ESTIMATION OF LONG-TERM DISCHARGE STATISTICS BY REGIONAL ADJUSTMENT1

ABSTRACT: A regional adjustment relationship was developed to estimate long-term (30-year) monthly median discharges from short term (three-year) records. This method differs from traditional approaches in that it is based on site-specific discharge data but does not require correlation of these data with discharges from a single hydrologically similar long-term gage. The method is shown to be statistically robust, and applicable to statistics other than the median.     

Acceleration of Exotic Plant Invasion in a Forested Ecosystem by a Generalist Herbivore

Abstract: The successful invasion of exotic plants is often attributed to the absence of coevolved enemies in the introduced range (i.e., the enemy release hypothesis). Nevertheless, several components of this hypothesis, including the role of generalist herbivores, remain relatively unexplored. We used repeated censuses of exclosures and paired controls to investigate the role of a generalist herbivore, white‐tailed deer (Odocoileus virginianus), in the invasion of 3 exotic plant species (Microstegium vimineum, Alliaria petiolata, and Berberis thunbergii) in eastern hemlock (Tsuga canadensis) forests in New Jersey and Pennsylvania (U.S.A.). This work was conducted in 10 eastern hemlock (T. canadensis) forests that spanned gradients in deer density and in the severity of canopy disturbance caused by an introduced insect pest, the hemlock woolly adelgid (Adelges tsugae). We used maximum likelihood estimation and information theoretics to quantify the strength of evidence for alternative models of the influence of deer density and its interaction with the severity of canopy disturbance on exotic plant abundance. Our results were consistent with the enemy release hypothesis in that exotic plants gained a competitive advantage in the presence of generalist herbivores in the introduced range. The abundance of all 3 exotic plants increased significantly more in the control plots than in the paired exclosures. For all species, the inclusion of canopy disturbance parameters resulted in models with substantially greater support than the deer density only models. Our results suggest that white‐tailed deer herbivory can accelerate the invasion of exotic plants and that canopy disturbance can interact with herbivory to magnify the impact. In addition, our results provide compelling evidence of nonlinear relationships between deer density and the impact of herbivory on exotic species abundance. These findings highlight the important role of herbivore density in determining impacts on plant abundance and provide evidence of the operation of multiple mechanisms in exotic plant invasion.     

地震损失经济学评估模型灾损参数的统计研究

地震应急管理有助于震后救灾工作的顺利进行。传统的灾损评估需要有关人员进入现场根据地震破坏情况进行评估,这会影响评估的时效性。通过对地震灾损参数进行统计学研究,利用现有的研究成果,以统计指数、数据包络分析为理论基础,将现有的基于不同房屋结构类型、不同破坏等级的震害矩阵进行降维,确定了灾损参数,并以青海玉树地震为例,运用灾损参数实现了灾损的快速评估。     

种间关系预测(ICE)模型在水质基准研究中的应用

水质基准研究主要是基于物种的实验室测试的毒性数据开展的。对于一些毒性数据相对缺乏的化学品,水质基准研究就会受到一定的影响。本文从水质基准研究方法的角度,阐述了种间关系预测(ICE)的基本原理和基本方法,系统介绍了ICE模型的毒性预测方法在水质基准研究中的应用,并通过锌的ICE案例研究证明了模型在中国的可利用性。同时,对ICE模型的不确定性和适用性进行了分析。最后,对ICE模型存在的问题和未来的发展方向进行了探索和展望。     

基于修正A值法估算西安市大气环境容量研究

采用以单箱模型法为基础的A值法对西安市大气容量进行估算,并将干沉降、湿沉降和化学转化三个消除过程引入模型测算中,借鉴国内外对于大气常规污染物的清除系数的科学研究成果,对研究区域的SO2、NO2、PM10及PM2.5等4项常规污染物的环境容量进行估算。结果表明,执行2012年新的环境质量标准下,西安市SO2、NO2、PM10及PM2.5大气环境容量分别为13.86×104吨/年,9.24×104吨/年、1.62×105吨/年及8.09×104吨/年。     

Applied tracer tests in fractured rock: Can we predict natural gradient solute transport more accurately than fracture and matrix parameters?

Applied tracer tests provide a means to estimate aquifer parameters in fractured rock. The traditional approach to analysing these tests has been using a single fracture model to find the parameter values that generate the best fit to the measured breakthrough curve. In many cases, the ultimate aim is to predict solute transport under the natural gradient. Usually, no confidence limits are placed on parameter values and the impact of parameter errors on predictions of solute transport is not discussed. The assumption inherent in this approach is that the parameters determined under forced conditions will enable prediction of solute transport under the natural gradient. This paper considers the parameter and prediction uncertainty that might arise from analysis of breakthrough curves obtained from forced gradient applied tracer tests. By adding noise to an exact solution for transport in a single fracture in a porous matrix we create multiple realisations of an initial breakthrough curve. A least squares fitting routine is used to obtain a fit to each realisation, yielding a range of parameter values rather than a single set of absolute values. The suite of parameters is then used to make predictions of solute transport under lower hydraulic gradients and the uncertainty of estimated parameters and subsequent predictions of solute transport is compared. The results of this study show that predictions of breakthrough curve characteristics (first inflection point time, peak arrival time and peak concentration) for groundwater flow speeds with orders of magnitude smaller than that at which a test is conducted can sometimes be determined even more accurately than the fracture and matrix parameters.     

USING ARTIFICIAL NEURAL NETWORKS TO ESTIMATE MISSING RAINFALL DATA1

ABSTRACT: Missing rainfall data from a time series or a spatial field of observations can present a serious obstacle to data analysis, modeling studies and operational forecasting in hydrology. Numerous schemes for replacing missing data have been proposed, ranging from simple weighted averages of data points that are nearby in time and space to complex statistically-based interpolation methods and function fitting schemes. This paper presents a technique for replacing missing spatial data using a backpropagation neural network applied to concurrent data from nearby gauges. Tests performed on a sample of gauges in the Middle Atlantic region of the United States show that this technique produces results that compare favorably to simple techniques such as arithmetic and distance-weighted averages of the values from nearby gauges, and also to linear optimization methods such as regression.     

MODELING GROUND WATER FLOW USING FLUX BOUNDARY CONDITIONS1

ABSTRACT: Determination of the boundary conditions for modeling ground water flow is a critical point especially in regional models. Normally the regional models require model areas that are greater than the given area of interest. This work focuses on the prediction of hydraulic heads in regional models using flux boundary conditions. The model uses flux boundary conditions that were estimated using a radial flow analog and Darcy's law. The regional model that is presented uses no parameter identification (inverse estimation) procedures. In the present work, the Houston area was used. The simulation of the hydrological conditions of the Chicot and Evangeline Aquifers that underlie the Houston area were made using the available information about the geological profile in the Houston region and the current information about the existing production wells. The regional model works as a forward problem. The system parameters such as hydraulic conductivity, specific storage, and hydrological stresses were specified, and the model predicts the hydraulic head. Actual data from piezometers operated by the U.S. Geological Survey (USGS) in many places throughout Houston were used as initial conditions. Some piezometric head data were generated using the regional variable theory called kriging to supply head estimates in areas where data were unavailable. The Modular Three Dimensional Finite Difference Groundwater Flow Model developed by the USGS was used to predict the hydraulic heads. The predicted ground water heads are compared to the actual data. The results show that the model performs well for locations where data were available.     

NON-ZERO LOWER LIMIT IN LOW FLOW FREQUENCY ANALYSIS?1

ABSTRACT: The implications of fitting distributions with non-zero lower limits to low flow data are examined. The 3-parameter Weibull distribution is fitted to annual minimum flow series from 60 long term stations in Canada. The relations between the estimated lower limit and three sampling variables (skewness, smallest, and largest observations) were investigated. The lower limit strongly depends on the sample skewness; it varies directly with the sample skewness, which in turn is highly influenced by the largest observation. For a given skewness, the value of the estimated lower limit is determined by the value of the smallest observation. Therefore, the lower limit cannot be accurately determined, and the resulting low flow estimates will be either too small or too high.     

THE EFFECT OF MAINTENANCE ON STORM WATER DETENTION BASIN EFFICIENCY1

ABSTRACT: Storm water detention is an effective and popular method for controlling the effects of increased urbanization and development. Detention basins are used to control both increases in flow rates and sedimentation. While numerous storm water management policies have been proposed, they most often fail to give adequate consideration to maintenance of the basin. Sediment accumulation with time and the growth of grass and weeds in the emergency spillway are two maintenance problems. A model that was calibrated with data from a storm water detention basin in Montgomery County, Maryland, is used to evaluate the effect of maintenance on the efficiency of the detention basin. Sediment accumulation in the basin caused the peak reduction factor to decrease while it increased as vegetation growth in the emergency spillway increased. Thus, the detention basin will not function as intended in the design when the basin is not properly maintained. Thus, maintenance of detention basins should be one component of a comprehensive storm water management policy.