Evaluation of biological water purification functions of inland lakes using an aquatic ecosystem model

An effective measure to cope with eutrophication of lakes is to remove nutrients that can cause algal blooming by taking advantage of natural water purification processes. Here the term “purification” is defined, in a wide sense, as the potential role of a water body to contribute to the reduction of pollutants and thus controlling eutrophication. Also regarded as a kind of ecological regulating services, biological purification involves various processes concerning seasonal nutrient fixation, such as uptake by aquatic macrophytes, biofouling onto foliage substrates, feeding by organisms in higher trophic level, and eternal loss or removal of substance from the water. In order to evaluate the water purification ability, a numerical lake ecosystem model highlighting the role of macrophyte colonies in the shore zone was developed and applied to Lakes Suwa, Kasumi and Biwa, as well as five small lakes attached to Lake Biwa.     

环境模型参数优化方法的比较

模型参数优化是通过极小化目标函数使得模型输出和实际观测数据之间达到最佳的拟合程度.由于环境模型本身的复杂性,常规优化算法难以达到参数空间上的全局最优.近年来,随着计算机运算效率的快速提高,直接优化方法得到了进一步开发与广泛应用.本文比较了CRS、SCEUA、SA和Annealing-Simplex等4种算法应用于环境模型参数优化的结果和计算效率.     

废弃打印机硒鼓回收过程墨粉防爆研究

对打印机墨粉爆炸的有关参数(包括最大爆炸压力、爆炸指数Kmax、爆炸下限、粉尘层着火温度、粉尘云着火温度)进行了研究。结果表明:墨粉的爆炸压力比其组成树脂粉低,这可能与其中不可燃的磁性氧化铁添加物有关;墨粉的爆炸指数为18,易于发生燃烧和爆炸;墨粉的爆炸下限(<50 g/m3)较低,爆炸上限很高,易于形成可爆粉尘云,但高于400℃时不着火,不易发生自燃。研究结果将为废弃硒鼓墨粉的防爆提供基础数据,对防灾决策的深入研究具有参考价值。     

TROPICAL EUTROPHIC LAKE MODELING AND PARAMETER DISCRIMINATION1

ABSTRACT: Water quality data collected between 1978 and 1981 in a highly lake in Northern Venezuela, Lake Valencia, were analyzed to detect spatial and temporal trends. Based on the results of the analyses, an appropriate nutrient-algae dynamics model was formulated. Because many parameters, such as the algae concentration were constant over time, and the model is time dependent, the model had to be calibrated with the use of a large and structured trial-and-error calibration process. Through the calibration process, the most sensitive parameters of the model were identified, and are in order of importance: the chlorophyll-to-nitrogen ratio for algae, the algae settling velocity, the phosphorus release rate from the sediments, the chlorophyll-to-phosphorus ratio for algae, and the exchange coefficient in the upper layer of the lake. Model simulations showed that a reduction in the nitrogen load to the lake as well as a reduction in the phosphorus load will decrease the algae population. These model simulations had a high degree of uncertainty associated with them, making additional sampling directed towards the measurement of the sensitive parameters desirable.     

“禁麻”对武汉市空气质量的影响

从武汉市取缔正三轮摩托车("麻木")的事件出发,简述了正三轮摩托车的污染危害,计算了取缔车辆1年排放的有害物质,通过监测数据说明了对大气环境的影响。     

CALIBRATING AND VERIFYING THE SSARR MODEL -MISSOURI RIVER WATERSHEDS STUDY1

The Streamflow Synthesis and Reservoir Regulation (SSARR) model was calibrated and verified on the Madison and Gallatin watersheds in the upper Missouri River drainage. The study was performed to determine if the SSARR model could simulate snowmelt-runoff volumes to effect better operation of six multipurpose reservoirs on the Missouri River. Physical watershed characteristics and parameter sensitivity are incorporated into a procedure which expedites model calibration. Criteria are established to facilitate parameter development and to objectively evaluate calibration and verification results. A ratio of simulated to observed snowmelt-runoff volumes of the Madison River averaged 1.00 and 1.02 for calibration (N = 8 years) and verification (N = 6 years) with corresponding standard deviations of 0.08 and 0.13. Gallatin volume ratios averaged 0.99 and 0.95 for calibration (N = 7 years) and verification (N = 5 years) with respective standard deviations of 0.08 and 0.28.     

APPLICATION OF COMPUTER INTENSIVE STATISTICS TO PARAMETER UNCERTAINTY IN STREAMFLOW SYNTHESIS1

ABSTRACT: This paper introduces the application of Computer Intensive Statistics (CIS) to the evaluation of parameter uncertainty with specific reference to the parameters in the ARMA models used in the synthesis of streamflows. The CIS provides an empirically derived joint distribution for all parameters. Random values from this distribution can be drawn for application in the model for the generation of a specific synthetic sample. The CIS originally proposed by Efron and discussed herein is of general applicability in the evaluation of uncertainty in any statistic derived from a set of data. Some comments and limitations of the CIS are discussed in the concluding remarks.     

长治市冰雹气候特征及预报研究

对1980—2003年长治市冰雹天气的气候背景进行了统计分析，明确了冰雹发生的时空尺度，地理分布，月、年际变化，冰雹发源地以及冰雹主要影响路径；利用500hPa天气图，给出了降雹的天气形势及高空冷空气的活动路径；分析了冰雹天气的0℃层高度、-20℃层高度、水汽条件和稳定度等参数；采用最优子集回归方法对850hPa和500hPa高空指标站进行了选取，分析了这些站点及本站14时（压、温、湿、风）的气象要素，建立了综合性预报模型。     

防化服结构和缝制工艺优化设计研究

本文研究了防化服的设计原则,对我国某型防化服装进行了分析,在腰部、袖型、膝部的结构上进行改进,使服装更趋合理、人性化,更便于作业活动。针对防化服影响防护效果的缝制工艺参数,利用二次通用旋转实验设计,变化机针针号、线迹密度及缝纫线细度三个因素五个水平;针对“三防”面料进行防油、防水、防静电测试,得到防护性能与缝制工艺参数之间的回归方程,并绘出等值曲线图,进一步分析了缝制工艺对面料防油、防水、防静电性能的影响,通过Borda数找出最优缝制工艺参数,并将应用到防化服的加工制作中。     

Approaches to Evaluate Water Quality Model Parameter Uncertainty for Adaptive TMDL Implementation1

Abstract: The National Research Council recommended Adaptive Total Maximum Daily Load implementation with the recognition that the predictive uncertainty of water quality models can be high. Quantifying predictive uncertainty provides important information for model selection and decision‐making. We review five methods that have been used with water quality models to evaluate model parameter and predictive uncertainty. These methods (1) Regionalized Sensitivity Analysis, (2) Generalized Likelihood Uncertainty Estimation, (3) Bayesian Monte Carlo, (4) Importance Sampling, and (5) Markov Chain Monte Carlo (MCMC) are based on similar concepts; their development over time was facilitated by the increasing availability of fast, cheap computers. Using a Streeter‐Phelps model as an example we show that, applied consistently, these methods give compatible results. Thus, all of these methods can, in principle, provide useful sets of parameter values that can be used to evaluate model predictive uncertainty, though, in practice, some are quickly limited by the “curse of dimensionality” or may have difficulty evaluating irregularly shaped parameter spaces. Adaptive implementation invites model updating, as new data become available reflecting water‐body responses to pollutant load reductions, and a Bayesian approach using MCMC is particularly handy for that task.