Sensitivity and Uncertainty of Ground‐Water Discharge Estimates for Semiarid Shrublands1

Abstract: We proposed a step‐by‐step approach to quantify the sensitivity of ground‐water discharge by evapotranspiration (ET) to three categories of independent input variables. To illustrate the approach, we adopt a basic ground‐water discharge estimation model, in which the volume of ground water lost to ET was computed as the product of the ground‐water discharge rate and the associated area. The ground‐water discharge rate was assumed to equal the ET rate minus local precipitation. The objective of this study is to outline a step‐by‐step procedure to quantify the contributions from individual independent variable uncertainties to the uncertainty of total ground‐water discharge estimates; the independent variables include ET rates of individual ET units, areas associated with the ET units, and precipitation in each subbasin. The specific goal is to guide future characterization efforts by better targeting data collection for those variables most responsible for uncertainty in ground‐water discharge estimates. The influential independent variables to be included in the sensitivity analysis are first selected based on the physical characteristics and model structure. Both regression coefficients and standardized regression coefficients for the selected independent variables are calculated using the results from sampling‐based Monte Carlo simulations. Results illustrate that, while as many as 630 independent variables potentially contribute to the calculation of the total annual ground‐water discharge for the case study area, a selection of seven independent variables could be used to develop an accurate regression model, accounting for more than 96% of the total variance in ground‐water discharge. Results indicate that the variability of ET rate for moderately dense desert shrubland contributes to about 75% of the variance in the total ground‐water discharge estimates. These results point to a need to better quantify ET rates for moderately dense shrubland to reduce overall uncertainty in estimates of ground‐water discharge. While the approach proposed here uses a basic ground‐water discharge model taken from an earlier study, the procedure of quantifying uncertainty and sensitivity can be generalized to handle other types of environmental models involving large numbers of independent variables.     

Using Multi-Scale Sampling and Spatial Cross-Correlation to Investigate Patterns of Plant Species Richness

Land managers need better techniques to assess exoticplant invasions. We used the cross-correlationstatistic, I _YZ, to test for the presence ofspatial cross-correlation between pair-wisecombinations of soil characteristics, topographicvariables, plant species richness, and cover ofvascular plants in a 754 ha study site in RockyMountain National Park, Colorado, U.S.A. Using 25 largeplots (1000 m²) in five vegetation types, 8 of 12variables showed significant spatial cross-correlationwith at least one other variable, while 6 of 12variables showed significant spatial auto-correlation. Elevation and slope showed significant spatialcross-correlation with all variables except percentcover of native and exotic species. Percent cover ofnative species had significant spatialcross-correlations with soil variables, but not withexotic species. This was probably because of thepatchy distributions of vegetation types in the studyarea. At a finer resolution, using data from ten1 m² subplots within each of the 1000 m² plots, allvariables showed significant spatial auto- andcross-correlation. Large-plot sampling was moreaffected by topographic factors than speciesdistribution patterns, while with finer resolutionsampling, the opposite was true. However, thestatistically and biologically significant spatialcorrelation of native and exotic species could only bedetected with finer resolution sampling. We foundexotic plant species invading areas with high nativeplant richness and cover, and in fertile soils high innitrogen, silt, and clay. Spatial auto- andcross-correlation statistics, along with theintegration of remotely sensed data and geographicinformation systems, are powerful new tools forevaluating the patterns and distribution of native andexotic plant species in relation to landscape structure.     

Nutrient dynamics between sediment and overlying water in the inner part of Izmir Bay, Eastern Aegean

In this article a concept is described in order to predict and map the occurrence of benthic communities within and near the German Exclusive Economic Zone (EEZ) of the North Sea. The approach consists of two work steps: (1) geostatistical analysis of abiotic measurement data and (2) calculation of benthic provinces by means of Classification and Regression Trees (CART) and GIS-techniques. From bottom water measurements on salinity, temperature, silicate and nutrients as well as from punctual data on grain size ranges (0–20, 20–63, 63–2,000 μ) raster maps were calculated by use of geostatistical methods. At first the autocorrelation structure was examined and modelled with help of variogram analysis. The resulting variogram models were then used to calculate raster maps by applying ordinary kriging procedures. After intersecting these raster maps with punctual data on eight benthic communities a decision tree was derived to predict the occurrence of these communities within the study area. Since such a CART tree corresponds to a hierarchically ordered set of decision rules it was applied to the geostatistically estimated raster data to predict benthic habitats within and near the EEZ.     

2007年11-12月国内环境事件

简要统计了2007年11-12月国内发生的各种环境事件47起,包括沙尘天气2起,污染事件15起,地震22起,山体滑坡和泥石流6起,以及旱灾2起.对自然灾害进行了讨论.     

江苏省空气质量预报准确度及改进方法分析

介绍了江苏省重污染天气监测预报预警系统以及大气重污染预警会商流程,将2015年13个地级市的模式预报、人工预报结果分别与实际观测值进行比较。结果表明:人工预报更准确,PM_(2.5)日均值、臭氧日最大8 h平均值、AQI 3个指标人工预报和实况的相关性分别比模式预报高出12.8%、0.3%、11.4%,平均标准误差(MNE)分别低20.7%、3.1%、23.1%。依据国家空气质量预报技术指南评分办法,对各市2015年全年空气质量级别为"良"时进行评分。通过开展07∶00预报更新,使2015年上半年空气质量预报级别得分平均提高了0.9分,全年级别得分平均提高了2.6分;通过改进模式预报参数,使PM_(2.5)日均预报值、臭氧日最大8 h平均预报值、AQI预报值和实际观测值的相关性比上年同期分别提高26.0%、5.0%、33.9%,MNE分别降低3.6%、31.3%、7.6%。     

新形势下对环境统计工作的思考

分析了环境统计工作的定位和内容,以及第二次全国污染源普查、排污许可证与排污税制度、环境质量考核制度给环境统计工作带来的改革契机。针对固定源、城镇生活源与农业面源、移动源,提出了统计调查工作的设想。建议改变环境统计调查焦点,实现污染源统计空间格局"一张图";开拓环境统计分析品牌,推动环境统计方法研究;以政策管理需求为导向,完成环境统计工作体系的重构。     

RISK OF EXTREME EVENTS IN A MULTIOBJECTIVE FRAMEWORK1

ABSTRACT: This paper summarizes advances made in risk-based decisionmaking in water resources through use of the partitioned multiobjective risk method (PMRM). (Risk is a measure of the probability and severity of adverse effects.) In the PMRM, the risk of extreme events is differentiated from risk involving less extreme damage severity and is evaluated within a multiobjective framework. Study of the extreme-event risk function f₄(*) has addressed the following issues: methods for calculating f₄(*); the sensitivity of f₄(*) to various parameters, particularly to the partitioning point of the extreme-event range and the selection of probability density functions; insight provided by the statistics of extremes; and the impact of f₄(*) on risk management, for example, in the application of the PMRM to water resources problems. In particular, this paper shares with the reader recent research results on the PMRM, the relationship between the statistics of extremes and the conditional expected value, derived formulas for f₄(*), distribution-free estimates of f₄(*), documented case studies in dam safety, and future research directions.     

UNCERTAINTY OF EXTREME FLOOD ESTIMATES INCORPRATING HISTORICAL DATA1

ABSTRACT: The ability to predict extreme floods is an important part of the planning process for any water project for which failure will be very costly. The length of a gage record available for use in estimating extreme flows is generally much shorter than the recurrence interval of the desired flows, resulting in estimates having a high degree of uncertainty. Maximum likelihood estimators of the parameters of the three parameter lognormal (3PLN) distribution, which make use of historical data, are presented. A Monte Carlo study of extreme flows estimated from samples drawn from three hypothetical 3PLN populations showed that inclusion of historical flows with the gage record reduced the bias and variance of extreme flow estimates. Asymptotic theory approximations of parameter variances and covariances calculated using the second and mixed partial derivatives of the log likelihood function agreed well with Monte Carlo results. First order approximations of the standard deviations of the extreme flow estimates did not agree with the Monte Carlo results. An alternative method for calculating those standard deviations, the “asymptotic simulation” method, is described. The standard deviations calculated by asymptotic simulation agree well with the Monte Carlo results.     

GROUND AND SURFACE WATER QUALITY IMPACTS OF NORTH CAROLINA SANITARY LANDFILLS1

ABSTRACT: Ground and surface water quality monitoring data from 71 municipal sanitary landfills in North Carolina were analyzed to determine the nature and extent of current contamination problems and identify any common characteristics associated with this contamination. A total of 322 surface and 411 ground water quality records were analyzed using the SAS data system. Almost all the landfill records included inorganic and heavy metal analyses while approximately half of the records also included organic analyses by CC/MS. Our analysis indicates that landfills are having measurable impacts on ground and surface water quality, but these impacts may not be as severe as is commonly assumed. Statistically significant increases were detected in the average concentrations in ground water and downstream surface water samples when compared to upstream surface water samples. The largest percentage increases were observed for zinc, turbidity, total organic carbon, conductivity, total dissolved solids, and lead. Violations of ground water quality standards for heavy metals and hazardous organic compounds were detected at 53 percent of the landfills where adequate data existed. The moat common heavy metal violations were for lead (18 percent), chromium (18 percent), zinc (6 percent), cadmium (6 percent), and arsenic (6 percent) (percentage of landfills violating shown in parenthesis). The organic compounds that appear to pose the greatest threat to ground water are the chlorinated solvents (8 percent), petroleum derived hydrocarbons (8 percent), and pesticides (5 percent). A comparison of monitoring data from sanitary landfills and secondary wastewater treatment plants suggests that the concentrations of heavy metal and organic pollutants discharged to surface waters from these two sources are similar.     

城市污水测算统计方法

当今城市生活污水统计以人口与供水量为依据测算 ,难以满足治理和管理工作需要。在城市污水处理场和污水在线监控系统建设快速发展条件下建立以排污口监测统计为基础的城市污水统计系统 ,能够较真实反映生活污水质量和分布 ,满足环境管理工作需要。