Manure placement depth impacts on crop yields and N retained in soil

The objective of this study was to determine the impact of manure placement depth on crop yield and N retention in soil. Experimental treatments were deep manure injection (45 cm), shallow manure injection (15 cm), and conventional fertilizer-based management with at least three replications per site. Water infiltration, and changes in soil N and P amounts were measured for up to 30 months and crop yield monitored for three seasons following initial treatment. Deep and shallow manure injections differed in soil inorganic N distributions. For example, in the manure slot the spring following application, NO₃-N in the surface 60 cm was higher (p < .01) when injected 15 cm (21.4 μ g/g) into the soil than 45 cm (11.7 μ g/g), whereas NH₄-N had opposite results with shallow injection having less (p = 0.045) NH₄-N (102 μ g/g) than deep (133 μ g/g) injection. In the fall one year after the manure was applied, NO₃-N and NH₄-N were lower (p = 0.001) in the shallow injection than the deep injection. The net impact of manure placement on total N was that deep injection had 31, 59, and 44 more kg N ha^{? 1} than the shallow injection treatment 12, 18, and 30 months after application, respectively. Deep manure injection did not impact soybean (Glycine max L.) yield, however corn (Zea mays L.) yield increased if N was limiting. The higher corn yield in the deep injected treatment was attributed to increased N use efficiency. Higher inorganic N amounts in the deep injection treatment were attributed to reduced N losses through ammonia volatilization, leaching, or denitrification. Results suggest that deep manure placement in glacial till soil may be considered a technique to increase energy, N use efficiency, and maintain surface and ground water quality. However, this technique may not work in glacial outwash soils due to the inability to inject into a rocky subsurface.     

渠县近5年大气污染特征及预测分析

本文应用污染损害综合指数法,分析了四川省渠县近5年来的大气变化及其危害程度,并运用GM(1,1)模型对渠县未来8年的大气状况作预测。结果表明,渠县大气环境主要污染物为可吸入微粒,其浓度变化呈逐年下降趋势,从2008年开始TSP有明显下降,SO2与NO2含量较低并且比较稳定。通过GM(1,1)模型对渠县空气质量进行预测得知,SO2、NO2逐渐下降,TSP的浓度将大幅度下降,在未来的8年里渠县的空气环境质量得到大幅度的提高。     

天堂河河道治理工程水质改善预测分析

河道治理工程重在改善河道的水质,以恢复河流生态系统。本文以北京市大兴区天堂河河道治理工程为例,介绍了河道治理工程环境影响评价中的水质改善预测分析,首先分析生态需水量和供氧量是否满足河流生态需水要求,后又利用地面水环评助手软件预测了河流水质,预测分析了天堂河水质目标的可达性,旨在为以后的河道治理类工程环境影响评价提供参考。     

流动注射法测定水中阴离子表面活性剂的探讨

本文采用流动注射分析技术在线测定水中阴离子表面活性剂,使用的仪器为德国BRAN＋LUEBBE公司自动分析仪。方法在0.050～0.400mg/L范围内,可以获得较好的线性方程,相关系数〉0.9990,检出限为0.015mg/L,水样的回收率在92%～109%,此方法符合水质测定阴离子表面活性剂的要求。并对影响阴离子表面活性剂测定的因素进行探讨。     

浊漳河山西省潞城市境内段河流生态健康评价研究

浊漳河山西省潞城市境内干流段及南源段河道生态环境目前最突出的问题在于水质恶化、水量减少以及生物多样性衰退。本文从水质、水量、生物状况三个要素出发,通过建立浊漳河潞城市境内河段的水生态健康评价体系,对浊漳南源及干流段进行了生态健康诊断。结果显示,浊漳干流段生态健康总指数36.74,呈生态病态状;南源段生态健康总指数60.03,呈基本健康状态。据此,浊漳河潞城境内段目前的核心问题是生态恢复问题,应当针对其存在的问题选择适当的生态修复模式,采取相应的生态环境管理方法,把生态系统的恢复和重建作为其流域治理的最终目标。     

基于RS和GIS的山东省17城市生态环境质量动态变化研究

运用遥感动态监测与地理信息系统技术相结合的方法,以2005年和2009年遥感解译数据、土地侵蚀数据及环境统计数据为数据源,依据《生态环境状况评价技术规范(试行)》(HJ/T192-2006),对山东省17个城市生态环境质量现状及动态变化趋势进行了评价。结果表明:2009年17个城市生态环境状况指数在59.81～78.08之间,生态环境质量状况总体良好;2005-2009年17城市生态环境状况指数变化值在0.06～3.5之间,生态环境质量状况基本稳定。     

遗传投影寻踪回归在城市环境质量评价中的应用

引入投影降维的思想,将遗传投影寻踪与回归分析技术运用到城市环境质量评价中。将此技术与神经网络方法进行实例比较,投影寻踪回归方法不但可以合理地作出环境质量的综合评价,而且消除了神经网络方法中类别判断不够精确的影响。     

Watershed Regressions for Pesticides (warp) Models for Predicting Atrazine Concentrations in Corn Belt Streams1

Stone, Wesley W. and Robert J. Gilliom, 2012. Watershed Regressions for Pesticides (WARP) Models for Predicting Atrazine Concentrations in Corn Belt Streams. Journal of the American Water Resources Association (JAWRA) 48(5): 970‐986. DOI: 10.1111/j.1752‐1688.2012.00661.x Abstract: Watershed Regressions for Pesticides (WARP) models, previously developed for atrazine at the national scale, are improved for application to the United States (U.S.) Corn Belt region by developing region‐specific models that include watershed characteristics that are influential in predicting atrazine concentration statistics within the Corn Belt. WARP models for the Corn Belt (WARP‐CB) were developed for annual maximum moving‐average (14‐, 21‐, 30‐, 60‐, and 90‐day durations) and annual 95th‐percentile atrazine concentrations in streams of the Corn Belt region. The WARP‐CB models accounted for 53 to 62% of the variability in the various concentration statistics among the model‐development sites. Model predictions were within a factor of 5 of the observed concentration statistic for over 90% of the model‐development sites. The WARP‐CB residuals and uncertainty are lower than those of the National WARP model for the same sites. Although atrazine‐use intensity is the most important explanatory variable in the National WARP models, it is not a significant variable in the WARP‐CB models. The WARP‐CB models provide improved predictions for Corn Belt streams draining watersheds with atrazine‐use intensities of 17 kg/km² of watershed area or greater.     

Comparison of the Performance of Statistical Models in Forecasting Monthly Total Dissolved Solids in the Rio Grande1

Abudu, S., J.P. King, Z. Sheng, 2011. Comparison of the Performance of Statistical Models in Forecasting Monthly Total Dissolved Solids in the Rio Grande. Journal of the American Water Resources Association (JAWRA) 48(1): 10‐23. DOI: 10.1111/j.1752‐1688.2011.00587.x Abstract: This paper presents the application of autoregressive integrated moving average (ARIMA), transfer function‐noise (TFN), and artificial neural networks (ANNs) modeling approaches in forecasting monthly total dissolved solids (TDS) of water in the Rio Grande at El Paso, Texas. Predictability analysis was performed between the precipitation, temperature, streamflow rates at the site, releases from upstream reservoirs, and monthly TDS using cross‐correlation statistical tests. The chi‐square test results indicated that the average monthly temperature and precipitation did not show significant predictability on monthly TDS series. The performances of one‐ to three‐month‐ahead model forecasts for the testing period of 1984‐1994 showed that the TFN model that incorporated the streamflow rates at the site and Caballo Reservoir release improved monthly TDS forecasts slightly better than the ARIMA models. Except for one‐month‐ahead forecasts, the ANN models using the streamflow rates at the site as inputs resulted in no significant improvements over the TFN models at two‐month‐ahead and three‐month‐ahead forecasts. For three‐month‐ahead forecasts, the simple ARIMA showed similar performance compared to all other models. The results of this study suggested that simple deseasonalized ARIMA models could be used in one‐ to three‐month‐ahead TDS forecasting at the study site with a simple, explicit model structure and similar model performance as the TFN and ANN models for better water management in the Basin.     

An Ex Post Evaluation of Ohio’s Great Miami Water Quality Trading Program1

Newburn, David A. and Richard T. Woodward, 2011. An Ex Post Evaluation of Ohio’s Great Miami Water Quality Trading Program. Journal of the American Water Resources Association (JAWRA) 48(1): 156‐169. DOI: 10.1111/j.1752‐1688.2011.00601.x Abstract: Market‐based approaches to address water quality problems have resulted in only limited success, especially in trading programs involving both point and nonpoint sources. We analyze one of the largest point‐nonpoint trading programs – the Great Miami Trading Program in Ohio, administered by the Miami Conservancy District (MCD). Our evaluation focuses on the economic and institutional aspects of the program, including cost effectiveness, efficiency of bidding, transaction costs, trading ratios, and innovation. We use a unique dataset consisting of all bids from agricultural nonpoint sources and interviews of soil and water conservation district (SWCD) agents in the watershed. We find that the MCD’s reliance on county‐level SWCD offices to recruit and advise farmers has been essential to achieve relatively high rates of farmer participation. Additionally, the MCD is able to partly free ride on the administrative costs that SWCD offices receive to assist federal conservation programs, which is helpful to lower costs for a fledgling trading program. However, the involvement of SWCD offices reduced the potential cost savings from the reverse auction structure because some agents were able to learn about the threshold price over the six rounds of bidding and help farmers bid strategically. Overall, the program structure serves as an effective model for future trading programs in other regions that seek to involve agricultural nonpoint sources.