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Ankeny, IA, United States

Jones C.S.,University of Iowa | Kult K.J.,Iowa Soybean Association
Journal of Environmental Quality | Year: 2016

In recent years, the agricultural community has reduced flow of nitrogen from farmed landscapes to stream networks through the use of woodchip denitrification bioreactors. Although deployment of this practice is becoming more common to treat high-nitrate water from agricultural drainage pipes, information about bioreactor management strategies is sparse. This study focuses on the use of water monitoring, and especially the use of alkalinity monitoring, in five Iowa woodchip bioreactors to provide insights into and to help manage bioreactor chemistry in ways that will produce desirable outcomes. Results reported here for the five bioreactors show average annual nitrate load reductions between 50 and 80%, which is acceptable according to established practice standards. Alkalinity data, however, imply that nitrous oxide formation may have regularly occurred in at least three of the bioreactors that are considered to be closed systems. Nitrous oxide measurements of influent and effluent water provide evidence that alkalinity may be an important indicator of bioreactor performance. Bioreactor chemistry can be managed by manipulation of water throughput in ways that produce adequate nitrate removal while preventing undesirable side effects. We conclude that (i) water should be retained for longer periods of time in bioreactors where nitrous oxide formation is indicated, (ii) measuring only nitrate and sulfate concentrations is insufficient for proper bioreactor operation, and (iii) alkalinity monitoring should be implemented into protocols for bioreactor management. © American Society of Agronomy, Crop Science Society of America, and Soil Science Society of America. 5585 Guilford Rd., Madison, WI 53711 USA. Source

Hua G.,South Dakota State University | Salo M.W.,South Dakota State University | Schmit C.G.,South Dakota State University | Hay C.H.,Iowa Soybean Association
Water Research | Year: 2016

Woodchip bioreactors have been increasingly used as an edge-of-field treatment technology to reduce the nitrate loadings to surface waters from agricultural subsurface drainage. Recent studies have shown that subsurface drainage can also contribute substantially to the loss of phosphate from agricultural soils. The objective of this study was to investigate nitrate and phosphate removal in subsurface drainage using laboratory woodchip bioreactors and recycled steel byproduct filters. The woodchip bioreactor demonstrated average nitrate removal efficiencies of 53.5-100% and removal rates of 10.1-21.6 g N/m3/d for an influent concentration of 20 mg N/L and hydraulic retention times (HRTs) of 6-24 h. When the influent nitrate concentration increased to 50 mg N/L, the bioreactor nitrate removal efficiency and rate averaged 75% and 18.9 g N/m3/d at an HRT of 24 h. Nitrate removal by the woodchips followed zero-order kinetics with rate constants of 1.42-1.80 mg N/L/h when nitrate was non-limiting. The steel byproduct filter effectively removed phosphate in the bioreactor effluent and the total phosphate adsorption capacity was 3.70 mg P/g under continuous flow conditions. Nitrite accumulation occurred in the woodchip bioreactor and the effluent nitrite concentrations increased with decreasing HRTs and increasing influent nitrate concentrations. The steel byproduct filter efficiently reduced the level of nitrite in the bioreactor effluent. Overall, the results of this study suggest that woodchip denitrification followed by steel byproduct filtration is an effective treatment technology for nitrate and phosphate removal in subsurface drainage. © 2016. Source

Stott D.E.,U.S. Department of Agriculture | Cambardella C.A.,Ames Laboratory | Tomer M.D.,Ames Laboratory | Karlen D.L.,Ames Laboratory | Wolf R.,Iowa Soybean Association
Soil Science Society of America Journal | Year: 2011

Soil quality assessment is a proactive process for understanding the long-term effects of crop and soil management practices within agricultural watersheds. Fields with both well-developed and poor (N-deficient) corn (Zea mays L.) canopy growth were identifi ed within the Iowa River's South Fork Watershed. Our objectives were to quantify several soil quality indicators, including the near-surface soil organic carbon (SOC) content, and determine if the Soil Management Assessment Framework (SMAF) could distinguish between the well-developed and poor corn canopy areas. Four sites, three representing the major soil series in the well-developed canopy areas and one in the poor area, were identifi ed and sampled (0-10 cm) within 50 fi elds. Th ere were no significant diff erences between performance zones when analyzed collectively. Using SMAF indicator scores, SOC, bulk density (D b), water-fi lled pore space (WFPS), electrical conductivity (EC), and microbial biomass carbon (MBC) were significantly lower in the poor canopy areas; however, no single indicator scored significantly less across all 50 fi elds. When separated by landscape position (hilltop, sideslope, toeslope, or depression), only SOC was significantly diff erent between performance zones across each position. Other indicators that diff ered in at least one slope position included D b, WFPS, MBC, EC, P, Fe, Cu, Zn, or potentially mineralizable C. A majority of fi elds had multiple indicators with SMAF ratings at least 0.10 lower in the poor areas than in the corresponding well-developed canopy areas. Soil quality assessment on a fi eld-by-fi eld basis thus provides an approach for identifying potential specific soil-based causes for the poor canopy development. © Soil Science Society of America, 5585 Guilford Rd., Madison WI 53711 USA. All rights reserved. Source

Jones C.S.,Iowa Soybean Association | Schilling K.E.,Iowa Geological and Water Survey
Journal of Environmental Quality | Year: 2011

Fluvial sediment is a ubiquitous pollutant that negatively aff ects surface water quality and municipal water supply treatment. As part of its routine water supply monitoring, the Des Moines Water Works (DMWW) has been measuring turbidity daily in the Raccoon River since 1916. For this study, we calibrated daily turbidity readings to modern total suspended solid (TSS) concentrations to develop an estimation of daily sediment concentrations in the river from 1916 to 2009. Our objectives were to evaluate longterm TSS patterns and trends, and relate these to changes in climate, land use, and agricultural practices that occurred during the 93-yr monitoring period. Results showed that while TSS concentrations and estimated sediment loads varied greatly from year to year, TSS concentrations were much greater in the early 20th century despite drier conditions and less discharge, and declined throughout the century. Against a backdrop of increasing discharge in the Raccoon River and widespread agricultural adaptations by farmers, sediment loads increased and peaked in the early 1970s, and then have slowly declined or remained steady throughout the 1980s to present. With annual sediment load concentrated during extreme events in the spring and early summer, continued sediment reductions in the Raccoon River watershed should be focused on conservation practices to reduce rainfall impacts and sediment mobilization. Overall, results from this study suggest that eff orts to reduce sediment load from the watershed appear to be working. © 2011 by the American Society of Agronomy, Crop Science Society of America, and Soil Science Society of America. Source

Liang X.,Nanjing University | Schilling K.,University of Iowa | Zhang Y.-K.,Nanjing University | Zhang Y.-K.,University of Iowa | Jones C.,Iowa Soybean Association
Water Resources Management | Year: 2016

Daily nitrate-nitrogen (NO3-N) loads in the Raccoon River, Iowa, were estimated using Ordinary kriging (OK), Cokriging (CK), and a standard rating curve method (LOADEST) based on a dataset of 3451 measurements of NO3-N concentration collected over 19 years. The CK estimation utilizes the temporal correlation of NO3-N load with daily discharge and honors the measured points to improve estimation relative to regression based models. Loads were estimated using the observed concentrations and three subsets of the measured data that correspond to three frequencies (weekly, biweekly, and monthly). Results indicated that daily NO3-N loads were best estimated by CK using measured loads with daily discharge. Daily load estimates produced by OK using weekly data matched well with measured values, but discrepancies emerged when samples were collected less frequently, e.g., biweekly and monthly. For the entire 19-year dataset, compared to measured loads, the estimated total NO3-N load decreased using OK when samples were collected monthly, but increased using CK. Load estimation using the seven-parameter LOADEST model did not perform well for the Raccoon River because the correlation of NO3-N concentration to river discharge was poor. For the site studied, weekly and biweekly sampling may be sufficient to estimate daily NO3-N loads with CK when daily discharge data is available. © 2016, Springer Science+Business Media Dordrecht. Source

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