农田土壤氮素渗漏淋失研究进展

对农田土壤氮素淋失的相关研究进行综述和总结是研究农业面源氮素污染的一个至关重要的前提。本文从土壤氮素渗漏淋失形态和迁移机理、氮素渗漏淋失的研究方法和影响土壤氮素渗漏淋失的因素三方面进行了详细的分析介绍,概述了近年来国内外农田氮素渗漏淋失的研究进展和研究成果,并在此基础上展望了未来氮素淋失研究工作的重点。研究结论对农田土壤的水肥管理措施及浅层地下水硝氮污染的减缓有一定的理论和借鉴意义     

宁夏灌区不同类型农田土壤氮素累积与迁移特征

在宁夏灌区选择设施菜田（n=4）和水旱轮作大田（n=4）,通过田间多点取样观测和室内分析的方法,研究了2种类型农田土壤氮素累积与分布特点,以及其迁移对浅层地下水的影响。结果表明,设施菜田0~150 cm土壤剖面溶解性总氮（TSN）、硝态氮（NO3--N）和溶解性有机氮（SON）含量都显著高于大田,前者分别是后者的1.5~5.6、1.5~3.4倍和1.6~9.8倍。设施菜田土壤氮素主要累积在0~5 cm和5~20 cm土层,而大田主要在40~100 cm土体。设施菜田和大田土壤溶解性总氮占全氮比例分别在5.4%~11.5%和2.2%~4.9%之间,前者的淋失风险较高。设施菜田各形态氮素累积量表现为SON＆gt;NO3--N＆gt;NH4＋-N,大田为NO3--N＆gt;SON＆gt;NH4＋-N。设施菜田浅层地下水中TSN、NO3--N和SON含量也都显著高于大田,前者平均含量分别是后者的9.5、13.8倍和7.0倍。因此,硝态氮和溶解性有机氮都是2种类型农田氮素累积的主要形态,也是浅层地下水污染的重要来源。     

有机固废好氧堆肥中氮素转化的研究现状

目前我国有机固废产量大、处理时间长,好氧堆肥是有机固废资源化利用的有效技术手段。氮素转化与损失是影响堆肥质量的关键,降低氮素损失有助于提高堆肥产品的质量。阐述了氮素转化原理,总结了厨余垃圾、剩余污泥及畜禽粪便等有机固废好氧堆肥中氮素转化的研究现状,并对控制氮素损失的研究提出了展望。     

太湖生态模拟系统构建与应用

湖泊生态系统模拟在湖泊富营养化研究中发挥着越来越重要的作用，是湖泊生态生态系统管理的重要手段。湖泊生态系统模型及其相关软件的发展经历了从简单的回归模型、单一的营养盐平衡模型到目前复杂的生态系统动力学模型。本文详细的介绍了湖泊生态模拟的原理、结构框架设计、功能、运行环境及参数等特性，借助太湖有关资料建立了太湖生态系统模拟模型，并对该模型进行了验证分析，验证结果表明该模型在太湖有很好的适应性。     

设施高肥力蔬菜地氮素调控下磷素特征研究

设施蔬菜种植中存在不合理施肥现象,土壤养分严重失调。为了解设施蔬菜地高氮肥力水平下不同氮素水平对磷素的养分吸收影响,2004—2007年在山东寿光进行不同氮素水平调控和秸秆还田试验,并于2007年冬春季进行裂区淋滤试验。结果表明,不同水平的氮素调控影响磷素含量变化,空白（NN）、有机肥（MN）、有机肥＋秸秆（MN＋S）供氮水平下土壤全磷含量逐年下降,降幅NN〉MN〉MN＋S,全磷增幅传统氮素（cN）〉传统氮素＋秸秆（CN＋S）〉氮素优化＋秸秆（SN＋S）〉氮素优化（sN）。CN、CN＋S供氮水平下土壤速效磷含量达到213．7、225．4mg·kg^-1,增长了17．1％、23．5％,磷素累积明显;其他供氮水平下速效磷含量逐年下降,降幅NN〉MN〉MN＋S〉SN＋S〉SN〉CN〉CN＋S,减少氮素供应有利于减缓磷素累积,促进磷的吸收利用。除NN供氮水平下土壤有机磷含量下降外,其他处理均不同程度增加,CN、CN＋S供氮水平下土壤有机磷含量累积明显（308．4、331Amg·ks。）,分别增长了28．5％、38．2％。SN＋S供氮水平下磷的吸收系数（HO,,rrg·100g。）达到了1571,增长了143．6％;CN、CN＋S供氮水平下磷的吸收系数出现了负增长,CN供氮水平下达到了416（P2O5,mg·100g^-1）,下降了35．5％。添加麦秸秆极大地提高了磷的吸收能力,在一定程度上能减缓土壤速效磷的累积。淋溶液中全磷含量SN〉SN＋S,有机磷含量SN〉SN＋S,秸秆还田对阻控有机磷素淋溶有一定的作用,但整个冬春生长季渗滤液中全磷含量在2．6～12．0mg·L^-1,有机磷含量在OA2～4．1mg·L^-1,淋出液水质仍超过了国家安全水质标准。因此,在高肥力水平下进行氮素调控,优化氮素供应量,促进了磷素的吸收利用,对农民在高肥力水平下施肥具有指导意义。建议农民在以后的种植中减少氮肥供应量及添加高碳源秸秆进行还田,以提高肥料的利用率,减少氮磷对土壤及水体的污染。     

盘锦地区稻田田面水氮素动态变化及化学氮肥投入阈值研究

以水稻为供试作物,水稻土为供试土壤,采用田间定位试验的方法,以施肥后田面水中的总氮（TN）、NH4^＋-N和NO3^--N浓度为指标,进行了施氮后田面水中氮素释放规律研究。结果表明,施肥后田面水中的总氮（TN）、NH4＋-N和NO3--N浓度随着施肥量的增加而增加,随着时间的推移三者的浓度呈先上升后下降的趋势,一周后趋于稳定;以氮素表观盈余率和植株吸氮量为指标,从环境安全角度研究水稻生产化学氮肥投入阈值,初步确定试验区环境安全化学氮肥投入阈值为189.22～218.98 kg·hm^-2;以水稻产量为指标,进行了粮食安全氮肥投入阈值研究,初步确定试验区水稻生产粮食安全化学氮肥投入阈值为202.24～288.89 kg·hm^-2。综合考虑粮食安全和环境安全,试验区化学氮肥投入阈值为202.24～218.98 kg·hm^-2。     

不同经营措施对杉木人工林土壤碳库的影响

森林土壤有机碳在陆地生态系统碳循环中发挥着关键作用。以我国亚热带杉木人工林为研究对象,以常绿阔叶林为对照,分析比较了不同经营措施对土壤碳矿化、微生物特征、碳库管理指数的影响。结果表明,与连栽杉木纯林相比,杉木火力楠混交模式和轮栽模式均显著增加了土壤微生物量碳含量、土壤微生物熵、易氧化有机碳和碳库管理指数,提高了土壤微生物对底物的利用效率,土壤易氧化有机碳可作为反映土壤碳库质量的有效指标。     

基于高光谱的土壤重金属含量预测模型建立与评价

研究不同重金属元素的统计特性以及与光谱不同变换形式之间的相关性,通过逐步回归算法和最佳适应值函数F为指标选取最佳波段,运用偏最小二乘回归方法构建了不同变换形式的光谱反射率与重金属含量的反演模型。结果表明:研究区内Zn、Cu和Ni主要受自然因素影响,Cr受外界因素影响程度较大且存在一定的积累现象。不同光谱变换方式的建模精度和预测能力大小有以下关系,光谱对数微分光谱一阶微分光谱倒数微分光谱连续统去除光谱倒数对数原始光谱。采用光谱对数一阶微分建模可以作为反演研究区土壤重金属含量的最佳模型,从而为研究区土壤重金属含量快速监测和大尺度的土壤重金属污染评价提供技术支撑。     

小麦氮素营养效率的研究进展

植物氮营养效率的高低决定着植物氮素吸收利用能力的大小,设法提高作物氮素营养效率是提高氮肥利用率、减少养分资源浪费的重要途径之一.对近年来有关小麦氮素营养效率方面的研究进行了综述,展望了今后开展小麦氮素营养效率方面的研究工作.     

镁盐/矿化垃圾改性对污水污泥产气性能的影响

本文通过建立3个模拟填埋柱,研究考察了原生污水污泥、矿化垃圾改性污泥和镁盐改性污泥的产气性能.研究发现,矿化垃圾改性可大幅度提高污水污泥的生物气产生量.在60d内,原生污水污泥和矿化垃圾改性污泥的累计生物气产生量分别为9.7L/kg污泥和21.3L/kg污泥.而60d内镁盐改性污泥没有生物气产生,其主要原因在于污泥可生物降解性的降低,以及污泥pH的提高.对于规模较大且具备生物气资源化利用的污泥填埋场,可利用矿化垃圾改性以加速填埋气产生,提高能源利用效率.对于规模较小且无生物气收集装置的污泥填埋场则可选择镁盐进行改性,以抑制生物气的产生,降低甲烷排放量.     

Floodplain Trapping and Cycling Compared to Streambank Erosion of Sediment and Nutrients in an Agricultural Watershed

Floodplains and streambanks can positively and negatively influence downstream water quality through interacting geomorphic and biogeochemical processes. Few studies have measured those processes in agricultural watersheds. We measured inputs (floodplain sedimentation and dissolved inorganic loading), cycling (floodplain soil nitrogen [N] and phosphorus [P] mineralization), and losses (bank erosion) of sediment, N, and P longitudinally in stream reaches of Smith Creek, an agricultural watershed in the Valley and Ridge physiographic province. All study reaches were net depositional (floodplain deposition > bank erosion), had high N and P sedimentation and loading rates to the floodplain, high soil concentrations of N and P, and high rates of floodplain soil N and P mineralization. High sediment, N, and P inputs to floodplains are attributed to agricultural activity in the region. Rates of P mineralization were much greater than those measured in other studies of nontidal floodplains that used the same method. Floodplain connectivity and sediment deposition decreased longitudinally, contrary to patterns in most watersheds. The net trapping function of Smith Creek floodplains indicates a benefit to water quality. Further research is needed to determine if future decreases in floodplain deposition, continued bank erosion, and the potential for nitrate leaching from nutrient‐enriched floodplain soils could pose a long‐term source of sediment and nutrients to downstream rivers.     

全球环境变化对土壤有机碳库影响的研究进展

全球环境变化对土壤生态系统有机碳库的影响是当前研究的热点。本文综述了大气CO2浓度升高、温度上升、氮沉降等环境因素变化对土壤有机碳输入与土壤呼吸可能的影响,介绍了关于全球环境变化对土壤有机碳库影响的研究手段及其存在的问题,并就今后研究土壤有机碳对全球变化的响应提出了几点建议。     

Nitrogen mineralization from organic residues: research opportunities

Research on nitrogen (N) mineralization from organic residues is important to understand N cycling in soils. Here we review research on factors controlling net N mineralization as well as research on laboratory and field modeling efforts, with the objective of highlighting areas with opportunities for additional research. Among the factors controlling net N mineralization are organic composition of the residue, soil temperature and water content, drying and rewetting events, and soil characteristics. Because C to N ratio of the residue cannot explain all the variability observed in N mineralization among residues, considerable effort has been dedicated to the identification of specific compounds that play critical roles in N mineralization. Spectroscopic techniques are promising tools to further identify these compounds. Many studies have evaluated the effect of temperature and soil water content on N mineralization, but most have concentrated on mineralization from soil organic matter, not from organic residues. Additional work should be conducted with different organic residues, paying particular attention to the interaction between soil temperature and water content. One- and two-pool exponential models have been used to model N mineralization under laboratory conditions, but some drawbacks make it difficult to identify definite pools of mineralizable N. Fixing rate constants has been used as a way to eliminate some of these drawbacks when modeling N mineralization from soil organic matter, and may be useful for modeling N mineralization from organic residues. Additional work with more complex simulation models is needed to simulate both gross N mineralization and immobilization to better estimate net N mineralized from organic residues.     

SOIL MOISTURE PREDICTION USING SUPPORT VECTOR MACHINES1

ABSTRACT: Herein, a recently developed methodology, Support Vector Machines (SVMs), is presented and applied to the challenge of soil moisture prediction. Support Vector Machines are derived from statistical learning theory and can be used to predict a quantity forward in time based on training that uses past data, hence providing a statistically sound approach to solving inverse problems. The principal strength of SVMs lies in the fact that they employ Structural Risk Minimization (SRM) instead of Empirical Risk Minimization (ERM). The SVMs formulate a quadratic optimization problem that ensures a global optimum, which makes them superior to traditional learning algorithms such as Artificial Neural Networks (ANNs). The resulting model is sparse and not characterized by the “curse of dimensionality.” Soil moisture distribution and variation is helpful in predicting and understanding various hydrologic processes, including weather changes, energy and moisture fluxes, drought, irrigation scheduling, and rainfall/runoff generation. Soil moisture and meteorological data are used to generate SVM predictions for four and seven days ahead. Predictions show good agreement with actual soil moisture measurements. Results from the SVM modeling are compared with predictions obtained from ANN models and show that SVM models performed better for soil moisture forecasting than ANN models.     

Simulating urban waste compost effects on carbon and nitrogen dynamics using a biochemical index

Composting has emerged as a valuable route for the disposal of urban waste, with the prospect of applying composts on arable fields as organic amendments. Proper management of urban waste composts (UWCs) requires a capacity to predict their effects on carbon and nitrogen dynamics in the field, an issue in which simulation models are expected to play a prominent role. However, the parameterization of soil organic amendments within such models generally requires laboratory incubation data. Here, we evaluated the benefit of using a biochemical index based on Van Soest organic matter fractions to parameterize a deterministic model of soil C and N dynamics, NCSOIL, as compared with a standard alternative based on laboratory incubation data. The data included C mineralization and inorganic N dynamics in samples of a silt loam soil (Typic Hapludalf) mixed with various types of UWC and farmyard manure. NCSOIL successfully predicted the various nitrogen mineralization-immobilization patterns observed, but underestimated CO(2) release by 10 to 30% with the less stable amendments. The parameterization based on the biochemical index achieved a prediction error significantly larger than the standard parameterization in only 10% of the tested cases, and provided an acceptable fit to experimental data. The decomposition rates and C to N ratios of compost organic matter varied chiefly according to the type of waste processed. However, 62 to 66% of their variance could be explained by the biochemical index. We thus suggest using the latter to parameterize organic amendments in C and N models as a substitute for time-consuming laboratory incubations.     

Simulation of Daily Flow Pathways,Tile‐Drain Nitrate Concentrations,and Soil‐Nitrogen Dynamics Using SWAT

Tile drainage significantly alters flow and nutrient pathways and reliable simulation at this scale is needed for effective planning of nutrient reduction strategies. The Soil and Water Assessment Tool (SWAT) has been widely utilized for prediction of flow and nutrient loads, but few applications have evaluated the model's ability to simulate pathway‐specific flow components or nitrate‐nitrogen (NO₃‐N) concentrations in tile‐drained watersheds at the daily time step. The objectives of this study were to develop and calibrate SWAT models for small, tile‐drained watersheds, evaluate model performance for simulation of flow components and NO₃‐N concentration at daily intervals, and evaluate simulated soil‐nitrogen dynamics. Model evaluation revealed that it is possible to meet accepted performance criteria for simulation of monthly total flow, subsurface flow (SSF), and NO₃‐N loads while obtaining daily surface runoff (SURQ), SSF, and NO₃‐N concentrations that are not satisfactory. This limits model utility for simulating best management practices (BMPs) and compliance with water quality standards. Although SWAT simulates the soil N‐cycle and most predicted fluxes were within ranges reported in agronomic studies, improvements to algorithms for soil‐N processes are needed. Variability in N fluxes is extreme and better parameterization and constraint, through use of more detailed agronomic data, would also improve NO₃‐N simulation in SWAT. Editor's note : This paper is part of the featured series on SWAT Applications for Emerging Hydrologic and Water Quality Challenges. See the February 2017 issue for the introduction and background to the series.     

A SEDIMENT RESUSPENSION AND WATER QUALITY MODEL OF LAKE OKEECHOBEE1

ABSTRACT: The influence of sediment resuspension on the water quality of shallow lakes is well documented. However, a search of the literature reveals no deterministic mass-balance eutrophication models that explicitly include resuspension. We modified the Lake Okeechobee water quality model - which uses the Water Analysis Simulation Package (WASP) to simulate algal dynamics and phosphorus, nitrogen, and oxygen cycles - to include inorganic suspend. ed solids and algorithms that: (1) define changes in depth with changes in volume; (2) compute sediment resuspension based on bottom shear stress; (3) compute partition coefficients for ammonia and ortho-phosphorus to solids; and (4) relate light attenuation to solids concentrations. The model calibration and validation were successful with the exception of dissolved inorganic nitrogen species which did not correspond well to observed data in the validation phase. This could be attributed to an inaccurate formulation of algal nitrogen preference and/or the absence of nitrogen fixation in the model. The model correctly predicted that the lake is light-limited from resuspended solids, and algae are primarily nitrogen limited. The model simulation suggested that biological fluxes greatly exceed external loads of dissolved nutrients; and sediment-water interactions of organic nitrogen and phosphorus far exceed external loads. A sensitivity analysis demonstrated that parameters affecting resuspension, settling, sediment nutrient and solids concentrations, mineralization, algal productivity, and algal stoichiometry are factors requiring further study to improve our understanding of the Lake Okeechobee ecosystem.     

春玉米产量、氮肥效率及土壤矿质氮对施氮的响应

为了提高氮肥增产效益,减少对环境的污染,通过田间试验研究了施氮量对春玉米产量、氮肥效率及土壤矿质氮的影响。结果表明,施氮量较低时,春玉米籽粒产量随施氮量增加显著增加,当施氮量高于180kg·hm2时,产量保持不变或有减少趋势。氮肥农学利用率、氮素吸收效率、氮素偏生产力和氮收获指数均随着施氮量增加显著降低,氮肥表观利用率和氮肥生理利用率均先增加后降低。从苗期到收获期,施氮处理0～60cm土层硝态氮含量呈现“上升一下降一上升一下降一稳定”的变化趋势,而60～120cm土层硝态氮在春玉米生长后期有增加的趋势。随着土层加深,土壤硝态氮含量呈波浪式下降,施氮量240kg·hm-2和300kg·hm-2处理在60～100cm土层硝态氮含量均显著高于其他处理。随着施氮量增加,0～120cm土层硝态氮累积量显著增加,当施氮量超过240kg·hm-2时,土层中累积的硝态氮存在着较大的淋溶风险。综合考虑产量、氮肥效率和环境效应,179—209kgN·hm。是本试验条件下春玉米的合理施氮量。     

氮沉降对草原凋落物分解的影响

大气氮沉降增加是全球变化的重要现象之一,草原生态系统对氮沉降增加的响应成为草地生态学的研究热点之一。凋落物分解是草原生态系统养分循环和能量流动的主要途径,氮沉降增加引起草原植物群落结构变化,导致凋落物质量、土壤肥力、土壤微生物和土壤动物的变化,最终影响凋落物的分解。本文综述了氮沉降对草原凋落物结构、化学组成和分解环境的影响等方面的国内外最新研究进展,讨论了需进一步加强研究的内容,以期为进一步拓展该领域研究的广度和深度、为全面分析和评估全球变化对草原生态系统的影响提供参考。     

EVALUATION OF Ann AGNPS NITROGEN LOADING IN AN AGRICULTURAL WATERSHED1

ABSTRACT: Pollutants entering a water system can be very destructive to the health of that system. Best Management Practices (BMPs) are used to reduce these pollutants, but understanding the most effective practices is very difficult. Watershed models are an effective tool to aid in the decision‐making process of selecting the BMPs that are most effective in reducing the pollutant loading and are also the most cost effective. The Annualized Agricultural Nonpoint Source Pollution model (AnnAGNPS 2.0) is a technological tool that can be used to estimate watershed response to agricultural management practices. The main purpose of this paper is to test the performance of AnnAGNPS 2.0 on nitrogen loading using comparisons with measurements from the Deep Hollow watershed of the Mississippi Delta Management Systems Evaluation Area (MDMSEA) project. Previous work has demonstrated the capability of the model to simulate runoff and sediment. From sensitivity analyses in this study, initial nitrogen concentration in the soil and crop nitrogen uptake had the most impact on the nitrogen loadings. AnnAGNPS simulations of monthly nitrogen loadings are poor. However, statistical test (t‐test) showed that the predicted nitrogen loading is not significantly different from observed nitrogen loading at the 95 percent level of confidence.