土壤连续属性空间插值方法及其精度的研究进展

作为土壤变化的时空定量监测方法,土壤属性空间插值方法及其精度是计量土壤学和"数字土壤"领域的重要研究内容。文章首先介绍了土壤属性空间插值的常用方法,包括克立格插值法(Kriging)、反距离权重法(IDW)、样条插值法(Spline)、贝叶斯最大熵(BME)、地理加权回归(GWR)以及高精度曲面建模方法(HASM);其次阐述了土壤属性空间插值精度验证的方法和指标;再次总结了能够提高土壤属性插值精度的6种途径,包括合理选择插值方法、准确设定插值方法参数、合理设计采样数目和密度、注意空间自相关程度和范围的影响、科学安排实验分析顺序以及结合辅助信息进行插值;最后从插值方法的选择、验证指标的选取以及辅助信息的结合三个方面指出了土壤属性空间插值方法及其精度的未来研究方向。     

Sea level rise and eelgrass (Zostera marina) production: A spatially explicit relative elevation model for Padilla Bay, WA

The dynamics that govern the elevation of a coastal wetland relative to sea level are complex, involving non-linear feedbacks among opposing processes. Changes in the balance between these processes can result in significant alterations to vegetation communities that are adapted to a specific range of water levels. Given that current sedimentation rates in Padilla Bay, Washington are likely less than historical levels and that eustatic sea level rise is accelerating, the extensive Zostera marina (eelgrass) meadows in the bay may be at risk of eventual submergence. We developed a spatially explicit relative elevation model and used it to project changes in the productivity and distribution of eelgrass in Padilla Bay over the next century. The model is mechanistic and incorporates many of the processes and feedbacks that govern coastal wetland elevation change. Accretion estimates made using ²¹⁰Pb dating of sediment cores, sediment characteristics measured within cores, and eelgrass productivity and decomposition data were used to initialize and calibrate the model. Validation was performed using an elevation change rate measured with a network of surface elevation tables. Both the field data and model simulations revealed a net accretion deficit for the bay. Simulations using current rates of sea level rise indicated an overall expansion of eelgrass within Padilla Bay over the next century as it migrates from the center of the bay shoreward.     

异烟酸-吡唑啉酮光度法测定地表水中氰化物的质量控制指标研究

通过对大量监测数据进行统计分析,获得异烟酸-吡唑啉酮光度法（HJ484—2009）测定水中氰化物质量控制评定指标。研究表明：样品浓度在0．05～0．3mg／L范围内时,建议控制室内相对标准偏差≤3％,室间相对标准偏差≤10％;样品浓度小于等于0．05mg／L时,建议控制相对偏差≤10％;样品浓度大于0．05mg／L时,...     

粒子群优化的RBF瓦斯涌出量预测

瓦斯涌出量是煤矿瓦斯灾害的主要来源,它直接影响煤矿安全生产和经济技术指标。瓦斯涌出量的传统预测方法是将其影响因素线性化后提出的,具有一定的局限性。本文基于群体智能理论,提出了一种基于粒子群算法优化的RBF神经网络瓦斯涌出量预测模型。研究表明RBF神经网络预测精度与网络权值和RBF参数初始值有很大关系,因此本文采用粒子群算法优化RBF网络权值和其他参数,形成PSO-RBF预测模型。该模型通过计算种群粒子的适应度,确定全局最优值,寻找网络参数的最优值。实验结果表明PSO-RBF优于传统的RBF预测模型,训练速度和预测精度显著提高。     

Effects of soil nematodes communities on litter decomposition in urban forest of Dalian北大核心CSCD

In order to further expound the effect of soil nematodes on litter decomposition in urban forest, this study investigated the responses of soil nematodes communities to litter decomposition by litterbags technology at different mesh sizes in Dalian National Forest Park. Soil nematodes community composition, decomposition rate of litter and nutrient release were also analyzed. It found a total of 4 418 nematodes from 39 genera. Higher relative density of soil nematodes was found in the bags with 0.1 mm mesh size (1.55 individuals and 7.34 orders per g of dry litter) compared to the bags with 0.02 mm mesh size (0.21 individuals and 0.49 orders per g of dry litter). There were very few soil nematodes in the 0.02 mm litter bags. Thus we regarded that soil nematodes only affected the 0.1 mm litter bags. The mass loss rates as well as C and P release rates was higher in litter bags with 0.1 mm mesh size than in those with 0.02 mm mesh size, indicating a significant influence of soil nematodes on mass loss and nutrient release. The contribution of soil nematodes to the litter mass loss was about 24%. The effect of soil nematodes on the nutrient release rates differed among elements. The soil nematodes had a bigger influence on the release rate of N than that of other elements, whereas the influence on K release rate was the lowest. The results showed that soil nematodes communities has a significant effect on the litter decomposition and nutrient release of the forest litter in Dalian city, especially promoting the mass loss rates and N release rates.     

ACCURACY AND PRECISION OF NRCS MODELS FOR SMALL WATERSHEDS1

ABSTRACT: In the last 30 years, the National Resource Conservation Service's TR‐55 and TR‐20 models have seen a dramatic increase in use for stormwater management purposes. This paper reviews some of the data that were originally used to develop these models and tests how well the models estimate annual series peak runoff rates for the same watersheds using longer historical data record lengths. The paper also explores differences between TR‐55 and TR‐20 peak runoff rate estimates and time of concentration methods. It was found that of the 37 watersheds tested, 25 were either over‐ or under‐predicting the actual historical watershed runoff rates by more than 30 percent. The results of this study indicate that these NRCS models should not be used to model small wooded watersheds less than 20 acres. This would be especially true if the watershed consisted of an area without a clearly defined outlet channel. This study also supports the need for regulators to allow educated hydrologists to alter pre‐packaged model parameters or results more easily than is currently permitted.     

湖泊水质参数空间最优估计精度分析

在湖泊研究中,往往要了解污染的空间分布状况,其核心是空间最优估计问题.本文在阐述了克立格方差特点的基础上,以太湖为例,对湖泊水质参数空间最优估计的精度问题进行了分析.结果显示,估计精度受变差函数、各采样点的空间配置关系等因素的影响.空间结构直接决定着估计精度的大小,而与各信息采样点的值的大小无关.     

济南市空气质量数值预报研究

在大规模大气环境参数综合野外测试资料的基础上,为在济南市开展大气污染业务预报新近开发了空气质量数值预报模式系统.该系统由污染源模型(SM)、下垫面参数化模型(XDM)、诊断模式(DM)、中尺度-α气象模式(M-αM)、中尺度-β气象模式(M-βM)、行星边界层(PBL)湍流统计量参数化模式(PBLTM)、干湿沉积模式(DWDM)和高分辨化学模式(HRCM)组成.该系统已成功地应用于济南市空气质量数值预报工作,其预报与实测质量浓度之间有很好的一致性,日平均预报准确率可达80%以上.      

提高GPS定位精度的群调度滤波算法*

为解决现行安全生产科技领域中全球定位系统（GPS）/惯性导航系统（INS）融合系统容易产生较大时变误差的关键问题,满足GPS定位信号的精度和信号数据处理时间的要求,提出1种群调度滤波算法,通过实验仿真,分别与模糊算法、机器学习算法及卡尔曼滤波网络算法进行比较研究。结果表明:群调度滤波算法兼顾了定位精度与数据处理时间,具有较大优势,可在航空安全、船舶安全、应急监测、灾后抢险等安全科技领域广泛应用。     

酸性土壤条件下纳米氧化锌长期暴露对蕹菜生长和叶绿素荧光参数的影响

为了探明酸性土壤条件下纳米氧化锌（nano-ZnO）长期暴露对蕹菜的生理生态效应,通过盆栽实验,设置7个浓度系列的nano-ZnO,70 d后测定相对叶绿素含量、生长参数和叶绿素荧光参数。结果显示,随nano-ZnO浓度升高,蕹菜相对叶绿素含量和生长参数先缓慢增加后显著下降。nano-ZnO对蕹菜生物量在根部和冠部间的分配无显著影响。相对叶绿素含量与nano-ZnO浓度呈显著负相关（r=-0.879,p<0.001）。在nano-ZnO质量比为160 mg/kg时,光合有效辐射190μmol/(m²·s)诱导的激发能过剩,但过剩激发能可通过热耗散保护机制消耗,以避免发生光损伤。酸性土壤条件下,弱光诱导的蕹菜叶绿素荧光参数对nano-ZnO长期暴露不敏感,但蕹菜的生物量累积易受nano-ZnO长期暴露的影响。