北京地区冬季SO2浓度的时空分布和年际变化特征研究

用统计分析方法,对1984~1988年和1999~2000年间北京市冬季SO2的时空分布及多年变化特征进行分析,得到以下结果:(1)1984-1988年间,除定陵点位(清洁对照点)为单峰分布外,北京市SO2的城区日变化特征基本呈双峰双谷型特征分布。而在1999~2000年间,城区峰值开始降低,定陵点位峰值相对升高;(2)就多年变化特征而言,定陵点位SO2浓度呈升高趋势,且浓度高于0.03 mg/m3的事件出现频率增高;城区的SO2浓度降低,浓度高于0.3 mg/m3的事件出现频率减低。在此基础上,对影响北京市SO2的日间变化、年内变化、年际变化的污染源因子进行具体解析,发现改善燃煤质量是减少SO2排放量的有效途径。研究结论证明了城区SO2浓度水平与燃煤品质的紧密关系,对于我国各地区的SO2减排具有重要参考意义。     

基于GIS的流域水质目标管理TMYL构架研究——以赣江流域为例

以赣江流域为例,提出了基于GIS的TMYL计划技术框架,构建了以保持水生态系统健康为目标的流域水质目标管理技术体系.在ARCGIS9.3的环境中,利用GIS的叠置技术,建立基于控制单元为管理核心、污染源在线监控为配套建设的三级监控体系.结合流域水污染防治绩效评估体系的建立及评估分析,为流域水污染控制的总量控制方案和对策...     

Generating Synthetic Rainfall on Various Timescales—Daily, Monthly and Yearly

The main objective of this paper is to present a model for generating synthetic rainfall totals on various timescales to be applicable for a variety of uses. Many large-scale ecological and water resource models require daily, monthly and yearly rainfall data as input to the model. As historical data provides only one realisation, synthetic generated rainfall totals are needed to assess the impact of rainfall variability on water resources systems (Srikanthan, In: MODSIM2005, Melbourne, Dec. 2005, pp. 1915–1921, 2005). Thus, our preferred model should simulate rainfall for yearly, monthly and daily periods. We believe that, for water supply issues, no higher resolution is needed, although higher resolution would be useful in models designed to measure the risk of local flooding. The critical factors are daily, monthly and yearly totals and daily, monthly and yearly variation. A model for generating yearly totals will be described using traditional time series methods. This model, along with a similarly constructed daily generation model by Piantadosi et al. (A New Model for Correlated Daily Rainfall, 2008), will be cascaded to start with a synthetic yearly total, then generate a synthetic sequence of monthly totals (through selection from a large number of realisations) that match the yearly total, and subsequently perform a similar operation for sequences of daily totals to match the required monthly totals. We present a new model for the generation of synthetic monthly rainfall data, which we demonstrate for Parafield in Adelaide, South Australia. The rainfall for each month of the year is modelled as a non-negative random variable from a mixed distribution with either a zero outcome or a strictly positive outcome. We use maximum likelihood to find parameters for both the probability of a zero outcome and the gamma distribution that best matches the observed probability density for the strictly positive outcomes. We describe a new model that generates correlated monthly rainfall totals using a diagonal band copula with a single parameter to generate lag-1 correlated random numbers. Our model preserves the marginal monthly distributions and, hence, also preserves the monthly and yearly means. We show that, for Parafield, the correlation between rainfall totals for successive months is not significant, and so, it is reasonable to assume independence. This is, however, not true for daily rainfall. We describe a new model that generates correlated daily rainfall totals using a diagonal band copula with a single parameter to generate lag-1 correlated random numbers. This is an extended version of a paper presented at the 17th Biennial Congress on Modelling and Simulation, Christchurch, New Zealand, December 2007.