Monte Carlo analysis of field water flow comparing uni- and bimodal effective hydraulic parameters for structured soil

Soil structure critically affects the hydrological behaviour of soils. In this paper, we examined the impact of areal heterogeneity of hydraulic properties of a structured soil on soil ensemble behaviour for various soil water flow processes with different top boundary conditions (redistribution and drainage plus evaporation and infiltration). Using a numerical solution of the Richards' equation in a stochastic framework, the ensemble characteristics and flow dynamics were studied for drying and wetting processes observed during a time interval of ten days when a series of relatively intense rainfall events occurred. The effects of using unimodal and bimodal interpretative models of hydraulic properties on the ensemble hydrological behaviour of the soil were illustrated by comparing predictions to mean water contents measured over time in several sites at field scale. Although the differences between unimodal and bimodal fitting are not significant in terms of goodness of fit, the differences in process predictions are considerable with the bimodal soil simulating water content measurements much better than unimodal soil. We also investigated the relative contribution of the soil variability of each parameter on the variance of the water contents obtained as the main output of the stochastic simulations. The variability of the structural parameter, weighting the two pore space fractions in the bimodal interpretative model, has the largest contribution to water content variance. The contribution of each parameter depends only partly on the coefficient of variation, much more on the sensitivity of the model to the parameters and on the flow process being observed. We observed that the contribution of the retention parameters to uncertainty increases during drainage processes; the opposite occurs with the hydraulic conductivity parameters.     

Spatial modelling of the probability of obtaining a detectable concentration of ammonia in Moreton Bay, Australia

Ammonia is an important water quality variable, which in excess, can be detrimental to waterways and their ecosystems. In the Ecosystem Health Monitoring Program in South-east Queensland ammonia is monitored monthly, however, often more than 50% of the ammonia observations in Moreton Bay are below detection limit, making it difficult to draw useful inferences. In this paper a clipped Gaussian random field is used to spatially model and map the probability of detectable concentration of ammonia. The methodology is applied to the Moreton Bay samples collected in February 2005. The results suggest that for this month the oceanic impacted areas have higher probability of detectable ammonia concentration than the areas closer to the main sources of anthropogenic inputs.     

建筑物消防系统可靠性分析

为评估建筑物消防系统的可靠性,首先将系统分为探测报警系统和灭火系统等部分,再用事件树法分析事故发生时消防系统不同部分的反应情况.通过贝叶斯理论及历史统计数据得到系统失效率的不确定性概率分布,建立消防系统可靠性随时间变化的数学模型; 用蒙特卡罗方法模拟求得系统可靠性的时间函数并对模型的不确定性参数进行敏感性分析.该方法将统计数据与经验公式、理论方法相结合,并利用蒙特卡罗方法处理模型中的不确定性,不仅能够有效估计消防系统的可靠性,还可对其他类似系统的可靠性进行分析,并通过敏感性分析为进一步减少估计的不确定性提出合理建议.     

剑麻纤维基多孔炭材料的制备及其吸附氯苯的研究

以剑麻纤维为原料,通过简易的一步炭化活化法制备了一系列多孔炭材料,分别探究了3种温和的金属盐活化剂、活化剂与剑麻纤维的质量比和活化温度对炭材料的氯苯吸附量的影响,并通过BET、SEM、XRD、Raman、FT-IR、元素分析等手段表征其物理化学性质.结果表明,当采用CuCl₂为活化剂、CuCl₂与剑麻纤维的质量比为10∶1及活化温度为800℃时,制备得到的剑麻纤维基多孔炭(PCC)吸附性能最佳,其在氯苯浓度为1560 mg·m^-3时,吸附量达到856 mg·g^-1,而未经CuCl₂活化的炭材料(PC)的氯苯吸附量仅为15 mg·g^-1.氯苯吸附性能的提升主要归因于比表面积、孔容、无序性和表面含氧官能团的增加.此外,采用巨正则系综蒙特卡洛(GCMC)方法模拟氯苯分子在制备的多孔炭材料中的吸附行为,结果表明,该材料中孔径为0.5 nm的孔对氯苯分子的吸附能力最强,且对氯苯吸附起主导作用的为苯环中心和Cl原子与炭材料上连接含氧官能团的H原子之间的静电作用力.     

复杂气井套管力学分析与可靠度评价

为建立考虑地层和套管参数随机性的套管可靠度评价理论方法,以便得到复杂井况下套管传统设计安全系数与可靠指标之间的关系,提出了非均匀地应力和内压联合作用下,沿套管最大外挤力方向管壁任意位置发生屈服失效时外壁等效均匀外挤力的计算方法;建立了套管抗挤和抗内压三轴强度计算公式以及有效内压计算方法;根据套管载荷和强度影响因素统计参数以及评价过程中参数测试标准值,利用蒙特卡洛法（MC）建立了完整的套管可靠度计算和评价方法;通过实例对传统安全系数与可靠指标的对应关系进行了研究。研究结果表明:指定条件下,套管安全系数与可靠指标之间存在对应关系;利用建立的方法编制计算程序可以为传统设计法中安全系数代表的安全程度进行量化;可靠度评价方法能够为安全系数的选取提供指导。     

A Monte Carlo study of radon detection in cylindrical diffusion chambers

The functioning of radon diffusion chambers was studied using the Monte Carlo code RAMMX developed here. The alpha particles from radon are assumed randomly produced in the volume of the cylinder, and those from the progeny are assumed to originate randomly at the cylindrical surface. The energy spectrum, the distribution of incident angles, and the distribution of path lengths of the alpha particles on the detector were obtained. These quantities vary depending on input parameters such as initial alpha particle energy, radius and depth of the diffusion chamber, detector size and atmospheric pressure. The calculated energy spectrum for both ²²²Rn and ²²⁰Rn was compared with experiment, permitting the identification of each peak and its origin, and a better understanding of radon monitoring. Three aspects not considered in previous calculations are progeny alphas coming from surfaces of the monitor, taking into account the atmospheric pressure, and including the isotope ²²⁰Rn.     

Assessing and testing prediction uncertainty for single tree-based models: A case study applied to northern hardwood stands in southern Québec, Canada

Estimating prediction uncertainty for a single tree-based model is hindered by the complex structure of these models. In this paper, we addressed this issue with a case study applied to northern hardwood stands in Québec, Canada. SaMARE is a stochastic single tree-based model that was designed for these types of stands. Using a Monte Carlo approach, the model can provide a mean predicted value and its confidence limits for some plot-level attributes.The mean predicted values were compared to observed values in terms of bias and accuracy. In addition to these common statistics, we compared nominal coverage of Monte Carlo-simulated confidence intervals with real (observed) coverage to verify the adequacy of the simulated uncertainty. A comparison was made using several plot-level attributes, which exhibited an increasing discriminative complexity. This complexity ranges from coarse attributes, such as all-species basal area, up to more complex ones, such as basal area for stems of a particular species and with sawlog potential.The results showed that in terms of absolute value, biases were small, but could be relatively high with respect to the average observed value when the discriminative complexity of the attribute increased. The comparison between nominal and real coverage of confidence intervals gave satisfactory results for all-species plot-level attributes. However, for some species-specific attributes, the Monte Carlo-simulated confidence intervals overestimated the real coverage.     

UNCERTAINTY ANALYSIS OF BMP EFFECTWENESS FOR CONTROLLING NITROGEN FROM URBAN NONPOINT SOURCES1

ABSTRACT: The effectiveness of urban Best Management Practices (BMPs) in achieving the No-Net-Increase Policy (NNTP), a policy designed to limit nonpoint nitrogen loading to Long Island Sound (US), is analyzed. A unit loading model is used to simulate annual nitrogen exported from the Norwalk River watershed (Connecticut) under current and future conditions. A probabilistic uncertainty analysis is used to incorporate uncertainty in nitrogen export coefficients and BMP nitrogen removal effectiveness. The inclusion of uncertainty in BMP effectiveness and nitrogen export coefficients implies that additional BMPs, or BMPs with a greater effectiveness in nitrogen removal, will be required to achieve the NNIP. Even though including uncertainty leads to an increase in BMP implementation rates or BMP effectiveness, this type of analysis provides the decision maker with a more realistic assessment of the likelihood that implementing BMPs as a management strategy will be successful. Monte Carlo simulation results indicate that applying BMPs to new urban developments alone will not be sufficient to achieve the NNIP since BMPs are not 100 percent effective in removing the increase in nitrogen caused by urbanization. BMPs must also be applied to selected existing urban areas. BMPs with a nitrogen removal effectiveness of 40–60 percent, probably the highest level of removal that can be expected over an entire watershed, must be applied to at least 75 percent of the existing urban area to achieve the NNIP This high rate of application is not likely to be achieved in urbanized watersheds in the LIS watershed; therefore, additional point source control will be necessary to achieve the NNIP     

A WATER QUALITY‐BASED APPROACH FOR WATERSHED WIDE BMP STRATEGIES1

ABSTRACT: Watershed management strategies generally involve controlling nonpoint source pollution by implementing various best management practices (BMPs). Currently, stormwater management programs in most states use a performance‐based approach to implement onsite BMPs. This approach fails to link the onsite BMP performance directly to receiving water quality benefits, and it does not take into account the combined treatment effects of all the stormwater management practices within a watershed. To address these issues, this paper proposes a water quality‐based BMP planning approach for effective nonpoint source pollution control at a watershed scale. A coupled modeling system consisting of a watershed model (HSPF) and a receiving water quality model (CE‐QUAL‐W2) was developed to establish the linkage between BMP performance and receiving water quality targets. A Monte Carlo simulation approach was utilized to develop alternative BMP strategies at a watershed level. The developed methodology was applied to the Swift Creek Reservoir watershed in Virginia, and the results show that the proposed approach allows for the development of BMP strategies that lead to full compliance with water quality requirements.     

A GIS/Simulation Framework for Assessing Change in Water Yield over Large Spatial Scales

Recent legislation to initiate vegetation management in the Central Sierra hydrologic region of California includes a focus on corresponding changes in water yield. This served as the impetus for developing a combined geographic information system (GIS) and simulation assessment framework. Using the existing vegetation density condition, together with proposed rules for thinning to reduce fire risk, a set of simulation model inputs were generated for examining the impact of the thinning scenario on water yield. The approach allows results to be expressed as the mean and standard deviation of change in water yield for each 1-km² map cell that is thinned. Values for groups of cells are aggregated for typical watershed units using area-weighted averaging. Wet, dry, and average precipitation years were simulated over a large region. Where snow plays an important role in hydrologic processes, the simulated change in water yield was less than 0.5% of expected annual runoff for a typical watershed. Such small changes would be undetectable in the field using conventional stream flow analysis. These results suggest that use of water yield increases to help justify forest-thinning activities or offset their cost will be difficult.