A NEW LOOK AT FLOOD RISK DETERMINATION1

ABSTRACT: The probability distributions of annual peak flows used in flood risk analysis quantify the risk that a design flood will be exceeded. But the parameters of these distributions are themselves to a degree uncertain and this uncertainty increases the risk that the flood protection provided will in fact prove to be inadequate. The increase in flood risk due to parameter uncertainty is small when a fairly long record of data is available and the annual flood peaks are serially independent, which is the standard assumption in flood frequency analysis. But standard tests for serial independence are insensitive to the type of grouping of high and low values in a time series, which is measured by the Hurst coefficient. This grouping increases the parameter uncertainty considerably. A study of 49 annual peak flow series for Canadian rivers shows that many have a high Hurst coefficient. The corresponding increase in flood risk due to parameter uncertainty is shown to be substantial even for rivers with a long record, and therefore should not be neglected. The paper presents a method of rationally combining parameter uncertainty due to serial correlation, and the stochastic variability of peak flows in a single risk assessment. In addition, a relatively simple time series model that is capable of reproducing the observed serial correlation of flood peaks is presented.     

A modeling assessment of the thermal regime for an urban sport fishery

Water temperature is almost certainly a limiting factor in the maintenance of a self-sustaining rainbow trout (Oncorhynchus mykiss, formerlySalmo gairdneri) and brown trout (Salmo trutta) fishery in the lower reaches of the Cache la Poudre River near Fort Collins, Colorado, USA. Irrigation diversions dewater portions of the river, but cold reservoir releases moderate water temperatures during some periods. The US Fish and Wildlife Service’s Stream Network Temperature Model (SNTEMP) was applied to a 31-km segment of the river using readily available stream geometry and hydrological and meteorological data. The calibrated model produced satisfactory water temperature predictions (R ²=0.88,P<0.001, N=49) for a 62-day summer period. It was used to evaluate a variety of flow and nonflow alternatives to keep water temperatures below 23.3°C for the trout. Supplemental flows or reduced diversions of 3 m³/sec would be needed to maintain suitable summer temperatures throughout most of the study area. Such flows would be especially beneficial during weekends when current irrigation patterns reduce flows. The model indicated that increasing the riparian shade would result in little improvement in water temperatures but that decreasing the stream width would result in significant temperature reductions. Introduction of a more thermally tolerant redband trout (Oncorhynchus sp.), or smallmouth bass (Micropterus dolomieui) might prove beneficial to the fishery. Construction of deep pools for thermal refugia might also be helpful.     

采场通风方式与瓦斯运移规律研究

采场是煤矿生产的核心地带,而采场通风系统是确保采场作业安全,创造良好生产环境的重要环节。本文以采场风流流动及瓦斯运移理论为基础,通过现场试验、模型模拟试验及计算机模拟研究等方法,着重研究了中国常用的和有发展前途的走向长壁后退式U型通风方式、U+L型通曲方式、后退式Y型通风方式条件下采场风流流动及瓦斯运移规律。     

电旋风除尘模型实验研究

本研究试图将电除尘器与旋风除尘器组合为一体,以求取得较高的除尘效率,并利用旋转气流实现自动清灰。本文介绍了切向进气直流式电旋风除尘的模型试验,通过实测不同工况下的除尘效率和压力损失,应用经典除尘理论,建立了相应的数学模型。     

Prediction of thermal hazards from fireballs

Various models of fireball diameter have been evaluated by statistical techniques. The model of Gayle for fireball diameter estimation showed good agreement between the predicted and experimental data. The models relating to fireball duration, transmissivity and view factor have been selected based on their relative merits. A user interactive computer program has been developed to predict thermal hazards from fireballs in chemical process industries.     

四川酸性物湿沉降模式及预测

酸沉降是一复杂的大气物理和化学过程，涉及诸多复杂影响因素。目前，我国酸雨湿沉降模式还仅限于模拟云下洗脱成酸过程，而对云中的成酸过程还未进行深入研究，这不仅在理论上不完善，而且更重要是在许多情况下与我省实际情况不符。本课题针对四川省特定的地理，气象特点和严重的大气污染情况，并借鉴国外研究成果，提出了考虑酸性沉降的云中和云下成酸过程和各种影响因素的综合酸雨湿沉降模式，并根据此模式来估算和预测四川省酸雨     

中国生态农业与绿色食品

本文从农业环境问题和食品安全性出发，阐述了中国生态农业的兴起及特点，绿色食品生产的要求，生态农业与绿色食品的关系。介绍了几种可用于开发绿色食品的优化生态模式。     

PARTITIONING SMALL SCALE SPATIAL VARIABILITY OF RUNOFF AND EROSION ON SAGEBRUSH RANGELAND1

ABSTRACT: Most hydrologic models require input parameters which represent the variability found across an entire landscape. The estimation of such parameters is very difficult, particularly on rangeland. Improved model parameter estimation procedures are needed which incorporate the small-scale and temporal variability found on rangeland. This study investigates the use of a surface soil classification scheme to partition the spatial variability in hydrologic and interrill erosion processes in a sagebrush plant community. Four distinct microsites were found to exist within the sagebrush coppice-dune dune-interspace complex. The microsites explained the majority of variation in hydrologic and interrill erosion response found on the site and were discernable based on readily available soil and vegetation information. The variability within each microsite was quite low and was not well correlated with soil and vegetation properties. The surface soil classification scheme defined in this study can be quite useful for defining sampling procedures, for understanding hydrologic and erosion processes, and for parameterizing hydrologic models for use on sagebrush range-land.     

试用模糊数学方法对电焊作业防护措施进行综合评价

选择北京市四家锅炉厂的电焊工５６名，即从事手把焊、氩弧焊、ＣＯ２气体保护焊、电弧气爆等特种工种作业人员。通过调查，提出单项四级评分标准，再依模糊数学模型，进行综合评价。按Ｂ＝Ａ·Ｒ，求得Ｂ中最大元为０．７０７。最后总评为甲级。此结果与权数分配有关。此方法，可为劳动卫生管理（防护措施评级）提供依据。     

CALCULATION OF NONLINEAR CONFIDENCE AND PREDICTION INTERVALS FOR GROUND-WATER FLOW MODELS1

ABSTRACT: A method is derived to efficiently compute nonlinear confidence and prediction intervals on any function of parameters derived as output from a mathematical model of a physical system. The method is applied to the problem of obtaining confidence and prediction intervals for manually-calibrated ground-water flow models. To obtain confidence and prediction intervals resulting from uncertainties in parameters, the calibrated model and information on extreme ranges and ordering of the model parameters within one or more independent groups are required. If random errors in the dependent variable are present in addition to uncertainties in parameters, then calculation of prediction intervals also requires information on the extreme range of error expected. A simple Monte Carlo method is used to compute the quantiles necessary to establish probability levels for the confidence and prediction intervals. Application of the method to a hypothetical example showed that includsion of random errors in the dependent variable in addition to uncertainties in parameters can considerably widen the prediction intervals.