METHODS AND DATA REQUIREMENTS FOR RIVER-QUALITY ASSESSMENT1

ABSTRACT: The U.S. Geological Survey is now (1975) conducting an intensive river-quality assessment of the Willamette River basin, Oregon. The objectives are to (1) define a practical framework for conducting comprehensive river-quality assessments, (2) develop and document methods for evaluating basin-development alternatives in terms of potential impacts on river quality, (3) determine the kinds and amounts of data required to adequately assess various types of river-quality problems, and (4) apply the framework, data, and methods to assess the existing or potential river-quality problems of the Willamette River basin. This paper covers objectives 2, 3, and 4 by examining the rationales behind the selection and application of methods and the design of data programs for assessing specific river-quality problems. The rationales are those developed for assessing (1) the effect of population and industrial growth and resulting waste discharges on river-dissolved oxygen, (2) the potentially harmful effects on land and river quality of accelerated erosion resulting from intensive land-use development, and (3) the potential for nuisance algal growth. The goal of the assessment program and, thus, the context of the rationales is to provide technically sound information that is appropriate and adequate for resource planning and management.     

WATER DATA - A NEW AWARENESS1

ABSTRACT: One of the most significant changes m the field of hydrology in the past few years has been the increase m demand for basic data resulting from a new awareness on the part of planners, developers and managers of the essential nature of such data. For many years data collection has been an onerous, routine operation, following which the data were processed and stored - either in publications or file drawers - and the job considered completed. Two developments have changed that picture: the realization that we are drastically altering OUT environment, and the advent of the computer. The first forced us into a recognition of our need for accurate basic data and the second provided a new methodology for handling and using it. The change is evidenced m many ways and numerous activities are underway at both State and Federal level for all facets of the acquisition and handling of water data. The collection of basic data still involves hard routine work and a conscientious-effort to maintain a high level of quality. Hopefully, recognition of the absolutely essential nature of an adequate data base will result in the continued enhancement of the basic data collector and the concomitant increase in support of his activities.     

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.     

A data mining approach to simulating farmers' crop choices for integrated water resources management

Water and land resources in Thailand are increasingly under pressure from development. In particular, there are many resource conflicts associated with agricultural production in northern Thailand. Communities in these areas are significantly constrained in the land and water management decisions they are able to make. This paper describes the application of a data mining approach to describing and simulating farmers' decision rules in a catchment in northern Thailand. This approach is being applied to simulate social, economic and biophysical constraints on farmers' decisions in these areas as part of an integrated water management model.     

浅谈网络安全策略

由于计算机网络表现的脆弱性使网络容易受到各种攻击，所以网络信息的安全和保密是一个非常重要的问题。本文从计算机网络安全策略出发，对解决计算机网络安全策略原则及网络的安全技术进行了综述。     

浅谈环境监测数据的审核

阐述了环境监测数据审核程序与内容,对监测数据的审核方法进行了综述。     

How has a shortage of census and geological information impeded the regularization of artisanal and small‐scale mining?

There is growing consensus that a combination of laissez‐faire policies, ad hoc regulation and debilitating support services has perpetuated socio‐economic and environmental deterioration in the artisanal and small‐scale mining (ASM) industry. However, a lack of anthropological and geological information on ASM prevents many governments both from improving the policy environment of the industry, and from providing more robust extension services to its operators. This article aims to examine more precisely how a deficiency of baseline census and geological data has inhibited industry formalization and undermined many of the measures implemented to address pressing problems at ASM sites. Specifically, it is argued that insufficient knowledge of artisanal mining populations — including their demographic structure — and of areas suitable for ASM activities affects the ability of a government to regularize, as well as to improve, the organization of this largely informal sector of industry. Case studies of Ghana and Zimbabwe are used to illustrate how the undertaking of low‐budget projects in areas of geological prospecting and population analysis could improve the efficiency of ASM assistance.     

Application of non-market valuation to the Florida Keys marine reserve management

The quality of the coral reefs in the Florida Keys is essential to sustain nature-based tourism in the Keys. The recently established marine reserves (MR) are expected to improve the reef environment, particularly coral and fish abundance and diversity. In this paper, a combined model of travel cost and contingent behavior was estimated in order to measure the non-market recreational benefits of reef quality improvements. The results indicated that an average visitor would undertake 43-80% more number of trips to the Florida Keys and experience a 69% increase in the use values per trip, as a result of the MR-induced reef quality improvements. The above non-market value estimates were further applied to evaluating alternative management proposals for funding the MR program. It was found that the annual management costs of the MR program would constitute an insignificant portion--only around one to 2%--of the annual recreational benefits that the MR would generate. The results provide a strong economic justification for designing user-based funding mechanisms in order to make the MR program self-sustaining in the future.     

The National Vegetation Classification Standard applied to the remote sensing classification of two semiarid environments

The National Vegetation Classification Standard (NVCS) was implemented at two US National Park Service (NPS) sites in Texas, the Padre Island National Seashore (PINS) and the Lake Meredith National Recreation Area (LMNRA), to provide information for NPS oil and gas management plans. Because NVCS landcover classifications did not exist for these two areas prior to this study, we created landcover classes, through intensive ground and aerial reconnaissance, that characterized the general landscape features and at the same time complied with NVCS guidelines. The created landcover classes were useful for the resource management and were conducive to classification with optical remote sensing systems, such as the Landsat Thematic Mapper (TM). In the LMNRA, topographic elevation data were added to the TM data to reduce confusion between cliff, high plains, and forest classes. Classification accuracies (kappa statistics) of 89.9% (0.89) and 88.2% (0.87) in PINS and LMNRA, respectively, verified that the two NPS landholdings were adequately mapped with TM data. Improved sensor systems with higher spectral and spatial resolutions will ultimately refine the broad classes defined in this classification; however, the landcover classifications created in this study have already provided valuable information for the management of both NPS lands. Habitat information provided by the classifications has aided in the placement of inventory and monitoring plots, has assisted oil and gas operators by providing information on sensitive habitats, and has allowed park managers to better use resources when fighting wildland fires and in protecting visitors and the infrastructure of NPS lands.     

ESTIMATING THE MEAN AND VARIANCE OF CENSORED PHOSPHORUS CONCENTRATIONS IN FLORIDA RAINFALL1

ABSTRACT: The total phosphorous (TP) concentrations in the South Florida rainfall have been recorded in weekly intervals with a detection limit (D_L) of 3.5 μg/L. As a large amount of the data is reported as below the D_L, appropriate statistical methods are needed for data analysis. Thus, an attempt was made to identify an appropriate method to estimate the mean and variance of the data. In particular, a method to separate the statistics for the below D_L portion from the estimated population statistics is proposed. The estimated statistics of the censored data are compared with the statistics of the uncensored data available from the recent years’ laboratory records. It was found that the one-step restricted maximum likelihood method is the most accurate for the wet TP data, and that the proposed method to combine the estimated statistics for TP < D_L portion and the sample statistics for TP ≥ D_L portion improves estimates compared to the conventional maximum likelihood estimates.