基于PCA-SOM的北京市平谷区地下水污染溯源

为了解北京市平谷区地下水污染物来源,以平谷区2010—2018年监测数据为基础,使用PCA(主成分分析法)识别了地下水水质指标因子,使用自组织映射识别了污染物的空间分布.结果表明:通过监测指标间的Pearson检验发现, 平谷区地下水电导率与ρ(Ca2+)(p=0.936)、总碱度与ρ(HCO₃2-)(p=0.981)、ρ(Mg2+)与总硬度(p=0.944)指标之间显著相关.地下水化学类型主要以HCO₃-Ca型为主,其次为HCO₃-Mg型.NH₄+、SO₄2-、Cd、Fe(Ⅱ)、NO₂指标空间分布离散性和差异性较大,存在局部富集现象.通过因子分析法筛选出影响平谷区地下水水质的8个公因子,首要影响因子为溶滤-富集作用(贡献率为22.398%),次要影响因子为农业、养殖业和填埋场等人为活动作用(贡献率为16.533%),雨水下渗作用(贡献率为8.035%)、工业源人为活动(贡献率为7.466%)对地下水也有一定影响.通过比较各指标的SOM(Self-Organizing Map,自组织映射)特征图像和监测井映射特征图像,发现NH₄+受山前地带林业、种植业和平原地带农业、养殖业的双重影响,Na+、Mn受平原地带人为活动的影响;同时,NH₄+、NO₃-、NO₂三者之间及Fe(Ⅱ)与Fe(Ⅲ)之间来源不同,Cd、Al、氰化物三者具有同一来源.研究显示,PCA-SOM(PCA与SOM相结合)可以对地下水化学组分来源进行定性识别与定量分析.      

Review of the remediation strategies for soil water repellency

Many regions of the world are predicted to experience water scarcity due to more frequent and more severe droughts and increased water demands. Water use efficiency by plants can be negatively affected by soil water repellency (SWR). It is timely to review existing techniques to remedy SWR. Ideally remediation addresses the origins of a problem. However, the fundamental mechanisms of how and why SWR develops are still poorly understood. In this review it was hypothesized that SWR occurs where the balance of input-decomposition of organic matter is impaired, due to either increased input or decreased decomposition rates of hydrophobic substances. Direct and indirect strategies to remedy SWR were distinguished. While direct remediation aims at abolishing the causes of SWR, indirect strategies seek to manage sites with SWR by treating its symptoms. The 12 reviewed strategies include applying surfactants, clay, slow-release fertilizers, lime, and fungicides, bioremediation of SWR through stimulating earthworms, choosing adapted vegetation, irrigation, cultivation, soil aeration and compaction. Some of the techniques have been applied successfully only in laboratory experiments. Our review highlights that it is not straightforward to cure SWR based on easily measurable and site-specific soil and vegetation properties, and that long-term, large-scale field experiments are required to improve the understanding of the evolution of SWR as cornerstone to develop cost-effective and efficient remediation strategies. We also identified current research gaps around the diagnosis and prevention of SWR.     

文本聚类算法的分析与比较

聚类是一种重要的文本信息处理方法,文章介绍了常用的文本聚类算法,从这些算法的适用范围、初始参数的影响、终止条件以及对噪声的敏感性等方面对它们进行了分析与比较.对文本聚类算法的应用有一定的指导意义.     

Integrating soil carbon cycling with that of nitrogen and phosphorus in the watershed model SWAT: Theory and model testing

In this paper we describe and test a sub-model that integrates the cycling of carbon (C), nitrogen (N) and phosphorus (P) in the Soil Water Assessment Tool (SWAT) watershed model. The core of the sub-model is a multi-layer, one-pool soil organic carbon (S_C) algorithm, in which the decomposition rate of S_C and input rate to S_C (through decomposition and humification of residues) depend on the current size of S_C. The organic N and P fluxes are coupled to that of C and depend on the available mineral N and P, and the C:N and N:P ratios of the decomposing pools. Tillage explicitly affects the soil organic matter turnover rate through tool-specific coefficients. Unlike most models, the turnover of soil organic matter does not follow first order kinetics. Each soil layer has a specific maximum capacity to accumulate C or C saturation (S_x) that depends on texture and controls the turnover rate. It is shown in an analytical solution that S_x is a parameter with major influence in the model C dynamics. Testing with a 65-yr data set from the dryland wheat growing region in Oregon shows that the model adequately simulates the S_C dynamics in the topsoil (top 0.3 m) for three different treatments. Three key model parameters, the optimal decomposition and humification rates and a factor controlling the effect of soil moisture and temperature on the decomposition rate, showed low uncertainty as determined by generalized likelihood uncertainty estimation. Nonetheless, the parameter set that provided accurate simulations in the topsoil tended to overestimate S_C in the subsoil, suggesting that a mechanism that expresses at depth might not be represented in the current sub-model structure. The explicit integration of C, N, and P fluxes allows for a more cohesive simulation of nutrient cycling in the SWAT model. The sub-model has to be tested in forestland and rangeland in addition to agricultural land, and in diverse soils with extreme properties such high or low pH, an organic horizon, or volcanic soils.     

Simulating soil organic matter with CQESTR (v. 2.0): Model description and validation against long-term experiments across North America

Soil carbon (C) models are important tools for examining complex interactions between climate, crop and soil management practices, and to evaluate the long-term effects of management practices on C-storage potential in soils. CQESTR is a process-based carbon balance model that relates crop residue additions and crop and soil management to soil organic matter (SOM) accretion or loss. This model was developed for national use in U.S and calibrated initially in the Pacific Northwest. Our objectives were: (i) to revise the model, making it more applicable for wider geographic areas including potential international application, by modifying the thermal effect and incorporating soil texture and drainage effects, and (ii) to recalibrate and validate it for an extended range of soil properties and climate conditions. The current version of CQESTR (v. 2.0) is presented with the algorithms necessary to simulate SOM at field scale. Input data for SOM calculation include crop rotation, aboveground and belowground biomass additions, tillage, weather, and the nitrogen content of crop residues and any organic amendments. The model was validated with long-term data from across North America. Regression analysis of 306 pairs of predicted and measured SOM data under diverse climate, soil texture and drainage classes, and agronomic practices at 13 agricultural sites having a range of SOM (7.3–57.9 g SOM kg⁻¹), resulted in a linear relationship with an r² of 0.95 (P < 0.0001) and a 95% confidence interval of 4.3 g SOM kg⁻¹. Using the same data the version 1.0 of CQESTR had an r² of 0.71 with a 95% confidence interval of 5.5 g SOM kg⁻¹. The model can be used as a tool to predict and evaluate SOM changes from various management practices and offers the potential to estimate C accretion required for C credits.     

长期施肥对土壤有机质积累的影响

20年的NPK施肥定位试验,有利于深刻揭示土壤肥力特征与营养平衡规律。以位于黄淮海平原的中国科学院禹城综合试验站为例,探讨和估算了长期定量施肥对冬小麦（TriticuspaestvumL．）、夏玉米（ZeaMaysL．）生长和土壤有机质（SOM）的影响。结果表明,长期的N、P肥配施或N、P、K均衡施肥,可显著增加SOM储量,并且后者要优于前者;SOM增加主要集中在0-20cm深度的土层,40-60cm基本不变;生物量对SOM储量变化影响明显,NPK,NP处理作物生长良好,作物残体输人明显优于其他处理;0-40cm可以代表该区用以计算土壤固碳潜力,并且在N、P、K均衡施肥条件下,0-40cm土层中SOM储量长期以来持续增加,并未达到上限,每年的平均固碳速率（以C计）达182．8kg·hm-1,约是全球平均水平的1．5倍,全国平均水平的1．1倍。华北平原若按N、P、K均衡施肥,农田土壤每年固碳潜力将达到1．6-2．4Tg·a-1。     

利用PARAFAC及SOM研究不同来源及粒径胶体的三维荧光光谱特征

利用三维荧光光谱法(3D-EEM)结合平行因子分析(PARAFAC)和自组织神经网络分析(SOM),解析了不同来源水体中不同粒径胶体的荧光特性,同时与挑峰法进行比较,以期寻找一种更好的分析天然胶体来源、粒径、荧光特性间关系的方法.基于PARAFAC模型,研究区水体中不同粒径胶体共解析出2个类腐殖质荧光峰(C1和C3)及3个类蛋白荧光峰(C2、C4和C5).其中,300 k Da~1μm分级胶体荧光强度最高,C1、C2、C3组分的荧光强度随粒径增大而增强,C4、C5组分的荧光强度随粒径增大而减弱.不同来源胶体(生活污水:进水和出水;农业污水:大盈和天恩桥;天然水体:吴淞口)的荧光强度变化大致规律为:吴淞口进水大盈天恩桥出水.SOM分析结果与PARAFAC一致,且可视化程度更高,但EEM-SOM模型存在输入变量多、兼具挑峰法缺点的问题.而PARAFAC-SOM模型不仅兼具了前两者的优点,还具有输入变量少、运行时间短、可靠性高等优点.同时,该模型还成功应用于胶体其他理化参数的分析(Parameters-SOM模型),使得前期工作结果系统性更强、更直观.因此,PARAFAC-SOM模型是相对较好的分析天然胶体来源、粒径、荧光特性间关系的方法.     

Evidence for the Stepwise Behavioral Response Model (SBRM): the effects of Carbamate Pesticides on medaka (Oryzias latipes) in an online monitoring system

The Stepwise Behavioral Response Model (SBRM), which is a conceptual model, postulated that an organism displays a time-dependent sequence of compensatory Stepwise Behavioral Response (SBR) during exposure to pollutants above their respective thresholds of resistance. In order to prove the model, in this study, the behavioral responses (BRs) of medaka (Oryzias latipes) in the exposure of Arprocarb (A), Carbofuran (C) and Methomyl (M) were analyzed in an online monitoring system (OMS). The Self-Organizing Map (SOM) was utilized for patterning the obtained behavioral data in 0.1 TU (Toxic Unit), 1 TU, 2 TU, 5 TU, 10 TU and 20 TU treatments with control. Some differences among different Carbamate Pesticides (CPs) were observed in different concentrations and the profiles of behavior strength (BS) on SOM were variable depending upon levels of concentration. The time of the first significant decrease of BS (SD-BS) was in inverse ratio to the CP concentrations. Movement behavior showed by medaka mainly included No effect, Stimulation, Acclimation, Adjustment (Readjustment) and Toxic effect, which proved SBRM as a time-dependence model based on the time series BS data. Meanwhile, it was found that SBRM showed evident stress-dependence. Therefore, it was concluded that medaka SBR was both stress-dependent and time-dependent, which supported and developed SBRM, and data mining by SOM could be efficiently used to illustrate the behavioral processes and to monitor toxic chemicals in the environment.     

The formation and fate of chlorinated organic substances in temperate and boreal forest soils

Background, aim and scope  Chlorine is an abundant element, commonly occurring in nature either as chloride ions or as chlorinated organic compounds (OCls). Chlorinated organic substances were long considered purely anthropogenic products; however, they are, in addition, a commonly occurring and important part of natural ecosystems. Formation of OCls may affect the degradation of soil organic matter (SOM) and thus the carbon cycle with implications for the ability of forest soils to sequester carbon, whilst the occurrence of potentially toxic OCls in groundwater aquifers is of concern with regard to water quality. It is thus important to understand the biogeochemical cycle of chlorine, both inorganic and organic, to get information about the relevant processes in the forest ecosystem and the effects on these from human activities, including forestry practices. A survey is given of processes in the soil of temperate and boreal forests, predominantly in Europe, including the participation of chlorine, and gaps in knowledge and the need for further work are discussed. Results  Chlorine is present as chloride ion and/or OCls in all compartments of temperate and boreal forest ecosystems. It contributes to the degradation of SOM, thus also affecting carbon sequestration in the forest soil. The most important source of chloride to coastal forest ecosystems is sea salt deposition, and volcanoes and coal burning can also be important sources. Locally, de-icing salt can be an important chloride input near major roads. In addition, anthropogenic sources of OCls are manifold. However, results also indicate the formation of chlorinated organics by microorganisms as an important source, together with natural abiotic formation. In fact, the soil pool of OCls seems to be a result of the balance between chlorination and degradation processes. Ecologically, organochlorines may function as antibiotics, signal substances and energy equivalents, in descending order of significance. Forest management practices can affect the chlorine cycle, although little is at present known about how. Discussion  The present data on the apparently considerable size of the pool of OCls indicate its importance for the functioning of the forest soil system and its stability, but factors controlling their formation, degradation and transport are not clearly understood. It would be useful to estimate the significance and rates of key processes to be able to judge the importance of OCls in SOM and litter degradation. Effects of forest management processes affecting SOM and chloride deposition are likely to affect OCls as well. Further standardisation and harmonisation of sampling and analytical procedures is necessary. Conclusions and perspectives  More work is necessary in order to understand and, if necessary, develop strategies for mitigating the environmental impact of OCls in temperate and boreal forest soils. This includes both intensified research, especially to understand the key processes of formation and degradation of chlorinated compounds, and monitoring of the substances in question in forest ecosystems. It is also important to understand the effect of various forest management techniques on OCls, as management can be used to produce desired effects.     

荧光溶解性有机质EEMs的新旧自组织映射图解析方法比较研究

目前,对地表水体荧光溶解性有机质(Fluorescent Dissolved Organic Matter,FDOM)三维激发发射矩阵(Excitation-Emission Matrices,EEMs)数据的解析仍旧存在挑战.本文结合原始EEMs和从中分离的荧光平行因子分析(Parallel Factor Analysis,PARAFAC)组分,利用自组织映射图(Self-Organizing Maps,SOM),开展了基于传统EEMs-SOM和新型PARAFAC-SOM神经网络模型的复杂荧光数据解析能力对比研究,以此探索和改进EEMs多元解析方法技术体系.模型以已发表论文原始数据为基础构建,研究对象为南太湖重要入湖河流东苕溪水系.结果显示:EEMsSOM模型需依赖常规"摘峰法"对各荧光峰做出主观判断,不能有效识别重叠荧光峰,且人为割裂多激发共发射荧光物质峰之间的联系,从而弱化分析结果的实际环境意义,但神经元的模式荧光光谱可视化效果较佳,且操作简便,耗时较少;PARAFAC-SOM模型克服了上述缺陷,可清除EEMs中的噪声或无用信息,大幅降低输入变量数(从1742个降至4个),缩减运算时间,较大地改善了输出结果的准确性,获得无损可靠且实际环境意义较强的结果,但该法的PARAFAC预处理要求较高,工作量较大;两类模型解析结论大体一致,对前期研究进行了全新的阐述和补充,且生动揭示了FDOM在多级河流水体中的空间赋存变化规律及河流的动态污染过程.综上,推荐在今后研究中综合使用两类优势互补的模型以实现对EEMs的深度解析.