A PRELIMINARY QUANTIFICATION OF THE IMPACTS OF ASPEN TO CONIFER SUCCESSION ON WATER YIELD - I. HEAT PULSE METHODOLOGY FOR MODEL CALIBRATION1

ABSTRACT: Twenty-six aspen (Populus tremuloides Michx.), 20 subalpine fir (Abies lasiocarps (Hook.) Nutt.), and 20 Engelmann spruce (Pices engelmanil (Parry) Engelm.) of various sizes were cut under water and suspended in permanent reserviors at a northern Utah site. The reservoirs were asealed so that all water loss was due to consumption by the trees. Sap velocities, as computed from heat pulse velocities, were related to conducting areas of the tree trunks. Computed transpiration volumes were then correlated with actual water losses from the reservoirs. Coefficients of determination (R²) of 0.87, 0.86, and 0.82 were obtained for the fir, aspen, and sprucs, respectively. Reservoir water loss for each species for each season was then used to adjust a plant activity index for computing transpiration within ASPCON, a model describing the hydrology of aspen to conifer succession. The plant activity index reflects the variation in the capability of a plant community to transpire water over the year. Assumptions and limitations of the heat pulse velocity technique are also outlined.     

试论酸度计在pH测定中的定位问题

本文阐述了酸度计在测定ｐＨ时温度补偿的原理,分析了错误定位的原因,指出了正确的定位方法     

基于COMSOL的采空区埋管抽采参数优化数值研究

针对回采工作面上隅角瓦斯浓度超限问题,提出了回采工作面采空区埋管抽采的方法。以保德煤矿81307工作面为研究对象,运用数值模拟软件COMSOL模拟采空区无抽采和不同抽采参数条件下工作面内瓦斯分布规律,研究埋管抽采参数对上隅角瓦斯浓度的影响规律,确定最佳的采空区埋管抽采参数。同时进行现场抽采参数优化试验,对瓦斯浓度进行监测,研究结果表明:合适的布置间距、抽采负压和抽采流量能够有效解决上隅角瓦斯超限问题,试验期间内,上隅角瓦斯体积分数最大为0.74%,进风流中瓦斯体积分数最大为0.2%,工作面风流中瓦斯体积分数最大为0.45%,回风流中瓦斯体积分数最大为0.5%,均没有超过安全标准。     

基于SAE-ARP958环天线校准技术研究

目的介绍基于SAE-ARP958环天线校准技术,研究提高该校准精确性的方法,为精确监测电磁环境提供保障。方法研制一套基于SAE-ARP958环天线的校准装置,提出采用直径分别为30,10,4 cm的三个发射环天线作为磁场发生装置的校准方案,并利用对比测试的方法对校准方案进行优化。结果优化后的校准方案能够实现环天线的精确校准。结论基于SAE-ARP958环天线校准方法具有不受待校环尺寸限制的优点,而且精确性高,值得向具有较多不同尺寸的环天线用户推广。     

Modeling of real scale waste activated sludge anaerobic digestion process by Anaerobic Digestion Model 1 (ADM1)

In this study, real-scale wastewater treatment plant (Hurma WWTP) sludge anaerobic digestion process was modeled by Anaerobic Digestion Model (ADM1) with the purpose of generating the data to understand the process better by contributing to the prediction of the process operational conditions and process performance, which will be a base for future anaerobic sludge stabilization process investments.

Real-scale anaerobic sludge digestion process data was evaluated in terms of known process and state variables and also process yields. Average VS removal yield, methane production yield, and methane production rate values of the anaerobic sludge digestion unit were calculated as 46.4%, 0.49 m³CH₄/kg VS_removed, and 0.33 m³ CH₄/m³day, respectively. In this study, ADM1 was intended to predict the behavior of real-scale anaerobic digester processing sewage sludge under dynamic conditions. To estimate the variables of real-scale sludge anaerobic digestion process with high accuracy and to provide high model prediction performance, values of the four parameters (disintegration rate constant, carbohydrate hydrolysis rate constant, protein hydrolysis rate constant, and lipid hydrolysis rate constant) that have strong effects on structured ADM1 were estimated by using the parameter estimation module in Aquasim program and their values were found as 0.101, 10, 10, and 9.99, respectively. When the numbers of kinetic parameters with the processes included in ADM1 along with the dynamic and non-linear structure of the real scale anaerobic digestion were taken into consideration, model simulations were in good agreement with measured results of the biogas flow rate, methane flow rate, pH, total alkalinity, and volatile fatty acids.     

Evaluating the Applicability of a Two‐dimensional Flow Model of a Highly Heterogeneous Domain to Flow and Environmental Management

Two‐dimensional simulation of highly heterogeneous domains, especially those with disparate length scales, roughness conditions, and geometries, often leads to challenges such as long computation times and numerical instability. Simulation of challenging domains is often needed to guide flood management and environmental regulation agencies in operation and potential domain modifications. This work evaluates the ability of a two‐dimensional unsteady hydrodynamic model to represent long‐duration transient flows over a domain with highly heterogeneous roughness, geometric characteristics, and length scales through bed roughness representation. The domain includes 13 km of Cache Creek and the 14.5 km² Cache Creek Settling Basin, which traps both sediment and mercury. Calibration under different bed roughness methods, validation, and modeling results of bathymetric modification scenarios are presented. The modeling approach's performance supports its application as a tool for management of similar domains, such as settling basins, leveed floodplains, and reservoirs. Accurate representation of flow dynamics can also inform environmental management that involves transport of sediments, nutrients, and heavy metals. This study found that a two‐dimensional unsteady flow model can accurately represent long‐duration transient flow in a large settling basin with highly heterogeneous characteristics without parsing of the domain or flow events simulated.     

模拟纳污水体底质参数变化

本文介绍了模拟纳污水体中ＷＡＲ，ＷＭＲ，ＷＣＨ，ＳＡＲ，ＳＭＲ，ＳＳＦ和ＲＯＣ的变化。过程曲线表明水体污染时底质参数出现累积现象。     

Small sample estimation for Taylor's power law

An analysis of counts of sample size N=2 arising from a survey of the grass Bromus commutatus identified several factors which might seriously affect the estimation of parameters of Taylor's power law for such small sample sizes. The small sample estimation of Taylor's power law was studied by simulation. For each of five small sample sizes, N=2, 3, 5, 15 and 30, samples were simulated from populations for which the underlying known relationship between variance and mean was given by ² = c^d. One thousand samples generated from the negative binomial distribution were simulated for each of the six combinations of c=1,2 and 11, and d=1, 2, at each of four mean densities, =0.5, 1, 10 and 100, giving 4000 samples for each combination. Estimates of Taylor's power law parameters were obtained for each combination by regressing log₁₀ s ² on log₁₀ m, where s ² and m are the sample variance and mean, respectively. Bias in the parameter estimates, b and log₁₀ a, reduced as N increased and increased with c for both values of d and these relationships were described well by quadratic response surfaces. The factors which affect small-sample estimation are: (i) exclusion of samples for which m = s ² = 0; (ii) exclusion of samples for which s ² = 0, but m > 0; (iii) correlation between log₁₀ s ² and log₁₀ m; (iv) restriction on the maximum variance expressible in a sample; (v) restriction on the minimum variance expressible in a sample; (vi) underestimation of log₁₀ s ² for skew distributions; and (vii) the limited set of possible values of m and s ². These factors and their effect on the parameter estimates are discussed in relation to the simulated samples. The effects of maximum variance restriction and underestimation of log₁₀ s ² were found to be the most severe. We conclude that Taylor's power law should be used with caution if the majority of samples from which s ² and m are calculated have size, N, less than 15. An example is given of the estimated effect of bias when Taylor's power law is used to derive an efficient sampling scheme.     

水网区域的水质模拟预报及污染容量

本文研究了頔塘河震泽段的水质指标(BOD、DO)在水体中的迁移转化规律,建立起模拟頔塘河震泽段的水持数学模型。在以水环境规划为目标的水质数值模拟中,首次结合全面的水文分析及该河段的模型参数估计,给出頔塘河震泽段的水质模拟预报及全年污染容量的计算,作为水质管理规划的定量依据。     

A Bayesian approach to evaluating site impairment

In the United States, each state is required to list water resources that are declared to be impaired under guidelines set by the Clean Water Act. Measurements are typically collected on a number of chemical constituents and compared with a standard. If there are too many measurements exceeding the standard, then the site is declared impaired. The approach is non-statistical but similar to a Binomial test. The Binomial approach would convert the measurements to binary data then test if the proportion exceeding the standard is excessive. Both methods convert measurements to binary values hence exclude potentially important information in the data. We present a statistical approach using a Bayesian model that uses the raw data instead of the binary transformed data. The population distribution of a family of location-scale parameter models is studied under the model. Posterior distributions from the Bayesian analysis are used in the decision-making process and error probabilities for the Bayesian and the Binomial approaches are compared for a normal population.