A FRAMEWORK FOR PHOSPHORUS TRANSPORT MODELING IN THE LAKE OKEECHOBEE WATERSHED1

ABSTRACT: A modeling framework was developed to determine phosphorus loadings to Lake Okeechobee from watersheds located north of the lake. This framework consists of the land-based model CREAMS-WT, the in-stream transport model QUAL2E, and an interface procedure to format the land-based model output for use by the in-stream model. QUAL2E hydraulics and water quality routines were modified to account for flow routing and phosphorus retention in both wetlands and stream channels. Phosphorus loadings obtained from previous applications of CREAMS-WT were used by QUAL2E, and calibration and verification showed that QUAL2E accurately simulated seasonal and annual phosphorus loadings from a watershed. Sensitivity and uncertainty analyses indicated that the accuracy of monthly loadings can be improved by using better estimates of in-stream phosphorus decay rates, ground water phosphorus concentrations, and runoff phosphorus concentrations as input to QUAL2E.     

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.     

THE USE OF A SIMPLE MODEL AND UNCERTAINTY ANALYSIS IN LAKE MANAGEMENT1

ABSTRACT: A simple, black-box lake model was developed for phosphorus, using nonlinear regression analysis on a data base of north temperate lakes. The uncertainty associated with the model was then combined with the parameter uncertainty and the independent variable uncertainty to provide an estimate of the confidence limits associated with a predicted value. The prediction uncertainty is often neglected, yet it is an important measure of the usefulness of a model. Prediction uncertainty reflects the modeler's confidence in the model, and it should be used by a decision maker as a weight indicating the value of the model prediction. A procedure is outlined that combined lake modeling and uncertainty analysis for use in lake quality assessment and lake management. An example is provided illustrating the use of this procedure in nutrient budget sampling design, data analysis, and the evaluation of lake management strategies for a 208 program in New Hampshire.     

滴定法测定的不确定度评定——以EDTA法测定水中钙镁为例

用测量不确定度表示检测结果是当前国际上约定做法，然而如何对测量结果的不确定度进行合理评定，一直是困扰检测实验室的一个难题。作者依据测量不确定度的评定原则，通过实例，简要地阐述了滴定法测量不确定度评定方法，对环境检测领域测量不确定度的评定具有借鉴意义。     

测量试样中的氮氧化物含量不确定度评定

以实际监测数据为例，详细描述测量试样中的NOx含量不确定度评定方法，包括不确定度源的分析，A类标准不确定度评定、B类标准不确定度评定、合成标准不确定度和扩展不确定度等，对不确定度的分量作了详尽的分析和计算。     

Accounting for Uncertainty in Making Species Protection Decisions

Abstract:  Uncertainty gives rise to two decision errors in implementing the U.S. Endangered Species Act: listing species that are not in danger of extinction and delisting species that are in danger of extinction. I evaluated four methods (minimum standard, precautionary principle, minimax regret criterion, adaptive management) for deciding whether to list or delist a species when there is uncertainty about how those decisions are likely to influence survival of the species. A safe minimum standard criterion preserves some minimum amount or safe standard (population) of a species unless maintaining that amount generates unacceptable social cost. The precautionary principle favors not delisting a species when there is insufficient evidence on the efficacy of state management plans for protecting them. A minimax regret criterion selects the delisting decision that minimizes the maximum loss likely to occur under alternative ecosystem states. When the cost of making a correct decision is less than the cost of making an incorrect decision, the minimax regret criteria indicates that delisting is the optimal decision. Active adaptive management employs statistically valid experiments to test hypotheses about the likely impacts of delisting decisions. Safe minimum standard and minimax regret criterion are not compatible with the U.S. Endangered Species Act. The precautionary principle comes closest to describing how federal agencies make delisting decisions. Active adaptive management is scientifically superior to the other methods but is costly and time consuming and may not be compatible with the U.S. National Environmental Policy Act.     

Optimal Control Models and Elicitation of Attitudes towards Climate Damages

This paper examines the consequences of various attitudes towards climate damages through a family of stochastic optimal control models (RESPONSE): cost-efficiency for a given temperature ceiling; cost-benefit analysis with a pure preference for current climate regime and full cost-benefit analysis. The choice of a given proxy of climate change risks is actually more than a technical option. It is essentially motivated by the degree of distrust regarding the legitimacy of an assessment of climate damages and the possibility of providing in due time reliable and non controversial estimates. Our results demonstrate that (a) for early decades abatement, the difference between various decision-making frameworks appears to matter less than the difference between stochastic and non stochastic approach given the cascade of uncertainty from emissions to damages; (b) in a stochastic approach, the possibility of non-catastrophic singularities in the damage function is sufficient to significantly increase earlier optimal abatements; (c) a window of opportunity for action exists up to 2040: abatements further delayed may induce significant regret in case of bad news about climate response or singularities in damages.     

Sensitive Parameters In Predicting Exposure Contaminants Concentration In A Risk Assessment Process

A sensitivity analysis (SA) was conducted on the analytical models considered in the risk-based corrective-action (RBCA) methodology of risk analysis, as developed by the American Society for Testing of Materials (ASTM), to predict a contaminant‘s concentration in the affected medium at the point of human exposure. These models are of interest because evaluations regarding the best approach to contaminated site remediation are shifting toward increased use of risk-based decision, and the ASTM RBCA methodology represents the most effective and internationally widely used standardized guide for risk assessment process. This paper identifies key physical and chemical parameters that need additional precision and accuracy consideration in order to reduce uncertainty in models prediction, thereby saving time, money and engineering effort in the data collection process. SA was performed applying a variance-based method to organic contaminants migration models with reference to soil-to-groundwater leaching ingestion exposure scenario. Results indicate that model output strongly depends on the organic-carbon partition coefficient, organic-carbon content, net infiltration, Darcy velocity, source-receptor distance, and first-order decay constant.     

北京市燃气工业锅炉CO2排放因子及不确定性分析

降低碳排放评估的不确定性对于减排政策选择和成本效益分析十分重要,基于北京市227个天然气锅炉样本检测数据,分析影响CO₂排放因子的关键参数特征,评估北京市天然气锅炉本地化CO₂排放因子,采用蒙特卡洛模型对排放因子的不确定性进行分析,并将其与IPCC、国家清单、城市清单等同类排放因子进行了比较.结果表明:北京市天然气锅炉CO₂排放因子为2.052 kg/m3,90%概率分布范围为1.982~2.086 kg/m3;基于热值的CO₂排放因子推荐值为55.829 kg/GJ,90%概率分布范围为55.788~55.908 kg/GJ,排放因子的不确定范围为-3.59%~1.57%.北京市天然气锅炉CO₂排放因子稍低于IPCC2006国家温室气体清单指南推荐缺省值（0.5%）.天然气低位热值对排放因子的影响最大,其方差贡献率达94%,而单位热值含碳量和氧化率二者的方差贡献率仅占6%.通过北京市本地实测数据和蒙特卡洛模型模拟,给出了天然气锅炉排放因子及概率分布的范围,提高了评估精度,有助于改进北京市温室气体排放清单活动水平的数据收集工作,指导并降低天然气工业锅炉CO₂排放因子不确定性.      

新型长时热流测量装置的研制及应用

目的设计一种新型热流测量装置,使传感器满足长时间热流测量的需求,且传感器外表面可以适量打磨,与飞行器的气动外型面完好随型。方法采用铜和钢作为备选材料,施加相同的表面热流边界,对比敏感端内外壁温差情况。优化热流辨识传感器传热路径、敏感端厚度,通过有限元模型分析打磨对热流辨识结果的影响。基于优化结果,研制出热流测量装置,并通过地面试验验证该装置的有效性。结果从热响应获取时间延迟角度来看,Cu比钢具有较大的优势。综合考虑敏感端外表面需要与飞行器外表面随型打磨,选用5 mm的厚度具有一定的安全可靠性。敏感端的适度打磨基本不影响温度测量结果。辨识获得的热流数据与实际控制热流吻合较好,最大偏差约15%。结论成功研制了热流测量装置,并通过地面热试验证明了热流测量的有效性。