A novel approach to leveraging social media for rapid flood mapping: a case study of the 2015 South Carolina floods

Rapid flood mapping is critical for local authorities and emergency responders to identify areas in need of immediate attention. However, traditional data collection practices such as remote sensing and field surveying often fail to offer timely information during or right after a flooding event. Social media such as Twitter have emerged as a new data source for disaster management and flood mapping. Using the 2015 South Carolina floods as the study case, this paper introduces a novel approach to mapping the flood in near real time by leveraging Twitter data in geospatial processes. Specifically, in this study, we first analyzed the spatiotemporal patterns of flood-related tweets using quantitative methods to better understand how Twitter activity is related to flood phenomena. Then, a kernel-based flood mapping model was developed to map the flooding possibility for the study area based on the water height points derived from tweets and stream gauges. The identified patterns of Twitter activity were used to assign the weights of flood model parameters. The feasibility and accuracy of the model was evaluated by comparing the model output with official inundation maps. Results show that the proposed approach could provide a consistent and comparable estimation of the flood situation in near real time, which is essential for improving the situational awareness during a flooding event to support decision-making.     

基于弱光栅技术的地面沉降自动化监测系统

光纤监测技术具有分布式、精度高等特点,在地面沉降监测中具有独特优势。但受限于监测成本较高与监测环境复杂,目前地面沉降光纤监测多通过人工采集数据,限制了在特殊环境变化情况下地面沉降的实时信息获取。文章在地面沉降钻孔全断面光纤监测技术的基础上,设计并建立了基于弱光栅技术的地面沉降自动化监测系统。该监测系统利用弱反射光栅、时分复用、物联网和数据库等技术,通过4G无线通信手段实现了地面沉降在线自动化监测和远程数据实时采集,并通过客户端系统软件实现数据的存储、查询和分析。将其应用到衡水地区地面沉降监测中,结果表明:钻孔内土层压缩变形主要发生在以黏性土为主的隔水层（Ad2、Ad3、Ad4）;受季节性地下水开采的影响,钻孔100～400 m深度范围内砂土含水层存在波动变化,在监测期内,冬季略回弹,随后春季地下水开采量增大,地下水位下降,土层呈现压缩趋势。监测结果验证了该系统的可行性与准确性,使得整个地面沉降监测流程趋于自动化、规范化和低成本化,具有广泛的应用前景。     

浅议矿山地质环境问题及其生态环境修复措施以某矿区为例

矿山地质环境问题治理是一项复杂的长期系统工程,本文以某矿区为例,简要阐述了矿山地质环境存在问题,有针对性地提出治理措施。经济建设同时,坚持生态优先、绿色发展道路,切实把绿色发展理念贯穿于矿山资源开发、利用、保护的全过程,全力推进矿山地质环境治理和生态修复工程。     

对甘肃矿山生态保护修复资金管理的思考及建议

矿山开采生产的生态保护与修复工作,涉及自然资源、生态环境、水利、林草等多部门,结合矿政管理工作实际,梳理了矿山生态保护修复资金类型,总结剖析了目前不同部门分头管理存在的问题,在此基础上,提出应整合各部门矿山生态保护修复方案及资金,形成管理合力,把生态保护修复工作贯穿到从地质勘查、矿山建设、开采、闭坑、管护的全过程,边开采边治理,整体保护,综合整治,系统修复。     

基于IUCN《矿山生物多样性管理系列指南》的大宝山矿生态修复实践研究

为研究矿山开采及修复过程中如何开展生物多样性管理,本文借鉴IUCN(世界自然保护联盟)发布的《矿山生物多样性管理系列指南》成果,将相关理论和方法应用到广东大宝山矿生态修复实践中。文章在介绍IUCN的“综合生物多样性管理体系”方法主要内容的基础上,将其作为大宝山矿实施生态修复依据,阐述了该管理体系在矿山生态修复工程中的应用,并结合广东大宝山矿的实际情况,提出了大宝山矿生物多样性管理的保护与修复框架,包括全周期的生物多样性管理手段,重点阐述大宝山矿生物多样性调查与监测、评价、保护与受损控制及恢复的技术方案,最后分析了对中国矿山生物多样性保护和修复的启示,IUCN矿山生物多样性管理系列指南对于指导我国矿山生态修复具有重要作用。     

Landslide susceptibility zonation method based on C5.0 decision tree and K-means cluster algorithms to improve the efficiency of risk management

Machine learning algorithms are an important measure with which to perform landslide susceptibility assessments,but most studies use GIS-based classification methods to conduct susceptibility zonation.This study presents a machine learning approach based on the C5.0 decision tree(DT)model and the K-means cluster algorithm to produce a regional landslide susceptibility map.Yanchang County,a typical landslide-prone area located in northwestern China,was taken as the area of interest to introduce the proposed application procedure.A landslide inventory containing 82 landslides was prepared and subse-quently randomly partitioned into two subsets:training data(70％landslide pixels)and validation data(30％landslide pixels).Fourteen landslide influencing factors were considered in the input dataset and were used to calculate the landslide occurrence probability based on the C5.0 decision tree model.Susceptibility zonation was implemented according to the cut-off values calculated by the K-means clus-ter algorithm.The validation results of the model performance analysis showed that the AUC(area under the receiver operating characteristic(ROC)curve)of the proposed model was the highest,reaching 0.88,compared with traditional models(support vector machine(SVM)=0.85,Bayesian network(BN)=0.81,frequency ratio(FR)=0.75,weight of evidence(WOE)=0.76).The landslide frequency ratio and fre-quency density of the high susceptibility zones were 6.76/km2 and 0.88/km2,respectively,which were much higher than those of the low susceptibility zones.The top 20％interval of landslide occurrence probability contained 89％of the historical landslides but only accounted for 10.3％of the total area.Our results indicate that the distribution of high susceptibility zones was more focused without contain-ing more"stable"pixels.Therefore,the obtained susceptibility map is suitable for application to landslide risk management practices.     

区域自动气象站蓄电池异常状态判别方法

针对天津市一种常见的CAWS600型区域自动气象站对其供电及功耗进行了详细分析,利用对电池放电特性曲线的归一化处理,得到了针对12V38AH铅酸蓄电池的剩余容量估算方法,同时利用该站蓄电池工作电压的统计规律,提出了针对蓄电池工作电压的极值判定、时间/空间一致性质量控制方法,并对2017年逐10min观测数据进行检验。检验结果显示,文章提出的质量控制方法可以有效识别出蓄电池异常站点,针对2017年个站蓄电池持续放电情况可提前10d定位。     

基于北斗的自动气象站报文传输方案设计

针对北斗卫星下行通信受4G和WIFI信号带内干扰导致传输成功率低的情况,设计了基于增加传输次数来降低误码率的自动气象站报文北斗传输方案。首次提出并建成用于传输自动气象站报文的双北斗指挥机用户群,根据北斗用户机的传输能力设计专用的气象报文编码格式,利用冗余频度开展报文重发,实现单个时次报文的4次重复接收,稳定地保证了较高的传输成功率。方案同时实现了观测报文1min内到达预报员桌面,在稳定性和时效性上均取得了突破。     

太阳辐射管理地球工程对海洋酸化影响的模拟研究

研究地球工程对海洋酸化的影响对于评估地球工程对全球气候和环境的影响有重要意义。文中使用中等复杂程度的地球系统模式,模拟了典型CO₂高排放情景RCP8.5下,实施太阳辐射管理地球工程对海洋表面的pH和文石（碳酸钙的一种亚稳形态）饱和度的影响,并定量分析了各环境因子对海洋酸化影响的机理。模拟结果表明,在RCP8.5情景下,到2100年,相对于工业革命前水平,全球海洋表面平均pH下降了0.43,文石饱和度下降了1.77。相对于RCP8.5情景,2100年地球工程情景下全球海洋表面平均pH增加了0.003,而文石饱和度降低了0.16。地球工程通过改变溶解无机碳、碱度、温度等环境因子影响海洋酸化。相对于RCP8.5情景,实施地球工程引起的溶解无机碳浓度的增加使pH和文石饱和度均减小,碱度的增加使pH和文石饱和度均增大,温度的降低使pH增大而使文石饱和度减小。总体而言,太阳辐射管理地球工程可以降低全球温度,但无法减缓海洋酸化。     

Measuring,mapping and quantifying the effects of trust and informal communication on transboundary collaboration in the Great Lakes fisheries policy network

Ecosystem-based management of fisheries and other transboundary natural resources require a number of organizations across jurisdictions to exchange knowledge, coordinate policy goals and engage in collaborative activities. Trust, as part of social capital, is considered a key mechanism facilitating the coordination of such inter-organizational policy networks. However, our understanding of multi-dimensional trust as a theoretical construct and an operational variable in environmental and natural resource management has remained largely untested. This paper presents an empirical assessment of trust and communication measures applied to the North American Great Lakes fisheries policy network. Using a scale-based method developed for this purpose, we quantify the prevalence of different dimensions of trust and in/formal communication in the network and their differentiated impacts on decision-making and goal consensus. Our analysis reveals that calculation-based ‘rational trust’ is important for aligning mutual goals, but relationship-based ‘affinitive trust’ is most significant for influencing decision-making. Informal communication was also found to be a strong predictor of how effectively formal communication will influence decision-making, confirming the “priming” role of informal interactions in formal inter-agency dealings. The results also show the buffering and interactive functions of these components in strengthening institutional resilience, with procedural trust undergirding the system to compensate for a lack of well-developed relationships. Overall, this study provides evidence to suggest that informal communication and multi-dimensional trust constitute a crucial element for improving collaboration and reducing conflict in the networked governance of transboundary natural resource systems.