道路交通噪声预测声源简化研究

为了分析《环境影响评价技术导则声环境》(HJ 2.4—2009)中将道路声源简化为1条位于道路中心线处的线声源与按照车道数简化为多条线声源之间的误差,针对不同宽度的道路,推导了多条线声源与1条线声源在接收点噪声影响的误差计算公式,并基于Predictor-lima预测软件预测和现场噪声衰减规律实测进行了验证。研究结果表明,对于接收点到道路边缘的距离大于道路宽度的情况,可简化为1条线声源;对于接收点到道路边缘的距离小于道路宽度的情况,应按照车道数简化为多条线声源。     

基于因子分析法优选河流水体中氮浓度预测方法的研究

定量的河流水体中氮浓度预测方法有很多种,如何优选出预测精度较高的方法一直是学术界多年来致力于研究的重点。本研究采用因子分析法对预测方法的精度评价指标进行分析,并建立了预测方法精度的评价模型,对回归分析法、神经网络法、灰色系统法和增长率统计法4种水体氮浓度预测方法进行综合评估,优选出精度较高的河流水体氮浓度预测模型——BP神经网络预测模型。结果表明,此评估模型对类似研究具有一定的参考价值,能为选择出合适的河流水体氮浓度预测方法提供依据。     

湖北“两圈”区域发展可持续性评价与预测

利用可持续发展指数（SDI）对湖北“两圈”各市州发展现状进行了评价,而后利用9年的人均生物资源生态承载量年平均增长率、人口年平均增长率和足迹承载量比值年平均增长率及2006年相关数据对未来44年进行了预测。结果表明,截至2006年底,湖北省有一半以上国土面积的生物资源开采超过当地土地负荷,人均生物资源生态承载量持续下降,资源日益紧张,呈不可持续发展;武汉城市圈2006年生物资源生态足迹超出生物资源生态承载量的32%;鄂西生态文化旅游圈（简称：鄂西生态圈）除襄樊、荆州、荆门因人口多,生物资源生态足迹较大等原因导致SDI值较高外,其他市州的SDI值均较低;神农架的SDI最小;武汉城市圈人均生物资源生态承载量呈负增长,人口控制较好,足迹承载量比值增长较快;鄂西生态圈人均生物资源生态承载量呈负增长,增长速率大于武汉城市圈和湖北省,人口控制较差,足迹承载量比值增长较慢;按照现有发展模式,无论是武汉城市圈还是鄂西生态圈,无论其当前发展是可持续性还是不可持续的,未来他们都将进入不可持续的发展状态。因此,对“两圈”进行规划时要根据各自发展现状制定长期、科学的发展规划.     

事故状态下污染物排放对水环境影响的预测研究

对辽河油田欢喜岭采油厂在事故状态下污染物排放对大凌河水域环境的影响进行预测研究。计算了洪水淹没、油罐冒顶泄漏、油井井喷泄漏、联合站泄漏、管道泄漏、暴雨径流带走落地油等16种情景下对该河流水质的影响情况,并建立数学模型,进行情景模拟。研究结果表明,事故状态下对大凌河水质影响的次序由大到小依次为:洪水淹没、油罐冒顶泄漏、油井井喷泄漏、联合站泄漏、管道泄漏、暴雨径流。     

竹林关大柴沟大型泥石流的形成机理与发展趋势

通过对陕西省丹凤县竹林关镇大柴沟泥石流进行现场勘查分析,总结了泥石流的孕灾背景,揭示了泥石流的典型特征和基本物理力学参数,在此基础上,分别从泥石流的物质来源、形成环境、诱发条件等三大条件分析了泥石流的形成机理,归纳了大柴沟泥石流具有典型的滑坡激发性、周期暴发性、强烈致灾性等特点,对泥石流的危险性进行了现状分析和预测评价。结果表明:软硬相间的岩层和强烈的构造运动是造成岩体变形破碎的主要原因,为泥石流提供了丰富的物源,垂直高差较大、沟道狭窄为泥石流提供了良好的孕灾环境,百年一遇的暴雨是大柴沟泥石流形成的诱发条件,同时受暴雨影响,沟内产生多处浅表层滑坡堵塞沟道,为泥石流聚集了能量,以至形成规模更大、破坏性更强的泥石流。研究过程采用了实测计算与经验公式估算相结合的多种方法进行对比研究,也充分验证了经验公式的适用性。     

Probabilistic Flood Inundation Forecasting Using Rating Curve Libraries

One approach for performing uncertainty assessment in flood inundation modeling is to use an ensemble of models with different conceptualizations, parameters, and initial and boundary conditions that capture the factors contributing to uncertainty. However, the high computational expense of many hydraulic models renders their use impractical for ensemble forecasting. To address this challenge, we developed a rating curve library method for flood inundation forecasting. This method involves pre‐running a hydraulic model using multiple inflows and extracting rating curves, which prescribe a relation between streamflow and stage at various cross sections along a river reach. For a given streamflow, flood stage at each cross section is interpolated from the pre‐computed rating curve library to delineate flood inundation depths and extents at a lower computational cost. In this article, we describe the workflow for our rating curve library method and the Rating Curve based Automatic Flood Forecasting (RCAFF) software that automates this workflow. We also investigate the feasibility of using this method to transform ensemble streamflow forecasts into local, probabilistic flood inundation delineations for the Onion and Shoal Creeks in Austin, Texas. While our results show water surface elevations from RCAFF are comparable to those from the hydraulic models, the ensemble streamflow forecasts used as inputs to RCAFF are the largest source of uncertainty in predicting observed floods.     

Does Including Soil Moisture Observations Improve Operational Streamflow Forecasts in Snow‐Dominated Watersheds?

Changing climate and growing water demand are increasing the need for robust streamflow forecasts. Historically, operational streamflow forecasts made by the Natural Resources Conservation Service have relied on precipitation and snow water equivalent observations from Snow Telemetry (SNOTEL) sites. We investigate whether also including SNOTEL soil moisture observations improve April‐July streamflow volume forecast accuracy at 0, 1, 2, and 3‐month lead times at 12 watersheds in Utah and California. We found statistically significant improvement in 0 and 3‐month lead time accuracy in 8 of 12 watersheds and 10 of 12 watersheds for 1 and 2‐month lead times. Surprisingly, these improvements were insensitive to soil moisture metrics derived from soil physical properties. Forecasts were made with volumetric water content (VWC) averaged from October 1 to the forecast date. By including VWC at the 0‐month lead time the forecasts explained 7.3% more variability and increased the streamflow volume accuracy by 8.4% on average compared to standard forecasts that already explained an average 77% of the variability. At 1 to 3‐month lead times, the inclusion of soil moisture explained 12.3‐26.3% more variability than the standard forecast on average. Our findings indicate including soil moisture observations increased statistical streamflow forecast accuracy and thus, could potentially improve water supply reliability in regions affected by changing snowpacks.     

城市轨道交通噪声的声源特性研究进展

分析了城市轨道交通噪声的主要类型、基本特性、传播规律及其影响因素;综述了国内外城市轨道交通噪声的预测及测量分析技术的研究成果,并对其进行了总结比较,阐述了各种方法的特点、主要成就和局限;最后探讨了城市轨道交通噪声领域今后的研究方向和发展趋势,为解决城市轨道交通发展中的噪声问题提供了参考.     

MODIS Biophysical States and NEXRAD Precipitation in a Statistical Evaluation of Antecedent Moisture Condition and Streamflow1

Abstract: The potential of remotely sensed time series of biophysical states of landscape to characterize soil moisture condition antecedent to radar estimates of precipitation is assessed in a statistical prediction model of streamflow in a 1,420 km² watershed in south‐central Texas, Moderate Resolution Imaging Spectroradiometer (MODIS) time series biophysical products offer significant opportunities to characterize and quantify hydrologic state variables such as land surface temperature (LST) and vegetation state and status. Together with Next Generation Weather Radar (NEXRAD) precipitation estimates for the period 2002 through 2005, 16 raw and deseasoned time series of LST (day and night), vegetation indices, infrared reflectances, and water stress indices were linearly regressed against observed watershed streamflow on an eight‐day aggregated time period. Time offsets of 0 (synchronous with streamflow event), 8, and 16 days (leading streamflow event) were assessed for each of the 16 parameters to evaluate antecedent effects. The model results indicated a reasonable correlation (r² = 0.67) when precipitation, daytime LST advanced 16 days, and a deseasoned moisture stress index were regressed against log‐transformed streamflow. The estimation model was applied to a validation period from January 2006 through March 2007, a period of 12 months of regional drought and base‐flow conditions followed by three months of above normal rainfall and a flood event. The model resulted in a Nash‐Sutcliffe estimation efficiency (E) of 0.45 for flow series (in log‐space) for the full 15‐month period, ?0.03 for the 2006 drought condition period, and 0.87 for the 2007 wet condition period. The overall model had a relative volume error of ?32%. The contribution of parameter uncertainties to model discrepancy was evaluated.     

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。