利用中巴地球资源卫星数据反演武汉市湖泊营养状态指数

以武汉市主要湖泊为例,研究了利用中巴地球资源卫星（CBERS2）数据反演水体营养状态指数（TLI）。研究旨在评估利用中巴地球资源卫星数据来估算内陆水体富营养化程度的可能性。首先利用地面水质监测数据计算武汉市某些湖泊监测点的“真实的”营养状态指数（包括综合营养状态指数和修正的Carlson营养状态指数）,同时,在事先经过辐射校正和几何校正的CBERS2图像上,以9×9像元为采样窗口,提取各个对应地点的灰度值均值（从波段1至波段4）;然后,采用多元逐步回归分析,以各波段灰度值均值为自变量,建立营养状态指数经验遥感反演模型;最后,利用模型对整个湖泊水体的营养化状态指数进行反演,并绘制了其空间分布图。 结果显示,营养状态指数的自然对数值与CBERS2图像各波段灰度值之间存在较好相关关系,回归系数平方值(R²)为0.51。利用反演模型反演得到的湖区水质分布与实际情况基本相符。由于CBERS2图像数据可以从我国许多数据分发中心免费获取,这为低成本的水质遥感监测提供了一条途径。     

Modeling potential herbicide loss to surface waters on the Swiss plateau

Lack of sufficiently detailed data often limits the applicability of complex transport-reaction models for estimating potential herbicide loss to surface waters. Therefore, there is also a need for simple models that are easy to apply but still capture the main features of the underlying processes.In this study, a simple regression model was developed to assess the vulnerability of catchments in the Swiss Plateau to diffuse herbicide loss to surface waters. The model is designed as a screening tool to rank the catchments in a relative sense and not to calculate Predicted Environmental Concentrations (PEC) of pesticides. The main goal is to capture two dominating factors controlling diffuse herbicide transport into streams and rivers. These factors are herbicide application and fast flow processes that are mainly responsible for herbicide transport. In a first step vulnerability of sites to herbicide loss is estimated based on site-specific conditions irrespective of actual herbicide application. In the second step, this vulnerability assessment is combined with actual herbicide application data to estimate the potential herbicide loss.The fast flow index (FFI), derived from discharge data using a base flow separation method, was applied as a proxy for the amount of fast flow occurring. The influence of catchment attributes (including topographic, climatic and soil data) on the FFI was analyzed using a multiple regression approach based on data from 57 catchments of the Swiss Plateau. By combining regression analysis with mechanistic knowledge, a two factor non-linear model based on river density and soil permeability as dominant input factors was selected as the best model for FFI prediction given the available data. Higher dimensional models had to be excluded because the strong correlation between the potential input factors led to unrealistic dependences while only minimally improving the quality of the fit.The spatial pattern of the predicted FFI as a measure for the vulnerability to diffuse herbicide losses shows a clearly increasing trend from the western to the eastern part of the Swiss Plateau and towards the pre-alpine/alpine regions in the south.In general the pattern of herbicide use corresponds to site conditions typical of a low FFI. However, the spatial analysis revealed exceptions, namely areas in which high actual herbicide use coincides with a high FFI.Despite the uncertainties in the model, this simple approach seems to be useful for supporting site-adapted agricultural practice whenever the higher accuracy of more detailed models is not required or too expensive to achieve. In addition, in combination with data on actual herbicide application, it can support the design of monitoring strategies by identifying critical areas of actual herbicide loss.     

Development of a Quantitative Pasture Phosphorus Management Tool Using the SWAT Model1

Abstract: Assessment tools to evaluate phosphorus loss from agricultural lands allow conservation planners to evaluate the impact of management decisions on water quality. Available tools to predict phosphorus loss from agricultural fields are either: (1) qualitative indices with limited applicability to address offsite water quality standards, or (2) models which are prohibitively complex for application by most conservation planners. The purpose of this research was to develop a simple interface for a comprehensive hydrologic/water quality model to allow its usage by farmers and conservation planners. The Pasture Phosphorus Management (PPM) Calculator was developed to predict average annual phosphorus (P) losses from pastures under a variety of field conditions and management options. PPM Calculator is a vastly simplified interface for the Soil and Water Assessment Tool (SWAT) model that requires no knowledge of SWAT by the user. PPM Calculator was validated using 33 months of data on four pasture fields in northwestern Arkansas. This tool has been extensively applied in the Lake Eucha/Spavinaw Basin in northeastern Oklahoma and northwestern Arkansas. PPM Calculator allows conservation planners to take advantage of the predictive capacity of a comprehensive hydrologic water quality model typically reserved for use by hydrologists and engineers. This research demonstrates the applicability of existing water quality models in the development of user friendly P management tools.     

基于道化法(DOW)的计算机辅助软件开发

传统的评价方法费时费力,效率低下.将计算机技术与评价方法相结合是评价工作发展的趋势.介绍了为世界各国石油化工企业所广为接受的美国道化学公司(DOW)火灾、爆炸危险性指数评价法,以及根据该法的评价思路所开发的辅助软件的设计思路和功能.     

层次分析法在高层学生公寓火灾危险性评价中的应用

分析高层学生公寓的消防安全特点及其火灾发生危害性,评述现有的高层建筑火灾风险评价方法;在现有的评价方法的基础上,从人员因素、建筑物属性、安全疏散设施、报警与灭火系统、防火与防烟系统、建筑物内电气因素和消防安全管理7个方面综合考虑,建立了高层学生公寓的建筑火灾危险评价指标体系;利用层次分析法对高层学生公寓火灾危险性进行分析,确定其评价指标体系中各层次各指标的权重;分析结果表明:消防安全教育与培训是学生公寓火灾危险评价指标体系中最重要的因素。加强和改进高层学生公寓消防安全管理,对预防或减少高层学生公寓火灾具有现实指导价值。     

水环境质量综合评价的新模型

为检验已订的水环境质量评价标准的合理性,解决各单项水质指标的评估结果的不相容性问题,提高水质等级模型的分辨率,提出了一种新的水质评价模型-逻辑斯谛曲线(LOG)模型,它的水质等级是连续的实数值;根据LOG模型的参数值可以分析各水质指标值对水质等级的影响程度,从而检验原订水质等级标准的合理性;并给出了基于实码遗传算法的LOG建模的实施方案.实例研究说明,这套方案是实用的和通用的,在其它环境质量综合评价中也具有广泛的应用价值.     

水体中高锰酸盐指数的流动注射分析方法

研究了用流动注射分析技术测定水体中高锰酸盐指数。使用新发明的耐腐蚀恒流泵、低记忆高效混合器、不存留气泡流通池等部件,通过高温高压,缩短消解时间,从而建立了一种可用于无人值守的自动在线快速监测水体中高锰酸盐指数的分析方法。     

基于GIS的南京市典型蔬菜基地土壤重金属污染现状与评价

对南京市八卦洲蔬菜基地土壤中的铅、铬、铜和镉进行测定分析,利用不同的评价标准来评价其环境质量状况,同时借助GIS软件研究了污染指数的空间分布状况,并解析了其重金属污染的来源.结果表明,以自然背景值为评价标准,则蔬菜地土壤中的重金属都超过污染指标,其中镉为首要污染因子;以国标二级为评价标准,则除镉以外的三种重金属的单项污染指数值全都小于1,但其综合污染指数迭1.50,总体上属轻污染状况.南京化工因区、南京长江二桥和各种农业生产活动等可能是主要污染源.     

细菌在近海污染监测及评价中的应用研究

通过对天津渤海湾的三个河流入海口(青静黄排水河、独流减河和海河),不同季节实地采集的水样中微生物数量及理化因子如温度、盐度、溶解氧(DO)、化学需氧量(COD)、无机氮等的研究,发现细菌指标与理化指标对污染指示结果有一定的相似性,都指示青静黄排水河河口污染较严重.利用SPSS软件的相关性分析方法对实验结果进行分析,发现水环境中细菌指标与理化因子具有一定的相关性.其中异养菌数与COD呈显著正相关性(P<0.05),与DO呈负相关性(P=0.051);大肠菌群数与理化因子DO呈极显著负相关关系(P<0.01),与COD呈正相关关系(P=0.061),与NO3-N,盐度呈负相关性(P>0.05).其他细菌指标与各理化因子也存在一定的相关性,但不明显.