Upflow reactors for riparian zone denitrification

We used permeable reactive subsurface barriers consisting of a C source (wood particles), with very high hydraulic conductivities ( approximately 0.1-1 cm s(-1)), to provide high rates of riparian zone NO3-N removal at two field sites in an agricultural area of southwestern Ontario. At one site, a 0.73-m3 reactor containing fine wood particles was monitored for a 20-mo period and achieved a 33% reduction in mean influent NO3-N concentration of 11.5 mg L(-1) and a mean removal rate of 4.5 mg L(-1) d(-1) (0.7 g m(-2) d(-1)). At the second site, four smaller reactors (0.21 m3 each), two containing fine wood particles and two containing coarse wood particles, were monitored for a 4-mo period and were successful in attenuating mean influent NO3-N concentrations of 23.7 to 35.1 mg L(-1) by 41 to 63%. Mean reaction rates for the two coarse-particle reactors (3.2 and 7.8 mg L(-1) d(-1), or 1.5 and 3.4 g m(-2) d(-1)) were not significantly different (p > 0.2) than the rates observed in the two fine-particle reactors (5.0 and 9.9 mg L(-1) d(-1), or 1.8-3.5 g m(-2) d(-1)). A two-dimensional ground water flow model is used to illustrate how permeable reactive barriers such as these can be used to redirect ground water flow within riparian zones, potentially augmenting NO3- removal in this environment.     

DETERMINATION OF BEST TIMING FOR POULTRY WASTE DISPOSAL: A MODELING APPROACH1

ABSTRACT: Confined production of poultry results in significant volumes of waste material which are typically disposed of by land application. Concerns over the potential environmental impacts of poultry waste disposal have resulted in ongoing efforts to develop management practices which maintain high quality of water downstream of disposal areas. The timing of application to minimize waste constituent losses is a management practice with the potential to ensure high quality of streams, rivers, and lakes downstream of receiving areas. This paper describes the development and application of a method to identify which time of year is best, from the standpoint of surface water quality, for land application of poultry waste. The procedure consists of using a mathematical simulation model to estimate average nitrogen and phosphorus losses resulting from different application timings, and then identifying the timings which minimize losses of these nutrients. The procedure was applied to three locations in Arkansas, and three different criteria for optimality of application timing were investigated. One criterion was oriented strictly to water quality, one was oriented only to crop production, and the last was a combination. The criteria resulted in different windows of time being identified as optimal. Optimal windows also varied with location of the receiving area. The results indicate that it is possible to land-apply poultry waste at times which both minimize nutrient losses and maximize crop yield.     

Focusing biodiversity research on the needs of decision makers

The project on Biodiversity Uncertainties and Research Needs (BURN) ensures the advancement of usable knowledge on biodiversity by obtaining input from decision makers on their priority information needs about biodiversity and then using this input to engage leading scientists in designing policy-relevant research. Decision makers articulated concerns related to four issues: significance of biodiversity; status and trends of biodiversity; management for biodiversity; and the linkage of social, cultural, economic, legal, and biological objectives. Leading natural and social scientists then identified the research required to address the decision makers' needs and determined the probability of success. The diverse group of experts reached consensus on several fundamental issues, helping to clarify the role of biodiversity in land and resource management. The BURN participants identified several features that should be incorporated into policy-relevant research plans and management strategies for biodiversity. Research and assessment efforts should be: multidisciplinary and integrative, participatory with stakeholder involvement, hierarchical (multiple scales), and problem- and region-specific. The activities should be focused regionally within a global perspective. Meta-analysis of existing data is needed on all fronts to assess the state of the science. More specifically, the scientists recommended six priority research areas that should be pursued to address the information needs articulated by decision makers: (1) characterization of biodiversity, (2) environmental valuation, (3) management for sustainability—for humans and the environment (adaptive management), (4) information management strategies, (5) governance and stewardship issues, and (6) communication and outreach. Broad recommendations were developed for each research area to provide direction for research planning and resource management strategies. The results will directly benefit those groups that require biodiversity research to address their needs—whether to develop policy, manage natural resources, or make other decisions affecting biodiversity.     

A dynamic model for intertemporal allocation of old-growth forests in the Pacific Northwest

Across the globe, continued policy debates regarding the management of old-growth forests center around the difficult task of balancing economic and ecological considerations. Though the forests of the Pacific Northwest United States are among the most studied old-growth ecosystems, ecological and economic analyses have yielded public land management directives that remain controversial. Specifically, the recently adopted Northwest Forest Plan lacks explicit goals for maintaining intergenerational equity for the use of forest resources and the diversity of old-growth ecosystems. Unlike previous studies which rely on monetary quantification of costs and benefits, this study develops and applies a conceptual framework for evaluating socially optimal Pacific Northwest old-growth forest utilization strategies. Conditions for the optimal management of old-growth forests are derived using dynamic programming. The objective function synthesizes relevant biological and economic attributes of the old-growth allocation problem. Results in the form of extraction paths are compared given social pressure for consumptive and non-consumptive benefits, as well as different planning horizons, rates of social time preference, and environmental variance. Lengthening the planning horizon results in a vast divergence of optimal policies in the absence of discounting. Extraction rates appear to approach zero as the planning horizon approaches infinity. While higher rates of social time preference increase the rate of extraction, forest stocks remaining at the terminal time period equal levels remaining with a lower discount rate. Increasing environmental variance results in a higher level of stock remaining at the terminal time period. This analysis, while specific to the old-growth controversy of the Pacific Northwest, does provide general guidelines for addressing similar problems of multiple uses of natural areas, particularly where such uses are mutually incompatible, or where one use may be irreversibly destructive to another.     

SHORT-TERM FORECASTING OF SNOWMELT RUNOFF USING ARMAX MODELS1

ABSTRACT: Time series models of the ARMAX class were investigated for use in forecasting daily riverflow resulting from combined snowmelt/rainfall. The Snowmelt Runoff Model (Martinec-Rango Model) is shown to have a form similar to the ARMAX model. The advantage of the ARMAX approach is that analytical model identification and parameter estimation techniques are available. In addition, previous forecast errors can be included to improve forecasts and confidence limits can be estimated for the forecasts. Diagnostic checks are available to determine if the model is performing properly. Finally, Kalman filtering can be used to allow the model parameters to vary continuously to reflect changing basin runoff conditions. The above advantages result in improved flow forecasts with fewer model parameters.     

Hedging a Commodity Power Rate

Many of the aluminium smelters in the Pacific Northwest served by the Bonneville Power Administration (BPA) have become non-competitive and operate in the role of swing producer in the US and world markets. To avoid these cyclical swings in power demand, BPA is presently studying methods designed to link the price of power charged to smelters with the market price of aluminium. A linked-rate system tends to stabilize incomes to smelters, but increases fluctuations to the utility. These, in turn, could be stabilized by a hedging operation on the London Metals Exchange.     

Sensitivity and first-step uncertainty analyses for the preferential flow model MACRO

Sensitivity analyses for the preferential flow model MACRO were carried out using one-at-a-time and Monte Carlo sampling approaches. Four different scenarios were generated by simulating leaching to depth of two hypothetical pesticides in a sandy loam and a more structured clay loam soil. Sensitivity of the model was assessed using the predictions for accumulated water percolated at a 1-m depth and accumulated pesticide losses in percolation. Results for simulated percolation were similar for the two soils. Predictions of water volumes percolated were found to be only marginally affected by changes in input parameters and the most influential parameter was the water content defining the boundary between micropores and macropores in this dual-porosity model. In contrast, predictions of pesticide losses were found to be dependent on the scenarios considered and to be significantly affected by variations in input parameters. In most scenarios, predictions for pesticide losses by MACRO were most influenced by parameters related to sorption and degradation. Under specific circumstances, pesticide losses can be largely affected by changes in hydrological properties of the soil. Since parameters were varied within ranges that approximated their uncertainty, a first-step assessment of uncertainty for the predictions of pesticide losses was possible. Large uncertainties in the predictions were reported, although these are likely to have been overestimated by considering a large number of input parameters in the exercise. It appears desirable that a probabilistic framework accounting for uncertainty is integrated into the estimation of pesticide exposure for regulatory purposes.