城市汽车空气污染控制基准研究

本文论述了城市汽车空气污染研究的目标、基本方法及城市汽车污染控制区的划分原则和方法.汽车类型流动源采用整个控制区平均浓度作为分析对比的基础不合适,应该专门研究确定基准控制点.为了合理选择确定控制计算点,提出3种方法:峰值法、核心区和重点控制区法、9点平均法.9点平均法可以有效增加各类污染源的敏感点,同时又可避免增加该点位影响过大的缺陷.这种方法在其他类型大气污染源控制中也能发挥作用.     

黑河流域生态环境的脆弱性及其对地下水的依赖性

本文通过翔实的素材阐述了河西走廊黑河流域生态环境的脆弱性及其对地下水环境的依赖性,根据野外实地考察实料揭月了适合西北生态脆弱区的地下水可持续利用模式,并指出了生态环境保护与水资源利用协调发展的国土安全意义.     

黄河断流与黄河的水资源承载力

分析了黄河断流的时空特征、根源和危害，提出了水资源承载力的概念。黄河的水资源承载力即指在生态系统良性循环的条件下，黄河对人类取用水资源的最大承受能力。只有建立起水资源承载力的概念，人类才会谨慎地取用水资源，小心地保护水资源。     

SOIL SALINITY PREDICTION USING ARTIFICIAL NEURAL NETWORKS1

ABSTRACT: This study explores the applicability of Artificial Neural Networks (ANNs) for predicting salt build‐up in the crop root zone. ANN models were developed with salinity data from field lysimeters subirrigated with brackish water. Different ANN architectures were explored by varying the number of processing elements (PEs) (from 1 to 30) for replicate data from a 0.4 m water table, 0.8 m water table, and both 0.4 and 0.8 m water table lysimeters. Different ANN models were developed by using individual replicate treatment values as well as the mean value for each treatment. For replicate data, the models with twenty, seven, and six PEs were found to be the best for the water tables at 0.4 m, 0.8 m and both water tables combined, respectively. The correlation coefficients between observed salinity and ANN predicted salinity of the test data with these models were 0.89, 0.91, and 0.89, respectively. The performance of the ANNs developed using mean salinity values of the replicates was found to be similar to those with replicate data. Not only was there agreement between observed and ANN predicted salinity values, the results clearly indicated the potential use of ANN models for predicting salt build‐up in soil profile at a specific site.     

岷江生态环境问题及其对策研究

本文主要探讨岷江流域的生态环境问题及其对策。全文分为两个部分。(1)研究岷江生态环境问题;(2)解决岷江生态环境问题的主要对策。     

充分利用水资源 改善生态环境

本文结合攀枝花地区实际,论述了水资源利用率高低是影响经济发展和改善生态环境的重要因素,调查分析了攀枝花地区水资源利用率低的原因;提出了提高水资源利用率的对策和措施。为促进经济发展和改善生态环境提供了依据。     

USING SOIL TEXTURE TO ESTIMATE SATURATED HYDRAULIC CONDUCTIVITY AND THE IMPACT ON RAINFALL-RUNOFF SIMULATIONS1

ABSTRACT: In this paper a new set of soil texture data is used to estimate the spatial distribution of saturated hydraulic conductivity values for a small rangeland catchment. The estimates of conductivity are used to re-excite and re-evaluate a quasi-physically based rainfall-runoff model. The performance of the model is significantly reduced with conductivity estimates gleaned from soil texture data rather than the infiltration data used in our previous efforts.     

LANDSAT MID-INFRARED DATA AND GIS IN REGIONAL SURFACE SOIL-MOISTURE ASSESSMENT1

ABSTRACT: Landsat satellite Thematic Mapper (TM) data were used to assess regional soil moisture conditions. The mid-infrared (MIR) data of TM band 7 were overlain onto four principal land-use categories (Agricultural/Irrigated, Urban/Clearings, Forest/ Wetlands, Water) using a geographic information system (GIS). M data were used to assess four qualitative surface soil-moisture conditions (water/very wet, wet, moist, and dry) within each land-use category of a 208,354 ha southwestern Florida study area. The MIR response was inversely related to the qualitative surface soil-moisture content. Integration of Landsat TM MIR data with land use through GIS appears to be a useful technique for high-resolution regional soil moisture assessment, and further research to reline this technique is recommended.     

SPATIAL DISTRIBUTION OF POINT SOIL MOISTURE ESTIMATES USING LANDSAT TM DATA AND FUZZY-C CLASSIFICATION1

ABSTRACT: Many hydrologic models have input data requirements that are difficult to satisfy for all but a few well-instrumented, experimental watersheds. In this study, point soil moisture in a mountain watershed with various types of vegetative cover was modeled using a generalized regression model. Information on sur-ficial characteristics of the watershed was obtained by applying fuzzy set theory to a database consisting of only satellite and a digital elevation model (DEM). The fuzzy-c algorithm separated the watershed into distinguishable classes and provided regression coefficients for each ground pixel. The regression model used the coefficients to estimate distributed soil moisture over the entire watershed. A soil moisture accounting model was used to resolve temporal differences between measurements at prototypical measurement sites and validation sites. The results were reasonably accurate for all classes in the watershed. The spatial distribution of soil moisture estimates corresponded accurately with soil moisture measurements at validation sites on the watershed. It was concluded that use of the regression model to distribute soil moisture from a specified number of points can be combined with satellite and DEM information to provide a reasonable estimation of the spatial distribution of soil moisture for a watershed.     

GROUND-WATER RECHARGE THROUGH ACTWE SAND DUNES IN NORTHWESTERN NEVADA1

ABSTRACT: Most water-resouree investigations in semiarid basins of the Great Basin in western North America conclude that ground-water recharge from direct precipitation on the valley floor is negligible. However, many of these basins contain large areas covered by unvegetated, active sand dunes that may act as conduits for ground-water recharge. The potential for this previously undocumented recharge was investigated in an area covered by sand dunes in Desert Valley, northwestern Nevada, using a deep percolation model. The model uses daily measurements of precipitation and temperature th determine energy and moisture balances, from which estimates of long-term mean annual recharge are made. For the study area, the model calculated a mean annual recharge rate of as much as 1.3 inches per year, or 17 percent of the long-term mean precipitation. Model simulations also indicate that recharge would be virtually zero if the study area were covered by vegetation rather than dunes.