Evaluation of a Watershed Model for Estimating Daily Flow Using Limited Flow Measurements1

Abstract: The Soil and Water Assessment Tool (SWAT) model was evaluated for estimation of continuous daily flow based on limited flow measurements in the Upper Oyster Creek (UOC) watershed. SWAT was calibrated against limited measured flow data and then validated. The Nash‐Sutcliffe model Efficiency (NSE) and mean relative error values of daily flow estimations were 0.66 and 15% for calibration, and 0.56 and 4% for validation, respectively. Also, further evaluation of the model’s estimation of flow at multiple locations was conducted with parametric paired t‐test and nonparametric sign test at a 95% confidence level. Among the five main stem stations, four stations were statistically shown to have good agreement between predicted and measured flows. SWAT underestimated the flow of the fifth main stem station possibly because of the existence of complex flood control measures near to the station. SWAT estimated the daily flow at one tributary station well, but with relatively large errors for the other two tributaries. The spatial pattern of predicted flows matched the measured ones well. Overall, it was concluded from the graphical comparisons and statistical analyses of the model results that SWAT was capable of reproducing continuous daily flows based on limited flow data as is the case in the UOC watershed.     

NaCl和KCl对厌氧污泥抑制的动力学研究

在厌氧颗粒污泥和厌氧絮状污泥系统中,进行盐质量浓度(NaCl或KCl质量浓度,下同)对厌氧污泥抑制动力学的研究,得到不同拟合的COD降解动力学方程及参数.实验结果表明:当盐质量浓度为10～30 g/L时,KCl对厌氧污泥的COD比降解速率的抑制程度大于NaCl;当盐质量浓度由0 g/L增至10 g/L时,半速率常数逐渐增加;当盐质量浓度由10 g/L增至30 g/L时,半速率常数逐渐减小;在厌氧污泥系统中,NaCl抑制作用下的盐抑制常数高于KCl,且颗粒污泥的盐抑制常数高于絮状污泥.     

人工神经网络方法在拟建小区域环境质量评价中的应用

人工神经网络的评价方法用于小区域环境质量评价中,根据本地区特点因地制宜地选择环境质量参数,代入模型中进行环境质量评价及预测,对用于环境质量评价的BP人工神经网络模型进行了改进,即对网络模型的训练样本进行了扩充,从而提高了模型的抗干扰能力和准确性.将改进了的BP人工神经网络模型应用于四川省资阳市沱江二桥拟建项目小区域的大气、地表水环境质量评价中, 对该市小区域大气、地表水环境质量状况进行评价,评价结果表明,BP人工神经网络模型用于环境质量评价是可行的,且评价结论客观,评价模型普遍适用.     

可靠性理论在公共安全领域的应用研究

对公共安全体系从系统可靠性的视角,综合运用可靠性方面的知识,构建公共安全系统混联模型;进而将可靠性分配理论与故障树分析方法相结合,根据系统安全目标的要求,确定混联系统的第一层次各单元事件的可靠性目标值,对构成各单元的各个下属单元采取最小工作量可靠度分配方法,从而建立系统中各单元可靠度再分配量化模型。通过建筑物火灾引起人员伤亡事故实例,详述系统各单元可靠性分配的计算过程。研究表明,可靠性理论可以成功地应用到公共安全领域;使系统在给定的目标值条件下达到系统的安全性优化,实现了公共安全保障效能,减小灾害损失。     

战时火力发电厂重要目标分类防护探讨

基于重要目标防护准则和模糊聚类算法,构建火力发电厂目标评价准则指标体系和模糊聚类模型,实现了火力发电厂重要目标的分类防护,进而选用具有针对性的防护措施,解决了重要目标在战时防护措施选择不完善、不合理的问题,有效地提升了战时火力发电厂的生存能力;通过模糊聚类模型实现分类防护,不仅有利于提高重要目标防护效率,而且使得防护资源少、力量弱,供需突出的问题得以改善,同时,在应对自然灾害等重大突发事件发生时,有助于保护发电厂的生产能力。通过案例给出战时某火力发电厂的具体防护措施,合理地解决了发电厂重要目标和关键部位的防护问题。     

道路交叉口冲突仿真分析

针对基于事故的安全评价在数量、周期、均值、随机性等方面以及基于现场冲突观测识别在主观性、可靠性、成本、指标全面性等方面存在的问题,提出基于冲突仿真的交叉口安全预评价分析方法:研究利用安全间接分析(SSAM)模型分析冲突的基本原理和冲突时间(TTC)、遭遇时间(PET)等分析指标的计算方法;以及利用VISSIM仿真软件进行冲突仿真分析应注意的策略。以邢台市某道路交叉口安全改善方案为例,进行改善前后冲突仿真的比较分析。研究结果表明,改善后在通行效率显著提升的同时,交叉、追尾、车道变换冲突的数量均显著减少,TTC值有所增加,说明改善后安全程度有所提升。笔者提出的方法和案例应用为道路交叉口改善措施的安全预评价提供了一种分析途径和有益借鉴。     

金竹山土朱煤矿开采地表沉降规律与灰色预测模型研究

针对金竹山矿业公司土朱煤矿煤层赋存条件,依据采动理论的裂缝垂直分带模型,分析地表沉降和塌陷的机理;提出在采煤活动阶段应进行地表实际位移观测,经数据处理后得到地面沉降曲线,以确保地面人类活动的安全;在采煤活动后阶段则实施灰色预测地面沉降,即通过采煤活动阶段的地表实际观测数据为历史原始数据序列,建立灰色Logistic模型;并对采煤活动后阶段的地面沉降进行预测。精度检验表明:灰色Logistic模型预测精度高,利用该模型预测地面沉降可减少地面沉降监测经费和实时提供预警信息,以确保开采区域内人们生命财产安全。     

Artificial neural network based carbon monoxide persistence models for episodic urban air quality management

This paper describes the development of artificial neural network (ANN) based carbon monoxide (CO) persistence (ANNCOP) models to forecast 8-h average CO concentration using 1-h maximum predicted CO data for the critical (winter) period (November–March). The models have been developed for three 8-h groupings of 10 p.m. to 6 a.m., 6 a.m. to 2 p.m. and 2–10 p.m., at two air quality control regions (AQCRs) in Delhi city, representing an urban intersection and an arterial road consisting heterogeneous traffic flows. The result indicates that time grouping of 2–10 pm is dominantly affected by inversion conditions and peak traffic flow. The ANNCOP model corresponding to this grouping predicts the 8-h average CO concentrations within the accuracy range of 68–71%. The CO persistence values derived from ANNCOP model are comparable with the persistence values as suggested by the Environmental Protection Agency (EPA), USA. This work demonstrates that ANN based model is capable of describing winter period CO persistence phenomena.     

基于BP模型对城市交通噪声的数据处理和预测

城市交通噪声的预测和评价技术是城市交通可持续发展的重要研究内容,直接为城市交通规划中环境容量分析和环境影响评价服务。本文通过实测的大量数据,运用神经网络中的BP模型及其算法建立车辆数、道路宽度和交通噪声之间的关系,对城市道路交通噪声数据进行处理和预测。     

Inverse modeling of multicomponent reactive transport through single and dual porosity media

Compacted bentonite is foreseen as buffer material for high-level radioactive waste in deep geological repositories because it provides hydraulic isolation, chemical stability, and radionuclide sorption. A wide range of laboratory tests were performed within the framework of FEBEX (Full-scale Engineered Barrier EXperiment) project to characterize buffer properties and develop numerical models for FEBEX bentonite. Here we present inverse single and dual-continuum multicomponent reactive transport models of a long-term permeation test performed on a 2.5 cm long sample of FEBEX bentonite. Initial saline bentonite porewater was flushed with 5.5 pore volumes of fresh granitic water. Water flux and chemical composition of effluent waters were monitored during almost 4 years. The model accounts for solute advection and diffusion and geochemical reactions such as aqueous complexation, acid-base, cation exchange, protonation/deprotonation by surface complexation and dissolution/precipitation of calcite, chalcedony and gypsum. All of these processes are assumed at local equilibrium. Similar to previous studies of bentonite porewater chemistry on batch systems which attest the relevance of protonation/deprotonation on buffering pH, our results confirm that protonation/deprotonation is a key process in maintaining a stable pH under dynamic transport conditions. Breakthrough curves of reactive species are more sensitive to initial porewater concentration than to effective diffusion coefficient. Optimum estimates of initial porewater chemistry of saturated compacted FEBEX bentonite are obtained by solving the inverse problem of multicomponent reactive transport. While the single-continuum model reproduces the trends of measured data for most chemical species, it fails to match properly the long tails of most breakthrough curves. Such limitation is overcome by resorting to a dual-continuum reactive transport model.