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.     

RUNOFF PREDICTION USING REMOTE SENSING IMAGERY1

ABSTRACT: Percent imperviousness is an important parameter in modeling the urban rainfall-runoff process and is usually determined using manual methods such as random sampling or conventional accounting methods. In this study two computerized methods are used for estimating the percent imperviousness of urban watersheds using high altitude remote sensing imagery. These methods include the Laser Image Processing Scanner and the Video-Tape Camera system. Imperviousness is directly estimated in the former method while in the latter it is estimated as a function of the statistics of the responses on emulsions of the imagery. The percent imperviousness computed by utilizing remote sensing imagery was used with the conceptual models of rainfall-runoff models. The models were applied to four urban watersheds and the runoff prediction results indicate that imperviousness determined by using remote sensing imagery was as accurate as that obtained by the manual methods, and that the use of remote sensing imagery requires significantly less time and money.     

CN算法应用于我国23次强震的预测研究

本文用CN算法研究了我国近期大陆东部和西部南北带及邻近区域共23次强震前的TIP,即强震发生概率增长时间。结果表明,18次强震发生在被判定的强震发生概率增长时间的TIP内。TIP警戒约占总研究时空域的30％,获得了较好的中期地震预测效果。表明CN算法可作为强震中期预测的手段之一。     

由三个地震模式讨论1995年日本阪神大震的预报问题

本文由我们已往提出的三个地震模式讨论了１９９５年日本阪神大震（Ｍ７．２）的预报问题。这些模式是立交模式、组合模式和调制模式。此外还用柯里奥利力（Ｃｏｒｒｉｏｌｉ）的效应讨论了主震３年后最强余震的预报。     

Potential and Shortcomings of Numerical Weather Prediction Models in Providing Meteorological Data for Urban Air Pollution Forecasting

The last decade progress in numericalweather prediction (NWP) modelling and studies of urbanatmospheric processes for providing meteorological data forurban air pollution forecasting is analysed on examples ofseveral European meteorological centres. Modern nested NWP models are utilising land-use databasesdown to 1 km resolution or finer, and are approaching thenecessary horizontal and vertical resolution suitable forcity scale. The recent scientific developments in the fieldof urban atmospheric physics and the growing availabilityof high-resolution urban surface characteristics datapromise further improvements of the capability of NWPmodels for this aim. A strategy to improve NWP data forthe urban air pollution forecasting is suggested.     

基于神经网络的温度预测

室内温度与诸多影响因素之间的非线性、复杂性等关系 ,给建模、预测带来了难度 ,引入了人工神经网络 ;利用人工神经网络的非线性、并行计算和自学习特性进行建模 ,实现了对温度模拟     

降低企业库存风险问题研究

大多数企业都面临着库存风险问题 ,库存过多 ,造成积压 ,不仅占用大量资金和场地 ,加重企业的利息负担 ,而且长期存放会使物品陈旧过时 ,失去原有的价值和使用价值。如何降低库存风险 ,使库存经常处于合理水平 ,是每个企业都十分关心的问题。笔者分析了库存管理中存在的问题 ,提出需求预测和安全库存的确定 ,是降低库存风险的两个重要前提 ,同时讨论了安全库存的计算方法 ,以及降低库存风险的主要措施     

W_q方法及σ_H方法在华东地区中强震预报中的应用

应用两种描述地震活动平静的特征参数Wq 和σH 对华东地区 1972年以来ML≥ 2 .3地震进行时空扫描。结果表明 :Wq 在华东地区大多数M >5地震之前均出现 1年左右或稍长时间的平静异常 ,震中一般在平静异常区的边缘或内部。对Wq 空间异常区σH 的时间扫描在某些地区也能够较好地显示1年左右的平静异常。这可能说明了地震活动平静也是中强地震的一种中短期预报指标     

热带气旋的短期气候预报检验

用非线性预报的方法，作西太平洋、南海、以及登陆我国、登陆广东热带气旋的短期气候预测，用逐日气压场作登陆广东热带气旋的时段和地段以及南海海面带气旋出现的时间的气候预测。对近3年的热带气候预报进行检验，效果较满意。     

我国农业水旱灾害的时间分布及重灾年景趋势预测

分析了我国 1970～ 1999年农业水旱灾害的时间分布特征。分析结果表明 :在研究时段内 ,我国农业自然灾害总体上呈增长态势。该时段可划分为两个明显的阶段 :80年代中期以前 ,总灾、水灾及旱灾对农业生产的危害较轻 ;80年代中期之后 ,呈现出影响范围广、损失增大的趋势 ,重灾年份明显增加。旱灾和水灾是威胁我国农业生产最为严重的自然灾害 ,尤以旱灾为甚。我国农业遭受旱灾威胁的范围多年基本不变 ,而旱灾受灾率波动明显 ,成灾率逐年增长 ,这与近几年农田水利设施建设缓慢、灌溉能力降低有关 ;水灾受灾率和成灾率具有特别显著的同步特点 ,表明水灾致灾能力强 ,一旦发生 ,极易成灾 ,水灾危害加剧与防洪、抗洪能力低下及生态环境恶化有关。各灾种的受灾率和成灾率呈正相关关系 ,表明我国农业生产系统的抗灾能力总体上较弱。　　本文还用灰色系统理论的建模方法 ,建立了农业总受灾率 -总成灾率、水灾受灾率 -成灾率、旱灾受灾率 -成灾率的重灾年景灰色灾变GM(1,1)预测模型 ,对未来 10年我国农业灾害趋势进行了预测分析。灰色预测结果表明 ,2 0 10年之前 ,除 2 0 0 3,2 0 0 6年水旱灾害危害较小外 ,其它年份均为灾情严重年份 ,其受灾率和成灾率均高于近 30年的平均水平。其中 ,2 0 0 4 ,2 0 0 7年将为水灾重