Waste streams associated with a variety of agricultural runoff sources are major contributors of nutrients, pesticides and enteric microorganisms to surface and ground waters. Water soluble anionic polyacrylamide (PAM) was found to be a highly effective erosion-preventing and infiltration-enhancing polymer, when applied at rates of 1-10 g m (super -3) in furrow irrigation water. Water flowing from PAM treated irrigation furrows show large reductions in sediment, nutrients and pesticides. Recently PAM and PAM+CaO and PAM+Al(SO (sub 4) ) (sub 3) mixtures have been shown to filter bacteria, fungi and nutrients from animal wastewater. Low concentrations of PAM [175-350 g PAM ha (super -1) as PAM or as PAM+CaO and PAM+Al(SO (sub 4) ) mixture] applied to the soil surface, resulted in dramatic decreases (10 fold) of total, coliform and fecal streptococci bacteria in cattle, fish and swine wastewater leachate and surface runoff. PAM treatment also filtered significant amounts of NH (sub 4) , PO (sub 4) and total P in cattle and swine wastewater. This points to the potential of developing PAM as a water quality protection measure in combination with large-scale animal feeding operations. Potential benefits of PAM treatment of animal facility waste streams include: (1) low cost, (2) easy and quick application, (3) suitability for use with other pollution reduction techniques. Research on the efficacy of PAM for removal of protozoan parasites and viruses and more thorough assessment of PAM degradation in different soils is still needed to completely evaluate PAM treatment as an effective waste water treatment. We will present analysis and feasibility of using PAM, PAM+Al(SO (sub 4) ) (sub 3) , and PAM+CaO application for specific applications. Our results demonstrate their potential efficacy in reducing sediment, nutrients and microorganisms from animal production facility effluents. Abstract

Carbon sequestration in agricultural soils is controlled by the balance of added organic residues and microbial oxidation of both residues and native organic matter (OM) as moderated by management and tillage. The PC-based model CQESTR predicts decomposition of residues, organic amendments and soil OM, based on cropping practices. CQESTR uses RUSLE (Revised Universal Soil Loss Equation) crop rotation and management practice, crop production, and operation databases. These data are supplemented with residue nitrogen and soil OM, bulk density, and layer thickness. CQESTR was calibrated with soil carbon data from 70-year-long experiments at the Research Center at Pendleton, OR. The calibrated model provides estimates with a 95% confidence interval of 0.33% OM. Validation at 11 independent sites resulted in a matching of observed with calculated OM with a 95% confidence interval of 0.55% OM. A 12th site, with a history of severe erosion, provided a poor match.