Assessing Public Perceptions of Computer-Based Models

Although there is a solid body of research on both collaborative decision-making and on processes using models, there is little research on general public attitudes about models and their use in making policy decisions. This project assessed opinions about computer models in general and attitudes about a specific model being used in water planning in the Middle Rio Grande Region of New Mexico, United States. More than 1000 individuals were surveyed about their perceptions of computer-based models in general. Additionally, more than 150 attendees at public meetings related to the Middle Rio Grande planning effort were surveyed about their perceptions of the specific Rio Grande-based model. The results reveal that the majority of respondents are confident in their ability to understand models and most believe that models are appropriate tools for education and for making policy decisions. Responses also reveal that trust in who develops a model is a key issue related to public support. Regarding the specific model highlighted in this project, the public revealed tremendous support for its usefulness as a public engagement tool as well as a tool to assist decision-makers in regional water planning. Although indicating broad support for models, the results do raise questions about the role of trust in using models in contentious decisions.     

Nature and fate of Hudson Bay permafrost

Two aspects of the permafrost of the Hudson Bay region are examined. The first is the climatological conditions that support permafrost especially along the southwestern shore of Hudson Bay. The second is the fate of the permafrost using recent climate change scenarios. The continuous permafrost along the shores of southwestern Hudson Bay is examined from a climatological perspective. Two hypotheses are explored to explain the presence of continuous permafrost in this region in spite of the relatively "warm" local climate. Possible errors in the calculation of thawing degree days and the asymmetries in frozen and unfrozen soil thermal conductivities are successively examined. Only the second hypothesis is likely to explain the presence of permafrost in southwestern Hudson Bay. Sophisticated climate models are used to assess the potential change in permafrost distribution in the Hudson Bay region. Nine simulations using three different versions of the Canadian Centre of Climate Modelling and Analysis (CCCma) general circulation model are used to project permafrost distribution. Two surface temperature thresholds, –5 and –10 °C, are used to diagnose permafrost grid points. All simulations, including those that include reduction of CO₂ emissions, showed at least a 50% reduction of permafrost by 2100 using these temperature thresholds. Electronic Publication     

Developing an optimal sampling design. A case study in a coastal marine ecosystem

The development of a sampling design for optimisingsampling site locations collected from a coastalmarine environment has been the purpose of the presentwork; application of statistical analysis and spatialautocorrelation methods have been carried out. Thedataset included data collected from 34 sampling sitesspaced out in the Strait of Lesbos, Greece, arrangedin a 1×1 NM grid. The coastal shallow ecosystem wassubdivided into three zones, an inner one (7stations), a middle one (16 stations) and an offshorezone (11 stations). The standard error of thechlorophyll-a concentrations in each zone hasbeen used as the criterion for the sampling designoptimisation, resulting into reallocation of thesampling sites into the three zones. The positions ofthe reallocated stations have been assessed byestimation of the spatial heterogeneity and anisotropyof chlorophyll-a concentrations usingvariograms. Study of the variance of the initialdataset of the inner zone taking into account spatialheterogeneity, revealed two different sub-areas andtherefore, the number of the inner stations has beenreassessed. The proposed methodology eliminates thenumber of sampling sites and maximises the informationof spatial data from marine ecosystems. It isdescribed as a step-by-step procedure and could bewidely applied in sampling design concerning coastalpollution problems.     

Spatial-Scale Effects on Relative Importance of Physical Habitat Predictors of Stream Health

A common theme in recent landscape studies is the comparison of riparian and watershed land use as predictors of stream health. The objective of this study was to compare the performance of reach-scale habitat and remotely assessed watershed-scale habitat as predictors of stream health over varying spatial extents. Stream health was measured with scores on a fish index of biotic integrity (IBI) using data from 95 stream reaches in the Eastern Corn Belt Plain (ECBP) ecoregion of Indiana. Watersheds hierarchically nested within the ecoregion were used to regroup sampling locations to represent varying spatial extents. Reach habitat was represented by metrics of a qualitative habitat evaluation index, whereas watershed variables were represented by riparian forest, geomorphology, and hydrologic indices. The importance of reach- versus watershed-scale variables was measured by multiple regression model adjusted-R² and best subset comparisons in the general linear statistical framework. Watershed models had adjusted-R² ranging from 0.25 to 0.93 and reach models had adjusted-R² ranging from 0.09 to 0.86. Better-fitting models were associated with smaller spatial extents. Watershed models explained about 15% more variation in IBI scores than reach models on average. Variety of surficial geology contributed to decline in model predictive power. Results should be interpreted bearing in mind that reach habitat was qualitatively measured and only fish assemblages were used to measure stream health. Riparian forest and length-slope (LS) factor were the most important watershed-scale variables and mostly positively correlated with IBI scores, whereas substrate and riffle-pool quality were the important reach-scale variables in the ECBP.     

逆向物流与再生资源回收利用

逆向物流是重新挖掘产品使用价值,节约资源,保护环境,实施可持续发展的重要战略措施.论述了逆向物流与再生资源回收利用之间的关系,分析了再生资源企业开展逆向物流的优劣势,提出了再生资源企业参与逆向物流的模式.     

Regional Assessment of Nutrient and Pesticide Leaching in the Vegetable Production Area of Rattaphum Catchment, Thailand

Regional groundwater vulnerability maps to indicate the impact of leaching of chemicals under different management scenarios were prepared for the Rattaphum Catchment using several leaching models and GIS techniques. The Attenuation Factor (AF) model was used to simulate the leaching potential of several pesticides for selected soils in the catchment under different rates of recharge from irrigation. The LEACHN model was used to simulate the NO₃ ⁻ leaching potential and LEACHP was used to simulate leaching potential of metolachlor under different management scenarios. The results showed that only a small number of pesticides have the potential to contaminate the shallow groundwater. However, the risk of contamination with nutrients is much higher due to the mobility and conservative nature of the NO₃ ⁻. The LEACHP results indicated that the intensive use of agrochemicals in the vegetable growing area, especially during the rainy season when the groundwater is near the surface, increases the risk of pesticide contamination. The results of upscaling from the farm to the catchment scale using soil maps and GIS techniques under various management scenarios and chemical application rates showed that the most effective strategy to reduce chemical leaching is by reducing pesticide application rates and optimizing the application of irrigation water. The identification of potential high risk farms by ranking soils and agricultural practices could be used to formulate management practices that reduce pesticide contamination of the surface and ground water resources in the area.     

PREDICTIVE ASSESSMENT OF SEVERITY OF AGRICULTURAL DROUGHTS BASED ON AGRO-CLIMATIC FACTORS1

ABSTRACT: Past historical evidence indicates that droughts have had great impacts on human life. Drought (or scarcity of water) is assessed based on two key factors, namely, the estimated water demand, and the expected water supply. The formulation of these key factors for a region largely depends on the agro-climatic and economic conditions. Consideration of one such key factor is the relationship between the crop yield and water deficit in the assessment and prediction of agricultural droughts. The varying nature of this relationship from crop to crop adds to the complexity of agricultural drought analysis. To overcome this difficulty in analyzing agricultural droughts of a region, it is adequate to consider and place emphasis on a single crop (i.e., an index crop) grown homogeneously over the major area of the region. From one year to another year, the pattern of water requirement during the growing season of an index crop is rather stationary, and the water supply in arid and semi-arid area is mainly from seasonal random precipitation. In a region, grain yield of the index crop and, in turn, assessment of the severity of drought can reasonably be predicted as a function of the time of crop sowing and the distribution of rainfall, provided that temporal and spatial effects of other contributing factors (crop variety, soil fertility status, crop disease, pest control, cultivation practices etc.) on grain yield are considered to be uniformly distributed (i.e., stable). A predictive method of assessing agricultural droughts in an arid area of western India is presented. The major crop (Pearl Millet) of this region is grown from. July through September. The formulation of the proposed predictive method inherently implies that the grain yield of the main crop is a reliable indicator of agricultural drought. In the development of this predictive relationship (i.e., a regression type model) a number of potential yet simple variables affecting the grain yield in the region were investigated. The soil moisture index, although generally considered significant compared to the simple variables, has been found to account for insignificant variation in the grain yield. Results of our investigations suggest that it would be advisable to exclude the soil moisture index variable from the model. The proposed regression model can be used in the prediction of grain yield of the main crop several months ahead of crop harvesting operations and, in turn, the assessment of agricultural drought severity as mild, moderate, or severe. Such an assessment is expected to be helpful to planners for arranging appropriate measures to effectively combat agricultural drought situations.     

城市土地地质经济评价的理论与方法

城市土地地质经济评价是根据城市建设中存在着土地利用与地质环境不协调的矛盾，以及制定土地价格时忽略地质环境因素而提出的新概念。文章论述了该评价的基本思路、类型、指标体系、模型和方法．并以厦门海沧开发区土地利用适宜性地质经济评价为例，简述了该评价理论和方法的重大实践意义。     

SPACE-TIME TRADEOFFS ACROSS THE HYDROLOGIC DATA SETS OF COMPETING RAINFALL-RUNOFF MODELS: A PRELIMINARY ANALYSIS1

ABSTRACT: The concept of a space-time tradeoff is extended to the hydrologic data sets of competing rainfall-runoff modeling techniques. Examples are given by comparing the performance of a regression model and a quasi-physically based model using data from an experimental catchment and data synthetically generated. Space-time tradeoffs are demonstrated within the data sets of the two modeling techniques, but not across the competing hydrologic data sets.     

ANALYSIS OF ROCK STRESS AROUND A LIQUID WASTE INJECTION SYSTEM IN ILLINOIS1

: The danger to the environment associated with the injection of liquid industrial wastes into a deep, confined, subsurface rock formation may arise from the transport of the waste laterally or vertically in the formation. The pattern of lateral transport, which can take place as a result of convection as well as dispersion and diffusion, can be determined by an approximate analytical solution to the mass transport equation. Vertical transport may take place through both natural fractures and fractures created by hydrostatic stresses generated around the well during injection. To determine the stresses, we used the finite element method to get a numerical solution of the flow equation. We applied a solution of the flow equation to calculate the stress buildup and decay for the Jones & Laughlin Steel Corporation's injection well near Hennepin in Putnam County, Illinois. According to our computations, the stress buildup due to injection is about 0.16 pounds per square inch per foot - psi - (0.362 Newton per square centimeter per meter), which, added to normal pressure, makes an estimated total stress of 0.60 psi/ft (1.36 Newton/cm²/m). That pressure is insufficient to cause fracturing of the Cambrian Eau Claire aquitard, the confining bed for the disposal zone.