Research Progress and Prospect on Reactivation of Ancient Landslides

The ancient landslide has endured long-term slope evolution which results in its complicated material and special rock-soil properties. The risk of ancient landslide reactivation is substantially increasing due to the increase of intensified human engineering activities and the frequency of extreme weather events. Many ancient landslides have been reactivated all over the world and led to serious fatalities and severe damage to many important engineering facilities such as transportation and hydropower engineering projects. On the basis of the analysis of the research situation about the ancient landslides at home and abroad, the main research advances were summarized including the regional developing laws and recognizing of the ancient landslides, the mechanics properties of ancient landslide body and related sliding zone, reactivation mechanism of ancient landslides, reactivating process and modeling analysis of ancient landslides, early recognization of ancient landslide reactivation, etc. To meet the demands of disaster prevention and reduction, three key scientific issues were put forward to be solved: ①automaticaly establishing the methodology and identification criterions for recognition of ancient landslide; ②revealing the reactivation mechanism of ancient landslide based on a new strength theory; ③establishing the early rapid recognition method and predictive model for ancient landslide reactivation. Solving the above mentioned scientific theory and methodology will facilitate the planning and site selection of major projects as well as the disaster prevention and reduction in ancient landslide developing areas.     

A modified three-dimensional ionospheric tomography algorithm with side rays

The three-dimensional ionospheric tomography (3DCIT) algorithm based on Global Navigation Satellite System (GNSS) observations have been developed into an effective tool for ionospheric monitoring in recent years. However, because the rays that come into or come out from the side of the inversion region cannot be used, the distribution of the rays in the edge and bottom part of the inversion region is scarce and the electron density cannot be effectively improved in the inversion process. We present a three-dimensional tomography algorithm with side rays (3DCIT-SR) applying the side rays to the inversion. The partial slant total electron content (STEC) of side rays in the inversion region is obtained based on the NeQuick2 model and GNSS-STEC. The simulation experiment results show that the algorithm can effectively improve the distribution of GNSS rays in the inversion region. Meanwhile, the iteration accuracy has also been significantly improved. After the same number of iterations, the iterative results of 3DCIT-SR are closer to the truth than 3DCIT, in particular, the inversion of the edge regions is improved noticeably. The GNSS data of the International GNSS Service (IGS) stations in Europe are used to perform real data experiments, and the inversion results show that the electron density profiles of 3DCIT-SR are closer to the ionosonde measurements. The accuracy improvement of 3DCIT-SR is up to 56.3% while the improvement is more obvious during the magnetic storm compared to the case of a calm ionospheric state .     

A comparative analysis of the NDVIg and NDVI3g in monitoring vegetation phenology changes in the Northern Hemisphere

Phenology is a sensitive and critical feature of vegetation and is a good indicator for climate change studies. The global inventory modelling and mapping studies (GIMMS) normalized difference vegetation index (NDVI) has been the most widely used data source for monitoring of the vegetation dynamics over large geographical areas in the past two decades. With the release of the third version of the NDVI (GIMMS NDVI3g) recently, it is important to compare the NDVI3g data with those of the previous version (NDVIg) to link existing studies with future applications of the NDVI3g in monitoring vegetation phenology. In this study, the three most popular satellite start of vegetation growing season (SOS) extraction methods were used, and the differences between SOSg and SOS3g arising from the methods were explored. The amplitude and the peak values of the NDVI3g are higher than those of the NDVIg curve, which indicated that the SOS derived from the NDVIg (SOSg) was significantly later than that derived from the NDVI3g (SOS3g) based on all the methods, for the whole northern hemisphere. In addition, SOSg and SOS3g both showed an advancing trend during 1982–2006, but that trend was more significant with SOSg than with SOS3g in the results from all three methods. In summary, the difference between SOSg and SOS3g (in the multi-year mean SOS, SOS change slope and the turning point in the time series) varied among the methods and was partly related to latitude. For the multi-year mean SOS, the difference increased with latitude intervals in the low latitudes (0–30°N) and decreased in the mid- and high-latitude intervals. The GIMMS NDVI3g data-sets seemed more sensitive than the GIMMS NDVIg in detecting information about the ground, and the SOS3g data were better correlated both with the in situ observations and the SOS derived from the Moderate Resolution Imaging Spectroradiometer NDVI. For the northern hemisphere, previous satellite measures (SOS derived from GIMMS NDVIg) may have overestimated the advancing trend of the SOS by an average of 0.032 d yr^–1.     

Mapping fine‐scale urban housing prices by fusing remotely sensed imagery and social media data

The accurate mapping of urban housing prices at a fine scale is essential to policymaking and urban studies, such as adjusting economic factors and determining reasonable levels of residential subsidies. Previous studies focus mainly on housing price analysis at a macro scale, without fine‐scale study due to a lack of available data and effective models. By integrating a convolutional neural network for united mining (UMCNN) and random forest (RF), this study proposes an effective deep‐learning‐based framework for fusing multi‐source geospatial data, including high spatial resolution (HSR) remotely sensed imagery and several types of social media data, and maps urban housing prices at a very fine scale. With the collected housing price data from China's biggest online real estate market, we produced the spatial distribution of housing prices at a spatial resolution of 5 m in Shenzhen, China. By comparing with eight other multi‐source data mining techniques, the UMCNN obtained the highest housing price simulation accuracy (Pearson R = 0.922, OA = 85.82%). The results also demonstrated a complex spatial heterogeneity inside Shenzhen's housing price distribution. In future studies, we will work continuously on housing price policymaking and residential issues by including additional sources of spatial data.     

小冰期时中国南方地区降水模式的差异研究

小冰期是过去一千年中全球气候变化的重要事件之一。关于小冰期时中国季风区和西风影响区气候变化的对比研究众多,但是缺乏中国南方地区降水模式时空差异的研究,难以了解中国南方地区降水变化规律。为了系统地了解小冰期时中国南方地区降水的复杂性,本文将中国南方地区划分为东南—华南沿海地区、中部地区以及西南地区三个区域,总共选取了19条高分辨率的古气候记录进行对比研究,主要有以下几点认识:(1)相对于中世纪暖期而言,小冰期期间中国南方东南—华南沿海地区的气候偏湿,这可能与雨带在中国南方的滞留时间延长和沿海地区受台风的影响增强有关。(2)中国中部地区秦岭南麓和神农架高山林区在小冰期时期主要呈"冷湿"的模式,差异在于秦岭南麓区域主要在小冰期中后期偏湿,这与中部其他区域偏"冷干"的模式不同。这种区域差异可能是由于地形地势和大气环流的复杂性导致。(3)中国西南地区受印度夏季风和东亚夏季风的共同影响,且该区域地形复杂,其气候变化在小冰期时期存在更加明显的空间差异,没有呈现出比较一致的降水模式。与小冰期期间的降水变化不同的是,近30年东南—华南沿海地区除了台湾和雷州半岛,其他区域降水明显减少,可能受气温和人类活动等因素的影响。通过结合高分辨率的古气候记录,我们系统分析了中国南方小冰期的干湿模式在时空上的差异及其可能的影响因子,这对于认识小冰期时中国南方不同区域降水的复杂性及未来旱涝灾害的防控具有一定意义。     

论中国国家公园地质考察与评价——以浙江丽水百山祖国家公园为例

鉴于保护地调查评价历史与目标,国家公园地质考察评价基准是地质学关于地球的“时间、空间、演化”知识的发现路径,既识别国家公园候选地的国家符合性地质事件,又识别国家公园自然性、独特性、优美性、多样性、整体性的地质机制,提供国家公园最重要的自然生态系统与自然景观保育管理的地质学支撑。浙江丽水百山祖国家公园符合性的地质事件是公园发现的4.0~4.2 Ga冥古宙陆核物质的锆石晶体、中生代岛弧陆盆火山酸性火山岩系列和从流纹岩山岭到花岗岩—变质岩谷底的“峰—岭—丘—谷（盆）”的亚热带滨海山地地貌结构,地貌结构发育演化是百山祖公园最重要的自然生态系统、区域性流域水源地、独特山水景观的形成基础。保护百祖山公园地貌结构和过程的完整性与真实性是确保其重要自然生态系统自然演化和生态服务产品持续供给的基础。     

Effects of different soil and water conservation measures on hydrological extremes and flood processes in the Yanhe River,Loess Plateau,China

The runoff and sediment load of the Loess Plateau have changed significantly due to the implementation of soil and water conservation measures since the 1970s. However, the effects of soil and water conservation measures on hydrological extremes have rarely been considered. In this study, we investigated the variations in hydrological extremes and flood processes during different periods in the Yanhe River Basin (a tributary of the Loess Plateau) based on the daily mean runoff and 117 flood event data from 1956 to 2013. The study periods were divided into reference period (1956–1969), engineering measures period (1970–1995), and biological control measures period (1996–2013) according to the change points of the annual streamflow and the actual human activity in the basin. The results of the hydrological high extremes (HF1_max, HF3_max, HF7_max) exhibit a decreasing trend (P?<?0.01), whereas the hydrological low extremes (HBF1_min, HBF3_min, HBF7_min) show an increasing trend during 1956–2013. Compared with the hydrological extremes during the reference period, the hydrological high extremes increased during the engineering measures period at low (<?15%) and high frequency (>?80%), whereas decreased during the biological control measures period at almost all frequencies. The hydrological low extremes generally increased during both the engineering measures and biological control measures periods, particularly during the latter period. At the flood event scale, most flood event indices in connection with the runoff and sediment during the engineering measures period were significantly higher than those during the biological control measures period. The above results indicate that the ability to withstand hydrological extremes for the biological control measures was greater than that for the engineering measures in the studied basin. This work reveals the effects of different soil and water conservation measures on hydrological extremes in a typical basin of the Loess Plateau and hence can provide a useful reference for regional soil erosion control and disaster prevention policy-making.

     

冻土机械切削破碎机理的研究进展

冻土开挖困难、破碎效率低是高寒地区工程建设、地基施工等面临的技术难题。冻土机械切削破碎是冻土开挖的主要方法,其机理研究是提高冻土破碎效率的前提和基础。首先总结了温度、含水率、围压等对冻土复杂力学特性的影响,进而调研分析了冻土机械切削破碎的典型切削力学模型,发现冻土切削机械破碎模式不仅与冻土力学特性密切相关,也与切削参数和刀具结构直接相关,冻土切削过程中存在着最优的切削前角（30°~60°）,且深切削和浅切削时冻土内部受力方式存在差异也会导致破坏形式的不同;温度、含水率、围压所造成的冻土力学性能变化会直接导致冻土破坏过程和切削破碎机理的改变,冻土强度随着温度降低表现出先升高然后保持稳定的特性,随着含水率升高呈现出先升高后降低的趋势,冻土破碎存在脆性、塑脆过渡及塑性等不同破坏形式。通过系统总结冻土切削破碎机理研究进展,进一步明确了冻土力学性质主要影响因素、变化特点及其切削破坏损伤特征,为冻土机械切削破碎的切削参数和切削具结构优化提供了设计依据。     

长江中游沿岸地下水中有机质分子组成特征及其对碘富集的指示

长期摄入高碘地下水（碘浓度＞100 μg/L）会造成人体甲状腺机能损伤.天然有机质被认为是影响高碘地下水形成的关键组分,为研究地下水中溶解性有机质（DOM）分子组成对碘富集的影响,选取长江中游沿岸浅层地下水作为研究对象,运用傅立叶变换离子回旋共振质谱仪（FT-ICR-MS）表征不同碘浓度地下水中DOM分子组成差异.研究发现碘易富集在还原环境的浅层地下水中,地下水中碘的浓度与溶解性有机碳（DOC）浓度无显著关系,DOM分子总数越多碘浓度越高;高碘地下水较低碘水DOM分子均一性、多样性更强,氧化程度和不饱和程度更高,含更多芳香性结构.长江中游沿岸高碘地下水的形成受DOM分子组成控制,主要与不饱和程度高尤其是含芳香性结构的大分子DOM有关,含芳香性结构的DOM分子与碘络合在高碘地下水的形成过程中起重要作用.      

华北克拉通南缘古元古代晚期汝阳群微体化石及其古环境意义:来自微细构造和生物标志化合物的证据

华北克拉通南缘古元古代晚期汝阳群白草坪组页岩中产出大量的具刺和细网状纹饰的球形疑源类,其中以Shuiyousphaeridium macroreticulatum与Dictyosphaera macroreticulata化石标本最具代表性.利用扫描电子显微镜结合光学生物显微镜对其膜壳微细构造进行观察,结果显示:膜壳表面的刺饰形态具有多样性分叉;其膜壳壁可能是由多边形网脊及膜层构成,而不是由多角形板片及膜层构成.同时通过对比研究,认为两种最具代表性的特征分子可能是同一生物不同阶段的产物.此外,通过对赋存微体化石页岩进行生物标志化合物分析,检测到的姥鲛烷/植烷比(Pr/Ph)大于1、伽马蜡烷丰度中等及生物标志化合物(C₃₀藿烷、C₂₇甾烷和三环萜烷),结合前人关于汝阳群沉积环境的研究,不仅指示了汝阳群微体化石群沉积古环境应为正常的海洋环境——滨海-浅海相,也指示了元古代真核生物已经存在,为重建微体化石群和探讨早期生命演化提供了重要的理论依据.