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Accurate and reliable forecasts of quickflow, including interflow and overland flow, are essential for predicting rainfall–runoff events that can wash off recently applied agricultural nutrients. In this study, we examined whether a gridded version of the Sacramento Soil Moisture Accounting model with Heat Transfer (SAC-HT) could simulate and forecast quickflow in two agricultural watersheds in east-central Pennsylvania. Specifically, we used the Hydrology Laboratory–Research Distributed Hydrologic Model (HL-RDHM) software, which incorporates SAC-HT, to conduct a 15-yr (2003–17) simulation of quickflow in the 420-km2 Mahantango Creek watershed and in WE-38, a 7.3-km2 headwater interior basin. We directly calibrated HL-RDHM using hydrologic observations at the Mahantango Creek outlet, while all grid cells within Mahantango Creek, including WE-38, were calibrated indirectly using scalar multipliers derived from the basin outlet calibration. Using the calibrated model, we then assessed the quality of short-range (24–72 h) deterministic forecasts of daily quickflow in both watersheds over a 2-yr period (July 2017–October 2019). At the basin outlet, HL-RDHM quickflow simulations showed low biases (PBIAS = 10.5%) and strong agreement (KGE″ = 0.81) with observations. At the headwater scale, HL-RDHM overestimated quickflow (PBIAS = 69.0%) to a greater degree, but quickflow simulations remained satisfactory (KGE″ = 0.65). When applied to quickflow forecasting, HL-RDHM produced skillful forecasts (>90% of Peirce and Gerrity skill scores above 0.5) at all lead times and significantly outperformed persistence forecasts, although skill gains in Mahantango Creek were slightly lower. Accordingly, short-range quickflow forecasts by HL-RDHM show promise for informing operational decision-making in agriculture. Significance Statement Daily runoff forecasts can alert farmers to rainfall–runoff events that have the potential to wash off recently applied fertilizers and manures. To gauge whether daily runoff forecasts are accurate and reliable, we used runoff monitoring data from a large agricultural watershed and one of its headwater tributaries to evaluate the quality of short-term runoff forecasts (1–3 days ahead) that were generated by a National Weather Service watershed model. Results showed that the accuracy and reliability of daily runoff forecasts generally improved in both watersheds as lead times increased from 1 to 3 days. Study findings highlight the potential for National Weather Service models to provide useful short-term runoff forecasts that can inform operational decision-making in agriculture.

Understanding the processes that mobilize and transport dissolved phosphorus (P) during storms is critical to managing P in flat landscapes with open ditch drainage and legacy soil P. In this study, we used routine baseflow monitoring and intensive storm sampling at a ditch-drained site on Maryland's Lower Eastern Shore (July 2017-September 2018) to assess whether concentration-discharge (C-Q) relationships and chemical and isotopic hydrograph separation could provide insight into the processes that mobilize and transport dissolved P in ditch drainage. Using a segmented regression model, we determined that long-term C-Q relationships for dissolved P differed above and below a discharge threshold of 6.4 L s-1 . Intensive storm sampling revealed that small storms (n = 3) occurring at or below the discharge threshold generally exhibited complex hysteresis and dissolved P dilution patterns that were consistent with deeper (>122 cm) groundwater inputs with low dissolved P concentrations (0.04 mg L-1 ). In contrast, large storms occurring well above the discharge threshold (n = 4) induced rising water tables and preferential flow pathways that most likely tapped dissolved P-enriched shallow (

HighlightsWe used SWAT-VSA to assess the effects of climate change with rising CO2 on the water balance of a karst basin.For future climate, SWAT-VSA with rising CO2 yielded 7.1% less ET and 6.3% more runoff than standard SWAT-VSA.Rising CO2 also affected variable source areas, with greater ET declines and runoff increases in the wettest soils.Findings suggest CO2 effects on water balance should be included in future climate change studies with SWAT-VSA.Abstract. Characterizing the effects of climate change on hydrology is important to watershed management. In this study, we used SWAT-VSA to examine the effects of climate change and increasing atmospheric CO2 (CO2) on the water balance of Spring Creek watershed, a mixed land-use karst basin in the Upper Chesapeake Bay watershed. First, we modified the stomatal conductance and leaf area index (LAI) routines of SWAT-VSA’s Penman-Monteith evapotranspiration (ET) procedure and enabled the model to accept daily CO2 data. Using downscaled climate projections from nine global climate models (GCMs), we then compared water balance estimations from baseline SWAT-VSA against two modified versions of SWAT-VSA. One SWAT-VSA version integrated daily CO2 levels (SWAT-VSA_CO2), while another version added flexible stomatal conductance and LAI routines (SWAT-VSA_CO2+Plant) to the dynamic CO2 capacity. Under current climate (1985-2015), the three SWAT-VSA models produced generally similar water balance estimations, with 51% of precipitation lost to ET and the remainder converted to runoff (10%), lateral flow (9%), and percolate (30%). For future climate (2020-2065), water balance simulations diverged between baseline SWAT-VSA and the two modified SWAT-VSA models with CO2. Notably, variable stomatal conductance and LAI routines produced no detectable effects beyond that of CO2. For the 2020-2065 period, baseline SWAT-VSA projected ET increases of 0.7 mm year-1, while SWAT-VSA models with CO2 suggested that annual ET could decline by approximately -0.4 mm year-1 over the same period. As a result, the two CO2-based SWAT-VSA models predicted streamflow increases of almost 1.6 mm year-1 over the 2020-2065 period, which were roughly double the streamflow increases projected by baseline SWAT-VSA. In general, SWAT-VSA models with CO2 effects produced 22.4% more streamflow in 2045-2065 than the SWAT-VSA model without CO2. Results also showed that adding daily CO2 to SWAT-VSA reduced ET in wetter parts of Spring Creek watershed, leading to greater runoff losses from variable source areas compared to baseline SWAT-VSA. Findings from the study highlight the importance of considering increasing atmospheric CO2 concentrations in water balance simulations with SWAT-VSA in order to gain a fuller appreciation of the hydrologic uncertainties with climate change. Keywords: Carbon dioxide, Climate change, Hydrologic model, Water balance, Watershed.

Peatlands provide a setting that is well suited for cranberry agriculture in the Northeastern United States. However, misconceptions exist about the amounts and forms of nitrogen (N) and phosphorus (P) export from cranberry farms. In this study, we report inorganic and organic forms of N and P export from five peatlands cultivated for cranberry production in southeastern, Massachusetts, United States. We then compare N loading rates among cranberry farms in southeastern Massachusetts, row crop farms in the Midwestern United States, and uncultivated peatlands in the United States and United Kingdom. Based on a fluvial mass balance analysis, we find that nonriparian cranberry farms export 2.56 kg of P ha⁻¹ year⁻¹of total P and 12.1 kg of N ha⁻¹ year⁻¹of total N. Total N export from riparian or “flow through” farms is two times higher than nonriparian farms due to less retention of N fertilizer in the vadose zone of riparian farms. Gross total N export from riparian and nonriparian cranberry farms consists of 35% particulate organic N, 26% dissolved organic N, 31% ammonium (NH₄⁺), and 8% nitrate (NO₃⁻). The low proportions of NO₃⁻ export (13% of total dissolved N [TDN]) for cranberry farms differ from NO₃⁻ export for row crop farms (75% of TDN; p

Soil erosion and nutrient loss from surface runoff and subsurface leaching are critical problems for cultivated land. Conservation initiatives show a persistent need for field-scale cropland vulnerability assessments to inform farm management options and prioritize efforts at watershed or regional scales. The Soil Vulnerability Index (SVI) was developed by USDA9s Natural Resources Conservation Service (NRCS) to assess inherent vulnerability of cropland to surface runoff and leaching using readily available soil and topographic inputs: hydrologic soil group, slope, erodibility K-factor, coarse fragments, and organic carbon (C). The SVI has been evaluated in a few watersheds but requires further evaluation across a wider range of physiographic and climatic conditions. The objective of this study was to evaluate the ability of the SVI to correctly identify vulnerability class based on slope, digital elevation model (DEM) resolution, hydrologic soil group, and soil erodibility across 13 of USDA9s Conservation Effects Assessment Project (CEAP) watersheds. The SVI classification was consistent with model output classification with a similarity rate of more than 70% when the SVI component corresponded to the primary route of loss for nutrients or sediment. Results showed that SVIs were consistent with local scientific expertise about the site vulnerability to runoff and leaching, and were particularly useful in areas with mixed slopes and hydrologic soil groups. In watersheds with uniform C or D hydrologic soil groups, the SVI was primarily driven by slope. In these cases, it was important to use a digital elevation map with 10 m resolution or higher to more finely distinguish vulnerability. In areas with uniform slopes and hydrologic soil group, and in areas with uniformly steep slopes, the SVI was not able to identify fields with greater or lower vulnerability than others. In these cases, vulnerability assessments required additional factors: depth of restrictive layer, clay content, slope length, and landscape position. While the SVI was able to categorize vulnerability correctly in mixed soil and slope conditions, findings from this project highlight the need for incorporating DEM-sourced slope and other factors like depth of restrictive layer, clay content, slope length, and landscape position into the SVI to ensure that the SVI is applicable to the broad range of geomorphic conditions found in the United States.

Little is known about the regional extent and variability of nitrate from atmospheric deposition that is transported to streams without biological processing in forests. We measured water chemistry and isotopic tracers (δ18O and δ15N) of nitrate sources across the Northern Forest Region of the U.S. and Canada and reanalyzed data from other studies to determine when, where, and how unprocessed atmospheric nitrate was transported in catchments. These inputs were more widespread and numerous than commonly recognized, but with high spatial and temporal variability. Only 6 of 32 streams had high fractions (>20%) of unprocessed atmospheric nitrate during baseflow. Seventeen had high fractions during stormflow or snowmelt, which corresponded to large fractions in near-surface soil waters or groundwaters, but not deep groundwater. The remaining 10 streams occasionally had some (

Despite ongoing management efforts, phosphorus (P) loading from agricultural landscapes continues to impair water quality. Wastewater treatment research has enhanced our knowledge of microbial mechanisms influencing P cycling, especially regarding microbes known as polyphosphate accumulating organisms (PAOs) that store P as polyphosphate (polyP) under oxic conditions and release P under anoxic conditions. However, there is limited application of PAO research to reduce agricultural P loading and improve water quality. Herein, we conducted a meta-analysis to identify articles in Web of Science on polyP and its use by PAOs across five disciplines (i.e., wastewater treatment, terrestrial, freshwater, marine, and agriculture). We also summarized research that provides preliminary support for PAO-mediated P cycling in natural habitats. Terrestrial, freshwater, marine, and agriculture disciplines had fewer polyP and PAO articles compared to wastewater treatment, with agriculture consistently having the least. Most meta-analysis articles did not overlap disciplines. We found preliminary support for PAOs in natural habitats and identified several knowledge gaps and research opportunities. There is an urgent need for interdisciplinary research linking PAOs, polyP, and oxygen availability with existing knowledge of P forms and cycling mechanisms in natural and agricultural environments to improve agricultural P management strategies and achieve water quality goals.

We previously discovered a method to estimate the groundwater mean residence time using the changes in the enantiomeric ratio of metolachlor ethanesulfonic acid (MESA), (2-[(2-ethyl-6-methylphenyl)(2-methoxy-1-methylethyl)amino]-2-oxoethanesulfonic acid), a metabolite of the herbicide metolachlor. However, many grab samples would be needed for each watershed over an extended period, and this is not practical. Thus, we examined the use of a polar organic chemical integrative sampler (POCIS) deployed for 28 days combined with a modified liquid chromatography-mass spectrometry LC-MS/MS method to provide a time-weighted average of the MESA enantiomeric ratio. POCISs equipped with hydrophilic-lipophilic-balanced (HLB) discs were deployed at five sites across the United States where metolachlor was used before and after 1999 and compared the effectiveness of the POCIS to capture MESA versus grab samples. In addition, an in situ POCIS sampling rate (Rs) for MESA was calculated (0.15 L/day), the precision of MESA extraction from stored POCIS discs was determined, and the effectiveness of HLB to extract MESA was examined. Finally, using molecular modeling, the influence of the asymmetric carbon of metolachlor degradation on the MESA enantiomeric ratio was predicted to be negligible. Results of this work will be used in projects to discern the groundwater mean residence times, to evaluate the delivery of nitrate-N from groundwater to surface waters under various soil, agronomic, and land use conditions, and to examine the effectiveness of conservation practices.

Commercial cranberry (Vaccinium macrocarpon Ait.) is cultivated on postglacial deposits of peat capped by 0.3–1 m of anthropogenic sand. Despite distinct soil layering, a general paucity of information exists on the physical properties of sand and peat in cranberry bogs. Field measurements and ground penetrating radar (GPR) were used to determine sand and peat thicknesses of 30 cranberry bogs in Massachusetts, United States. GPR-based estimates of peat volume and detailed soil maps were then used to develop a geospatial model of mean peat thickness (L*) in cranberry bogs. The model was applied to 505 cranberry bogs that covered in area of 2827 ha. Based on model results and field measurements, average sand and peat thicknesses were 0.5 and 0.9 m, respectively. For individual bogs, mean peat thickness exhibited considerable range, with deep peat (L* > 1.8 m) identified in 22% of the cranberry bogs. Peat was absent (L* = 0 m) in 26% of the cranberry bogs, which reflected modified upland or glaciolacustrine soils rather than peat. Using average thickness, nutrient concentration, and bulk density of peat and sand layers, a typical cranberry bog stores 750 Mg ha− 1 of carbon, 22,900 kg ha− 1 of nitrogen, and 790 kg ha− 1 of phosphorus. We estimate that peat stores 91% and 78% (by mass) of carbon and nitrogen in cranberry bogs, respectively. In contrast, sand stores the majority of P (78% by mass) in cranberry bogs.

Phosphorus (P) Index evaluations are critical to advancing nutrient management planning in the United States. However, most assessments until now have focused on the risks of P losses in surface runoff. In artificially drained agroecosystems of the Atlantic Coastal Plain, subsurface flow is the predominant mode of P transport, but its representation in most P Indices is often inadequate. We explored methods to evaluate the subsurface P risk routines of five P Indices from Delaware, Maryland (two), Virginia, and North Carolina using available water quality and soils datasets. Relationships between subsurface P risk scores and published dissolved P loads in leachate (Delaware, Maryland, and North Carolina) and ditch drainage (Maryland) were directionally correct and often statistically significant, yet the brevity of the observation periods (weeks to several years) and the limited number of sampling locations precluded a more robust assessment of each P Index. Given the paucity of measured P loss data, we then showed that soil water extractable P concentrations at depths corresponding with the seasonal high water table (WEP) could serve as a realistic proxy for subsurface P losses in ditch drainage. The associations between WEP and subsurface P risk ratings reasonably mirrored those obtained with sparser water quality data. As such, WEP is seen as a valuable metric that offers interim insight into the directionality of subsurface P risk scores when water quality data are inaccessible. In the long term, improved monitoring and modeling of subsurface P losses clearly should enhance the rigor of future P Index appraisals.

The advent of real-time, short-term farm management tools is motivated by the need to protect water quality above and beyond the general guidance offered by existing nutrient management plans. Advances in high-performance computing and hydrologic or climate modeling have enabled rapid dissemination of real-time information that can assist landowners and conservation personnel with short-term management planning. This paper reviews short-term decision support tools for agriculture that are under various stages of development and implementation in the United States: (i) Wisconsin's Runoff Risk Advisory Forecast (RRAF) System, (ii) New York's Hydrologically Sensitive Area Prediction Tool, (iii) Virginia's Saturated Area Forecast Model, (iv) Pennsylvania's Fertilizer Forecaster, (v) Washington's Application Risk Management (ARM) System, and (vi) Missouri's Design Storm Notification System. Although these decision support tools differ in their underlying model structure, the resolution at which they are applied, and the hydroclimates to which they are relevant, all provide forecasts (range 24-120 h) of runoff risk or soil moisture saturation derived from National Weather Service Forecast models. Although this review highlights the need for further development of robust and well-supported short-term nutrient management tools, their potential for adoption and ultimate utility requires an understanding of the appropriate context of application, the strategic and operational needs of managers, access to weather forecasts, scales of application (e.g., regional vs. field level), data requirements, and outreach communication structure. USDA-NRCS Conservation Innovation Grants This review was supported, in part, by USDA-NRCS Conservation Innovation Grants to improve P indexing and modeling and to improve short-term forecasting tools for nutrient management planning.

P availability often limits primary production in freshwater ecosystems and excessive P inputs promote accelerated eutrophication. Microbial mechanisms may control O2-dependent uptake/release of P in stream sediments and biofilms, but specific organisms responsible for these cycles have not been identified. Polyphosphate accumulating organisms (PAOs) are purposely enriched in treatment plants to remove P from wastewater. PAOs release P under anaerobic conditions and take it up under aerobic conditions. We hypothesized that alternating aerobic/anaerobic conditions promote patterns of P uptake/release similar to those attributed to PAOs in wastewater treatment. We collected intact, native stream biofilms and subjected them to laboratory treatments to impose conditions similar to what may occur because of diel oxygenic and respiratory cycles: 1) continuous sparging with air and 2) alternate sparging with air or anaerobic gas (20∶80% by volume CO2∶N2). We monitored PO43−, Ca, Mg, total Mn, K, Fe2+, an...

Most empirical studies of field management effects on runoff water quality rely on edge-of-field monitoring, which is generally unreplicated and prone to high variances, or small plots, which constrain the use of conventional farm equipment and can hinder insight into landscape processes that drive hydrology. We sought to develop field-scale lysimeters that were sufficiently large to support assessment of landscape processes but also replicated to allow quantitative comparisons of hydrologic processes. A hillslope underlain by limestone bedrock with a recent history of hydrologic observation was selected in central Pennsylvania. Twelve 15 m x 27 m plots were established and defined by earthen berms on all sides to isolate and collect overland flow, along with tile drains to collect shallow lateral flow. Over three years, considerable variability in site hydrology was observed between lysimeters, highlighting differences in the extent of hydrologic isolation of some lysimeters as well as in flows that potentially bypassed our collection infrastructure. Even so, clear patterns were observed in surface and subsurface flow that enabled grouping of plots based on hydrologic similarities. Results illustrate the experimental opportunities and limitations of developing field-scale lysimeters for agronomic inference.

Urea-N is linked to harmful algal blooms in lakes and estuaries, and urea-N-based fertilizers have been implicated as a source. However, the export of urea-N-based fertilizers appears unlikely, as high concentrations of urea-N are most commonly found in surface waters outside periods of fertilization. To evaluate possible autochthonous production of urea-N, we monitored urea-N released from drainage ditch sediments using mesocosms. Sediments from a cleaned (recently dredged) drainage ditch, uncleaned ditch, forested ditch, riparian wetland, and an autoclaved sand control were isolated in mesocosms and flooded for 72 h to quantify urea-N, NH-N, and NO-N in the floodwater. Sediments were flooded with different N-amended solutions (distilled HO, 1.5 mg L NH-N, 3.0 mg L NH-N, 2.6 mg L NO-N, or 5.1 mg L NO-N) and incubated at three water temperatures (16, 21, and 27°C). Urea-N concentrations in mesocosms representing uncleaned and cleaned drainage ditches were significantly greater than nonagricultural sediments and controls. While flooding sediments with N-enriched solution had no clear effect on urea-N, warmer (27°C) temperatures resulted in significantly higher urea-N. Data collected from field ditches that were flooded by a summer rainstorm showed increases in urea-N that mirrored the mesocosm experiment. We postulate that concentrations of urea-N in ditches that greatly exceed environmental thresholds are mediated by biological production in sediments and release to stagnant surface water. Storm-driven urea-N export from ditches could elevate the risk of harmful algal blooms downstream in receiving waters despite the dilution effect.

Hennig Brandt's discovery of phosphorus (P) occurred during the early European colonization of the Chesapeake Bay region. Today, P, an essential nutrient on land and water alike, is one of the principal threats to the health of the bay. Despite widespread implementation of best management practices across the Chesapeake Bay watershed following the implementation in 2010 of a total maximum daily load (TMDL) to improve the health of the bay, P load reductions across the bay's 166,000-km(2) watershed have been uneven, and dissolved P loads have increased in a number of the bay's tributaries. As the midpoint of the 15-yr TMDL process has now passed, some of the more stubborn sources of P must now be tackled. For nonpoint agricultural sources, strategies that not only address particulate P but also mitigate dissolved P losses are essential. Lingering concerns include legacy P stored in soils and reservoir sediments, mitigation of P in artificial drainage and stormwater from hotspots and converted farmland, manure management and animal heavy use areas, and critical source areas of P in agricultural landscapes. While opportunities exist to curtail transport of all forms of P, greater attention is required toward adapting P management to new hydrologic regimes and transport pathways imposed by climate change. Public domain – authored by a U.S. government employee

The evolution of phosphorus (P) management decision support tools (DSTs) and systems (DSS), in support of food and environmental security has been most strongly affected in developed regions by national strategies (i) to optimize levels of plant available P in agricultural soils, and (ii) to mitigate P runoff to water bodies. In the United States, Western Europe, and New Zealand, combinations of regulatory and voluntary strategies, sometimes backed by economic incentives, have often been driven by reactive legislation to protect water bodies. Farmer-specific DSSs, either based on modeling of P transfer source and transport mechanisms, or when coupled with farm-specific information or local knowledge, have typically guided best practices, education, and implementation, yet applying DSSs in data poor catchments and/or where user adoption is poor hampers the effectiveness of these systems. Recent developments focused on integrated digital mapping of hydrologically sensitive areas and critical source areas, sometimes using real-time data and weather forecasting, have rapidly advanced runoff modeling and education. Advances in technology related to monitoring, imaging, sensors, remote sensing, and analytical instrumentation will facilitate the development of DSSs that can predict heterogeneity over wider geographical areas. However, significant challenges remain in developing DSSs that incorporate "big data" in a format that is acceptable to users, and that adequately accounts for catchment variability, farming systems, and farmer behavior. Future efforts will undoubtedly focus on improving efficiency and conserving phosphate rock reserves in the face of future scarcity or prohibitive cost. Most importantly, the principles reviewed here are critical for sustainable agriculture.

Delineating hydrologic and pedogenic factors influencing groundwater flow in riparian zones is central in understanding pathways of water and nutrient transport. In this study, we combined two-dimensional time-lapse electrical resistivity imaging (ERI) (depth of investigation approximately 2 m) with hydrometric monitoring to examine hydrological processes in the riparian area of FD-36, a small (0.4 km2 ) agricultural headwater basin in the Valley and Ridge region of east-central Pennsylvania. We selected two contrasting study sites, including a seep with groundwater discharge and an adjacent area lacking such seepage. Both sites were underlain by a fragipan at 0.6 m. We then monitored changes in electrical resistivity, shallow groundwater, and nitrate-N concentrations as a series of storms transitioned the landscape from dry to wet conditions. Time-lapse ERI revealed different resistivity patterns between seep and non-seep areas during the study period. Notably, the seep displayed strong resistivity reductions (∼60%) along a vertically aligned region of the soil profile, which coincided with strong upward hydraulic gradients recorded in a grid of nested piezometers (0.2- and 0.6-m depth). These patterns suggested a hydraulic connection between the seep and the nitrate-rich shallow groundwater system below the fragipan, which enabled groundwater and associated nitrate-N to discharge through the fragipan to the surface. In contrast, time-lapse ERI indicated no such connections in the non-seep area, with infiltrated rainwater presumably perched above the fragipan. Results highlight the value of pairing time-lapse ERI with hydrometric and water quality monitoring to illuminate possible groundwater and nutrient flow pathways to seeps in headwater riparian areas.

Studies of harmful algal blooms and associated urea concentrations in the Chesapeake Bay and in coastal areas around the globe strongly suggest that elevated urea concentrations are associated with harmful algal blooms. The observed increased frequency and toxicity of these blooms in recent decades has been correlated with increased agricultural use of N inputs and increased use of urea as a preferred form of commercial N. This rainfall simulation study sought to assess the potential for different N fertilizers and manures to contribute to urea in runoff from a Coastal Plain soil on the Eastern Shore of Maryland. Under worst-case conditions, ~1% of urea-N applied as commercial fertilizer and surface-applied poultry litter was lost in runoff in a simulated rainfall event, roughly equivalent to a 1-yr return period rain storm in the study area, 12 h after application. Cumulative urea-N losses, including four subsequent weekly rainfall events, approached 1.7% from urea-N fertilizer containing a urease inhibitor. Urea-N loss from incorporated poultry litter was negligible, and losses from dairy manure were intermediate. These losses are likely confined to hydrological contributing areas that extend several meters from a drainage ditch or stream for storms with frequent recurrence intervals. Cumulative dissolved N losses in runoff (urea-N + ammonium-N + nitrate-N) as a proportion of total applied plant-available N were

Elevated phosphorus (P) concentrations in subsurface drainage water are thought to be the result of P bypassing the soil matrix via macropore flow. The objectives of this study were to quantify event water delivery to tile drains via macropore flow paths during storm events and to determine the effect of tillage practices on event water and P delivery to tiles. Tile discharge, total dissolved P (DP) and total P (TP) concentrations, and stable oxygen and deuterium isotopic signatures were measured from two adjacent tile-drained fields in Ohio, USA during seven spring storms. Fertilizer was surface-applied to both fields and disk tillage was used to incorporate the fertilizer on one field while the other remained in no-till. Median DP concentration in tile discharge prior to fertilizer application was 0.08 mg L−1 in both fields. Following fertilizer application, median DP concentration was significantly greater in the no-tilled field (1.19 mg L−1) compared to the tilled field (0.66 mg L−1), with concentrations remaining significantly greater in the no-till field for the remainder of the monitored storms. Both DP and TP concentrations in the no-till field were significantly related to event water contributions to tile discharge, while only TP concentration was significantly related to event water in the tilled field. Event water accounted for between 26 and 69% of total tile discharge from both fields, but tillage substantially reduced maximum contributions of event water. Collectively, these results suggest that incorporating surface-applied fertilizers has the potential to substantially reduce the risk of P transport from tile-drained fields.

Time-lapse electrical resistivity imaging (ERI) combined with salt tracers can enhance our understanding of subsurface flow and transport in ditch-drained agroecosystems. In a nearly level field adjacent to a drainage ditch, we installed 192 electrodes in a 72-m2 plot along with five hydrometric stations to enable time-lapse ERI monitoring during storms. Immediately prior to a wintertime rainstorm, we applied 5 kg of KBr to a shallow trench located roughly 11 m upgradient from the ditch. Antecedent conditions prior to the storm were wet, assuring a hydrologically connected state that favored tracer dissolution and movement in the subsurface. We monitored the evolution of the tracer plume with ERI over a seven-day period. Four-dimensional (4D) delineation of precipitation and tracer transport using time-lapse ERI showed that the tracer plume moved preferentially downward through a discontinuity in the argillic horizon within the first 57 hrs. Over the following 79 hrs, the tracer plume exhibited steady, lateral movement towards the drainage ditch within a more permeable sandy horizon situated just below the argillic. A spatial moment analysis of logarithmic changes in conductivity in the sand layer revealed seepage velocities ranging from 0.0027 to 0.0482 m d−1; these values were positively correlated with hydraulic gradients, suggesting laminar flow processes typical of sandy aquifers. Increasing groundwater velocities with hydraulic gradients suggest that solute transfers from groundwater to ditch are likely to be faster in storms, especially during wet periods. Even so, predominantly slow lateral transport within the sandy horizon, even during storms, indicates that critical source areas of pollutant loss are likely within a few meters of the ditch.

Streamflow forecasts are essential for water resources management. Although there are many methods for forecasting streamflow, real-time forecasts remain challenging. This study evaluates streamflow forecasts using a process-based model (Soil and Water Assessment Tool-Variable Source Area model-SWAT-VSA), a stochastic model (Artificial Neural Network -ANN), an Auto-Regressive Moving-Average (ARMA) model, and a Bayesian ensemble model that utilizes the SWAT-VSA, ANN, and ARMA results. Streamflow is forecast from 1 to 8 d, forced with Quantitative Precipitation Forecasts from the US National Weather Service. Of the individual models, SWAT-VSA and the ANN provide better predictions of total streamflow (NSE 0.60-0.70) and peak flow, but underpredicted low flows. During the forecast period the ANN had the highest predictive power (NSE 0.44-0.64), however all three models underpredicted peak flow. The Bayesian ensemble forecast streamflow with the most skill for all forecast lead times (NSE 0.49-0.67) and provided a quantification of prediction uncertainty. National Science FoundationNational Science Foundation (NSF) [1360415, 1343802]; USDAUnited States Department of Agriculture (USDA) [2012-67019-19434] We would like to acknowledge high-performance computing support from Yellowstone (http://n2t.net/ark:/85065/d7wd3xhc) provided by NCAR's Computational and Information Systems Laboratory, support from the National Science Foundation under award numbers 1360415 and 1343802, and funding support from the USDA under project number 2012-67019-19434. All data and methods used in this manuscript are available upon request. Public domain – authored by a U.S. government employee

As we plan our week's activities, we often turn to the seven day weather forecast. Could we plan even further into the future?

Cranberry ( Ait.) production in Massachusetts represents one-fourth of the US cranberry supply, but water quality concerns, water use, and wetland protection laws challenge the future viability of the state's cranberry industry. Pond water used for harvest and winter flooding accounts for up to two-thirds of phosphorus (P) losses in drainage waters. Consequently, use of P sorbing salts to treat pond water holds promise in the mitigation of P losses from cranberry farms. Laboratory evaluation of aluminum (Al)-, iron (Fe)-, and calcium (Ca)-based salts was conducted to determine the application rate required for reducing P in shallow (0.4 m) and deep (3.2 m) water ponds used for cranberry production. Limited P removal (22%) with calcium carbonate and calcium sulfate was consistent with their relatively low solubility in water. Calcium hydroxide reduced total P up to 49%, but increases in pond water pH (8) could be detrimental to cranberry production. Ferric sulfate and aluminum sulfate applications of 15 mg L (ppm) resulted in near-complete removal of total P, which decreased from 49 ± 3 to10 μg P L (ppb). However, ferric sulfate application lowered pH below the recommend range for cranberry soils. Field testing of aluminum sulfate demonstrated that at a dose of 15 mg L (∼1.4 Al mg L), total P in pond water was reduced by 78 to 94%. Laboratory and field experiments support the recommendation of aluminum sulfate as a cost-effective remedial strategy for reducing elevated P in surface water used for cranberry production.

Over the past 20 yr, there has been a proliferation of phosphorus (P) site assessment tools for nutrient management planning, particularly in the United States. The 19 papers that make up this special section on P site assessment include decision support tools ranging from the P Index to fate-and-transport models to weather-forecast-based risk calculators. All require objective evaluation to ensure that they are effective in achieving intended benefits to protecting water quality. In the United States, efforts have been underway to compare, evaluate, and advance an array of P site assessment tools. Efforts to corroborate their performance using water quality monitoring data confirms previously documented discrepancies between different P site assessment tools but also highlights a surprisingly strong performance of many versions of the P Index as a predictor of water quality. At the same time, fate-and-transport models, often considered to be superior in their prediction of hydrology and water quality due to their complexity, reveal limitations when applied to site assessment. Indeed, one consistent theme from recent experience is the need to calibrate highly parameterized models. As P site assessment evolves, so too do routines representing important aspects of P cycling and transport. New classes of P site assessment tools are an opportunity to move P site assessment from general, strategic goals to web-based tools supporting daily, operational decisions. USDA's Natural Resource Conservation Service The authors are grateful to USDA's Natural Resource Conservation Service for support of many of the studies reported in this special collection. Public domain – authored by a U.S. government employee

Corn has been a pillar of American agriculture for decades and continues to receive much attention from the scientific community for its potential to meet the food, feed and fuel needs of a growing human population in a changing climate. By midcentury, global temperature increase is expected to exceed 2°C where local effects on heat, cold and precipitation extremes will vary. The Northeast United States is a major dairy producer, corn consumer, and is cited as the fastest warming region in the contiguous U.S. It is important to understand how key agronomic climate variables affect corn growth and development so that adaptation strategies can be tailored to local climate changes. We analyzed potential local effects of climate change on corn growth and development at three major dairy locations in the Northeast (Syracuse, New York; State College, Pennsylvania and Landisville, Pennsylvania) using downscaled projected climate data (2000-2100) from nine Global Climate Models under two emission pathways (Representative Concentration Pathways (RCP) 4.5 and 8.5). Our analysis indicates that corn near the end of the 21st century will experience fewer spring and fall freezes, faster rate of growing degree day accumulation with a reduction in time required to reach maturity, greater frequencies of daily high temperature ≥35°C during key growth stages such as silking-anthesis and greater water deficit during reproductive (R1-R6) stages. These agronomic anomalies differ between the three locations, illustrating varying impacts of climate change in the more northern regions vs. the southern regions of the Northeast. Management strategies such as shifting the planting dates based on last spring freeze and irrigation during the greatest water deficit stages (R1-R6) will partially offset the projected increase in heat and drought stress. Future research should focus on understanding the effects of global warming at local levels and determining adaptation strategies that meet local needs.

There is strong interest in adapting denitrifying bioreactors to mid-Atlantic drainage systems to help address Chesapeake Bay water quality goals. Three ditch drainage-oriented bioreactors were constructed in 2015 in Maryland to evaluate site-specific design and installation concerns and nitrate (NO3-N) removal. All three bioreactor types removed NO3-N, as measured by load and/or concentration reduction, showing promise for denitrifying bioreactors in the mid-Atlantic's low gradient Coastal Plain landscape. The ditch diversion bioreactor (25% NO3-N load reduction; 0.97 g NO3-N removed m(-3) d(-1)) and the sawdust denitrification wall adjacent to a ditch (> 90% NO3-N concentration reduction; 1.9-2.9 g NO3-N removed m(-3) d(-1)) had removal rates within range of the literature. The in-ditch bioreactor averaged 65% NO3-N concentration reduction, but sedimentation is expected to be one of the biggest challenges. A robust water balance is critical for future assessment of bioreactors' contribution to water quality improvement in low gradient mid-Atlantic landscapes. USDA-NRCS Conservation Innovation Grant [69-3A75-13-232] Funding was from USDA-NRCS Conservation Innovation Grant # 69-3A75-13-232. Thanks to Mr. Don Mahan (UMES) for sample collection and producers who allowed use of their land as test sites. Public domain – authored by a U.S. government employee

Study region: The WE-38 Experimental Watershed, which is a small (7.3 km2) basin in the Ridge and Valley physiographic region of east-central Pennsylvania. Study focus: We used non-parametric Mann-Kendall tests to examine long-term (1968 to 2012) hydroclimatic (precipitation, temperature, streamflow) trends in WE-38 in the context of recent climate change across northeastern US. New hydrological insights for the region: Annual mean temperatures in WE-38 increased 0.38 °C per decade, leading to an expansion of the growing season (+2.8 days per decade) and a contraction of frost days (-3.6 days per decade). Consistent with increased temperatures, annual actual evapotranspiration rose significantly (+37.1 mm per decade) over the study period. Precipitation also trended upward, with October experiencing the most significant increases in monthly total rainfall (+8.2 mm per decade). While augmented October precipitation led to increased October streamflow (+5.0 mm per decade), the trend in WE-38 streamflow was downward, with the most significant declines in July (-1.2 mm per decade) and February (-7.5 mm per decade). Declines in summertime streamflow also increased the duration of hydrological droughts (maximum consecutive days with streamflow < 10th percentile) by 1.9 days per decade. While our findings suggest some challenges for producers and water resource managers, most notably with increased fall rainfall and runoff, some changes such as enhanced growing seasons can be viewed positively, at least in the near term.

No comprehensive protocols exist for the collection, standardization, and storage of agronomic management information into a database that preserves privacy, maintains data uncertainty, and translates everyday decisions into quantitative values. This paper describes the development of a relational database intended to meet the agronomic and ecosystem interests of potential users from a long-term experimental watershed located in Pennsylvania, United States9 Ridge and Valley physiographic province. We discuss the type and complexity of the data, which has historically been documented in free-form surveys collected through discussion with farmers. We detail the development process of a spatially and temporally explicit land management database and discuss the challenges in standardizing, without generalizing, 13 years of historic free-form data for 13 farms and 315 fields. Finally, we provide examples at field, farm, and watershed scales of how this database serves as a foundation for other data sets and modeling efforts that support research aimed at helping farmers meet long-term production, land stewardship, and water quality goals.

Riparian seeps have been recognized for their contributions to stream flow in headwater catchments, but there is limited data on how seeps affect stream water quality. The objective of this study was to examine the effect of seeps on the variability of stream NO3-N concentrations in FD36 and RS, two agricultural catchments in Pennsylvania. Stream samples were collected at 10-m intervals over reaches of 550 (FD36) and 490 m (RS) on 21 occasions between April 2009 and January 2012. Semi-variogram analysis was used to quantify longitudinal patterns in stream NO3-N concentration. Seep water was collected at 14 sites in FD36 and 7 in RS, but the number of flowing seeps depended on antecedent conditions. Seep NO3-N concentrations were variable (0.1-29.5 mg/l) and were often greater downslope of cropped fields compared to other land uses. During base flow, longitudinal variability in stream NO3-N concentrations increased as the number of flowing seeps increased. The influence of seeps on the variability of stream NO3-N concentrations was less during storm flow compared to the variability of base flow NO3-N concentrations. However, 24 h after a storm in FD36, an increase in the number of flowing seeps and decreasing streamflow resulted in the greatest longitudinal variability in stream NO3-N concentrations recorded. Results indicate seeps are important areas of NO3-N delivery to streams where targeted adoption of mitigation measures may substantially improve stream water quality.

Riparian seepage zones in headwater agricultural watersheds represent important sources of nitrate-nitrogen (NO₃–N) to surface waters, often connecting N-rich groundwater systems to streams. In this study, we examined how NO₃–N concentrations in seep and stream water were affected by NO₃–N processing along seep surface flow paths and by upslope applications of N from fertilizers and manures. The research was conducted in two headwater agricultural watersheds, FD36 (40 ha) and RS (45 ha), which are fed, in part, by a shallow fractured aquifer system possessing high (3–16 mg L⁻¹) NO₃–N concentrations. Data from in-seep monitoring showed that NO₃–N concentrations generally decreased downseep (top to bottom), indicating that most seeps retained or removed a fraction of delivered NO₃–N (16% in FD36 and 1% in RS). Annual mean N applications in upslope fields (as determined by yearly farmer surveys) were highly correlated with seep NO₃–N concentrations in both watersheds (slope: 0.06; R² = 0.79; p < 0.001). Strong positive relationships also existed between seep and stream NO₃–N concentrations in FD36 (slope: 1.01; R² = 0.79; p < 0.001) and in RS (slope: 0.64; R² = 0.80; p < 0.001), further indicating that N applications control NO₃–N concentrations at the watershed scale. Our findings clearly point to NO₃–N leaching from upslope agricultural fields as the primary driver of NO₃–N losses from seeps to streams in these watersheds and therefore suggest that appropriate management strategies (cover crops, limiting fall/winter nutrient applications, decision support tools) be targeted in these zones.

summary Shallow groundwater dynamics play a critical role in determining the chemistry and movement of nitrogen (N) in the riparian zone. In this study, we characterized N concentration variability and hydrologic transport pathways in shallow groundwater draining areas of a riparian area with and without emergent groundwater seeps. The study was conducted in FD36, an agricultural headwater catchment in the Ridge and Valley physiographic region of central Pennsylvania, USA. Three seep and adjacent non-seep areas were each instrumented with a field of 40 piezometers installed in a grid pattern (1.5-m spacing) at both 20- and 60-cm depths. Piezometers were monitored seasonally for approximately two years (October 2010–May 2012). Results showed that hydraulic head within seep areas was variable and some regions exhibited upward vertical hydraulic gradients of 0.18–0.27. Non-seep areas were characterized by uniform hydraulic head levels and were relatively hydrostatic. Nitrate-N (NO3-N) concentrations in seep areas were significantly greater than those in the non-seep areas at two of the three study sites. A two-component mixing model using chloride as a conservative tracer indicated that shallow groundwater in seep areas was primarily (53–75%) comprised of water from a shallow fractured aquifer, which had elevated NO3-N concentrations (5.7 mg L � 1 ). Shallow groundwater in non-seep areas, however, was comprised (58–82%) of perched water on top of the fragipan that was likely recharged locally in the riparian zone and had low NO3-N concentrations (0.6 mg L � 1 ). Higher NO3-N concentrations, variable hydraulic head, and groundwater emergence onto the land surface in seep areas provided evidence for preferential flow paths as an important conduit for water and N movement in these areas of the riparian zone. We conclude that the potential for N delivery to the stream in FD36 was much greater from seep areas compared to non-seep areas. Targeted management of seeps should be a priority in efforts to reduce NO3-N levels in riparian zones within headwater agricultural catchments. Published by Elsevier B.V.

Phosphorus (P) loss from agricultural watersheds has long been a critical water quality problem, the control of which has been the focus of considerable research and investment. Preventing P loss depends on accurately representing the hydrological and chemical processes governing P mobilization and transport. The Soil and Water Assessment Tool (SWAT) is a watershed model commonly used to predict run-off and non-point source pollution transport. SWAT simulates run-off employing either the curve number (CN) or the Green and Ampt methods, both assume infiltration-excess run-off, although shallow soils underlain by a restricting layer commonly generate saturation-excess run-off from variable source areas (VSA). In this study, we compared traditional SWAT with a re-conceptualized version, SWAT-VSA, that represents VSA hydrology, in a complex agricultural watershed in east central Pennsylvania. The objectives of this research were to provide further evidence of SWAT-VSA's integrated and distributed predictive capabilities against measured surface run-off and stream P loads and to highlight the model's ability to drive sub-field management of P. Thus, we relied on a detailed field management database to parameterize the models. SWAT and SWAT-VSA predicted discharge similarly well (daily Nash–Sutcliffe efficiencies of 0.61 and 0.66, respectively), but SWAT-VSA outperformed SWAT in predicting P export from the watershed. SWAT estimated lower P loss (0.0–0.25 kg ha−1) from agricultural fields than SWAT-VSA (0.0–1.0+ kg ha−1), which also identified critical source areas – those areas generating large run-off and P losses at the sub-field level. These results support the use of SWAT-VSA in predicting watershed-scale P losses and identifying critical source areas of P loss in landscapes with VSA hydrology. Copyright © 2014 John Wiley & Sons, Ltd.

Cost-effective heat mitigation strategies are imperative for maintaining milk production and dairy farm profitability in the U.S. with projected climate change. This study investigated the cost-effectiveness of four heat abatement strategies, including Minimal (open barn or shading), Moderate (forced ventilation), High (fans and misting), and Intense (air conditioning). Heat stress and subsequent impacts on milk production per cow were predicted across nine climatic regions in the U.S. for early (2015 to 2034), mid (2045 to 2064) and late (2081 to 2100) 21st century, using downscaled climate projections. Heat abatements were used to adjust predicted milk production losses and illustrate the potential to reduce milk production losses due to heat stress. Economic analysis included a cost-benefit ratio calculation associated with the implementation of each heat abatement. Results showed that milk production losses were expected to accelerate across the U.S. at a mean rate of 174±7 kg/cow/decade, with the fastest rate in the Southeast region. Relative to Minimal heat abatement, Moderate, High, and Intense heat abatements increased annual milk production per cow by 3%, 4%, and 6% during early-21st century, 3%, 6%, and 11% during mid-21st century, and 3%, 8%, and 21% during late-21st century, respectively. The cost effectiveness of different heat abatement strategies generally increased with subsequently stronger heat abatements. In mid- and late-21st century, mean annual net values of High and Intense heat stress abatement implementation approached -$30 to $190 /cow and -$20 to $590 /cow, respectively, with the largest net annual benefit in late-21st century under Intense abatement. Findings from the study demonstrate the value of using downscaled climate projections to shed light on local and regional strategies to abate heat stress on cattle and mitigate potential milk production losses due to climate change.

The water quality response to implementation of conservation measures across watersheds has been slower and smaller than expected. This has led many to question the efficacy of these measures and to call for stricter land and nutrient management strategies. In many cases, this limited response has been due to the legacies of past management activities, where sinks and stores of P along the land-freshwater continuum mask the effects of reductions in edge-of-field losses of P. Accounting for legacy P along this continuum is important to correctly apportion sources and to develop successful watershed remediation. In this study, we examined the drivers of legacy P at the watershed scale, specifically in relation to the physical cascades and biogeochemical spirals of P along the continuum from soils to rivers and lakes and via surface and subsurface flow pathways. Terrestrial P legacies encompass prior nutrient and land management activities that have built up soil P to levels that exceed crop requirements and modified the connectivity between terrestrial P sources and fluvial transport. River and lake P legacies encompass a range of processes that control retention and remobilization of P, and these are linked to water and sediment residence times. We provide case studies that highlight the major processes and varying timescales across which legacy P continues to contribute P to receiving waters and undermine restoration efforts, and we discuss how these P legacies could be managed in future conservation programs.

Identifying sites prone to surface runoff has been a cornerstone of conservation and nutrient management programs, relying upon site assessment tools that support strategic, as opposed to operational, decision making. We sought to develop simple, empirical models to represent two highly different mechanisms of surface runoff generation—saturation excess runoff and infiltration excess runoff—using variables available from short-term weather forecasts. Logistic regression models were developed from runoff monitoring studies in Pennsylvania, fitting saturation excess runoff potential to rainfall depth, rainfall intensity, and soil moisture, and infiltration excess runoff potential to rainfall depth and intensity. Testing of the models in daily hindcasting mode over periods of time and at sites separate from where they were developed confirmed a high degree of skill, with Brier Skill Scores ranging from 0.61 to 0.65 and Gilbert Skill Scores ranging from 0.39 to 0.59. These skill scores are as good as models used in weather forecasting. Results point to the capability to forecast site-specific surface runoff potential for diverse soil conditions, with advances in weather forecasting likely to further improve the predictive ability of runoff models of this type.

[1] Precipitation regimes are predicted to shift to more extreme patterns that are characterized by more heavy rainfall events and longer dry intervals, yet their ecological impacts on vegetation production remain uncertain across biomes in natural climatic conditions. This in situ study investigated the effects of these climatic conditions on aboveground net primary production (ANPP) by combining a greenness index from satellite measurements and climatic records during 2000–2009 from 11 long-term experimental sites in multiple biomes and climates. Results showed that extreme precipitation patterns decreased the sensitivity of ANPP to total annual precipitation (PT) at the regional and decadal scales, leading to decreased rain use efficiency (RUE; by 20% on average) across biomes. Relative decreases in ANPP were greatest for arid grassland (16%) and Mediterranean forest (20%) and less for mesic grassland and temperate forest (3%). The cooccurrence of heavy rainfall events and longer dry intervals caused greater water stress conditions that resulted in reduced vegetation production. A new generalized model was developed using a function of both PT and an index of precipitation extremes and improved predictions of the sensitivity of ANPP to changes in precipitation patterns. Our results suggest that extreme precipitation patterns have substantially negative effects on vegetation production across biomes and are as important as PT. With predictions of more extreme weather events, forecasts of ecosystem production should consider these nonlinear responses to altered extreme precipitation patterns associated with climate change.

The resilience of a global sample of ecosystems to an increase in drought conditions is assessed, comparing data from the early twenty-first with the late twentieth century; results indicate a cross-ecosystem capacity for tolerating low precipitation and responding to high precipitation during recent warm drought and yet suggest a threshold to resilience with prolonged warm drought. The early twenty-first century has seen a global increase in drought conditions. These authors describe the response of plant communities in a global sample of ecosystems to drought stress as a measure of ecosystem resilience, comparing data from the early twenty-first century with the late twentieth century. They find a common range of water-use efficiency values across timescales and locations, with the increases in dry years this century not yet compromising the ability to lower water-use efficiency in response to wetter years. This work will help provide an understanding of how vegetation production will respond to the altered hydroclimatic conditions predicted with climate change, important when making decisions about food production and resource management. Climate change is predicted to increase both drought frequency and duration, and when coupled with substantial warming, will establish a new hydroclimatological model for many regions1. Large-scale, warm droughts have recently occurred in North America, Africa, Europe, Amazonia and Australia, resulting in major effects on terrestrial ecosystems, carbon balance and food security2,3. Here we compare the functional response of above-ground net primary production to contrasting hydroclimatic periods in the late twentieth century (1975–1998), and drier, warmer conditions in the early twenty-first century (2000–2009) in the Northern and Southern Hemispheres. We find a common ecosystem water-use efficiency (WUEe: above-ground net primary production/evapotranspiration) across biomes ranging from grassland to forest that indicates an intrinsic system sensitivity to water availability across rainfall regimes, regardless of hydroclimatic conditions. We found higher WUEe in drier years that increased significantly with drought to a maximum WUEe across all biomes; and a minimum native state in wetter years that was common across hydroclimatic periods. This indicates biome-scale resilience to the interannual variability associated with the early twenty-first century drought—that is, the capacity to tolerate low, annual precipitation and to respond to subsequent periods of favourable water balance. These findings provide a conceptual model of ecosystem properties at the decadal scale applicable to the widespread altered hydroclimatic conditions that are predicted for later this century. Understanding the hydroclimatic threshold that will break down ecosystem resilience and alter maximum WUEe may allow us to predict land-surface consequences as large regions become more arid, starting with water-limited, low-productivity grasslands.

Watershed models such as the Soil Water Assessment Tool (SWAT) and the Agricultural Policy Environmental EXtender (APEX) are widely used to assess the fate and transport of agricultural nutrient management practices on soluble and particulate phosphorus (P) loss in runoff. Soil P-cycling routines used in SWAT2012 revision 586, however, do not simulate the short-term effects of applying a concentrated source of soluble P, such as manure, to the soil surface where it is most vulnerable to runoff. We added a new set of soil P routines to SWAT2012 revision 586 to simulate surface-applied manure at field and subwatershed scales within Mahantango Creek watershed in south-central Pennsylvania. We corroborated the new P routines and standard P routines in two versions of SWAT (conventional SWAT, and a topographically driven variation called TopoSWAT) for a total of four modeling "treatments". All modeling treatments included 5 yr of measured data under field-specific, historical management information. Short-term "wash off" processes resulting from precipitation immediately following surface application of manures were captured with the new P routine whereas the standard routines resulted in losses regardless of manure application. The new routines improved sensitivity to key factors in nutrient management (i.e., timing, rate, method, and form of P application). Only the new P routines indicated decreases in soluble P losses for dairy manure applications at 1, 5, and 10 d before a storm event. The new P routines also resulted in more variable P losses when applying manure versus commercial fertilizer and represented increases in total P losses, as compared with standard P routines, with rate increases in dairy manure application (56,000 to 84,000 L ha(-1)). The new P routines exhibited greater than 50% variation among proportions of organic, particulate, and soluble P corresponding to spreading method. In contrast, proportions of P forms under the standard P routines varied less than 20%. Results suggest similar revisions to other agroecosystem watershed models would be appropriate. USDA-NRCS Conservation Innovation Grants (CIG) The authors thank the USDA-NRCS Conservation Innovation Grants (CIG) for financial support in part as well as the strong collaborations of the CIG project teams. The authors also thank Gordan Folmar and Jim Richards from USDA-ARS for providing watershed hydrology data and field management information, respectively. Public domain – authored by a U.S. government employee