Uncertainty Assessment for Management of Soil Contaminants with Sparse Data

In order for soil resources to be sustainably managed, it is necessary to have reliable, valid data on the spatial distribution of their environmental impact. However, in practice, one often has to cope with spatial interpolation achieved from few data that show a skewed distribution and uncertain information about soil contamination. We present a case study with 76 soil samples taken from a site of 15 square km in order to assess the usability of information gleaned from sparse data. The soil was contaminated with cadmium predominantly as a result of airborne emissions from a metal smelter. The spatial interpolation applies lognormal anisotropic kriging and conditional simulation for log-transformed data. The uncertainty of cadmium concentration acquired through data sampling, sample preparation, analytical measurement, and interpolation is factor 2 within 68.3 % confidence. Uncertainty predominantly results from the spatial interpolation necessitated by low sampling density and spatial heterogeneity. The interpolation data are shown in maps presenting likelihoods of exceeding threshold values as a result of a lognormal probability distribution. Although the results are not deterministic, this procedure yields a quantified and transparent estimation of the contamination, which can be used to delineate areas for soil improvement, remediation, or restricted area use, based on the decision-makers probability safety requirement.     

Uncertainty Analysis In Dissolved Oxygen Modeling in Streams

Uncertainty analysis in surface water quality modeling is an important issue. This paper presents a method based on the first-order reliability method (FORM) to assess the exceedance probability of a target dissolved oxygen concentration in a stream, using a Streeter–Phelps prototype model. Basic uncertainty in the input parameters is considered by representing them as random variables with prescribed probability distributions. Results obtained from FORM analysis compared well with those of the Monte Carlo simulation method. The analysis also presents the stochastic sensitivity of the probabilistic outcome in the form of uncertainty importance factors, and shows how they change with changing simulation time. Furthermore, a parametric sensitivity analysis was conducted to show the effect of selection of different probability distribution functions for the three most important parameters on the design point, exceedance probability, and importance factors. Note: This version was published online in June 2005 with the cover date of August 2004.     

Early Effects of Atmospheric Ammonia Deposition on Calluna Vulgaris (L.) Hull Growing on an Ombrotrophic Peat Bog

This paper reports data from a field study investigating the impacts of elevated ammonia (NH₃) deposition on Calluna vulgaris growing on an ombrotrophic peat bog in S.E. Scotland. Shoot extension, foliar N concentrations, chlorophyll concentration and chlorophyll fluorescence were measured during the second growing season of exposure to a gradient of ammonia concentrations. Results indicate that NH₃ increases growth between 150–200 kg N ha^–1y^–1 cumulative deposition. Foliar N content increased significantly in response to NH₃ cumulative deposition up to 400 kg N ha^–1 y^–1 whereas chlorophyll a content significantly decreased. Measurements of Fv/Fm suggest that although NH₃ exposure altered the growth and reduced chlorophyll a, the efficiency of photosystem II was insensitive to NH₃-N deposition at this stage.     

Ecological Impact Assessment in Data-Poor Systems: A Case Study on Metapopulation Persistence

Legislation on the protection of biodiversity (e.g., European Union Habitat and Bird Directives) increasingly requires ecological impact assessment of human activities. However, knowledge and understanding of relevant ecological processes and species responses to different types of impact are often incomplete. In this paper we demonstrate with a case study how impact assessment can be carried out for situations where data are scarce but some expert knowledge is available. The case study involves two amphibian species, the great crested newt (Triturus cristatus) and the natterjack toad (Bufo calamita) in the nature reserve the Meinweg in the Netherlands, for which plans are being developed to reopen an old railway track called the Iron Rhine. We assess the effects of this railway track and its proposed alternatives (scenarios) on the metapopulation extinction time and the occupancy times of the patches for both species using a discrete-time stochastic metapopulation model. We quantify the model parameters using expert knowledge and extrapolated data. Because of our uncertainty about these parameter values, we perform a Monte Carlo uncertainty analysis. This yields an estimate of the probability distribution of the model predictions and insight into the contribution of each distinguished source of uncertainty to this probability distribution. We show that with a simple metapopulation model and an extensive uncertainty analysis it is possible to detect the least harmful scenario. The ranking of the different scenarios is consistent. Thus, uncertainty analysis can enhance the role of ecological impact assessment in decision making by making explicit to what extent incomplete knowledge affects predictions.     

基于GIS的毒气泄漏和扩散模拟及其影响评估

详细讨论了基于GIS(Arc View3．2)的毒气泄漏与扩散模拟的实现及扩散影响的评价。考虑到GIS二次开发语言的局限性,利用外部程序语言开发了毒气扩散浓度空间分布的计算程序,动态链接到GIS系统中来实现模拟。为减轻城市和大型企业在地震下有毒物质的泄漏与扩散灾害和应急反应提供了有效手段,也为平时有毒物质类重大危险源的管理提供了依据。     

森林火险等级分布模拟--中小尺度动力学模式

通过在地形坐标系中建立考虑森林植被影响的三维大气-土壤耦合动力学模式,对神农架林区历史上几次重大森林火灾发生期的气象要素场进行了模拟,并在此基础上计算神农架林区高分辨率的森林火险等级分布状态,揭示了林火发生的一些重要规律。     

环境水动力数值模拟的研究现状与展望

水动力数值模拟为水环境中污染物的迁移转化提供了重要的背景。水动力数值模拟的发展经历了数值计算、单因素模拟、多因素模拟3个阶段。本文在分析了环境水动力数值模拟的发展过程与研究现状的基础上,结合当前学科发展动态,预测了其未来研究的主要方向。     

EVALUATION OF PROBABILITY DENSITY FUNCTIONS IN PRECIPITATION MODELS FOR THE PACIFIC NORTHWEST1

ABSTRACT: Recent work has found that a one-parameter Weibull model of wet day precipitation amount based on the Weibull distribution provides a better fit to historical daily precipitation data for eastern U.S. sites than other one-parameter models. The general two-parameter Weibull distribution was compared in this study to other widely used distributions for describing the distribution of daily precipitation event sizes at 99 sites from the U.S. Pacific Northwest. Surprisingly little performance was sacrificed by reducing the two-parameter Weibull to a single-parameter distribution. Advantages of the single-parameter model included requiring only the mean wet day precipitation amount for calibration, invertibility for simulation purposes, and ease of analytical manipulation. The fit of the single-parameter Weibull to the 99 stations included in this study was significantly better than other single-parameter models tested, and performed as well as the widely endorsed, more cumbersome, two-parameter gamma model. Both the one-and two-parameter Weibull distributions are shown to have b-moments that are consistent with historical precipitation data, while the ratio of b-skew and b-variance in the gamma model is inconsistent with the historical recerd by this measure. In addition, it was found that the two-parameter gamma distribution was better fit using the method of moments estimators than maximum likelihood estimates. These findings suggested that the distribution in precipitation among sites in the Pacific Northwest with dramatically different settings are nearly identical if expressed in proportion to the mean site event size.     

LARGE AREA HYDROLOGIC MODELING AND ASSESSMENT PART II: MODEL APPLICATION1

ABSTRACT: This paper describes the application of a river basin scale hydrologic model (described in Part I) to Richland and Chambers Creeks watershed (RC watershed) in upper Trinity River basin in Texas. The inputs to the model were accumulated from hydro-graphic and geographic databases and maps using a raster-based GIS. Available weather data from 12 weather stations in and around the watershed and stream flow data from two USGS stream gauge station for the period 1965 to 1984 were used in the flow calibration and validation. Sediment calibration was carried out for the period 1988 through 1994 using the 1994 sediment survey data from the Richland-Chambers lake. Sediment validation was conducted on a subwatershed (Mill Creek watershed) situated on Chambers Creek of the RC watershed. The model was evaluated by well established statistical and visual methods and was found to explain at least 84 percent and 65 percent of the variability in the observed stream flow data for the calibration and validation periods, respectively. In addition, the model predicted the accumulated sediment load within 2 percent and 9 percent from the observed data for the RC watershed and Mill Creek watershed, respectively.     

LARGE AREA HYDROLOGIC MODELING AND ASSESSMENT PART I: MODEL DEVELOPMENT1

ABSTRACT: A conceptual, continuous time model called SWAT (Soil and Water Assessment Tool) was developed to assist water resource managers in assessing the impact of management on water supplies and nonpoint source pollution in watersheds and large river basins. The model is currently being utilized in several large area projects by EPA, NOAA, NRCS and others to estimate the off-site impacts of climate and management on water use, non-point source loadings, and pesticide contamination. Model development, operation, limitations, and assumptions are discussed and components of the model are described. In Part II, a GIS input/output interface is presented along with model validation on three basins within the Upper Trinity basin in Texas.