Southeast Watershed Research Laboratory

Denitrification is a critical process regulating the removal of bioavailable nitrogen (N) from natural and human-altered systems. While it has been extensively studied in terrestrial, freshwater, and marine systems, there has been limited communication among denitrification scientists working in these individual systems. Here, we compare rates of denitrification and controlling factors across a range of ecosystem types. We suggest that terrestrial, freshwater, and marine systems in which denitrification occurs can be organized along a continuum ranging from (1) those in which nitrification and denitrification are tightly coupled in space and time to (2) those in which nitrate production and denitrification are relatively decoupled. In aquatic ecosystems, N inputs influence denitrification rates whereas hydrology and geomorphology influence the proportion of N inputs that are denitrified. Relationships between denitrification and water residence time and N load are remarkably similar across lakes, river reaches, estuaries, and continental shelves. Spatially distributed global models of denitrification suggest that continental shelf sediments account for the largest portion (44%) of total global denitrification, followed by terrestrial soils (22%) and oceanic oxygen minimum zones (OMZs; 14%). Freshwater systems (groundwater, lakes, rivers) account for about 20% and estuaries 1% of total global denitrification. Denitrification of land-based N sources is distributed somewhat differently. Within watersheds, the amount of land-based N denitrified is generally highest in terrestrial soils, with progressively smaller amounts denitrified in groundwater, rivers, lakes and reservoirs, and estuaries. A number of regional exceptions to this general trend of decreasing denitrification in a downstream direction exist, including significant denitrification in continental shelves of N from terrestrial sources. Though terrestrial soils and groundwater are responsible for much denitrification at the watershed scale, per-area denitrification rates in soils and groundwater (kg N x km(-2) x yr(-1)) are, on average, approximately one-tenth the per-area rates of denitrification in lakes, rivers, estuaries, continental shelves, or OMZs. A number of potential approaches to increase denitrification on the landscape, and thus decrease N export to sensitive coastal systems exist. However, these have not generally been widely tested for their effectiveness at scales required to significantly reduce N export at the whole watershed scale.

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.

The NASA Soil Moisture Active Passive (SMAP) mission has utilized a set of core validation sites as the primary methodology in assessing the soil moisture retrieval algorithm performance. Those sites provide wellcalibrated in situ soil moisture measurements within SMAP product grid pixels for diverse conditions and locations. The estimation of the average soil moisture within the SMAP product grid pixels based on in situ measurements is more reliable when location specific calibration of the sensors has been performed and there is adequate replication over the spatial domain, with an up-scaling function based on analysis using independent estimates of the soil moisture distribution. SMAP fulfilled these requirements through a collaborative Cal/Val Partner program. This paper presents the results from 34 candidate core validation sites for the first eleven months of the SMAP mission. As a result of the screening of the sites prior to the availability of SMAP data, out of the 34

Abstract Phosphorus in runoff from agricultural land is an important component of nonpoint‐source pollution and can accelerate eutrophication of lakes and streams. Long‐term land application of P as fertilizer and animal wastes has resulted in elevated levels of soil P in many locations in the USA. Problems with soils high in P are often aggravated by the proximity of many of these areas to P‐sensitive water bodies, such as the Great Lakes, Chesapeake and Delaware Bays, Lake Okeechobee, and the Everglades. This paper provides a brief overview of the issues and options related to management of agricultural P that were discussed at a special symposium titled, “Agricultural Phosphorus and Eutrophication,” held at the November 1996 American Society of Agronomy annual meetings. Topics discussed at the symposium and reviewed here included the role of P in eutrophication; identification of P‐sensitive water bodies; P transport mechanisms; chemical forms and fate of P; identification of P source areas; modeling of P transport; water quality criteria; and management of soil and manure P, off‐farm P inputs, and P transport processes.

The National Aeronautics and Space Administration (NASA) Soil Moisture Active Passive (SMAP) satellite mission was launched on January 31, 2015. The observatory was developed to provide global mapping of high-resolution soil moisture and freeze-thaw state every two to three days using an L-band (active) radar and an L-band (passive) radiometer. After an irrecoverable hardware failure of the radar on July 7, 2015, the radiometer-only soil moisture product became the only operational soil moisture product for SMAP. The product provides soil moisture estimates posted on a 36 km Earth-fixed grid produced using brightness temperature observations from descending passes. Within months after the commissioning of the SMAP radiometer, the product was assessed to have attained preliminary (beta) science quality, and data were released to the public for evaluation in September 2015. The product is available from the NASA Distributed Active Archive Center at the National Snow and Ice Data Center. This paper provides a summary of the Level 2 Passive Soil Moisture Product (L2_SM_P) and its validation against in situ ground measurements collected from different data sources. Initial in situ comparisons conducted between March 31, 2015 and October 26, 2015, at a limited number of core validation sites (CVSs) and several hundred sparse network points, indicate that the V-pol Single Channel Algorithm (SCA-V) currently delivers the best performance among algorithms considered for L2_SM_P, based on several metrics. The accuracy of the soil moisture retrievals averaged over the CVSs was 0.038 m <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">3</sup> /m <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">3</sup> unbiased root-mean-square difference (ubRMSD), which approaches the SMAP mission requirement of 0.040 m <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">3</sup> /m <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">3</sup> .

Validation is an important and particularly challenging task for remote sensing of soil moisture. A key issue in the validation of soil moisture products is the disparity in spatial scales between satellite and in situ observations. Conventional measurements of soil moisture are made at a point, whereas satellite sensors provide an integrated area/volume value for a much larger spatial extent. In this paper, four soil moisture networks were developed and used as part of the Advanced Microwave Scanning Radiometer-Earth Observing System (AMSR-E) validation program. Each network is located in a different climatic region of the U.S., and provides estimates of the average soil moisture over highly instrumented experimental watersheds and surrounding areas that approximate the size of the AMSR-E footprint. Soil moisture measurements have been made at these validation sites on a continuous basis since 2002, which provided a seven-year period of record for this analysis. The National Aeronautics and Space Administration (NASA) and Japan Aerospace Exploration Agency (JAXA) standard soil moisture products were compared to the network observations, along with two alternative soil moisture products developed using the single-channel algorithm (SCA) and the land parameter retrieval model (LPRM). The metric used for validation is the root-mean-square error (rmse) of the soil moisture estimate as compared to the in situ data. The mission requirement for accuracy defined by the space agencies is 0.06 m <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">3</sup> /m <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">3</sup> . The statistical results indicate that each algorithm performs differently at each site. Neither the NASA nor the JAXA standard products provide reliable estimates for all the conditions represented by the four watershed sites. The JAXA algorithm performs better than the NASA algorithm under light-vegetation conditions, but the NASA algorithm is more reliable for moderate vegetation. However, both algorithms have a moderate to large bias in all cases. The SCA had the lowest overall rmse with a small bias. The LPRM had a very large overestimation bias and retrieval errors. When site-specific corrections were applied, all algorithms had approximately the same error level and correlation. These results clearly show that there is much room for improvement in the algorithms currently in use by JAXA and NASA. They also illustrate the potential pitfalls in using the products without a careful evaluation.

Abstract SWAT + is a completely restructured version of the Soil and Water Assessment Tool ( SWAT ) that was developed to face present and future challenges in water resources modeling and management and to meet the needs of the worldwide user community. It is expected to improve code development and maintenance; support data availability, analysis, and visualization; and enhance the model's capabilities in terms of the spatial representation of elements and processes within watersheds. The most important change is the implementation of landscape units and flow and pollutant routing across the landscape. Also, SWAT + offers more flexibility than SWAT in defining management schedules, routing constituents, and connecting managed flow systems to the natural stream network. To test the basic hydrologic function of SWAT +, it was applied to the Little River Experimental Watershed (Georgia) without enhanced overland routing and compared with previous models. SWAT + gave similar results and inaccuracies as these models did for streamflow and water balance. Taking full advantage of the new capabilities of SWAT + regarding watershed discretization and landscape and river interactions is expected to improve simulations in future studies. While many capabilities of SWAT have already been enhanced in SWAT + and new capabilities have been added, the model will continue to evolve in response to advancements in scientific knowledge and the demands of the growing worldwide user community. Editor's note: This paper is part of the featured series on SWAT Applications for Emerging Hydrologic and Water Quality Challenges. See the February 2017 issue for the introduction and background to the series .

Abstract Pearl millet [ Cenchrus americanus (L.) Morrone] is a staple food for more than 90 million farmers in arid and semi-arid regions of sub-Saharan Africa, India and South Asia. We report the ∼1.79 Gb draft whole genome sequence of reference genotype Tift 23D 2 B 1 -P1-P5, which contains an estimated 38,579 genes. We highlight the substantial enrichment for wax biosynthesis genes, which may contribute to heat and drought tolerance in this crop. We resequenced and analyzed 994 pearl millet lines, enabling insights into population structure, genetic diversity and domestication. We use these resequencing data to establish marker trait associations for genomic selection, to define heterotic pools, and to predict hybrid performance. We believe that these resources should empower researchers and breeders to improve this important staple crop.

Dosskey, Michael G., Philippe Vidon, Noel P. Gurwick, Craig J. Allan, Tim P. Duval, and Richard Lowrance, 2010. The Role of Riparian Vegetation in Protecting and Improving Chemical Water Quality in Streams. Journal of the American Water Resources Association (JAWRA) 46(2):261‐277. DOI: 10.1111/j.1752‐1688.2010.00419.x Abstract: We review the research literature and summarize the major processes by which riparian vegetation influences chemical water quality in streams, as well as how these processes vary among vegetation types, and discuss how these processes respond to removal and restoration of riparian vegetation and thereby determine the timing and level of response in stream water quality. Our emphasis is on the role that riparian vegetation plays in protecting streams from nonpoint source pollutants and in improving the quality of degraded stream water. Riparian vegetation influences stream water chemistry through diverse processes including direct chemical uptake and indirect influences such as by supply of organic matter to soils and channels, modification of water movement, and stabilization of soil. Some processes are more strongly expressed under certain site conditions, such as denitrification where groundwater is shallow, and by certain kinds of vegetation, such as channel stabilization by large wood and nutrient uptake by faster‐growing species. Whether stream chemistry can be managed effectively through deliberate selection and management of vegetation type, however, remains uncertain because few studies have been conducted on broad suites of processes that may include compensating or reinforcing interactions. Scant research has focused directly on the response of stream water chemistry to the loss of riparian vegetation or its restoration. Our analysis suggests that the level and time frame of a response to restoration depends strongly on the degree and time frame of vegetation loss. Legacy effects of past vegetation can continue to influence water quality for many years or decades and control the potential level and timing of water quality improvement after vegetation is restored. Through the collective action of many processes, vegetation exerts substantial influence over the well‐documented effect that riparian zones have on stream water quality. However, the degree to which stream water quality can be managed through the management of riparian vegetation remains to be clarified. An understanding of the underlying processes is important for effectively using vegetation condition as an indicator of water quality protection and for accurately gauging prospects for water quality improvement through restoration of permanent vegetation.

Phosphorus application in excess of crop needs has increased the concentration of P in surface soil and runoff and led many states to develop P-based nutrient management strategies. However, insufficient data are available relating P in surface soil, surface runoff, and subsurface drainage to develop sound guidelines. Thus, we investigated P release from the surface (0-5 cm depth) of a Denbigh silt loam from Devon, U.K. (30-160 mg kg-1 Olsen P) and Alvin, Berks, Calvin, and Watson soils from Pennsylvania (10-763 mg kg-1 Mehlich-3 P) in relation to the concentration of P in surface runoff and subsurface drainage. A change point, where the slopes of two linear relationships between water- or CaCl2-extractable soil P and soil test phosphorus (STP) (Olsen or Mehlich-3) meet, was evident for the Denbigh at 33 to 36 mg kg-1 Olsen P, and the Alvin and Berks soils at 185 to 190 mg Mehlich-3 P kg-1. Similar change points were also observed when STP was related to the P concentration of surface runoff (185 mg kg-1) and subsurface drainage (193 mg kg-1). The use of water and CaCl2 extraction of surface soil is suggested to estimate surface runoff P (r2 of 0.92 for UK and 0.86 for PA soils) and subsurface drainage P (r2 of 0.82 for UK and 0.88 for PA soils), and to determine a change point in STP, which may be used in support of agricultural and environmental P management.

Abstract Inputs of P are essential for profitable crop and livestock production. However, its export in watershed runoff can accelerate the eutrophication of receiving fresh waters. The specialization of crop and livestock farming has created regional imbalances in P inputs in feed and fertilizer and output in farm produce. In many areas, soil P exceeds crop needs and has enriched surface runoff with P. This paper provides a brief overview of P management strategies to maintain agricultural production and protect water quality that were discussed at the conference, “Practical and Innovative Measures for the Control of Agricultural Phosphorus Losses to Water,” sponsored by the Organization for Economic Cooperation and Development and held in Antrim, Northern Ireland, June 1998. The purpose of the conference was to assess current strategies for reducing the loads and concentrations of P from agricultural land to surface waters. Topics discussed at the interdisciplinary conference and reviewed here included sustainable P management in productive agriculture; assessing land application of P; evaluating and modeling P transport and transformations in soil, runoff, streams, and lakes; and implementation of integrated best management practices (BMPs). From these discussions, measures to control agricultural P transfer from soil to water may be brought about by optimizing fertilizer P use‐efficiency, refining animal feed rations, using feed additives to increase P absorption by the animal, moving manure from surplus to deficit areas, and targeting conservation practices, such as reduced tillage, buffer strips, and cover crops, to critical areas of P export from a watershed.

Estimation of soil moisture at large scale has been performed using several satellite-based passive microwave sensors and a variety of retrieval methods over the past two decades. The most recent source of soil moisture is the European Space Agency Soil Moisture and Ocean Salinity (SMOS) mission. A thorough validation must be conducted to insure product quality that will, in turn, support the widespread utilization of the data. This is especially important since SMOS utilizes a new sensor technology and is the first passive L-band system in routine operation. In this paper, we contribute to the validation of SMOS using a set of four in situ soil moisture networks located in the U.S. These ground-based observations are combined with retrievals based on another satellite sensor, the Advanced Microwave Scanning Radiometer (AMSR-E). The watershed sites are highly reliable and address scaling with replicate sampling. Results of the validation analysis indicate that the SMOS soil moisture estimates are approaching the level of performance anticipated, based on comparisons with the in situ data and AMSR-E retrievals. The overall root-mean-square error of the SMOS soil moisture estimates is 0.043 m <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">3</sup> /m <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">3</sup> for the watershed networks (ascending). There are bias issues at some sites that need to be addressed, as well as some outlier responses. Additional statistical metrics were also considered. Analyses indicated that active or recent rainfall can contribute to interpretation problems when assessing algorithm performance, which is related to the contributing depth of the satellite sensor. Using a precipitation flag can improve the performance. An investigation of the vegetation optical depth (tau) retrievals provided by the SMOS algorithm indicated that, for the watershed sites, these are not a reliable source of information about the vegetation canopy. The SMOS algorithms will continue to be refined as feedback from validation is evaluated, and it is expected that the SMOS estimates will improve.

Recent interest in tracking environmental benefits of conservation practices on agricultural watersheds throughout the United States has led to the development of the U.S. Department of Agriculture’s (USDA) Conservation Effects Assessment Project (CEAP). The purpose of CEAP is to assess environmental benefits derived from implementing various USDA conservation programs for cultivated, range, and irrigated lands. Watershed scale, hydrologic simulation models such as the Soil and Water Assessment Tool (SWAT) will be used to relate principal source areas of contaminants to transport paths and processes under a range in climatic, soils, topographic, and land use conditions on agricultural watersheds. To better understand SWAT’s strengths and weaknesses in simulating streamflow for anticipated applications related to CEAP, we conducted a study to evaluate the model’s performance under a range of climatic, topographic, soils, and land use conditions. Hydrologic responses were simulated on five USDA Agricultural Research Service watersheds that included Mahantango Creek Experimental Watershed in Pennsylvania and Reynolds Creek Experimental Watershed in Idaho in the northern part of the United States, and Little River Experimental Watershed in Georgia, Little Washita River Experimental Watershed in Oklahoma, and Walnut Gulch Experimental Watershed in Arizona in the south. Model simulations were performed on a total of 30 calibration and validation data sets that were obtained from a long record of multigauge climatic and streamflow data on each of the watersheds. A newly developed autocalibration tool for the SWAT model was employed to calibrate eleven parameters that govern surface and subsurface response for the three southern watersheds, and an additional five parameters that govern the accumulation of snow and snowmelt runoff processes for the two northern watersheds. Based on a comparison of measured versus simulated average annual streamflow, SWAT exhibits an element of robustness in estimating hydrologic responses across a range in topographic, soils, and land use conditions. Differences in model performance, however, are noticeable on a climatic basis in that SWAT will generally perform better on watersheds in more humid climates than in desert or semidesert climates. The model may therefore be better suited for CEAP investigations in wetter regions of the eastern part of the United States that are predominantly cultivated than the dryer regions of the West that are more characteristically rangeland.

Abstract The Soil Moisture Active Passive (SMAP) mission Level-4 Surface and Root-Zone Soil Moisture (L4_SM) data product is generated by assimilating SMAP L-band brightness temperature observations into the NASA Catchment land surface model. The L4_SM product is available from 31 March 2015 to present (within 3 days from real time) and provides 3-hourly, global, 9-km resolution estimates of surface (0–5 cm) and root-zone (0–100 cm) soil moisture and land surface conditions. This study presents an overview of the L4_SM algorithm, validation approach, and product assessment versus in situ measurements. Core validation sites provide spatially averaged surface (root zone) soil moisture measurements for 43 (17) “reference pixels” at 9- and 36-km gridcell scales located in 17 (7) distinct watersheds. Sparse networks provide point-scale measurements of surface (root zone) soil moisture at 406 (311) locations. Core validation site results indicate that the L4_SM product meets its soil moisture accuracy requirement, specified as an unbiased RMSE (ubRMSE, or standard deviation of the error) of 0.04 m3 m−3 or better. The ubRMSE for L4_SM surface (root zone) soil moisture is 0.038 m3 m−3 (0.030 m3 m−3) at the 9-km scale and 0.035 m3 m−3 (0.026 m3 m−3) at the 36-km scale. The L4_SM estimates improve (significantly at the 5% level for surface soil moisture) over model-only estimates, which do not benefit from the assimilation of SMAP brightness temperature observations and have a 9-km surface (root zone) ubRMSE of 0.042 m3 m−3 (0.032 m3 m−3). Time series correlations exhibit similar relative performance. The sparse network results corroborate these findings over a greater variety of climate and land cover conditions.

Abstract Mechanisms of nitrate (NO 3 ) removal from groundwater in riparian forests are poorly understood. This study was conducted in the Georgia coastal plain to: (i) determine changes in NO 3 and Cl concentrations within shallow groundwater moving from a row‐crop field to a stream; (ii) determine the spatial and temporal distribution of denitrifiration potential relative to changes in NO 3 concentrations; and (iii) determine whether NO 3 or C supply was limiting denitrification potential. Nitrate and Cl concentrations in groundwater were measured biweekly or monthly for October 1988 through May 1990. Denitrification potentials, indicated by the denitrification enzyme assay, were measured bimonthly from October 1988 through October 1989. Modified potential measurements, lacking either NO 3 , C, or both, were also performed bimonthly. Both NO 3 and NO 3 /Cl ratios in groundwater decreased by a factor of 7 to 9 in the first 10 m of forest. Within the next 40 m of forest, mean NO 3 concentration decreased from 1.80 to 0.81 mg NO 3 ‐N L −1 . Denitrifiration potential was more than two orders of magnitude higher in the top 10 cm of soil than in the top 10 cm of the shallow aquifer. Denitrification potential was consistently highest in surface soil nearest the field and nearest the stream and was limited by NO 3 availability in all surface soil samples. Denitrification potential was highest in October and August. Although NO 3 is definitely being removed from shallow groundwater, it is apparently not due to direct denitrification from the saturated zone. High denitrification potential in surface soils, especially near the field/forest interface, may contribute to NO 3 disappearance from shallow groundwater. Processes associated with intact riparian vegetation appear to play the primary role in N removal.

Switchgrass (Panicum virgatum L.) has been identified as a model herbaceous energy crop for the USA. In this review, we selectively highlight current USDA-ARS research on switchgrass for biomass energy. Intensive research on switchgrass as a biomass feedstock in the 1990s greatly improved our understanding of the adaptation of switchgrass cultivars, production practices, and environmental benefits. Several constraints still remain in terms of economic production of switchgrass for biomass feedstock including reliable establishment practices to ensure productive stands in the seeding year, efficient use of fertilizers, and more efficient methods to convert lignocellulose to biofuels. Overcoming the biological constraints will require genetic enhancement, molecular biology, and plant breeding efforts to improve switchgrass cultivars. New genomic resources will aid in developing molecular markers, and should allow for marker-assisted selection of improved germplasm. Research is also needed on profitable management practices for switchgrass production appropriate to specific agro-ecoregions and breakthroughs in conversion methodology. Current higher costs of biofuels compared to fossil fuels may be offset by accurately valuing environmental benefits associated with perennial grasses such as reduced runoff and erosion and associated reduced losses of soil nutrients and organic matter, increased incorporation of soil carbon and reduced use of agricultural chemicals. Use of warm-season perennial grasses in bioenergy cropping systems may also mitigate increases in atmospheric CO 2 . A critical need is teams of scientists, extension staff, and producer-cooperators in key agro-ecoregions to develop profitable management practices for the production of biomass feedstocks appropriate to those agro-ecoregions. Key words: Bioenergy, biomass conversion technologies, Panicum virgatum L., stand establishment, switchgrass improvement, USDA-ARS

Management practices for biomass production of bioenergy grasses may differ from management for forage. Our objective was to determine the yield and stand responses of ‘Alamo’ switchgrass ( Panicum virgatum L.) to N and P fertilization as affected by row spacing. A combination of five rates each of N and P were applied to plots during 1992 to 1998 at Stephenville, TX and 1993 to 1995 at Beeville, TX. Three row‐spacing treatments were applied as subplots. Biomass production was determined each year with a single harvest in late summer. Tiller density and tiller mass were measured during 1993 to 1996 at Stephenville. Biomass production was not influenced by the addition of P. Biomass production response to N at Beeville was greater in narrow rows than wide rows during the establishment year only. Biomass production responses to N were quadratic in 5 of 7 yr at Stephenville and linear at Beeville. A maximum yield of 22.5 Mg ha −1 occurred during 1995 at Stephenville at 168 kg N ha −1 . Lodging occurred at both locations but only at the 224 kg N ha −1 rate. Tiller density and mass increased as row width increased. Tiller mass also increased with increasing N fertility at Stephenville. This response was more important in determining biomass production than was tiller density. Average biomass production at 168 kg N ha −1 yr −1 was 14.5 and 10.7 Mg ha −1 yr −1 at Stephenville and Beeville, respectively. Biomass production without applied N tended to decline over the years. Our data indicated that switchgrass biomass production is sustainable at Stephenville only with the application of at least 168 kg N ha −1 yr −1 , but P application and row spacing are not crucial.

Abstract The NASA Soil Moisture Active Passive (SMAP) mission Level‐4 Soil Moisture (L.4_SM) product provides global, 3‐hourly, 9‐km resolution estimates of surface (0–5 cm) and root zone (0–100 cm) soil moisture with a mean latency of ~2.5 days. The underlying L4_SM algorithm assimilates SMAP radiometer brightness temperature (Tb) observations into the NASA Catchment land surface model using a spatially distributed ensemble Kalman filter. In Version 4 of the L4_SM modeling system the upward recharge of surface soil moisture from below under nonequilibrium conditions was reduced, resulting in less bias and improved dynamic range of L4_SM surface soil moisture compared to earlier versions. This change and additional technical modifications to the system reduce the mean and standard deviation of the observation‐minus‐forecast Tb residuals and overall soil moisture analysis increments while maintaining the skill of the L4_SM soil moisture estimates versus independent in situ measurements; the average, bias‐adjusted root‐mean‐square error in Version 4 is 0.039 m 3 /m 3 for surface and 0.026 m 3 /m 3 for root zone soil moisture. Moreover, the coverage of assimilated SMAP observations in Version 4 is near global owing to the use of additional satellite Tb records for algorithm calibration. L4_SM soil moisture uncertainty estimates are biased low (by 0.01–0.02 m 3 /m 3 ) against actual errors (computed versus in situ measurements). L4_SM runoff estimates, an additional product of the L4_SM algorithm, are biased low (by 35 mm/year) against streamflow measurements. Compared to Version 3, bias in Version 4 is reduced by 46% for surface soil moisture uncertainty estimates and by 33% for runoff estimates.

Soil organic carbon (SOC) is closely tied to soil health. However, additional biological indicators may also provide insight about C dynamics and microbial activity. We used SOC and the other C indicators (potential C mineralization, permanganate oxidizable C, water extractable organic C, and β-glucosidase enzyme activity) from the North American Project to Evaluate Soil Health Measurements to examine the continental-scale drivers of these indicators, the relationships among indicators, and the effects of soil health practices on indicator values. All indicators had greater values at cooler temperatures, and most were greater with increased precipitation and clay content. The indicators were strongly correlated with each other at the site-level, with the strongest relationship between SOC and permanganate oxidizable C. The indicator values responded positively to decreased tillage, inclusion of cover crops, application of organic nutrients, and retention of crop residue, but not the number of harvested crops in a rotation. The effect of decreased tillage on the C indicators was generally greater at sites with higher precipitation. The magnitude and direction of the response to soil health practices was consistent across indicators within a site but measuring at least two indicators would provide additional confidence of the effects of management, especially for tillage. All C indicators responded to management, an essential criterion for evaluating soil health. Balancing the cost, sensitivity, interpretability, and availability at commercial labs, a 24-hr potential C mineralization assay could deliver the most benefit to measure in conjunction with SOC.

Abstract The accumulation, management, and transfer of P in intensive farming systems has increased P export from agricultural watersheds and accelerated eutrophication of surface waters. Even though much research on P has been done in the last 20 years, there are still too few answers to the many questions now being asked regarding agricultural production and environmental quality. To address these concerns, four areas of research are suggested: (i) Soil P testing for environmental risk assessment —What losses are acceptable and can these losses be determined by plot‐scale or watershed‐scale studies? Threshold P levels in soil and water should be established in combination with an assessment of site vulnerability to P loss. (ii) Pathways of P transport —An analysis of the relative importance of different flow pathways is needed at a watershed scale. (iii) Best Management Practice (BMP) development and implementation —Overall, BMPs must attempt to bring P inputs and outputs into closer balance and should be targeted first to critical source areas within a watershed. Alternative management recommendations, uses, and market demand for manures must be developed. (iv) Strategic initiatives to manage P —To initiate lasting changes, research should focus on consumer‐supported programs that encourage farmer performance and stewardship to achieve agreed‐upon environmental goals.