农田土壤质地空间分布的三维随机模拟及其不确定性评价

定量描述土体三维构型对于土地利用及农田水肥管理研究极其重要.本研究根据华北山前冲积平原区一块农田内的109个土壤剖面观测数据,运用马尔科夫地质统计学方法构建了土壤质地种类的三维空间分布模型,在100次随机模拟的基础上,分别得到了土壤质地种类的优化分布图及其概率分布图.结果表明,一维嵌入转移概率模型能很好地描述农田水平和垂直方向上各土壤质地种类的空间连续性及毗邻转移趋势.优化分布图虽能直观反映土壤质地种类的空间分布特征,但存在明显的平滑效应,不能刻画土壤质地种类空间分布的不确定性.而采用概率分布的方式来描述土壤质地种类空间分布的不确定性,能够有效地克服该缺点.     

基于样点个体代表性的大尺度土壤属性制图方法

大空间尺度范围的土壤属性分布信息是陆地表层过程模拟的基础信息.基于野外样点进行空间插值是获得土壤属性空间分布信息的重要手段.现有的空间插值方法通常要求所用样点对研究区土壤属性空间分布规律具有良好的全局代表性.然而,受采样经费和野外采样条件的限制,所采集的样点往往难以全面地反映研究区土壤属性的空间分布规律.基于这样的样点用现有空间插值方法得到的土壤属性分布图通常精度较低,并且由样点全局代表性差带来的推测不确定性也无法得到度量.为了合理利用这些已采集的但全局代表性不好的样点,本文提出了基于样点“个体代表性”推测土壤属性空间分布并度量推测不确定性的方法.该方法在两点环境条件越相似、土壤属性就越相似的假设下,认为每一样点可以代表与其环境条件相似的地区,并且代表程度可以由两点的环境相似度度量;通过分析环境相似度计算推测不确定性,并以环境相似度为权重计算样点可代表地区的土壤属性值.将该方法应用于推测新疆伊犁地区土壤表层有机质含量,经验证,本文方法能够有效地利用全局代表性差的样点推测样点能够代表地区的土壤属性空间分布,并且所得的推测不确定性与预测残差呈现正向关系,能够有效地指示推测结果的可靠程度.     

茶叶中农残分析方法及残留量不确定度评定研究进展

对茶叶农药残留分析中提取方法、净化方法、检测技术以及农药残留量不确定度评定的研究进展进行了综述,并对茶叶农药残留分析的发展趋势进行了展望。     

净辐射通量观测方法及观测精度的不确定性研究

净辐射通量观测方法和观测精度的不确定性已日益被人们所认识和了解,除了各种净辐射通量观测方法自身存在的一些问题外,还涉及太阳辐射表的标定方法（特别是长波辐射表的标定）、各种辐射表的技术指标及正确使用和维护等问题,通过在野外对国产全波段净辐射表（Netpyrradiometer下称净辐射表）和“四路法”（4-waycomponent system)2种常用的净辐射通量观测方法进行对比试验。结果表明,净辐射通量观测精度随时间和天气状况变化有不确定性,温度变化和辐射表防风罩透过光谱的不一致性是导致辐射表测量不确定性的主要原因。     

The Matérn variogram model: Implications for uncertainty propagation and sampling in geostatistical surveys

The Matérn variogram model has been advocated because it is flexible and can represent varied behaviour at small lags. We show how the constraints on the spherical and exponential variogram at short lags ignore a possible source of uncertainty in the variogram and so in kriging surveys, that the Matérn model can describe. Matérn, spherical and exponential variogram models were fitted by maximum likelihood to a set of log₁₀(K) observations made on a regular grid at Broom's Barn Farm, Suffolk, England. The likelihood profiles of the Matérn parameter estimates were asymmetric. Thus the uncertainty of these estimates could only be adequately assessed by a Bayesian approach. The uncertainty of estimated parameters of the Matérn variogram was larger than for the exponential variogram. This is an indication that the assumption of an exponential model limits the behaviour that may be described by the variogram. Thus uncertainty analyses where an exponential variogram is assumed may underestimate the uncertainty of kriged estimates. Bayesian analysis of the kriged estimates of log₁₀(K) at Broom's Barn Farm using the Matérn variogram revealed an observable component of uncertainty due to variogram uncertainty. When an exponential variogram model was used, the estimate of this component of uncertainty was negligible. The Matérn variogram should therefore be used rather than the exponential model when assessing the adequacy of a variogram estimate. A method of designing sample schemes which is suitable for both estimating a Matérn variogram and interpolation is suggested.     

Estimating incidental takes of shearwaters in driftnet fisheries: lessons for the conservation of seabirds

We consider estimation of the magnitude of incidental fisheries ‘bycatch’ for two petrel species, sooty shearwaters (Puffinus griseus) and short-tailed shearwaters (Puffinus tenuirostris). There are clear statistical advantages in estimating bycatch for abundant species such as these, and our results may also guide the conservation and management of rarer species. We used fisheries statistics and observer data to estimate retrospectively the total numbers of sooty and short-tailed shearwaters bycatch in seven large-scale pelagic North Pacific driftnet fisheries between 1952 and 2001. Sensitivity analysis greatly simplified estimation of uncertainty by identifying four driftnet fisheries to be of particular importance in determining the magnitude and precision of the estimated bycatch totals. We estimated that between 1.0 and 12.8 million (95% CI) sooty shearwaters were killed by driftnets between 1952 and 2001. For short-tailed shearwaters we estimated between 4.6 and 21.2 million (95% CI) over the same period. More precise estimation was hampered by the paucity of available observer data, lack of reported detail and inconsistencies among data sources. Estimates may be strongly biased because some dead birds are misidentified or drop out of nets before hauling, or because some records were of live captures that were subsequently released. Improved estimation of overall take and its impact on populations of seabirds requires standardisation of reporting, allowance for potential sampling bias, as well as a clearer definition of the sampling unit and underlying bycatch probability distribution model, and knowledge of potential compensatory changes in population parameters.     

Uncertainties in up-scaling N2O flux from field to 1°×1° scale: A case study for Inner Mongolian grasslands in China

Since N₂O emissions cannot be measured easily at large scales, global emission estimates inevitably involve problems with scaling. To date, up-scaling processes depend highly on the models and database. Because of the limitation in resolution of the databases, which provide input parameters to drive the model's regional simulations, the uncertainties generated from the up-scaling processes must be quantified. In this paper, the uncertainties in up-scaling N₂O emissions from the field scale (∼1 km²) to 1°×1° scale (∼10,000 km²) were quantified in a case study from the Xilin River basin of Inner Mongolia, China. A revised process-based DNDC model was applied in the study for quantifying N₂O fluxes with a high-resolution (1 km²) soil database constructed with remote sensing data and GIS technique. The results showed that the uncertainties coming from spatial scaling effect is 63.6%, and from the partitioning of sensitive model parameter (SOC) is 86.4%. We found that inclusion of spatial heterogeneity of soil factors resulted in lower regional N₂O emission estimates. Utilization of the spatial structural information based on soil type was more effective for reducing the spatial scaling effect in comparison with the variability information calculated from Monte Carlo method.     

Evaluation method dependency of measured saturated hydraulic conductivity

Saturated hydraulic conductivity (Ks) is one of the most important hydraulic properties affecting water flow in soils. Spatial and seasonal variability as well as scale dependency are key factors which make it more difficult to accurately measure the saturated hydraulic conductivity. The uncertainty of the Ks values due to different evaluation methods was investigated using raw measured data obtained on two different Hungarian soils with three different in situ measuring devices (double ring, tension disc and mini disc infiltrometers), as well as with two laboratory methods. Since the very same raw infiltration data could result in significantly different Ks values, we have introduced the evaluation method dependency of the measured Ks values. Our investigations found that the effect of the applied evaluation method for assessing raw measured data can be just as significant as the effect of other factors, such as the scale effect, as well as the spatial and temporal variability.     

小麦水分含量测量不确定度的分析评定

[目的]分析评定小麦水分含量的测量不确定度.[方法]分析了测定小麦水分含量测量不确定度的来源,采用GB 5009.3-2010标准方法测定小麦水分含量,并对测量不确定度的影响因素进行分析.[结果]通过分析评定测定结果的不确定度,得出小麦水分含量测定结果扩展不确定度为0.03％.[结论]在小麦水分含量测量不确定度评定时,重复测量小麦水分含量是影响其测量不确定度的主要因素.     

气相色谱法测定大米中马拉硫磷的不确定度评定

[目的]对气相色谱法测定大米中马拉硫磷的不确定度进行评定.[方法]建立了气相色谱法测定大米中马拉硫磷的测量不确定的数学模型,分析了不确定度的主要来源,对该方法所得结果的已识别来源的不确定度进行评价,并计算相对合成不确定度和相对扩展不确定度.[结果]该研究测定过程所产生的测量不确定度主要来源于回收率和重复性试验,其他因素影响很小,用该法测得大米中马拉硫磷含量为0.008 58 mg/kg,扩展不确定度为0.000 51 mg/kg(95％,k=2).[结论]该评价方法及结果对提高马拉硫磷检测数据的可靠性与准确性有一定的指导意义.