Changing mechanism of global water scarcity events: Impacts of socioeconomic changes and inter-annual hydro-climatic variability

Changes in available fresh water resources, together with changes in water use, force our society to adapt continuously to water scarcity conditions. Although several studies assess the role of long-term climate change and socioeconomic developments on global water scarcity, the impact of inter-annual climate variability is less understood and often neglected. This paper presents a global scale water scarcity assessment that accounts for both temporal changes in socioeconomic conditions and hydro-climatic variability over the period 1960–2000. We thereby visualized for the first time possible over- and underestimations that may have been made in previous water scarcity assessments due to the use long-term means in their analyses. Subsequently, we quantified the relative contribution of hydro-climatic variability and socioeconomic developments on changing water scarcity conditions. We found that hydro-climatic variability and socioeconomic changes interact and that they can strengthen or attenuate each other, both regionally and at the global scale. In general, hydro-climatic variability can be held responsible for the largest share (>79%) of the yearly changes in global water scarcity, whilst only after six to ten years, socioeconomic developments become the largest driver of change. Moreover, our results showed that the growth in the relative contribution of socioeconomic developments to changing water scarcity conditions stabilizes towards 2000 and that the impacts of hydro-climatic variability remain significantly important. The findings presented in this paper could be of use for water managers and policy makers coping with water scarcity issues since correct information both on the current situation and regarding the relative contribution of different mechanisms shaping future conditions is key to successful adaptation and risk reduction.     

Probabilistic modelling of auto-correlation characteristics of heterogeneous slopes

Spatial variability of soil materials has long been recognised as an important factor influencing the reliability of geo-structures. This study stochastically investigates the influence of spatial variability of shear strength on the stability of heterogeneous slopes, focusing on the auto-correlation function, auto-correlation distance and cross-correlation between soil parameters. The finite element method is merged with the random field theory to probabilistically evaluate factor of safety and probability of failure via Monte-Carlo simulations. The simulation procedure is explained in detail with suggestions on improving efficiency of the Monte-Carlo process. A simple procedure to create cross-correlation between random variables, which allows direct comparison of the influence of each strength variable, is discussed. The results show that the auto-correlation distance and cross-correlation can significantly influence slope stability, while the choice of auto-correlation function only has a minor effect. An equation relating the probability of failure with the auto-correlation distance is suggested in light of the analyses performed in this work and other results from the literature.     

Reliability of digit length impression as a character of tetrapod ichnotaxobase: considerations from the Carboniferous–Permian ichnogenus Ichniotherium

Although the relative length of digit impressions is often adopted as a binding character in ichnotaxa discrimination and trackmaker identification, it cannot be considered unequivocally operative. The reliability of this character has been evaluated by means of principal component analysis on several well‐preserved footprints (both manus and pes) referred to as Ichniotherium sphaerodactylum from the Early Permian Tambach Formation (Thuringia, Germany). The analysis reveals a substantial variability of digit impression length (especially in the manus), relativizing the validity of digit IV length as a diagnostic character as practised in different ichnological studies. Regarding the use of such a character, results clearly suggest the need to preliminarily conduct explorative analysis on the whole available ichnological material in order to detect which digit is the most consistent from an ichnotaxonomical standpoint, thus avoiding an arbitrary selection. Such a preliminary analysis should provide a better control on ichnotaxonomical splitting/lumping, particularly in the case of allied footprints, and can also be considered a valuable tool, if associated to functionality analysis, in improving and refining trackmaker identification. Copyright © 2014 John Wiley & Sons, Ltd.     

基于土地利用格局变化的胶东半岛生境质量时空演变特征研究

生境质量受人类活动引起的土地利用变化影响日益严重,因此,对于生境质量的监测与评估具有重要意义。基于2000、2005、2010、2015和2020年土地利用数据,利用GIS空间分析技术和InVEST-Habitat Quality模型,对胶东半岛土地利用和生境质量时空特征进行定量化描述,甄别生境质量变化的热点区域,探究胶东半岛土地利用格局变化对生境质量的影响。结果表明：耕地一直是胶东半岛的主要土地利用类型,该地区整体土地转移的速率呈缓慢上升趋势,建设用地的转入和耕地的转出尤为突出;胶东半岛5个年份的生境质量平均值分别为0.565、0.560、0.552、0.548、0.545,总体上呈下降趋势;不同等级区域的面积占比大小依次为：中等、高、低、较高、较低;中等生境质量区域面积减少最多,而低等生境质量区域面积增加最多,内陆区域生境质量高值区面积小且分散,而生境质量低值区分布相对集中且呈块状、片状;生境质量指数变化速率在减缓;不同区域中,生境质量对于土地利用变化的响应不同,建设用地增加是胶东半岛地区生境质量整体下降的主要原因,而滨海湿地增加提高了局部区域的生境质量。本研究将为胶东半岛地区土地的规划管理和生态环境保护提供相关科学参考。     

实时路况支持下的南京市消防救援覆盖率时空模式分析

快速城镇化导致我国城市消防应急服务基础设施与城市发展不同步的问题日益凸显,城市消防救援覆盖率评估是提升消防服务质量与优化消防资源配置的重要手段。本文提出一种基于实时路况的城市消防救援覆盖率评估模型,通过考虑消防站管辖区域的空间限制,在2020年9月连续三周时间内利用高德地图API获取消防站到达历史火灾事件的实时出行救援时间,对南京市消防救援覆盖率的时空模式进行分析与挖掘。结果显示：① 南京城市火灾密集区域（简称火灾密集区）消防站的平均出行救援时间约10 min,非火灾密集区约16 min,均比国家规定的5 min到达时间标准明显要长,导致南京市消防站在5 min到达标准下的覆盖率仅为8.2%;② 由于南京火灾密集区消防站的平均行车救援距离仅为非火灾密集区的37%,导致火灾密集区火灾事件等待救援时间明显低于非火灾密集区,尤其火灾密集区西南部、东北部及部分消防站周边火灾事件等待救援时间相对较短,但南京全区火灾事件等待救援时间在5 min以内的比例不足7%,且等待救援时间在5~10 min之间的短距离火灾事件受早晚交通出行高峰期交通拥堵影响最大;③ 南京市消防站救援覆盖率受早晚交通出行高峰影响呈现早晚交通出行高峰期明显低于其他时段的“W”形变化模式,火灾密集区消防站在5 min到达标准下的救援覆盖率从非交通出行高峰期的11.5%降低到交通出行高峰期的8.4%,而非火灾密集区从6.1%降低到5%,火灾密集区东南部石门坎与东山交界区域和北部汉中门与迈皋桥周边区域早晚交通出行高峰时段等待救援时间超过15 min的火灾事件比非交通出行高峰时段明显增多;④ 在5 min到达标准下,南京市消防站救援覆盖率“W”形模式波动最小,10 min到达标准下的平均覆盖率为43.5%且波动最明显,15 min到达标准下的平均覆盖率达到75%。最后根据分析结果给出了南京市消防未来建设发展意见。     

耦合人群移动的COVID-19传染病模型研究进展

构建传染病模型可为疫情防控与公共卫生研究提供至关重要的规划与解析工具。由于宿主行为是传染病传播动态的决定性因素之一,有效耦合人群时空行为对以人为宿主的传染病建模具有重要意义。得益于人群移动大数据研究与应用的快速发展,新型冠状病毒肺炎（COVID-19）的疫情建模研究中呈现出了耦合人群移动建模的显著特征。为系统深入理解该项传染病模型研究中的重要进展,本文对相关文献进行分析与总结。首先,本文分析了COVID-19疫情与人群移动的交互影响,说明了耦合人群移动构建COVID-19模型的必要性。然后,根据建模的目的和原理,从疫情短期预测与过程模拟2个角度,对耦合人群移动的COVID-19传染病模型进行分类梳理。其中,根据耦合人群移动的方式,本文将面向疫情短期预测的模型分为人群移动一阶量与人群移动二阶量的耦合模型,将基于过程模拟的模型分为群体级别和个体级别的耦合模型。最后,本文评述了耦合人群移动的传染病模型研究进展和未来发展方向,认为该领域研究亟需更加深入建模与疾病传播相关的复杂人群时空行为、提升模型的空间解析能力、突破精细化时空传播模拟的计算瓶颈、拓展与前沿人工智能方法的融合,并构建普适而开放的建模数据与工具以促进应用发展。     

基于多粒度时空对象数据模型的城市基础设施建模与管理

城市基础设施的全方位描述与信息化管理是建设新型智慧城市的重要基础。目前在城市基础设施建模与管理方面,以地图为模板的空间数据模型、传统的面向对象空间数据模型以及实时GIS数据模型不支持对时空对象组成结构、行为能力等要素的描述,无法全面、精细地表达设施对象信息,而计算机、物联网和地理信息系统（Geographic Information System,GIS）领域已有的城市基础设施管理方案忽略了对设施自身信息的管理,无法较好地支持设施对象及其产生数据的一体化管理。针对上述问题,首先通过扩展GBT30428.2-2013标准,完成了城市基础设施的分类与编码;然后基于多粒度时空对象数据模型（Multi-granularity Spatiotemporal Object Data Model, MGSTODM）,提出了一种城市基础设施对象化描述模型,支持对城市基础设施信息的全方位描述与表达;在此基础上,提出一种城市基础设施对象化管理方法,设计了相应的技术架构,并研制了基于云存储的百万级城市基础设施对象化管理原型系统。试验结果表明,所提出的城市基础设施对象化描述模型与管理方法具备可行性、有效性和高效性。     

基于控制区空间变异性的耕地质量监测样点布控方法

监测样点布设是实现对区域耕地质量监测的基础。为了提高耕地质量监测精度,建立了一套基于监测控制区空间变异性的耕地质量监测样点布控方法。利用Neyman法确定在给定置信度和抽样误差下的研究区最优样点总数;根据耕地质量及其影响因素划定监测控制区,为研究区进行空间分层;利用变异系数为各控制区分配监测样点;在各控制区内采用空间随机法布设监测样点。为了对比该抽样法的估算精度,又采用空间随机抽样法和基于自然质量等别、基于控制区权重的分层抽样法等进行了其余4种抽样布设方案,并计算了5种样点布设方案的Kriging估计误差,通过对比发现,在相同的取样总数下,不同的样点布设方案估算精度差别显著,基于控制区空间变异性的耕地质量监测样区分层布控方法的RMSE最小。得出科学的监测样点布设方案,可以在最小的投入下获取最大的信息量,提高耕地质量监测效率和精度。     

Optimizing an index with spatiotemporal patterns to support GEOSS Clearinghouse

A variety of Earth observation systems monitor the Earth and provide petabytes of geospatial data to decision-makers and scientists on a daily basis. However, few studies utilize spatiotemporal patterns to optimize the management of the Big Data. This article reports a new indexing mechanism with spatiotemporal patterns integrated to support Big Earth Observation (EO) metadata indexing for global user access. Specifically, the predefined multiple indices mechanism (PMIM) categorizes heterogeneous user queries based on spatiotemporal patterns, and multiple indices are predefined for various user categories. A new indexing structure, the Access Possibility R-tree (APR-tree), is proposed to build an R-tree-based index using spatiotemporal query patterns. The proposed indexing mechanism was compared with the classic R*-tree index in a number of scenarios. The experimental result shows that the proposed indexing mechanism generally outperforms a regular R*-tree and supports better operation of Global Earth Observation System of Systems (GEOSS) Clearinghouse.     

Seasonal variability of phytoplankton biomass and composition in the major water masses of the Indian Ocean sector of the Southern Ocean

Long-term changes in phytoplankton biomass and community composition are important in the ecosystem and biogeochemical cycle in the Southern Ocean. We aim to ultimately evaluate changes in phytoplankton assemblages in this region on a decadal scale. However, yearly continuous data are lacking, and long-term datasets often include seasonal variability. We evaluated the seasonal changes in phytoplankton abundance/composition across latitudes in the Indian Ocean sector of the Southern Ocean via multi-ship observations along the 110°E meridian from 2011 to 2013. The chlorophyll a concentration was 0.3–0.5 mg m⁻³ in the Subantarctic Zone (40–50°S) and 0.4–0.6 mg m⁻³ in the Polar Frontal Zone (50–60°S); pico-sized phytoplankton (<10 μm), mainly haptophytes, were dominant in both zones. In the Antarctic Divergence area (60–65°S), the chlorophyll a concentration was 0.6–0.8 mg m⁻³, and nano-sized phytoplankton (>10 μm), mainly diatoms, dominated. Chlorophyll a concentrations and phytoplankton community compositions were the same within a latitudinal zone at different times, except during a small but distinct spring bloom that occurred north of 45°S and south of 60°S. This small seasonal variation means that this part of the Southern Ocean is an ideal site to monitor the long-term effects of climate change.