基于扫描矢量化地图数据生产的数据质量控制

概述了基于扫描矢量化GIS数据的生产过程 ,介绍了扫描矢量化质量控制的策略和方法 ,在地图扫描阶段采用栅格图纠正的方法对地图的变形进行纠正 ,以提高矢量化原图的质量 ,在基于扫描矢量化GIS数据的生产过程中 ,可从算法和软件使用工艺方面提高数据的质量     

The influence of land use change on karst water quality of Shuicheng Basin in Guizhou Province

The influence of land use and land cover on ecological environment is a focus of global change research. The paper chooses an industrial city-Shuicheng in Guizhou Province-as a study area because the karst water quality around the city is deteriorating with land use and land cover change. The natural susceptibility of karst water system is an important factor leading to karst water pollution. But land use and land cover change is also a main factor according to the chemical analysis of karst water quality and land use change. So it is a good way to protect karst water through rational planning and managing of land use and land cover.     

Water Quality Impacts of Climate and Land Use Changes in Southeastern Pennsylvania*

This study investigates potential changes in nitrogen and phosphorus loads under a warmer and wetter climate, urban growth, and combined changes in the Conestoga River Basin and its five subbasins in southeastern Pennsylvania. A GIS‐based hydrochemical model was employed for assessing the sensitivity of the basins to the projected changes in 2030. Under the HadCM2 climate change scenario, mean annual nitrogen and phosphorus loads are expected to increase, with great increases in spring but slight decreases in fall primarily because of changes in monthly precipitation. When climate change and urbanization occur concurrently, mean annual nitrogen loads further increase by 50% in the most urbanizing subbasin. Point source nitrogen control could mitigate negative effects of climate and land use changes, reducing mean annual nitrogen loads to the contemporary baseline level.     

西安市冬季冷暖的历史演变对采暖的影响

本文针对CAPPS2.0系统在业务化自动运行过程中的一些问题,提供了一套具体可行的解决方案,实现了CAPPS系统的全自动运行,具有很高的实用价值。     

侯马市酸雨概况及其气象条件分析

通过对侯马近14a酸雨观测资料分析,发现侯马出现酸雨的概率较大,强度较强,时间变化特征明显,与气象条件关系密切。     

Assessing the Comparability of Ammonium,Nitrate and Sulfate Concentrations Measured by Three Air Quality Monitoring Networks

Airborne fine particulate matter across the United States is monitored by different networks, the three prevalent ones presently being the Clean Air Status and Trend Network (CASTNet), the Interagency Monitoring of PROtected Visual Environment Network (IMPROVE) and the Speciation and Trend Network (STN). If combined, these three networks provide speciated fine particulate data at several hundred locations throughout the United States. Yet, differences in sampling protocols and samples handling may not allow their joint use. With these concerns in mind, the objective of this study is to assess the spatial and temporal comparability of the sulfate, nitrate and ammonium concentrations reported by each of these networks. One of the major differences between networks is the sampling frequency they adopted. While CASTNet measures pollution levels on seven-day integrated samples, STN and IMPROVE data pertain to 24-hour samples collected every three days. STN and IMPROVE data therefore exhibit considerably more short-term variability than their CASTNet counterpart. We show that, despite their apparent incongruity, averaging the data with a window size of four to six weeks is sufficient to remove the effects of differences in sampling frequency and duration and allow meaningful comparison of the signals reported by the three networks of concern. After averaging, all the sulfate and, to a lesser degree, ammonium concentrations reported are fairly similar. Nitrate concentrations, on the other hand, are still divergent. We speculate that this divergence originates from the different types of filters used to collect particulate nitrate. Finally, using a rotated principal component technique (RPCA), we determined the number and the geographical organization of the significant temporal modes of variation (clusters) detected by each network for the three pollutants of interest. For sulfate and ammonium, the clusters’ geographical boundaries established for each network and the modes of variations within each cluster seem to correspond. RPCA erformed on nitrate concentrations revealed that, for the CASTNet and IMPROVE networks, the modes of variation do not correspond to unified geographical regions but are found more sporadically. For STN, the clustered areas are unified and easily delineable. We conclude that the possibility of jointly using the data collected by CASTNet, IMPROVE and STN has to be weighed pollutant by pollutant. While sulfate and ammonium data show some potential for joint use, at this point, combining the nitrate data from these monitoring networks may not be a judicious choice.     

Study of statistically correcting model CMAQ-MOS for forecasting regional air quality

Based on analysis of the air pollution observational data at 8 observation sites in Beijing including outer suburbs during the period from September 2004 to March 2005, this paper reveals synchronal and in-phase characteristics in the spatial and temporal variation of air pollutants on a city-proper scale at deferent sites; describes seasonal differences of the pollutant emission influence between the heating and non-heating periods, also significantly local differences of the pollutant emission influence between the urban district and outer suburbs, i.e. the spatial and temporal distribution of air pollutant is closely related with that of the pollutant emission intensity. This study shows that due to complexity of the spatial and temporal distribution of pollution emission sources, the new generation Community Multi-scale Air Quality (CMAQ) model developed by the EPA of USA produced forecasts, as other models did, with a systematic error of significantly lower than observations, albeit the model has better capability than previous models had in predicting the spatial distribution and variation tendency of multi-sort pollutants. The reason might be that the CMAQ adopts average amount of pollutant emission inventory, so that the model is difficult to objectively and finely describe the distribution and variation of pollution emission sources intensity on different spatial and temporal scales in the areas, in which the pollution is to be forecast. In order to correct the systematic prediction error resulting from the average pollutant emission inventory in CMAQ, this study proposes a new way of combining dynamics and statistics and establishes a statistically correcting model CMAQ-MOS for forecasts of regional air quality by utilizing the relationship of CMAQ outputs with corresponding observations, and tests the forecast capability. The investigation of experiments presents that CMAQ-MOS reduces the systematic errors of CMAQ because of the uncertainty of pollution emission inventory and improves the forecast level of air quality. Also this work employed a way of combining point and area forecasting, i.e. taking the products of CMAQ for a center site to forecast air pollution for other sites in vicinity with the scheme of model products "reanalysis" and average over the "area".     

Use of time series analysis for the identification of tidal effect on groundwater in the coastal area of Kimje, Korea

The purpose of this study is to apply time series analysis to investigate whether the groundwater quality in the coastal area is affected by the tide. Continuous and regular in situ monitoring data of electrical conductivity (EC) and groundwater level, and tidal level data measured by the National Oceanographic Research Institute were used for the time series analysis. Through the time series analysis, it is known that EC and groundwater level conspicuously fluctuate with two periodicities (15.4 and 0.52-day), which is very similar to those of the tide. Also the behaviors of their fluctuations vary in accordance with the tidal period. These indicate that the groundwater quality has been mainly controlled by the tidal level, and the strength of tidal effect on the groundwater quality is different according to the tidal period.     

The Quantitative Identification of Regional Mine and Natural Earthquakes and Its Application

INTRODUCTIONThe structural mine earthquake in coal mines refers to the quake induced by excavationengineeringthatleadstorupturingor change of geological structure and weakness surfaceintheinteriorof rock mass.According to the origin,mine earthquakes can b…     

Groundwater flow regime under natural conditions as inferred from past evidence and contemporary field observations in a semi-arid basin: Cuenca de la Independencia, Guanajuato, México

This study was carried out in the Cuenca de la Independencia, a semi-arid basin in Central Mexico. The objective is to describe the main features of a groundwater flow regime under natural conditions, based on groundwater discharge manifestations. Information obtained from paleoecological, paleontological, archaeological and historical data suggests that, prior to heavy development (starting in the 1950s), the hydrogeologic regime was characterized by a larger groundwater availability in a more humid and colder climate. Manifestations associated to groundwater discharges are springs, lagoons, wetlands, saline soils, chalcedony deposits, phreatophytes, thermalism, and artesianism. The different types of manifestations and their position in the basin indicate the influence of groundwater flow systems hierarchically nested, forming concentric zones at ground level. The groundwater flow regime corresponds to a classical gravity-induced flow system with generation of local, intermediate and regional patterns. Integrating several types of data to establish the flow geometry and its dynamics has proven a useful tool to increase understanding of the original groundwater regimes. This approach can also be applied in other over-exploited semi-arid basins.