainfall erosivity, or the capacity of rainfall to cause erosion, is a topic which has garnered substantial confusion over the years. This confusion stems from a number of discrepancies between isoerodent maps of the United States (and the world) and erosivity (or erosion index) benchmark values in the literature. Resolving these discrepancies is important since several of the world‘s soil erosion models, applications, and assessments are based on Universal Soil Loss Equation (USLE) technologies such as USLE, RUSLE, or RUSLE2. A brief history of these discrepancies is provided below. McGregor et al. (1995) observed a 30% difference (greater) in erosivities obtained from 29 breakpoint gauges in the Goodwin Creek Watershed, Mississippi as compared to isoerodent maps for the same location as used in the RUSLE model. Similar findings had been reported prior to the development of RUSLE (McGregor et al., 1980) regarding erosion index (EI) values used in the USLE. There are a number of reasons for these differences. Climate change and climate variability may have contributed, but there is also the potential impact of differing data types, which is discussed more below. An updated isoerodent map was prepared for the arrival of RUSLE2, which used more recent climate data (1960-1999). However, this update switched from using breakpoint precipitation data to a less precise and more ‘lossy‘ fixed-interval precipitation data for erosivity calculations (McGehee et al., 2021). This more commonly available data type does not preserve precipitation characteristics as well as the breakpoint data type, and thus, introduces bias/error in erosivity calculations when compared to the approach of Wischmeier & Smith (1958) and Wischmeier (1959), who discovered the original relationship of erosivity to soil loss. The RUSLE2 erosivity map values were greater than those from RUSLE and USLE by about 10%, but these values still fall short of benchmark erosivity values from McGregor et al. (1995) and Flanagan et al. (2020) by 19% and 32%, respectively. It is unclear how much of these differences are a result of the differing time periods, measurement technologies, or erosivity calculation, gap-filling, and interpolation methods. McGehee et al. (2021) demonstrated the impact of different data types (e.g., breakpoint vs. fixed-intervals for common gauge precisions) on erosivity calculations, and McGehee et al. (2022) updated the national isoerodent map of the United States. Erosivity estimates based on fixed-interval precipitation data continued to fall below breakpoint-derived benchmarks, but these differences were substantially less than existing erosivity maps. These results point to potential insufficiencies in currently recommended intensity dampening correction and storm omission practices when using fixed-interval precipitation data to estimate erosivity values and map them over large areas. Work aimed at resolving these issues is ongoing. This presentation will provide a brief history of erosivity estimation and mapping in the United States, the most recent progress towards a more reliable dynamic national erosivity map for the United States and the world, and a glimpse of the future of these efforts.

Chemical cell surface modification is a fast-growing field of research, due to its enormous potential in tissue engineering, cell-based immunotherapy, and regenerative medicine. However, engineering of bacterial tissues by chemical cell surface modification has been vastly underexplored and the identification of suitable molecular handles is in dire need. We present here, an orthogonal nucleic acid-protein conjugation strategy to promote artificial bacterial aggregation. This system gathers the high selectivity and stability of linkage to a protein Tag expressed at the cell surface and the modularity and reversibility of aggregation due to oligonucleotide hybridization. For the first time, XNA (xeno nucleic acids in the form of 1,5-anhydrohexitol nucleic acids) were immobilized via covalent, SNAP-tag-mediated interactions on cell surfaces to induce bacterial aggregation.

The determination of field capacity (FC), irrigation thresholds, and irrigation amounts is characterized by site-specific soil hydraulic properties (SHPs). This study, conducted in two zones (zone 1 and zone 2) delineated based on soil, topography, and historical crop yield in Alabama (USA), focused on determining zone-specific FC using negligible drainage flux qfc criterion. The HYDRUS-1D model was used to optimize zone-specific SHPs using measured soil matric potential (h). The zone-specific FCs were determined using optimized and raw SHPs at 0.01 cm/day as qfc. The results showed that the optimized FC at qfc was at −39 kPa in zone 1 and raw FC was at −15 kPa. However, in zone 2, optimized FC was at −25 kPa and raw FC was at −59 kPa. To validate that optimized values are more accurate than raw values, a relationship between accumulated crop evapotranspiration (ETc) and required irrigation amount was determined using optimized parameters (SHPs and FC) and showed a stronger correlation in both zones than using raw parameters (SHPs and FC). At flux-based FC, the optimized irrigation thresholds and amounts in zone 1 were −88 kPa and 20 mm, and raw irrigation threshold and amount were −58 kPa and 33 mm, respectively. In zone 2, the optimized irrigation thresholds and amounts were −45 kPa and 18 mm, and raw irrigation threshold and amount were −116 kPa and 14 mm, respectively. Therefore, using raw and benchmark FC can result in inefficient irrigation strategies. The proposed novel method of optimizing zone-specific FC and irrigation thresholds can help with adopting timely best irrigation management schemes in respective zones.

Highlights Synthesize existing knowledge in defining and conceptualizing FEW Nexus. Provide scientists and practitioners in the FEW domains with the tools to define and conceptualize. The study provides narrow-broad definitions and simple-complex conceptualization frameworks for the FEW Nexus. Abstract. Food-energy-water (FEW) resources are fundamental to society’s functioning and understanding them is crucial for sustainable development and supporting life on earth. This article presents a review of the current approaches being used in the development of FEW Nexus frameworks, with an emphasis on the methods for defining and conceptualizing these frameworks by different types of stakeholders. This framework provides scientists, consultants, and practitioners in the FEW domains the tools and knowledge needed to successfully implement the Nexus. The article also describes knowledge gaps in the FEW Nexus domains. The objectives of this article are to (a) synthesize existing knowledge to support stakeholders in defining and conceptualizing their FEW Nexus, (b) provide a framework to clarify the definitions and conceptualizations of FEW Nexus for a project or an application being developed for a specific stakeholder application, and (c) apply the experience and principles of the FEW Nexus to other Nexus that can be developed. Stakeholders in this study include the users of the Nexus, scientists, and a range of practitioners, including policymakers, the private sector, practitioners in the field, and resource managers, among others. The following questions assisted in addressing the objectives: What are some existing definitions and conceptualizations in the FEW Nexus? Which elements are currently included in the definitions and conceptualizations? How should FEW Nexus be defined and conceptualized for a project or application? How can existing definitions be adapted, or new ones created, for a project or study? What are the consequences of choosing a particular definition or conceptualization? Based on this experience, the steps needed for developing a FEW Nexus are reviewed and clarified. The study provides narrow and broad definitions and simple and complex conceptualization frameworks of FEW Nexus that stakeholders can use while being aware of the limitations and knowledge gaps. Keywords: Food-Energy-Water (FEW) Nexus conceptualizations, FEW Nexus definitions, Narrow and broad definitions, Simple and complex conceptualizations.