中子仪测定砂性土壤水分的标定与测试参数的界定分析

以科尔沁沙地6个砂性土壤试验点为研究对象,实施中子水分仪测试土壤水分的标定试验,采用点聚图筛选和三点平滑处理土壤体积含水率数据,选用线性标定和非线性标定2种形式,系统分析中子仪计数时间、中子管安装稳定时间以及降雨、灌水等提高土壤含水率的方法对标定结果的影响,以界定中子仪的测试参数,经模拟与验证,确定砂性土壤的中子仪标定方程。结果表明：砂性土壤0-30cm表土采用二项式标定效果相对较好;砂土土质对中子仪读数影响较小,两种不同含水率的土壤可以统一标定;中子管安装稳定时间至少需7d,尤以经历一、两场较大降雨后进行标定其试验误差较小;标定和测量实施过程中,中子仪计数时间宜选用64s,再适当加大计数时间也能得到较好结果;在较大降雨和干旱两种状态下,选用64s中子仪计数时间进行测量,可得到砂性土壤测量水分范围为1.01%～29.92%且精度较高的标定方程。验证结果表明,中子仪测量结果能反映实际土壤含水量的分布状况,标定方程精度可满足实际测试要求。     

Use of overlap studies to evaluate method changes in water chemistry protocols

Long-term monitoring projects are usually plagued with method changes that occur in the midst of the monitoring record. Such changes can affect the data, resulting in observations of long-term trends that reflect the change in methods rather than the monitored system. This article describes two statistical approaches to evaluate the effect of method changes, illustrated by several examples from the U.S. Environmental Protection Agency's Long-Term Monitoring Project, a study of the effects of acidic deposition on surface water chemistry. Structural regression models or paired t-tests were applied to various overlapping datasets to determine whether statistically significant differences existed between methods. Statistically significant differences between method changes were seen for each of the following: different filter types, a change in anion analysis from colorimetric to ion Chromatographic techniques, and a change in sample collection method from an integrated hose sampler to a Kemmerer sampler. The characteristics under which each statistical approach was applied are discussed, as are considerations regarding calibration of the older portions of the data.     

Using power priors to improve the binomial test of water quality

To assess violations of water quality standards, measurements of water quality are collected on a regular basis over a period of time, and are then analyzed to evaluate the percentage of samples exceeding the standard. The challenge to the assessor is that often only a limited amount of data are used to determine if the stream is violating standards. Current assessment uses just the data for a period of two years. To address this issue, we present a Bayesian approach using power priors to incorporate historical information in decision-making. We demonstrate a modified power prior approach and discuss its properties under a binomial model. Exact error probabilities are compared using three approaches: a power prior approach to the binomial test, a Bayesian binomial test with noninformative prior, and a frequentist binomial test. Two examples are presented to illustrate the implementation of the power prior and its differences with alternative binary methods in water quality assessment.     

Use of a surface gamma-neutron gauge for in situ measurement of changes in bulk density of the tilled zone

Short-term temporal changes in bulk density and related soil-water properties of a tilled soil may appreciably influence the processes of infiltration, soil water storage, runoff and erosion. Using a properly-calibrated surface gamma-neutron gauge, the changes in bulk density and moisture content within the topsoil layer can be measured in situ and at a large number of locations, with a minimum amount of time and expense. In this study on a Bernow loam soil (Typic Paleudult), factory calibration for either the neutron or the gamma component of a Troxler gauge was found unsatisfactory when compared with soil cores. Field calibration was obtained for both these components. Two different methods tried for gamma calibration gave satisfactory and nearly the same results. These findings generally agreed with the results for two other soils, whose data were available from an earlier study. Using field calibrations, soil bulk density was measured weekly at several sites within 4 freshly-tilled plots, one left bare, two planted to corn and one to soya bean, in depth intervals of 0–10, 10–20 and 20–30 cm. The plots were irrigated 3 days before each measurement. Over a 15-week period, the major changes in bulk density occurred only within the 0–10-cm layer, and these changes were strongly correlated with the amount of water applied. The presence of crops did not significantly influence these changes measured in the interrow areas. However, some additional data in the 0–10-cm layer indicated that roots may modify soil bulk density in the crop row and interrow areas differently. Measurements of this type serve to provide important information for improving soil and water management.     

The conversion of permittivity as measured by a PR2 capacitance probe into soil moisture values for Des Moines lobe soils in Iowa

Measurement of soil moisture is essential for irrigation scheduling and capacitance sensors have been widely used to monitor soil moisture at different depths. Two approaches for converting permittivity measures using the capacitance probe (PR2, Delta‐T Devices) to soil water content are to (a) use the default equation and parameters provided by the manufacturer, and (b) use site specific calibration equations. The objective of this study was to evaluate the performance of the manufacturer’s default equation and in‐situ calibrated equations for estimating soil water content. Permittivity measurement using the PR2 probe coincided with soil sampling during the growing seasons in 2006, 2007 and 2008 for Des Moines lobe soils in north‐central Iowa. The default equation provided by Delta‐T Devices for the PR2 probe estimated the soil water content for 3 years with an average root mean square error (RMSE) and index of agreement (IoA) values of 0.097 cm³/cm³ and 0.587, respectively. The default equation was calibrated by a 1‐year (2006) and a 2‐year (2006 + 2007) data set. The resultant statistics indicate that site specific calibration gives more accurate estimates of soil water content compared to the uncalibrated default equation. Three‐year averaged RMSE and IoA values were 0.049 cm³/cm³ and 0.742 for equations calibrated by the 1‐year data set, and 0.034 cm³/cm³ and 0.807 for equations calibrated by the 2‐year data set. The results from this study indicate that a site specific calibration is necessary for the PR2 probe, and equations calibrated by data from a longer period performed better than data from a shorter period. Where a site‐specific field calibration cannot be applied, coefficients are provided for various cropping systems in Des Moines Lobe soils of Iowa based on the results from this study.     

东辽河流域吉林省境内的径流模拟研究

以东辽河吉林省境内河段为研究对象,采用SWAT分布式水文模型对东辽河泉太水文站进行径流模拟,模型采用2006—2008年实测的逐月径流资料进行参数的率定,并以2009—2010年为模型的验证期,分析对水文过程影响较大的因素、模型的模拟精度及对研究区的适用性。结果表明:泉太水文站率定期与验证期径流的模拟值与实测值总体上拟合较好,率定期与验证期径流模拟的相关系数（R²）均大于0.6,Nash-Suttclife效率系数（E_ns）均大于0.75,相对误差（R）均小于30%。验证期的月径流模拟相对误差较率定期小,且相关系数R²、效率系数均大于0.9,降雨是径流的重要影响因素,月径流模拟值与年内的降雨过程存在较好的正相关性,且率定期相关性较验证期相关性大。应用率定后的参数在SWAT模型中进行径流模拟的结果较好,精度较高。将SWAT模型应用于东辽河吉林省段的径流过程模拟,具有较强的适用性。     

Estimating the Health Impact of Climate Change With Calibrated Climate Model Output

Studies on the health impacts of climate change routinely use climate model output as future exposure projection. Uncertainty quantification, usually in the form of sensitivity analysis, has focused predominantly on the variability arise from different emission scenarios or multi-model ensembles. This paper describes a Bayesian spatial quantile regression approach to calibrate climate model output for examining to the risks of future temperature on adverse health outcomes. Specifically, we first estimate the spatial quantile process for climate model output using non-linear monotonic regression during a historical period. The quantile process is then calibrated using the quantile functions estimated from the observed monitoring data. Our model also down-scales the gridded climate model output to the point-level for projecting future exposure over a specific geographical region. The quantile regression approach is motivated by the need to better characterize the tails of future temperature distribution where the greatest health impacts are likely to occur. We applied the methodology to calibrate temperature projections from a regional climate model for the period 2041 to 2050. Accounting for calibration uncertainty, we calculated the number of excess deaths attributed to future temperature for three cities in the US state of Alabama.     

The use of inverse modelling and dipwell data in the calibration and evaluation of a soil water simulation model

The soil water regime is a key component of the current UK land evaluation systems. However, direct quantification requires many years of measurements which are not available for large parts of the country. One method for extending existing data is through the use of soil water simulation models. A physically based, one-dimensional soil water simulation model (SOIL) was calibrated against relatively easily obtained dipwell, soil water retention and saturated hydraulic conductivity data for eight relatively level sites in Scotland with limited potential for lateral flow. However, the calibration was only possible through the use of an inverse modelling procedure to select a matric potential which gave a ‘best-fit' to the appearance of saturated conditions in the dipwells. The calibrated model was subsequently able to accurately predict the fluctuations in the perched watertable to within one depth class in five soil profiles and only slightly greater than one depth class in the remainder. The technique offers the potential to extrapolate from a limited period of measured soil watertable data. However, care is needed as there were additional errors associated with the restrictions imposed by the model, by the input data and due to the nature of the calibration data.     

Performance of a distributed semi-conceptual hydrological model under tropical watershed conditions

Conceptual rainfall-runoff models at the watershed scale are useful tools for assisting in managing and planning water resources, making it possible to estimate streamflow and to predict hydrologic impacts due to land-use changes. The objective of this study was to calibrate and to validate the LAvras Simulation of Hydrology (LASH Model) (Beskow, 2009) in a Brazilian Tropical Watershed for daily streamflow. LASH is a continuous, distributed, semi-physically based model for simulation of different hydrologic components on a daily basis. The Shuffled Complex Evolution (SCE-UA) global search method was used with the LASH model in order to optimize model parameters that were found to be the most sensitive or not directly measurable. The LASH model was calibrated over a 2-year period, thereafter, the parameters obtained through the calibration were kept constant for the validation step using a different period of time from that analyzed during the calibration. The Nash–Sutcliffe coefficient (C_NS) values found were 0.820 and 0.764 during calibration and validation, respectively, whereas, the C_NS (log Q) values equal to 0.821 and 0.770 were obtained for the same periods. The SCE-UA method was found to be an efficient algorithm for searching ‘optimal’ model parameter values. It was possible to conclude that the model has a great potential for being applied in generating the long-term streamflow as well as flow-duration curves. Therefore, the model can reliably be applied under tropical conditions of this medium-sized watershed or other similar watersheds, thus making it useful to plan the sustainable development of similar tropical and subtropical watersheds.     

Modelling hydrology and sulphate concentration in small catchments in Central Ontario

The Birkenes-Storgama model of hydrology and streamwater chemistry which was modified by Seipet al. (1985) to simulate data for the Harp Lake #4 sub-catchment was applied to the Harp Lake #3, #4, and #6 sub-catchments for the 1980 to 1984 period. The model was roughly calibrated using a readily available optimization procedure on a relatively limited suite of model parameters. The calibration period was much shorter (8 mo for the hydrology sub-model and 12 mo for the sulphate sub-model) and the confirmation period longer (about 3 yr) than used previously. A statistical assessment indicates that the hydrology sub-model performs with good reliability over the confirmation period, and the sulphate sub-model performs fairly well. The need for modification to the sulphate sub-model may be indicated. An important result is that the Birkenes-Storgama model can be applied at new temporal and spatial locations without extensive calibration, and produce useful simulations.     

Trend detection in water quality time series of LRTAP-Quebec network lakes

After 5 yr of monitoring the LRTAP-Québec network lakes, time series having 25 to 30 values each for 5 water quality parameters or combinations of parameters, for 12 temporal lakes, were investigated in terms of trend detection capability. Their persistence and seasonality were determined, then the appropriate trend detection test was applied. Lakes of regions 2 and 3 in the eastern part of the network show patterns that indicate acidification from 1982 to 1985 followed by a slight recovery from 1985 to 1988 with a return to higher lakewater sulphate concentrations in 1988. In region 1 (eastern part of the network), there is evidence of acidification from 1982 to 1985 followed by a leveling off of sulphate and alkalinity values from 1985 to 1988. Lakes situated in regions 4 and 5 (western part of the network) show signs of recovery from acidification. For the series with neither persistence nor periodicity (as were most of the alkalinity series), trends were detected close to the original assumptions (i.e. one standard deviation) using the Kendall test. Series with seasonality only (such as most of the nitrate series) allow trend detection below one standard deviation, using the Seasonal Kendall test. Series with persistence only (sulphates for example), tested with the Spearman/Lettenmaier test, or both persistence and seasonality (some of the nitrate series), tested with the Hirsch and Slack test, allow trend detection above 1.5 and 2.5 standard deviations respectively. Work on a calibrated watershed weekly time series shows that even if the sampling frequency is doubled, the information content increases by 10 to 25% only. The trend to standard deviation ratio decreases much the same way. Thus, the network design seems to be appropriate for detecting trends with a trend to standard deviation ratio of 1 after 7 to 10 yr of operation with a confidence level (1-α) and a power of the test (1-Β) of 90%, respectively.     

Identifying declines in waterbirds: The effects of missing data, population variability and count period on the interpretation of long-term survey data

To manage and conserve wildlife populations effectively it is necessary to use methods that identify the often non-linear trends in populations, have an inbuilt assessment of trend quality and can analyse count data from a range of spatial scales. We present a method of trend analysis using generalised additive models. These produce smoothed indices of abundance that can be used to assess population change from one or more sites or time periods, with any number of estimates of abundance per index period. We apply this method to count data collected under the Wetland Bird Survey, a national scheme that monitors waterbirds in the United Kingdom. To highlight declining populations, ‘alerts’ were raised if the population decline was equal to or greater than 50%. Significance was determined using bootstrapped confidence intervals for analyses that included many sites, or a novel Monte-Carlo method for single site analyses. The impact of missing data, species count variability and the number of months used to calculate the population change was greater at individual sites than for national datasets, which were relatively insensitive to changes in the above parameters. For single sites it is essential that three or more counts be made per index period if reliable estimates of population change are required. We propose that the method presented could be applied to a wide range of national or other monitoring schemes for a variety of taxa.     

Comparison of concentrated-flow detachment equations for low shear stress

Several equations exist to describe the relationship between concentrated-flow detachment and shear stress (τ). However, the advantages and disadvantages of these equations for specific circumstances remain unclear. This study examines the performance of linear and power equations with and without a critical shear stress (τ_c) term for concentrated-flow detachment at low shear stress. Equations were fit to data collected from experiments on five midwestern US soils using flume experimental data at low shear stress levels. Field experimental data were also available for these soils. The linear equation was simple to use and parameter values were easily estimated with linear regression. However, significant lack of fit was found when the linear equation was applied to data collected from low to medium shear stress levels. The value of soil erodibility (K) for a soil varied by a factor of 3 and critical shear stress (τ_c) varied by a factor of 2.5. The linear equation prediction underestimated detachment (D) by 25% at high shear stress and overestimated detachment by 30% at low shear stress. In contrast, the power equations gave more stable erodibility parameters because these equations reduced the systematic nature of the observation residuals found with the linear equation. Correlation between rill detachment D and τ was generally lower with the linear compared to the power equations for conditions tested. For higher shear stresses and longer slopes, the linear equation may be acceptable where field experiments show a linear trend. It is suggested that τ_c only be used when it has a value significantly different from zero.     

土壤有机质含量可见-近红外光谱反演模型校正集优选方法

土壤有机质含量可见-近红外光谱反演过程中校正集的构建策略对模型的预测精度有重要影响。以江汉平原洪湖地区水稻土为研究对象,采用Kennard-Stone(KS)法,Rank-KS(RKS)和Sample set Partitioning based on joint X-Y distance(SPXY)法,构建样本数占总校正集不同比例的子校正集,通过偏最小二乘回归,建立土壤有机质含量的可见—近红外光谱反演模型。结果表明:KS法无法提高模型预测精度,但可以在保证标准差与预测均方根误差比(ratio of performance to standard deviation,RPD)2.0的前提下减少30%的校正样本;基于SPXY法的模型,当子校正集样本比例为总校正集的50%时达到最佳的模型预测精度,RPD为2.557;RKS法能够在保证预测精度的情况下(RPD2.0),最多减少总校正集70%的样本,对应模型RPD为2.212。当校正集与验证集的有机质含量分布相近时,能够以较少的建模样本达到与总校正集相近甚至更高的模型预测精度,提升土壤有机质光谱反演模型的实用性。     

提高柴油机燃烧过程仿真计算精度的标定方法

为提高柴油机燃烧过程仿真计算精度,该文提出了新的仿真模型标定方法:首先对仿真计算的喷雾液相贯穿距、总的喷雾贯穿距(含气相)和喷雾形态进行试验验证;然后基于喷雾过程标定结果,选择合适的燃烧模型,对仿真计算的缸压和放热率曲线进行试验验证。按照上述方法应用Fire软件研究了WAVE破碎模型、Dukowicz蒸发模型和ECFM-3Z燃烧模型相关参数对计算结果的影响,分别利用喷雾自由射流和单缸柴油机试验结果标定了喷雾和燃烧模型,并与仅利用缸压和放热率曲线标定仿真模型的传统方法进行了比较。结果表明:仅利用缸压和放热率曲线标定仿真模型的方法不能保证喷雾过程模拟的准确性,后续燃烧、排放模拟的准确性亦不能保证;采用新提出的仿真模型标定方法,能准确模拟单次和分段喷射条件下柴油机的缸内喷雾和燃烧过程,拓宽了应用范围,提高了仿真计算精度。     

Confirmation of declared provenance of European extra virgin olive oil samples by NIR spectroscopy

The potential of near-infrared transflectance spectroscopy (1100-2498 nm) combined with chemometric techniques to confirm the geographical origin of European olive oil samples was evaluated. In total, 913 extra virgin olive oil samples (210 Ligurian and 703 non-Ligurian) were collected over three consecutive harvests (2005, 2006, and 2007). A multivariate spectral fingerprint for Ligurian olive oil was developed and deployed to confirm or refute a claim that any given sample was Ligurian. Samples were pseudorandomly split into calibration (n = 280) and validation sets (n = 633); the only selection constraint applied was to insist on equal numbers of Ligurian and non-Ligurian samples in the calibration set. Following preliminary examination by principal component analysis, the full spectrum modeling method applied to the spectral data set was discriminant partial least-squares regression; various data pretreatments were also investigated. The best models correctly predicted the origins of samples in the prediction set up to 92.8 and 81.5% for Ligurian and non-Ligurian olive oil samples, respectively, using a first-derivative data pretreatment. The potential of this approach in commercial traceability and quality assurance schemes is noted.     

Quantification of kavalactones and determination of kava (Piper methysticum) chemotypes using near-infrared reflectance spectroscopy for quality control in vanuatu

Kava ( Piper methysticum Forst f., Piperaceae) has anxiolytic properties and the ability to promote a state of relaxation without the loss of mental alertness. The rapid growth of the nutraceutical market between 1998 and 2000 has been stopped by a ban in Europe and Australia because of some suspicion of liver toxicity. It is now important to develop a fast, cheap, and reliable quality test to control kava exports. The aim of this study is to develop a calibration of the near-infrared reflectance spectroscopy (NIRS) using partial least-squares (PLS) regression. Two hundred thirty-six samples of kava roots, stumps, and basal stems were collected from the Vanuatu Agricultural Research and Technical Centre germplasm collection and from four villages. These samples, representing 45 different varieties, were analyzed using NIRS to record their absorption spectra between 400 and 2500 nm. A set of 101 selected samples was analyzed for their kavalactone content using HPLC. The results were used for PLS calibration of the NIRS. The NIRS prediction of the kavalactone content and the dry matter were in agreement with the HPLC results. There were good correlations between these two series of results, and coefficients ( R (2)) were all close to 1. The measurements were reproducible and had repeatability on par with the HPLC method. The NIRS system has been calibrated for the six major kavalactone content measurements, and it is suggested that this method could be used for quality control in Vanuatu.     

基于RVM的配比变量排肥掺混均匀度离散元仿真及验证

采用试验测量或现有的间接标定方法很难实现配比变量排肥离散元仿真的参数标定,针对此标定难题,该文提出一种基于肥料掺混均匀度-仿真参数相关向量机模型主动寻优的标定方法。将配比变量离散元排肥过程看作特定的非线性系统,采用相关向量机机器学习方法揭示模型参数与肥料掺混均匀度之间的映射关系,建立回归元模型;基于最优模型参数值对应的肥料掺混均匀度值应与试验值一致,采用建立的元模型结合试验统计结果构建适应度函数;基于约束最优的数学思想建立数学模型,通过最优参数值遗传算法迭代计算,得到最优值。5种排肥转速下(30、40、50、60、70 r/min),排肥器采用碰撞边缘为外凸曲线形的A型掺混腔时,标定模型排肥后肥料掺混均匀度与试验值的相对误差均值:氮肥为6.4%,磷肥为4.1%,钾肥为5.9%;标定前氮肥为26.8%,磷肥为28.9%,钾肥为36.1%。采用碰撞边缘为直线形的B型掺混腔时,标定模型排肥后肥料掺混均匀度与试验值的相对误差均值:氮肥为5.8%,磷肥为5.6%,钾肥为4.9%;标定前氮肥为21.9%,磷肥为32.5%,钾肥为28.9%;采用碰撞边缘为内凹曲线形的C型掺混腔时,标定模型排肥后肥料掺混均匀度与试验值的相对误差均值:氮肥为5.0%,磷肥为3.7%,钾肥为8.7%;标定前氮肥为36.2%,磷肥为31.6%,钾肥为24.4%,该方法能够实现配比变量排肥离散元仿真参数准确有效的标定。     

Surface Armour and Erosion – Impacts on Long‐term Landscape Evolution

The parameterisation of landscape evolution models is key to their reliable use. To determine reliable parameter sets, data collected from many events over a number of years are required. However, for many recently disturbed, degraded and/or rehabilitated sites, this data may not represent the long‐term behaviour of the surface as armouring, weathering, together with vegetation establishment change the erodibility of the surface. Here, we evaluate a new armouring sub‐model within the SIBERIA landscape evolution model. The calibration of the armour model is conducted using 6 years of field data from four plots, each composed of different surface materials and vegetation characteristics. The calibrated model is then tested on an area of the proposed rehabilitated landform of the Ranger Uranium Mine in the Northern Territory, Australia. The SIBERIA model was then run for a simulated period of 100,000 years using parameters representing (i) a surface constructed of fresh waste rock; (ii) a vegetated surface; and (iii) the calibrated armour sub‐model. The results demonstrate that the different parameter sets produce catchments that are unique despite the same starting surface. Surface material properties exert a first‐order control on landscape evolution. Therefore making predictions for the evolution of a landscape requires a reliable understanding of the material properties. This requires a knowledge of what material will be placed where in the catchment. Copyright © 2017 John Wiley & Sons, Ltd.     

基于离散元法的面粉颗粒接触参数标定试验

为设计和优化面粉输送设备,应用离散元法对面粉进行准确地工程建模和分析,需要对其接触参数进行必要的标定。该研究依据颗粒缩放理论,用“Hertz-Mindlin with Johnson-Kendall-Roberts”接触模型表征面粉颗粒间黏性的影响,提出了一种基于静/动态休止角的接触参数标定方法。运用正交试验方法,对接触参数的敏感性和方差分析,表明面粉颗粒间的滚动摩擦系数、面粉颗粒与不锈钢表面间的静摩擦系数、表面能对静态休止角的影响极显著（P＜0.01）,并且多组接触参数都可以模拟出与试验相同的静态休止角。进一步研究表明,面粉颗粒与不锈钢表面间的静摩擦系数的合理取值范围为0.2～0.4。通过2种填充率、4种转速下基于动态休止角的参数标定,将其中与试验最为吻合的一组参数作为标定结果,其值如下：面粉颗粒之间恢复系数为0.6、面粉颗粒之间静摩擦系数为0.2、面粉颗粒之间滚动摩擦系数为0.1、面粉颗粒与不锈钢容器表面之间恢复系数为0.6、面粉颗粒与不锈钢容器表面之间静摩擦系数为0.6、面粉颗粒与不锈钢容器表面之间滚动摩擦系数为0.5、表面能为0.12 J/m²。使用该组参数对矩形容器中物料自由坍塌试验进行仿真,其结果与试验结果相符,验证了该标定方法的有效性。该研究提出的标定方法简单、易执行,对粉料输送设备的设计及优化具有一定的工程应用价值。