Selection Of Best Management Practices Research Articles

Assessment of best management practices to minimise the runoff of manure‐borne phosphorus in the United States

Phosphorus (P), an essential nutrient in crop and livestock agriculture, can cause and accelerate freshwater eutrophication. Intensification of farming systems has resulted in local accumulations of P in some agricultural watersheds with related increases in P runoff. In most cases, continual land application of manure at rates exceeding crop P removal is the proximate cause of P runoff. To mitigate associated water quality impairments, P‐based agricultural best management practices (BMPs) are now becoming a part of farm nutrient planning. This planning involves the selection, timing, and implementation of source and transport BMPs at field, farm, and watershed scales. Source measures include balancing P imports and exports, improved livestock feed management, chemical and physical treatment of manures, appropriate rate, method, and timing of land application based upon regular soil and manure testing, adequate manure storage and transport infrastructure, and composting. Transport measures aim to reduce runoff and erosion via practices such as conservation tillage, contour ploughing, and vegetative filter strips. To be effective, these measures must be carefully selected and targeted to areas at greatest risk to P loss. This vulnerability can be identified and ranked by P indices, which account for source and transport factors controlling P loss. We demonstrate that the P Index can provide flexible yet reliable manure management and provide farmers with options to minimise the risk of P loss from several farms in Pennsylvania, United States. Overall, a comprehensive and holistic approach to manure management can decrease P transfers from land to water.

A comparison of soil quality indexing methods for vegetable production systems in Northern California

Consultants, farm advisors, resource conservationists, and other land managers may benefit from decision tools that help identify the most sustainable management practices. Indices of soil quality (SQIs) can provide this service. Various methods were tested for choosing a minimum data set (MDS), transforming the indicators, and calculating indices using data from alternative vegetable production systems being evaluated near Davis, California. The MDS components were chosen using expert opinion (EO) or principal components analysis (PCA) as a data reduction technique. Multiple regressions of the MDS indicators (as independent variables) against indicators representing management goals (as iterative dependent variables) showed no significant differences between the EO and PCA selection techniques in their abilities to explain variability within each sustainable management goal. Linear and non-linear scoring techniques were also compared for MDS indicators. The non-linear scoring method was determined to be more representative of system function than the linear method. Finally, indicator scores were combined using either an additive index, a weighted additive index, or a decision support system. For almost all indexing combinations, the organic system received significantly higher SQI values than the low input or conventional treatments. The efficacy of the indices was tested by comparisons with individual indicators, variables representative of management goals, and another multivariate technique for decision making that used all available data rather than a subset (MDS). Comparison with the comprehensive multivariate technique showed results similar to all of the indexing combinations except the additive and weighted indices using the linearly scored, EO-selected MDS. This suggests that a small number of carefully chosen soil quality indicators, when used in a simple, non-linearly scored index, can adequately provide information needed for selection of best management practices.

Watershed optimization of best management practices using AnnAGNPS and a genetic algorithm

An optimization algorithm linked with a nonpoint source (NPS) pollution model can be used to optimize NPS pollution control strategies on a field‐by‐field basis in a watershed by maximizing NPS pollution reduction and net monetary return. In this paper a methodology is described which integrated a genetic algorithm (GA) (an optimization algorithm) with a continuous simulation, watershed‐scale, NPS pollution model, Annualized Agricultural Non‐Point Source Pollution model (AnnAGNPS) to optimize the selection of best management practices (BMP) on a field‐by‐field basis for an entire watershed. To test the methodology, optimization analysis was performed for a U.S. Department of Agriculture experimental watershed in Pennsylvania to identify BMPs that minimized long‐term (over a 4‐year period) water quality degradation and maximized net farm return on an annual basis. Results indicate that the GA was able to identify BMP schemes that reduced pollutant load by as much as 56% and increased net annual return by 109%.

Influence of Highway Runoff Chemistry, Hydrology, and Residence Time on Nonequilibrium Partitioning of Heavy Metals: Implications for Treatment at the Highway Shoulder

The control and treatment of highway-pavement storm water at the edge of the highway shoulder pose unique challenges due to the unsteady nature of processes, including rainfall runoff, mobilization and partitioning of heavy metals, variations in storm-water chemistry, residence time on the pavement, and delivery of particulate mass. Presented are heavy-metal partitioning results as influenced by pavement-runoff chemistry and hydrologic parameters from a series of eight rainfall-runoff events over a 2-year period. Water-quality characteristics such as low alkalinity, low hardness, and short pavement residence times cause a majority of the heavy-metal mass to remain in solution at the edge of the pavement, with partitioning coefficients approaching equilibrium conditions only toward the end of the event, as heavy metals partition to entrained solids. There are two primary implications when considering the application of typical best management practices (BMPs) for highway runoff within the right-of-way. The first implication is to use a BMP such as a detention basin or roadside swale to detain runoff and produce sufficient residence time so that partitioning to the entrained solids occurs. The second implication is to use a BMP such as an engineered infiltration trench to provide surface complexation for dissolved metals and filtration mechanisms for the particulate-bound metals. Although no simple solutions exist for the removal of a heavy metal or particle once it is released in the highway environment, knowledge of the dynamic processes in highway runoff can provide insights for the proper selection of BMPs, depending on the conditions at the highway site. A design should be based on the concept that BMPs, to be effective, are essentially garbage cans for heavy metals and solids and as such must be emptied and maintained.

Recommended Parameters to Report with BMP Monitoring Data

This paper discusses the need for the reporting of a variety of physical, chemical, climatic, geological, biological, and meteorological parameters along with the data required by various investigators on the performance of structural stormwater best management practices (BMPs) used to enhance stormwater quality. A standard list of minimum parameters is suggested. Such a list is needed if we want to exchange and transfer data between various studies being conducted throughout the world, or even within the United States. Transferability of performance results and consistency, or lack of it, in the performance of various BMPs, has been an ongoing problem. A mutually agreed upon minimum list of reporting parameters that can be used to relate the performance to some, or all, BMPs could begin to address this problem. Over time such standardization will conserve the resources being expended, not only by individual BMP investigations, but also in the selection and appropriate design of various BMPs.

GROUNDWATER DISCHARGE AND ITS IMPACT ON SURFACE WATER QUALITY IN A CHESAPEAKE BAY INLET1

ABSTRACT: Surface water, groundwater, and groundwater discharge quality surveys were conducted in Cherrystone Inlet, on Virginia's Eastern Shore. Shallow groundwater below agricultural fields had nitrate concentrations significantly higher than inlet surface waters and shallow groundwater underlying forested land. This elevated nitrate groundwater discharged to adjacent surface waters. Nearshore discharge rates of water across the sediment‐water interface ranged from 0.02 to 3.69 liters·m−2·hr−1 during the surveys. The discharge was greatest nearshore at low tide periods, and decreased markedly with increasing distance offshore. Vertical hydraulic heads, Eh, and inorganic nitrogen flux in the sediments followed similar patterns. Nitrate was the predominant nitrogen species discharged nearshore adjacent to agricultural land use, changing to ammonium farther offshore. Sediment nitrogen fluxes were sufficient to cause observable impacts on surface water quality; nitrate concentrations were up to 20 times greater in areas of groundwater discharge than in the main stem inlet water. Based on DIN:DIP ratios, nitrogen contributions from direct groundwater discharge and tidal creek inputs appear to be of significant ecological importance. This groundwater discharge links land use activity and the quality of surface water, and therefore must be considered in selection of best management practices and water quality management strategies.