Green Lake Landslide and other giant and very large postglacial landslides in Fiordland,New Zealand

Green Lake Landslide is an ancient giant rock slide in gneiss and granodiorite located in the deeply glaciated Fiordland region of New Zealand. The landslide covers an area of 45 km² and has a volume of about 27 km³. It is believed to be New Zealand's largest landslide, and possibly the largest landslide of its type on Earth. It is one of 39 known very large (10⁶–10⁷ m³) and giant (≥10⁸ m³) postglacial landslides in Fiordland discussed in the paper. Green Lake Landslide resulted in the collapse of a 9 km segment of the southern Hunter Mountains. Slide debris moved up to 2.5 km laterally and 700 m vertically, and formed a landslide dam about 800 m high, impounding a lake about 11 km long that was eventually infilled with sediments. Geomorphic evidence supported by radiocarbon dating indicates that Green Lake Landslide probably occurred 12 000–13 000 years ago, near the end of the last (Otira) glaciation. The landslide is described, and its geomorphic significance, age, failure mechanism, cause, and relevance in the region are discussed, in relation to other large landslides and recent earthquake-induced landslides in Fiordland. The slope failure occurred on a low-angle fault zone undercut by glacial erosion, and was probably triggered by strong shaking (MM IX–X) associated with a large (≥ M 7.5–8) earthquake, on the Alpine Fault c. 80 km to the northwest. Geology was a major factor that controlled the style and size of Green Lake landslide, and in that respect it is significantly different from most other gigantic landslides. Future large earthquakes on the Alpine Fault in Fiordland are likely to trigger more very large and giant landslides across the region, causing ground damage and devastation on a scale that has not occurred during the last 160 years, with potentially disastrous effects on towns, tourist centres, roads, and infrastructure. The probability of such an event occurring within the next 50 years may be as high as 45%.     

Effect of melt composition on basalt and peridotite interaction: laboratory dissolution experiments with applications to mineral compositional variations in mantle xenoliths from the North China Craton

Interaction between basaltic melts and peridotites has played an important role in modifying the lithospheric and asthenospheric mantle during magma genesis in a number of tectonic settings. Compositions of basaltic melts vary considerably and may play an important role in controlling the kinetics of melt–peridotite interaction. To better understand the effect of melt composition on melt–peridotite interaction, we conducted spinel lherzolite dissolution experiments at 2 GPa and 1,425 °C using the dissolution couple method. The reacting melts include a basaltic andesite, a ferro-basalt, and an alkali basalt. Dissolution of lherzolite in the basaltic andesite and the ferro-basalt produced harzburgite–lherzolite sequences with a thin orthopyroxenite layer at the melt–harzburgite interface, whereas dissolution of lherzolite in the alkali basalt produced a dunite–harzburgite–lherzolite sequence. Systematic variations in mineral compositions across the lithological units are observed. These mineral compositional variations are attributed to grain-scale processes that involve dissolution, precipitation, and reprecipitation and depend strongly on reacting melt composition. Comparison of mineral compositional variations across the dissolution couples with those observed in mantle xenoliths from the North China Craton (NCC) helps to assess the spatial and temporal variations in the extent of siliceous melt and peridotite interaction in modifying the lithospheric mantle beneath the NCC. We found that such melt–rock interaction mainly took place in Early Cretaceous, and is responsible for the enrichment of pyroxene in the lithospheric mantle. Spatially, siliceous melt–peridotite interaction took place in the ancient orogens with thickened lower crust.     

铁同位素的MC-ICP-MS测定方法与地质标准物质的铁同位素组成

详细报道了在低分辨和高分辨模式下运用MC-ICP-MS进行Fe同位素比值高精度测试的方法,对Fe同位素测定过程中谱峰干扰、基质效应、浓度效应、仪器测试的长期重现性等问题进行了评估,并对两种运行模式的测试结果进行了对比.在95%的可信度范围内,所建方法的外部精度优于0.5ε/ainu,达到国际同类实验室的先进水平,并且低分辨和高分辨两种模式下获得的Fe同位素测试结果是一致的.在此基础上对国家地质标准物质GBW07105(玄武岩)和GBW 07111(花岗闪长岩)进行了Fe同位素测定.相对于Fe同位素国际标样IRMM-014,GBW07105的Fe同位素成分为:ε57Fe=1.9±0.3(20),ε56Fe=1.3±0.2(2σ),ε57/56Fe=0.6±0.1(2σ);GBW 07111的Fe同位素成分为:ε57Fe=1.8±0.4(2σ),ε56Fe=1.2±0.2(2σ),ε57/56Fe=0.6±0.1(2σ).     

Neoglacial (<3000 years) till and flutes at Saskatchewan Glacier,Canadian Rocky Mountains,formed by subglacial deformation of a soft bed

Understanding the processes that deposit till below modern glaciers provides fundamental information for interpreting ancient subglacial deposits. A process‐deposit‐landform model is developed for the till bed of Saskatchewan Glacier in the Canadian Rocky Mountains. The glacier is predominantly hard bedded in its upper reaches and flows through a deep valley carved into resistant Palaeozoic carbonates but the ice margin rests on a thick (<6 m) soft bed of silt‐rich deformation till that has been exposed as the glacier retreats from its Little Ice Age limit reached in 1854. In situ tree stumps rooted in a palaeosol under the till are dated between ca 2900 and 2700 yr bp and record initial glacier expansion during the Neoglacial. Sedimentological and stratigraphic observations underscore the importance of subglacial deformation of glaciofluvial outwash deposited in front of the advancing glacier and mixing with glaciolacustrine carbonate‐rich silt to form a soft bed. The exposed till plain has a rolling drumlinoid topography inherited from overridden end moraines and is corrugated by more than 400 longitudinal flute ridges which record deformation of the soft bed and fall into three genetically related types: those developed in propagating incipient cavities in the lee of large subglacial boulders embedded in deformation till, and those lacking any originating boulder and formed by pressing of wet till up into radial crevasses under stagnant ice. A third type consists of U‐shaped flutes akin to barchan dunes; these wrap around large boulders at the downglacier ends of longitudinal scours formed by the bulldozing of boulders by the ice front during brief winter readvances across soft till. Pervasive subglacial deformation during glacier expansion was probably facilitated by large boulders rotating within the soft bed (‘glacioturbation’).     

新疆西天山高硫化型京希-伊尔曼德金矿床的识别标志及其找矿意义

经过详细的野外地质勘查、热液蚀变及蚀变矿物学研究，流体包裹体和同位素研究，首次将西天山京希－伊尔曼德金矿床确定为高硫化型浅成低温热液金矿床。该矿床的主要识别标志为：发育以多孔状石英为特征的硅化蚀变带和高级泥化蚀变带；成矿流体性质为低盐度[W(NaCl)为0.3-4.2%]、低pH值（3－4）和高氧化态；氧同位素δ（^18O)为1.7 ‰-4.3‰,δ(D)为－60‰--80‰。金主要富集在高级泥化带和中心硅化蚀变带内。系统研究和总结了成矿地质－地球化学制约因素以及区域、靶区和勘探区尺度的找矿标志。     

The Seasonal Prediction of the Exceptional Yangtze River Rainfall in Summer 2020

During June and July of 2020, the Yangtze River basin suffered from extreme mei-yu rainfall and catastrophic flooding. This study explores the seasonal predictability and associated dynamical causes for this extreme Yangtze River rainfall event, based on forecasts from the Met Office GloSea5 operational forecast system. The forecasts successfully predicted above-average rainfall over the Yangtze River basin, which arose from the successful reproduction of the anomalous western North Pacific subtropical high (WNPSH). Our results indicate that both the Indian Ocean warm sea surface temperature (SST) and local WNP SST gradient were responsible for the westward extension of the WNPSH, and the forecasts captured these tropical signals well. We explore extratropical drivers but find a large model spread among the forecast members regarding the meridional displacements of the East Asian mid-latitude westerly jet (EAJ). The forecast members with an evident southward displacement of the EAJ favored more extreme Yangtze River rainfall. However, the forecast Yangtze River rainfall anomaly was weaker compared to that was observed and no member showed such strong rainfall. In observations, the EAJ displayed an evident acceleration in summer 2020, which could lead to a significant wind convergence in the lower troposphere around the Yangtze River basin, and favor more mei-yu rainfall. The model forecast failed to satisfactorily reproduce these processes. This difference implies that the observed enhancement of the EAJ intensity gave a large boost to the Yangtze River rainfall, hindering a better forecast of the intensity of the event and disaster mitigation.     

Including spatial distribution in a data‐driven rainfall‐runoff model to improve reservoir inflow forecasting in Taiwan

Multi‐step ahead inflow forecasting has a critical role to play in reservoir operation and management in Taiwan during typhoons as statutory legislation requires a minimum of 3‐h warning to be issued before any reservoir releases are made. However, the complex spatial and temporal heterogeneity of typhoon rainfall, coupled with a remote and mountainous physiographic context, makes the development of real‐time rainfall‐runoff models that can accurately predict reservoir inflow several hours ahead of time challenging. Consequently, there is an urgent, operational requirement for models that can enhance reservoir inflow prediction at forecast horizons of more than 3 h. In this paper, we develop a novel semi‐distributed, data‐driven, rainfall‐runoff model for the Shihmen catchment, north Taiwan. A suite of Adaptive Network‐based Fuzzy Inference System solutions is created using various combinations of autoregressive, spatially lumped radar and point‐based rain gauge predictors. Different levels of spatially aggregated radar‐derived rainfall data are used to generate 4, 8 and 12 sub‐catchment input drivers. In general, the semi‐distributed radar rainfall models outperform their less complex counterparts in predictions of reservoir inflow at lead times greater than 3 h. Performance is found to be optimal when spatial aggregation is restricted to four sub‐catchments, with up to 30% improvements in the performance over lumped and point‐based models being evident at 5‐h lead times. The potential benefits of applying semi‐distributed, data‐driven models in reservoir inflow modelling specifically, and hydrological modelling more generally, are thus demonstrated. Copyright © 2012 John Wiley & Sons, Ltd.