FRACTIONAL DIFFERENCING MODELING IN HYDROLOGY1

ABSTRACT: Fractional differencing is a tool for modeling time series which have long-term dependence; i.e., series in which the correlation between distant observations, though small, is not negligible. Fractionally differenced ARIMA models are formed by permitting the differencing parameter d in the familiar Box-Jenkins ARIMA(p, d, q) models to take nonintegral values; they permit the simultaneous modeling of the long-term and short-term behavior of an observed time series. This paper discusses the usefulness of fractional differencing to time-series modeling, with emphasis on hydrologic applications. A methodology for fitting fractionally differenced ARIMA models is described, and examples are presented.     

IDENTIFICATION OF AQUIFER DISPERSIVITIES: METHODS OF ANALYSIS AND PARAMETER UNCERTAINTY1

ABSTRACT: This paper presents a method for estimating aquifer dispersivities in solute transport models. Sensitivity equations are derived for the calculation of sensitivity coefficients. A modified Gauss-Newton algorithm is used to perform the least-squares minimization. A statistical procedure is outlined to assess reliability of the estimated parameters. The solute transport model is solved by the upstream weighted, multiple cell balance method which combines the concepts of local mass balance and finite element approximations. A one-dimensional solute transport problem in a vertical column system is first used to illustrate the inverse technique. A second example considers the parameter identification problem for three-dimensional solute transport with a unidirectional steady and uniform flow field. The third example solves the parameter identification problem in a three-dimensional, stream-aquifer, solute transport system with steady state flow. Numerical experiments are conducted to study data requirements for parameter identification.     

AN EVALUATION OF WEEKLY AND MONTHLY TIME SERIES FORECASTS OF MUNICIPAL WATER USE1

ABSTRACT: A cascade model for forecasting municipal water use one week or one month ahead, conditioned on rainfall estimates, is presented and evaluated. The model comprises four components: long term trend, seasonal cycle, autocorrelation and correlation with rainfall. The increased forecast accuracy obtained by the addition of each component is evaluated. The City of Deerfield Beach, Florida, is used as the application example with the calibration period from 1976–1980 and the forecast period the drought year of 1981. Forecast accuracy is measured by the average absolute relative error (AARE, the average absolute value of the difference between actual and forecasted use, divided by the actual use). A benchmark forecast is calculated by assuming that water use for a given week or month in 1981 is the same as the average for the corresponding period from 1976 to 1980. This method produces an AARE of 14.6 percent for one step ahead forecasts of monthly data and 15.8 percent for weekly data. A cascade model using trend, seasonality and autocorrelation produces forecasts with AARE of about 12 percent for both monthly and weekly data while adding a linear relationship of water use and rainfall reduces the AARE to 8 percent in both cases if it is assumed that rainfall is known during the forecast period. Simple rainfall predictions do not increase the forecast accuracy for water use so the major utility of relating water use and rainfall lies in forecasting various possible water use sequences conditioned on sequences of historical rainfall data.     

Hazardous waste site identification using aerial photography: A pilot study in Burlington County,New Jersey,USA

The objective of the project was to identify all hazardous waste sites in Burlington County, New Jersey that could be detected on existing, medium-scale aerial photographs of the county. The complete set of over 1000 black- and-white stereopairs at a scale of 1:12,000 was carefully examined for initial identification of possible sites. All suspicious sites were examined again on color transparencies of the county at the same 1:12,000 scale. Out of the 1094 black- and-white photos, 250 required further checking on color transparencies using a zoom stereoscope. This examination resulted in a final identification of 67 sites, the locations of which were delineated on 1:24,000 USGS maps. The use of air photo interpretation techniques provided an effective procedure for identifying waste sites quickly as well as providing a useful demonstration program for county and state officials.     

SHORT-TERM FORECASTING OF SNOWMELT RUNOFF USING ARMAX MODELS1

ABSTRACT: Time series models of the ARMAX class were investigated for use in forecasting daily riverflow resulting from combined snowmelt/rainfall. The Snowmelt Runoff Model (Martinec-Rango Model) is shown to have a form similar to the ARMAX model. The advantage of the ARMAX approach is that analytical model identification and parameter estimation techniques are available. In addition, previous forecast errors can be included to improve forecasts and confidence limits can be estimated for the forecasts. Diagnostic checks are available to determine if the model is performing properly. Finally, Kalman filtering can be used to allow the model parameters to vary continuously to reflect changing basin runoff conditions. The above advantages result in improved flow forecasts with fewer model parameters.     

绵阳市大气降水pH值时空分布及酸雨成因研究

通过对绵阳市9个测点1998－1999年大气降水监测数据的统计分析，并结合历史数据，对大气降水pH值的时空分布及酸雨成因进行了研究。结果表明：绵阳市大气降水酸化严重，除主要受本地区大气污染影响外，还受大气中、长距离输送的影响。     

快速断电安全技术中半导体中性点开关结构性能的研究

对我国目前半导体中性点开关的结构 ,工作过程 ,性能进行了分析 ;现行中性点开关所存在的问题为电路拓扑结构不合理 ,关断时间过长或过短 ,过长不满足快速断电安全技术的要求 ,过短又易引起过电压 ,使中性点开关失控。笔者提出了采用绝缘门极双极性晶体管 (IGBT) ,构成半导体中性点开关的可行方案。同时指出 ,开发新型快速断电安全技术装置 ,将大大提高我国煤矿安全技术水平     

高层建筑火灾人员疏散和人员伤亡的模拟

基于建筑火灾全风网网络模型的基础上 ,结合紧急疏散模型 ,模拟火灾时期疏散时间和建筑物内人员滞留的情况 ,同时也可以模拟可能出现的伤亡情况 ,有助于高层建筑的疏散系统设计 ,为火灾的再现提供了一个有效的分析工具 ,也为高层建筑火灾的风险评价提供了理论数据     

陕西大暴雨时空分布特征及减灾对策

通过对陕西１９５７～１９９８年共４２年９７个测站的逐日降水量中大暴雨资料进行时间和空间尺度分析，总结归纳出陕西灾害性大暴雨的天气气候基本特征和规律性，并提出相应的减灾对策。     

Use of toxicity identification evaluation techniques to identify dredged material disposal options: A proposed approach

It is common to use the results of various solid-phase and aqueous-fraction toxicity tests as part of the decision-making process for selecting disposal options for dredged sediments. The mere presence of toxicity, however, does not provide a logical basis for selecting economical, environmentally protective disposal techniques. To achieve this, it is necessary to be able to identify specific compounds responsible for sediment toxicity. Toxicity identification evaluation (TIE) procedures, originally developed for complex effluents, represent a useful approach for identifying acutely toxic compounds in dredged materials. Herein we present a conceptual overview for TIE use in part of the decision-making framework for selecting dredged material disposal options; included are discussions concerning appropriate test fractions and species for TIE analyses, and specific TIE manipulations useful for ascertaining whether toxicity is due to any of a number of common sediment contaminants including ammonia, hydrogen sulfide, metals, or nonpolar organics.