Estimating the potential impact of vegetation on the water cycle requires accurate soil water parameter estimation

It is well known that vegetation dynamics at the catchment scale depends on the prevailing weather and soil moisture conditions. Soil moisture, however, is not equally distributed in space due to differences in topography, weather patterns, soil properties and the type and amount of vegetation cover. To elucidate the complex interaction between vegetation and soil moisture, the dynamic vegetation model LPJ-GUESS (Smith et al., 2001), which provides estimations of vegetation dynamics, but does not consider lateral water fluxes was coupled with the hydrological TOPMODEL (cf. Beven, 2001) in order to be able to evaluate the importance of these lateral fluxes. The new model LG-TM was calibrated and validated in two climatically different mountain catchments. The estimations of runoff were good, when monthly and weekly time scales were considered, although the low flow periods at winter time were somewhat underestimated. The uncertainty in the climate induced change vegetation carbon storage caused by the uncertainty in soil parameters was up to 3-5 kg C m⁻² (depending on elevation and catchment), compared to the total change in vegetation carbon storage of 5-9 kg C m⁻². Therefore accurate estimates of the parameters influencing the water holding capacity of the soil, for example depth and porosity, are necessary when estimating future changes in vegetation carbon storage. Similarly, changes in plant transpiration due to climatic changes could be almost double as high (88 mm m⁻²) in the not calibrated model compared to the new model version (ca 50 mm m⁻² transpiration change). The uncertainties in these soil properties were found to be more important than the lateral water exchange between grid cells, even in steep topography at least for the temporal and spatial resolution used here.     

Potential solar radiation pattern in relation to the monthly distribution of giant pandas in Foping Nature Reserve, China

Solar radiation is an important parameter in ecological process modeling, hydrological modeling and bio-physical modeling. However, models focusing on solar radiation in relation to giant panda habitat and seasonal distribution are limited. The research aims to form spatial models of 12 month solar radiation patterns and to investigate the relation between the solar radiation patterns and the monthly distribution patterns of giant pandas. The solar radiation model of Kumar et al. was adopted for this study in Foping Nature Reserve (NR), China. By comparing twelve monthly solar radiation patterns and calculating statistics such as maximum, minimum, mean and standard deviation of the solar radiation, diversified solar radiation patterns over different months were obtained. Maximum solar radiation occurred in June and July, while minimum solar radiation occurred in December and January. The annual sum of solar radiation was 6954 MJ/m² in Foping NR. The range in solar radiation was smaller in hot months and larger in cold months. Radio tracking data of giant pandas were collected for twelve months and the ensuing maps were overlaid with the twelve-month solar radiation map to analyze the relation between the giant panda's monthly distribution and solar radiation. Our results showed that giant pandas prefer areas with lower solar radiation in warm months and select areas with higher solar radiation in cold months, which illustrates that the distribution of giant pandas is indeed affected by solar radiation. To a certain degree, it also explains the behavior of seasonal movement by giant pandas in Foping NR.     

Crustacean habitat potential mapping in a tidal flat using remote sensing and GIS

To make a macrofaunal (crustacean) habitat potential map, the spatial distribution of ecological variables in the Hwangdo tidal flat, Korea, was explored. Spatial variables were mapped using remote sensing and a geographic information system (GIS) combined with field observations. A frequency ratio (FR) and logistic regression (LR) model were employed to map the macrofauna potential area for the Ilyoplax dentimerosa, a crustacean species. Spatial variables affecting the tidal macrofauna distribution were selected based on abundance and biomass and used within a spatial database derived from remotely sensed data of various types of sensors. The spatial variables included the intertidal digital elevation model (DEM), slope, distance from a tidal channel, tidal channel density, surface sediment facies, spectral reflectance of the near infrared (NIR) bands and the tidal exposure duration. The relation between the I. dentimerosa and each spatial variable was calculated using the FR and LR. The species was randomly divided into a training set (70%) to analyse habitat potential using FR and LR and a test set (30%) to validate the predicted habitat potential map. The relations were overlaid to produce a habitat potential map with the species potential index (SPI) value for each pixel. The potential habitat maps were compared with the surveyed habitat locations such as validation data set. The comparison results showed that the LR model (accuracy is 85.28%) is better in prediction than the FR (accuracy is 78.96%) model. The performance of models gave satisfactory accuracies. The LR provides the quantitative influence of variables on a potential habitat of species; otherwise, the FR shows the quantitative influence of a class in each variable. The combination of a GIS-based frequency ratio and logistic regression models and remote sensing with field observations is an effective method to determine locations favorable for macrofaunal species occurrences in a tidal flat.     

Application of Markov-chain model for vegetation restoration assessment at landslide areas caused by a catastrophic earthquake in Central Taiwan

The 921 earthquake caused a catastrophic disaster in Central Taiwan. Ten years have passed since the earthquake occurred. Vegetation succession is the basis for establishing a restoration reference which plays an important role in vegetation restoration at landslide sites. Generally, growth conditions for grass are easier and the growth rate is faster than that for trees. Therefore, grass can be considered a pioneer species or an important reference for the early vegetation succession stage. This is the reason why grass is required to be extracted from other land covers. Integrating remote sensing, geographic information system and image classification into vegetation succession models is very important. In this study, the Markov chain model was applied for vegetation restoration assessment and discussion. Chiufenershan and Ninety-nine peaks were selected as the study areas. Five SPOT satellite images are used for land cover mapping and vegetation restoration simulations. Four categories of land covers were extracted, including forest, grass, bare land and water, respectively. From the transitive probability matrix (derived from any two land covers), the results show that vegetation restoration at the Chiufenershan and Ninety-nine peaks landslide areas is ongoing, but that has been disturbed by natural disasters.     

浅谈四级环境监测站档案管理工作

简述了环境监测档案在环境保护、生态建设、社会经济发展中的重要价值,分析了当前四级环境监测档案管理中人员培养、信息化建设、保密管理等存在问题,提出,应完善档案管理设备,引进档案管理专业人才,落实档案管理职责,制定相关制度,加强档案密级管理,加快档案信息化建设.     

Information technology and emergency management: preparedness and planning in US states

The purpose of this paper is to examine the impact of information technology (IT) on emergency preparedness and planning by analysing a survey of US state government departments of emergency management. The research results show that there has been a significant impact of IT on emergency planning. IT has proven to be effective for all phases of emergency management, but especially for the response phase. There are numerous technologies used in emergency management, ranging from the internet, Geographic Information Systems and wireless technologies to more advanced hazard analysis models. All were generally viewed as being effective. Lack of financial resources and support from elected officials is a perennial problem in public administration, and was found to be prevalent in this study of IT and emergency management. There was evidence that state governments rating high on a performance index were more likely to use IT for emergency management.     

基于GIS和RS的重庆市滑坡遥感解译

地处三峡库区腹心的重庆市由于其复杂的自然地理环境及不断增加的人类工程活动,使该市域内滑坡灾害较为频繁。在分析重庆市滑坡特征的基础上,采用高精度遥感影像及基础地形数据,在地理信息系统和遥感等技术支持下综合解译重庆市滑坡灾害,探讨了针对重庆市滑坡灾害的解译和识别方法,为地方政府滑坡灾害防治提供决策支持。     

基于地理信息的城市消防监督管理系统构建

在分析地理信息系统的工作特点和优点的基础上,结合城市消防监督管理工作的实际,提出了利用地理信息系统平台开发消防地理信息系统的概念,专门服务于城市消防监督工作,并对消防地理信息系统的组成及工作原理进行了较为细致的分析。     

地震应急演练虚拟仿真应用技术

地震是一种破坏性极大的突发性自然灾害。破坏性地震发生后,各级政府和部门必须迅速应对这种突发性事件。开展应急演练培训,能提高应急管理人员的应急处置和科学决策能力。应用虚拟仿真应用技术构建了虚拟地震应急演练平台,提出了系统体系结构、想定编辑器、演练控制的设计思想以及虚拟应急演练的组织方式。虚拟地震应急演练平台使演练者能够通过看地震灾害现场,做出相应决策,从而增强受训者的临场感觉,提升地震应急管理人员的快速反应和应急处置能力。     

基于GIS的电力工程勘察信息系统设计研究

从分析电力行业工程勘察信息管理与利用现状入手,提出了基于地理信息系统GIS(以下简称GIS)的工程勘察设计一体化的设想,设计了工程勘察信息化集成应用系统的逻辑模型,阐述了系统所采用的组件式GIS和数据融合等关键技术,最后结合具体的工程实例,详细介绍了具有系统分析决策功能的任意工程地质剖面图的绘制和三维实体地层模型的构建...