Ray B. Bryant

Using soil phosphorus behavior to identify environmental thresholds

Concern over the transport of phosphorus from agricultural soils to surface waters has focused attention on the role of soil phosphorus in environmental risk assessment. This study explores the existence of natural soil phosphorus thresholds as expressed by Quantity/Intensity relationships. Fifty-ni

Effects of Hydrology and Field Management on Phosphorus Transport in Surface Runoff

Phosphorus (P) losses from agricultural landscapes arise from the interaction of hydrologic, edaphic, and management factors, complicated by their spatial and temporal variability. We monitored sites along two agricultural hillslopes to assess the effects of field management and hydrology on P transfers in surface runoff at different landscape positions. Surface runoff varied by landscape position, with saturation excess runoff accounting for 19 times the volume of infiltration excess runoff at the north footslope position, but infiltration excess runoff dominated at upslope landscape positions. Runoff differed significantly between south and north footslopes, coinciding with the extent of upslope soil underlain by a fragipan. Phosphorus in runoff was predominantly in dissolved reactive form (70%), with the highest concentrations associated with upper landscape positions closest to fields serving as major sources of P. However, the largest loads of P were from the north footslope, where runoff volumes were 24 times larger than from all other sites combined. Loads of P from the north footslope appeared to be primarily chronic transfers of desorbed soil P. Although runoff from the footslope likely contributed directly to stream flow and hence to stream water quality, 27% of runoff P from the upslope sites did not connect directly with stream flow. Findings of this study will be useful for evaluating the critical source area concept and metrics such as the P-Index.

Comparison of four models to determine surface soil moisture from C‐band radar imagery in a sparsely vegetated semiarid landscape

[1] Four approaches for deriving estimates of near-surface soil moisture from radar imagery in a semiarid, sparsely vegetated rangeland were evaluated against in situ measurements of soil moisture. The approaches were based on empirical, physical, semiempirical, and image difference techniques. The empirical approach involved simple linear regression of radar backscatter on soil moisture, while the integral equation method (IEM) model was used in both the physical and semiempirical approaches. The image difference or delta index approach is a new technique presented here for the first time. In all cases, spatial averaging to the watershed scale improved agreement with observed soil moisture. In the empirical approach, variation in radar backscatter explained 85% of the variation in observed soil moisture at the watershed scale. For the physical and best semiempirical adjustment to the physical model, the root-mean-square errors (RMSE) between modeled and observed soil moisture were 0.13 and 0.04, respectively. Practical limitations to obtaining surface roughness measurements limit IEM utility for large areas. The purely image-based delta index has significant operational advantage in soil moisture estimates for broad areas. Additionally, satellite observations of backscatter used in the delta index indicated an approximate 1:1 relationship with soil moisture that explained 91% of the variability, with RMSE = 0.03. Results showed that the delta index is scaled to the range in observed soil moisture and may provide a purely image based model. It should be tested in other watersheds to determine if it implicitly accounts for surface roughness, topography, and vegetation. These are parameters that are difficult to measure over large areas, and may influence the delta index.

Emerging technologies for removing nonpoint phosphorus from surface water and groundwater: introduction.

Coastal and freshwater eutrophication continues to accelerate at sites around the world despite intense efforts to control agricultural P loss using traditional conservation and nutrient management strategies. To achieve required reductions in nonpoint P over the next decade, new tools will be needed to address P transfers from soils and applied P sources. Innovative remediation practices are being developed to remove nonpoint P sources from surface water and groundwater using P sorbing materials (PSMs) derived from natural, synthetic, and industrial sources. A wide array of technologies has been conceived, ranging from amendments that immobilize P in soils and manures to filters that remove P from agricultural drainage waters. This collection of papers summarizes theoretical modeling, laboratory, field, and economic assessments of P removal technologies. Modeling and laboratory studies demonstrate the importance of evaluating P removal technologies under controlled conditions before field deployment, and field studies highlight several challenges to P removal that may be unanticipated in the laboratory, including limited P retention by filters during storms, as well as clogging of filters due to sedimentation. Despite the potential of P removal technologies to improve water quality, gaps in our knowledge remain, and additional studies are needed to characterize the long-term performance of these technologies, as well as to more fully understand their costs and benefits in the context of whole-farm- and watershed-scale P management.

Using Flue Gas Desulfurization Gypsum to Remove Dissolved Phosphorus from Agricultural Drainage Waters

High levels of accumulated phosphorus (P) in soils of the Delmarva Peninsula are a major source of dissolved P entering drainage ditches that empty into the Chesapeake Bay. The objective of this study was to design, construct, and monitor a within-ditch filter to remove dissolved P, thereby protecting receiving waters against P losses from upstream areas. In April 2007, 110 Mg of flue gas desulfurization (FGD) gypsum, a low-cost coal combustion product, was used as the reactive ingredient in a ditch filter. The ditch filter was monitored from 2007 to 2010, during which time 29 storm-induced flow events were characterized. For storm-induced flow, the event mean concentration efficiency for total dissolved P (TDP) removal for water passing through the gypsum bed was 73 ± 27% confidence interval (α = 0.05). The removal efficiency for storm-induced flow by the summation of load method was 65 ± 27% confidence interval (α = 0.05). Although chemically effective, the maximum observed hydraulic conductivity of FGD gypsum was 4 L s(-1), but it decreased over time to <1 L s(-1). When bypass flow and base flow were taken into consideration, the ditch filter removed approximately 22% of the TDP load over the 3.6-yr monitoring period. Due to maintenance and clean-out requirements, we conclude that ditch filtration using FGD gypsum is not practical at a farm scale. However, we propose an alternate design consisting of FGD gypsum-filled trenches parallel to the ditch to intercept and treat groundwater before it enters the ditch.

Whither goes soil science in the United States and Canada

Institutional and student surveys carried out in 1992 and 2004 suggest that soil science education is experiencing a significant decline in the United States and Canada. The present article reports on the data obtained in these surveys, particularly the fact that the enrollment in MSc and PhD programs in soil science in US and Canadian universities in 2004 was approximately 40% less than that in 1992. Some of the possible causes of this drop are analyzed in detail, such as the tendency of soil science education programs to keep emphasizing the agricultural side of soil science (i.e., its connection to crop production), despite the open intention of most students to pursue careers dealing predominantly, or at least in part, with environmental issues. It is argued that measures could still be taken by soil science educators and soil scientists to revert the downward trend in enrollments. Among these are licensing soil scientists, being vigilant about oversimplifications and misrepresentations of soil processes by researchers in other disciplines, expanding the scope of soil science and actively promoting its achievements, and making sure that the public at large is aware of the intrinsic, challenging complexity of soils and that it mandates a unique pluridisciplinary approach. We believe that if some of these measures were adopted, soil science could relatively and rapidly regain its place in the pantheon of science.

Grazing Can Reduce the Environmental Impact of Dairy Production Systems

Incorporating managed rotational grazing into a dairy farm can result in an array of environmental consequences. A comprehensive assessment of the environmental impacts of four management scenarios was conducted by simulating a 250-acre dairy farm typical of Pennsylvania with: (i) a confinement fed herd producing 22,000 lbs of milk per cow per year; (ii) a confinement fed herd producing 18,500 lbs; (iii) a confinement fed herd with summer grazing producing 18,500 lbs; and (iv) a seasonal herd maintained outdoors producing 13,000 lbs. Converting 75 acres of cropland to perennial grassland reduced erosion 24% and sediment-bound and soluble P runoff by 23 and 11%, respectively. Conversion to all perennial grassland reduced erosion 87% with sediment-bound and soluble P losses reduced 80 and 23%. Ammonia volatilization was reduced about 30% through grazing, but nitrate leaching loss increased up to 65%. Grazing systems reduced the net greenhouse gas emission by 8 to 14% and the C footprint by 9 to 20%. Including C sequestration further reduced the C footprint of an all grassland farm up to 80% during the transition from cropland. The environmental benefits of grass-based dairy production should be used to encourage greater adoption of managed rotational grazing in regions where this technology is well adapted.

Managing manure for sustainable livestock production in the Chesapeake Bay Watershed

Manure presents one of the greatest challenges to livestock (dairy and beef cattle, swine, poultry, equine, sheep, llamas, etc.) operations in the Chesapeake Bay Watershed, serving both as resource and liability. The Chesapeake Bay is threatened by excessive nutrient loadings, and, according to the US Environmental Protection Agency (USEPA), manure is the source of 18% of the nitrogen and 27% of the phosphorus entering the Chesapeake Bay annually (figure 1) (Chesapeake Bay Program 2010). Developing economical, practical, and effective manure management options for livestock producers will not only contribute to the restoration of the Chesapeake Bay, but will also provide a model for other areas where water quality and livestock production objectives must be balanced. The 166,000 km2 (64,000 mi2) Chesapeake Bay Watershed is home to 3.2 million animal units (animal unit = 454 kg [1,000 lbs] of livestock) generating roughly 36 million t (40 million tn) of livestock manure per year. In comparison, the 14 million humans who call the Chesapeake Bay Watershed home generate 3.6 million t (4 million tn) of waste annually (Brosch 2010; Blankenship 2005). The livestock manure contains approximately 259,000 t (285,000 tn) of nitrogen and 70,000 t (77,000 tn) of phosphorus. Most manure is…

An expert system for soil taxonomy

This study tested the feasibility of producing an automated expert system for Soil Taxonomy to identify soil order from stored data by building an expert system prototype. Soil Taxonomy rules for the Histosol, Spodosol, Andisol, and Oxisol orders were translated into decision tree format. Seventy independent properties were stored in tabular format for each pedon. Heuristic knowledge (expert rules) was added to the decision trees to query a minimum data set, with 13 field description properties required to contain data for each soil horizon, 20 default values, and three estimated values from lookup tables. The prototype expert system was developed using an object-oriented expert system shell. Twenty-seven subsections were named in the rules to identify the Histosol, Spodosol, Andisol, and Oxisol soil orders. Sixty-seven objects, 70 independent properties, and 135 calculated properties were needed to define these subsections and their properties. The tested prototype quickly and correctly identified the diagnostic horizons, nonspatial differentiae, and the soil order, proving the feasibility of developing an expert system for Soil Taxonomy using existing computer programs and programming methods. We recommend improvements in policy and procedure for recording field description data and development of the expert rules to add dynamic links to outside models and software and incorporate fuzzy logic. The project should be continued to improve the prototype interface and data output features and to complete an expert system to add the remaining soil orders for Soil Taxonomy.

Forecasting runoff from Pennsylvania landscapes

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.