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.     

Field Evaluation of DRAINMOD 5.1 Under a Cold Climate: Simulation of Daily Midspan Water Table Depths and Drain Outflows1

Abstract: The hydrologic performance of DRAINMOD 5.1 was assessed for the southern Quebec region considering freezing/thawing conditions. A tile drained agricultural field in the Pike River watershed was instrumented to measure tile drainage volumes. The model was calibrated using water table depth and subsurface flow data over a two‐year period, while another two‐year dataset served to validate the model. DRAINMOD 5.1 accurately simulated the timing and magnitude of subsurface drainage events. The model also simulated the pattern of water table fluctuations with a good degree of accuracy. The R² between the observed and simulated daily WTD for calibration was >0.78, and that for validation was 0.93. The corresponding coefficients of efficiency (E) were >0.74 and 0.31. The R² and E values for calibration/validation of subsurface flow were 0.73/0.48 and 0.72/0.40, respectively. DRAINMOD simulated monthly subsurface flow quite accurately (E > 0.82 and R² > 0.84). The model precisely simulated daily/monthly drain flow over the entire year, including the winter months. Thus DRAINMOD 5.1 performed well in simulating the hydrology of a cold region.     

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.     

Integrated model of simulated occupant injury risk and real medical costs

Introduction

The purpose of this study was to develop an integrated methodology that links occupant injury risk functions, estimated in the laboratory, with real world medical treatment costs by using the abbreviated injury score (AIS). Using our model, the expected medical treatment costs for crash injuries to various body regions and of different severities can be investigated.

Methods

First, the simulation results are compared with NHTSA crash data. We used a modified kinematics simulation model that incorporates an F = E^b function as a supplement to the previous Steffan's model to obtain a more accurate acceleration history a(t). Second, head injury criteria HIC₃₆ can be calculated from a(t), and we use the injury probability P as a function of HIC_36, as proposed by Kuppa, to obtain the injury risk function for various AIS values. Third, medical treatment cost models for various AIS values can be calculated by using a regression cost model with real world data. Finally, the injury risk function and medical treatment cost models are linked through AIS values. We establish an integrated methodology and predict medical costs and car safety data using real world police reports, medical treatment costs, and laboratory simulation results.

Results

Using head injuries in frontal crashes as an example, we focus on simulation parameters for different vehicle models, with and without airbags. We specifically examine impact closing speed, Delta-V, and impact directions.

Conclusion

Simulation results can be used to supplement insufficient real crash data, in particular ΔV, and injury risk results from police crash reports.

Impact on industry

The proposed integrated methodology may provide the vehicle industry with a new safety assessment method. Real crash data coupling provides consumers with more realistic and applicable information.     

Modeling perceived collision risk in port water navigation

An increase in the likelihood of navigational collisions in port waters has put focus on the collision avoidance process in port traffic safety. The most widely used on-board collision-avoidance system is the automatic radar plotting aid which is a passive warning system that triggers an alert based on the pilot’s pre-defined indicators of distance and time proximities at the closest point of approaches in encounters with nearby vessels. To better help pilot in decision making in close quarter situations, collision risk should be considered as a continuous monotonic function of the proximities and risk perception should be considered probabilistically. This paper derives an ordered probit regression model to study perceived collision risks. To illustrate the procedure, the risks perceived by Singapore port pilots were obtained to calibrate the regression model. The results demonstrate that a framework based on the probabilistic risk assessment model can be used to give a better understanding of collision risk and to define a more appropriate level of evasive actions.     

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.     

基于人工免疫原理的事故预防研究

介绍生物免疫识别模式,分析事故预防过程的实质是抑制潜在危险转化成事故的控制过程,分析比较事故预防与生物免疫识别模式在作用、生存环境、动作触发源等的共性,构建了基于免疫识别模式的事故预防系统并建立了事故预防数学模型;定义事故预防系统的识别率、失效率、误判率并给出了数学表达式,指出监测生产系统各环节状态信息是否符合系统的安全要求就是识别潜在危险的过程,是事故预防的关键,基于人工免疫原理的事故预防数学模型具有较强的健壮性、自适应性和动态防护性等特点。     

航空不安全事件人为因素分析R-S-TER模型的构建与应用研究

借鉴传统人为因素分析Reason模型和SHEL模型,结合TER模型的特点构建航空不安全事件人为因素分析的R-S-TER模型。分别采用Dijkstra算法和坐标轴方法应用R-S-TER模型对单个和多个航空不安全事件进行研究,找出各个不安全事件的主要事故链。运用C语言程序计算出了预防航空不安全事件的最优方案。应用R-S-TER模型可以有效地达到预防航空不安全人为因素的目的。     

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。