Effects of deep excavation on seismic vulnerability of existing reinforced concrete framed structures

In this paper the effects of deep excavation on seismic vulnerability of existing buildings are investigated. It is well known that deep excavations induce significant changes both in stress and strain fields of the soil around them, causing a displacement field which can modify both the static and dynamic responses of existing buildings. A FEM model of a real case study, which takes into account geometry, non-linear soil behavior, live and dead loads, boundary conditions and soil–structure interaction, has been developed in order to estimate the soil displacements and their effects on seismic behavior of a reinforced concrete framed system close to deep excavation. Considering a significant accelerometric seismic input, the non-linear dynamic responses of the reinforced concrete framed structure, both in the pre and post-excavation configurations, have been evaluated and, then, compared to estimate the modification in seismic vulnerability, by means of different seismic damage indices and inter-story drifts.     

Time-transgressive cryoplanation terrace development through nivation-driven scarp retreat

Cryoplanation terraces are elevated bedrock features resembling giant staircases, with alternating steep scarps and shallow sloping treads. These landscape-scale features have long been associated with periglacial environments, but the processes involved in their formation remain vaguely specified and contentious. The two leading hypotheses for the formation of cryoplanation terraces are centered on: (1) geologic structure; and (2) nivation-driven scarp retreat. The nivation-formation hypothesis invokes scarp retreat under erosion processes associated with late-lying snowbanks. To test whether cryoplanation terraces develop through scarp retreat, six relative weathering indices (fracture counts, Cailleux roundness, Cailleux flatness, Krumbein sphericity, rebound, and weathering rind thickness) were measured across well-developed terraces in unglaciated eastern Beringia (central and western Alaska) at Mt Fairplay, Eagle Summit, and Skookum Pass. Statistically significant differences in relative weathering indices detected through chi-square and multiple-comparison procedures indicate that material is less weathered closer to scarps, i.e. that these areas were more recently exposed than those distant from the scarp. Based on these findings, a refined model of time-transgressive cryoplanation terrace development through nivation-driven scarp retreat is proposed. This new qualitative model addresses the removal of weathered material from terrace treads down side slopes through piping and gravity-driven mass-wasting processes. © 2019 John Wiley & Sons, Ltd.     

Observed trends and relationships between ENSO and standardized hydrometeorological drought indices in central Chile

Droughts are natural phenomena that severely affect socio economic and ecological systems. In Chile, population and economic activities are highly concentrated in its central region (i.e. between latitudes 29°S and 40°S), which periodically suffers from severe droughts affecting agriculture, hydropower, and mining. Understanding the dynamics of droughts and large-scale atmospheric processes that influence the occurrence of dry spells is essential for forecasting and efficient early detection of drought events. Central Chile's climate is marked by a significant El Niño Southern Oscillation (ENSO) influence that might help to better characterize droughts as well as to identify the effects of ENSO on the spatial and temporal characteristics of meteorological and hydrological droughts in the region. We analysed the behaviour of the Standardized Precipitation Evapotranspiration Index (SPEI) and Standardized Streamflow Index (SSI) time series for 6-month accumulation periods over the austral winter and summer seasons. Multiple linear regression (MLR) and Generalized Linear Models (GLM) showed a significant ENSO influence on dry events for SPEI-6 and SSI-6 during winter and summer. We found that the magnitude of correlation between ENSO and SPEI-6 has changed over the last decades becoming weaker in winter periods and increasing in spring summer periods. Increasing trends in meteorological and hydrological drought events were also identified, along all latitudes, with significant trends during winter in the southern latitudes, and during summer in the semi-arid and Mediterranean zones. These results indicate that drought mitigation actions and policies are necessary to overcome their adverse effects. Given the monthly persistence of ENSO and its relationship to drought indices, there are opportunities for drought monitoring and seasonal forecasting that could become part of national drought management systems.     

Towards an automated approach to map flooded areas from Sentinel-2 MSI data and soft integration of water spectral features

In this work we propose an approach for mapping flooded areas from Sentinel-2 MSI (Multispectral Instrument) data based on soft fuzzy integration of evidence scores derived from both band combinations (i.e. Spectral Indices - SIs) and components of the Hue, Saturation and Value (HSV) colour transformation. Evidence scores are integrated with Ordered Weighted Averaging (OWA) operators, which model user’s decision attitude varying smoothly between optimistic and pessimistic approach. Output is a map of global evidence degree showing the plausibility of being flooded for each pixel of the input Sentinel-2 (S2) image. Algorithm set up and validation were carried out with data over three sites in Italy where water surfaces are extracted from stable water bodies (lakes and rivers), natural hazard flooding, and irrigated paddy rice fields. Validation showed more than satisfactory accuracy for the OR-like OWA operators (F-score > 0.90) with performance slightly decreased (F-score < 0.75) over heterogeneous conditions (e.g. rice fields). The algorithm was applied with no changes and/or tuning to independent sites from the Copernicus Emergency Management Service (EMS) activations to simulate operational conditions. Over these sites, the proposed approach achieved greater, more consistent and robust mapping accuracy compared to traditional approaches based on the segmentation of single input features. Moreover, OWA operators offer an appealing way of combining and aggregating multiple information in decision making by modelling uncertainty in decision process.     

Remotely-sensed assessment of the impact of century-old biochar on chicory crop growth using high-resolution UAV-based imagery

In recent years, special attention has been given to the long-term effects of biochar on the performance of agro-ecosystems owing to its potential for improving soil fertility, harvested crop yields, and aboveground biomass production. The present experiment was set up to identify the effects on soil-plant systems of biochar produced more than 150 years ago in charcoal mound kiln sites in Wallonia (Belgium). Although the impacts of biochar on soil-plant systems are being increasingly discussed, a detailed monitoring of the crop dynamics throughout the growing season has not yet been well addressed. At present there is considerable interest in applying remote sensing for crop growth monitoring in order to improve sustainable agricultural practices. However, studies using high-resolution remote sensing data to focus on century-old biochar effects are not yet available. For the first time, the impacts of century-old biochar on crop growth were investigated at canopy level using high-resolution airborne remote sensing data over a cultivated field. High-resolution RGB, multispectral and thermal sensors mounted on unmanned aerial vehicles (UAVs) were used to generate high frequency remote sensing information on the crop dynamics. UAVs were flown over 11 century-old charcoal-enriched soil patches and the adjacent reference soils of a chicory field. We retrieved crucial crop parameters such as canopy cover, vegetation indices and crop water stress from the UAV imageries. In addition, our study also provides in-situ measurements of soil properties and crop traits. Both UAV-based RGB imagery and in-situ measurements demonstrated that the presence of century-old biochar significantly improved chicory canopy cover, with greater leaf lengths in biochar patches. Weighted difference vegetation index imagery showed a negative influence of biochar presence on plant greenness at the end of the growing season. Chicory crop stress was significantly increased by biochar presence, whereas the harvested crop yield was not affected. The main significant variations observed between reference and century-old biochar patches using in situ measurements of crop traits concerned leaf length. Hence, the output from the present study will be of great interest to help developing climate-smart agriculture practices allowing for adaptation and mitigation to climate.     

Multispectral sensor spectral resolution simulations for generation of hyperspectral vegetation indices from Hyperion data

The use of multispectral satellite sensors for generation of hyperspectral indices is restricted because of their coarse spectral resolutions. In this study, we attempted to synthesize a few of these hyperspectral indices, viz. RedEdge Normalized Difference Vegetation Index (NDVI₇₀₅), Plant Senescence Reflectance Index (PSRI) and Normalized-Difference-Infrared-Index (NDII), for crop stress monitoring at regional scale using multispectral images, simulated from Hyperion data. The Hyperion data were resampled and simulated to corresponding spatial and spectral resolutions of AWiFS, OCM-2 and MODIS sensors using their respective filter function. Different possible combinations of two bands (i.e. simple difference, simple ratio and normalized difference) were computed using synthetic spectral bands of each sensor, and were regressed with NDVI₇₀₅, PSRI and NDII. Models with highest correlation were selected and inverted on Hyperion data of another date to synthesize respective multispectral indices. Synthetic broad band indices of multispectral sensors with their respective narrow band indices of Hyperion were found to be in good agreement.     

结合Sentinel-2光谱与纹理信息的冬小麦作物茬覆盖度估算

作物茬覆盖度的估算对于探究农业耕作方式对周围环境的影响具有十分重要的意义。目前,基于多光谱影像的作物茬指数是作物茬覆盖度估算的常用方法。然而,在作物茬高覆盖区域,指数法容易出现“饱和”现象。已有研究结果表明结合影像的光谱与纹理信息有助于改善指数法的“饱和”问题。Sentinel-2作为一颗多光谱卫星,空间分辨率可达10 m,与Landsat OLI相比,具有更丰富的纹理信息。因此,探究Sentinel-2光谱与纹理信息相结合在作物茬覆盖度估算上的潜力具有重要意义。本文以山东省禹城市为研究区,分析了Sentinel-2各波段反射率、归一化差值指数以及不同窗口大小下灰度共生矩阵统计量等遥感因子与野外实测作物茬覆盖度的相关性,并利用最优子集法对遥感因子进行筛选,构建作物茬覆盖度的最优估算模型。同时,使用留一法交叉验证对模型进行评价。结果表明在单因子分析中,归一化差异耕作指数NDTI（Normalized Difference Residue Index）与作物茬覆盖度的相关性最好,相关系数达0.735。使用NDTI、5×5窗口下Sentinel-2 8A波段的相关性统计量以及12波段的方差统计量构建的多元方程是作物茬覆盖度估算的最优模型,相关系数为0.869,均方根误差为11%。与仅使用光谱信息的最优模型相比,相关系数提高了0.094,均方根误差下降了3.5%。可见,结合Sentinel-2的纹理信息有助于提高作物茬覆盖度的估算精度。     

1961—2019年黑龙江省冬季气温季节内变化及环流异常特征

利用1961—2019年黑龙江省冬季气温、NCEP再分析资料和环流指数资料,采用多变量经验正交函数分解、合成分析、相关分析等方法,分析黑龙江省冬季气温季节内变化及其环流异常特征,并进一步对比了主要环流因子在冬季气温季节内演变不同模态中的相对贡献。结果表明：季节内变化是黑龙江省冬季气温变化的基本特征。黑龙江省冬季气温存在季节内一致变化、12月和翌年1—2月反位相变化、12月至翌年1月和2月反位相变化三个主要模态。当冬季气温处于第一模态分布一致偏暖(冷)时,环流呈现北极涛动(AO)正(负)位相的分布特征,东亚冬季风(EAWM)偏弱(强)。当冬季气温发生季节内冷暖转换时,季内极涡、高空急流、西伯利亚高压(SH)和EAWM强度、中高纬环流经向度等均有明显调整。第二模态1月和第三模态2月环流场分别呈现类似极地欧亚型(PEA)和东大西洋型(EA)遥相关的分布特征。AO、SH、EAWM、PEA和EA是冬季气温季节内演变的重要影响因子。     

Forecasting geomagnetic activity

A study of the daily, monthly and annual values of the geomagnetic activity indexAp for 1932 onwards and of the annualaa indices for 1868 onwards indicated that their variations had large random components. Long-term predictions were not possible from time-series extrapolations.     

Regionalisation of hydrological responses under land-use change and variable data quality

ABSTRACT

Estimating river flows at ungauged sites is generally recognised as an important area of research. In countries or regions with rapid land development and sparse hydrological gauging networks, three particular challenges may arise—data scarcity, data quality, and hydrological non-stationarity. Using data from 44 gauged sub-catchments of the upper Ping catchment in northern Thailand from the period 1995–2006, three relevant flow response indices (runoff coefficient, base flow index and seasonal elasticity of flow) were regionalised by regression against available catchment properties. The runoff coefficient was the most successfully regionalised, followed by base flow index and lastly the seasonal elasticity. The non-stationarity (represented by the differences between two 6-year sub-periods) was significant both in the flow response indices and in land use indices; however relationships between the two sets of indices were weak. The regression equations derived from regionalisation were not helpful in predicting the non-stationarity in the flow indices except somewhat for the runoff coefficient. A partly subjective data quality scoring system was devised, and showed the clear influence of rainfall and flow data quality on regionalisation uncertainty. Recommendations towards improving data support for hydrological regionalisation in Thailand include more relevant soils databases, improved records of abstractions and investment in the gauge network. Widening of the regionalisation beyond the upper Ping and renewed efforts at using remotely sensed rainfall data are other possible ways forward.

EDITOR Z.W. Kundzewicz ASSOCIATE EDITOR T. Wagener