Three decades of landslide activity in western Nepal: new insights into trends and climate drivers

In recent decades, landslide disasters in the Himalayas, as in other mountain regions, are widely reported to have increased. While some studies have suggested a link to increasing heavy rainfall under a warmer climate, others pointed to anthropogenic influences on slope stability, and increasing exposure of people and assets located in harm’s way. A lack of sufficiently high-resolution regional landslide inventories, both spatially and temporally, has prevented any robust consensus so far. Focusing on Far-Western Nepal, we draw on remote sensing techniques to create a regional inventory of 26,350 single landslide events, of which 8778 date to the period 1992–2018. These events serve as a basis for the analyses of landslide frequency relationships and trends in relation to precipitation and temperature datasets. Results show a strong correlation between the annual number of shallow landslides and the accumulated monsoon precipitation (r = 0.74). Furthermore, warm and dry monsoons followed by especially rainy monsoons produce the highest incidence of shallow landslides (r = 0.77). However, we find strong spatial variability in the strength of these relationships, which is linked to recent demographic development in the region. This highlights the role of anthropogenic drivers, and in particular road cutting and land-use change, in amplifying the seasonal monsoon influence on slope stability. In parallel, the absence of any long-term trends in landslide activity, despite widely reported increase in landslide disasters, points strongly to increasing exposure of people and infrastructure as the main driver of landslide disasters in this region of Nepal. By contrast, no climate change signal is evident from the data.

     

Dynamics of coastline changes in Mexico

Journal of Geographical Sciences - The goal of our work was to locate and quantify changes that occurred in 66% of the Mexican coastline, based on four land cover maps generated by the Mexican...     

Dynamic metabolite alterations of Portunus trituberculatus during larval development

Journal of Oceanology and Limnology - A mass mortality often occurs from molting to the megalopa stage during the larval development of the swimming crab Portunus trituberculatus. Larvae with...     

Sea Level Prediction in the Yellow Sea From Satellite Altimetry With a Combined Least Squares-Neural Network Approach

Accessible high-quality observation datasets and proper modeling process are critically required to accurately predict sea level rise in coastal areas. This study focuses on developing and validating a combined least squares-neural network approach applicable to the short-term prediction of sea level variations in the Yellow Sea, where the periodic terms and linear trend of sea level change are fitted and extrapolated using the least squares model, while the prediction of the residual terms is performed by several different types of artificial neural networks. The input and output data used are the sea level anomalies (SLA) time series in the Yellow Sea from 1993 to 2016 derived from ERS-1/2, Topex/Poseidon, Jason-1/2, and Envisat satellite altimetry missions. Tests of different neural network architectures and learning algorithms are performed to assess their applicability for predicting the residuals of SLA time series. Different neural networks satisfactorily provide reliable results and the root mean square errors of the predictions from the proposed combined approach are less than 2?cm and correlation coefficients between the observed and predicted SLA are up to 0.87. Results prove the reliability of the combined least squares-neural network approach on the short-term prediction of sea level variability close to the coast.     

夏季通风气象指数预报

随着人们生活水平的提高,对室内污染越来越关注,应"中国室内环境监测委员会"提出的需求,通风气象指数于2006年6月首次向北京公众发布,文章就首先研发并投入业务使用的夏季通风指数给出了详细论述.通过对2005年夏季(6～8月)的各气象要素(气压、温、湿、风、能见度、天空状况等)资料共1790个数据做检验分析,最终选取体感温度为主要预报因子并综合考虑夏季特殊天气条件和风力以及污染的影响,得出夏季通风指数在一天中7个时段的预报公式,并划分出相应的指数等级.     

青海省玉树地区高精度航磁调查与应用研究

青海玉树地区位于我国重要的西南"三江"成矿带,具有高海拔、切割剧烈等特点,而高精度航磁调查是一种精度高、见效快、成本低的方法技术手段.在该区运用直升机长杆硬架技术并采取随地形缓起伏的方法,获取了高质量的原始数据.在高精度航磁图上,磁异常信息十分丰富,通过详细的物性资料分析和严谨的异常解释工作,摸清了区域磁场基本特征,推...     

DNQ3型能见度仪故障分析及校准方法研究

为有效提高国家地面气象观测站能见度仪观测数据准确性和设备运行稳定性,对能见度仪开展日常维护、核查校准、数据质控和故障修复等工作显得尤为重要。该文通过对DNQ3型前向散射能见度仪硬件结构和基本工作原理的介绍,以及对一些典型故障进行分析,总结出能见度仪的检测维修流程,归纳了对应的故障解决措施,凝练出该型能见度仪的核查校准和疑误数据质控方法,为一线业务人员开展能见度仪常规维护、故障排查、运行监控等提供借鉴。     

我国深海矿产研究:进展与发现(2011-2020)

深海矿产是地球上尚未被人类充分认识和利用的最大潜在战略矿产资源,近十年我国在该领域的研究取得了重要进展.在太平洋国际海底区域申请到2块多金属结核勘探区、1块富钴结壳勘探区,在西南印度洋中脊申请到1块多金属硫化物勘探区.研究阐明了我国多金属结核和富钴结壳勘探区小尺度成矿规律,揭示了其成矿作用过程及古海洋古气候记录,探讨了...     

多源地理空间矢量数据关联分析

针对多源地理空间矢量数据多来源、难以集成综合利用这一现状,本文提出了多源地理空间矢量数据关联方法,并以此为基础构建了多源地理空间矢量数据关联的可视与计算查询系统。首先,对多源地理空间矢量数据关联的概念及分类进行了定义。然后,以此为基础,提出了关联关系构建技术：自适应四叉树编码技术、扫描线技术、几何匹配及语义匹配技术。最后,为实现关联关系的直观展示,设计了原型系统。关联技术的提出可建立起多源地理空间矢量数据之间的关联关系,原型系统的构建也为用户综合利用多源地理空间矢量数据提供了平台,提高了数据的利用率及数据查询的效能。     

加强目标观测,服务防灾减灾

以深入浅出的方式介绍了目标观测的定义、历史、确定目标观测敏感区的方法,以及实施目标观测与防灾减灾的关系;并以欧洲中期天气预报中心目标观测业务化为例,简明地概括了目标观测的实施过程;结合国内目标观测研究现状,对中国目标观测的未来提出了看法。