基于熵权-正态云模型的泥石流灾害易发性评价

近年来,由于极端天气事件频发和工程建设活动加剧,泥石流灾害对人类的威胁愈加严峻。因此,在综合分析泥石流灾害发育特征及形成机理的基础上,进行泥石流灾害易发性评价对防灾减灾工程活动具有指导意义。选取沟谷岸坡坡度、沟床纵坡比降、植被覆盖率、单位面积固体物源储量、汇水面积、雨季降雨量建立评价指标体系,采用熵权法确定评价指标权重,将泥石流灾害易发性分为高易发、中易发、低易发和不易发四级,建立基于正态云模型的泥石流灾害易发性评价方法,并以西秦岭地区5条泥石流沟为例验证了该评价模型的合理性。进一步将该模型用于陕西吴堡井沟泥石流灾害易发性评价,结果表明井沟泥石流具有中易发性,评价结果与实际相符。     

河北宣化赵川地区矿渣碎屑流工程特性及其启动机制

张家口宣化地区存在大量具有潜在危险的松散矿渣堆积体,文章以该地区具有代表性的响水沟松散矿渣堆积体为研究对象,对矿渣的颗粒组成、矿物成分、力学性质等进行详细的室内试验研究,结果表明:矿渣堆积体属砾质砂土,粘粒含量少,且级配不良,松散易流动。同一干密度下,随含水率增加,矿渣抗剪强度先增大后减小,当含水率为15%时,其粘聚力最低,表明响水沟矿渣堆积体失稳启动下滑的界限含水率可能在15%左右。综合以上分析结果,拟合得到粘聚力与含水率关系公式,初步预测矿渣碎屑流启动下滑的临界含水率。这一认识对该区矿渣堆积体的稳定性评价及碎屑流灾害预警有重要意义。      

基于LAHARZ的泥石流堆积范围预测模型的建立及应用

为了探究泥石流的堆积范围,利用LAHARZ软件,对北京市密云县泥石流沟喇嘛栅子南沟进行了数值模拟。结合泥石流沟小流域1：10 000数字高程模型图,模拟了泥石流的堆积范围。首先利用中国部分地区泥石流体积和堆积范围的数据资料,获得了泥石流体体积与其堆积范围的新的统计模型B=11.42V^0.7156;然后通过模拟沟道与实际沟道的对比,确定了最佳沟道阈值为15 000;再结合现场调查统计和降雨历史资料,确定了10年、20年、50年和100年一遇暴雨条件的泥石流体积值,分别为56 500、72 900、94 200和113 100 m³;最后在此基础上对该条泥石流沟的堆积范围进行了预测。结果表明,100年一遇的暴雨条件下泥石流堆积面积为48 729 m²,到达最远距离约为490 m,已影响下游村庄。     

甘肃省河西内陆河流量长期变化特征

利用甘肃省河西地区3条主要内陆河石羊河、黑河、疏勒河40余年的流量资料以及河西走廊地区和祁连山区气象资料对河西地区内陆河流量的长期变化特征进行了分析,并对所获结果进行了讨论,得到一些有意义的结论.     

北极地区楚克奇海域一次强逆温过程的分析

利用中国首次北极科学考察期间所获得的大气边界层资料,分析了楚克奇海域夏季一次强逆温过程.考察期间楚克奇海域上空的大气逆温强度(6.3℃/100 m)远远超过了北极地区夏季的气候平均值(0.5℃/100 m),该大气逆温存在明显的日变化,逆温强度自当地时间00时到18时逐步减弱.考察期间同样存在强大的逆湿结构,逆湿层内最大湿度差为6.4 g m-3.稳定边界层内大气向地面输送感热通量和潜热通量,输送最大值出现在夜间.研究同时段的大气环流资料后表明,考察区域西南的暖湿气流及其变化是造成此次夏季强逆温及其日变化的主要原因.     

非饱和土壤水流方程的极值原理

讨论了非饱和土壤水流问题及其数值计算方案的极值原理,在理论上证明了连续问题及其数值格式均满足极值原理,即在一定的条件下,预报变量的最大值和最小值只能在边界上达到,从而描述了特定的物理性质.这些问题在讨论入渗、蒸发问题的研究中是重要的.     

An experimental investigation of the effects of thawed soil depth on rill flow velocity

Water flow velocity is an important hydraulic variable in hydrological and soil erosion models, and is greatly affected by freezing and thawing of the surface soil layer in cold high-altitude regions. The accurate measurement of rill flow velocity when impacted by the thawing process is critical to simulate runoff and sediment transport processes. In this study, an electrolyte tracer modelling method was used to measure rill flow velocity along a meadow soil slope at different thaw depths under simulated rainfall. Rill flow velocity was measured using four thawed soil depths (0, 1, 2 and 10 cm), four slope gradients (5°, 10°, 15° and 20°) and four rainfall intensities (30, 60, 90 and 120 mm·h⁻¹). The results showed that the increase in thawed soil depth caused a decrease in rill flow velocity, whereby the rate of this decrease was also diminishing. Whilst the rill flow velocity was positively correlated with slope gradient and rainfall intensity, the response of rill flow velocity to these influencing factors varied with thawed soil depth. The mechanism by which thawed soil depth influenced rill flow velocity was attributed to the consumption of runoff energy, slope surface roughness, and the headcut effect. Rill flow velocity was modelled by thawed soil depth, slope gradient and rainfall intensity using an empirical function. This function predicted values that were in good agreement with the measured data. These results provide the foundation for a better understanding of the effect of thawed soil depth on slope hydrology, erosion and the parameterization scheme for hydrological and soil erosion models.     

Large debris flows in Chosica,Lima, Peru: the application of hydraulic infrastructure for erosion control and disaster prevention

Abstract

Large debris flows in steep-sloped ravines debouching to the Rimac River, in metropolitan Lima (Peruvian capital), have resulted in considerable loss of life and property adversely impacting communities in the region. Temporal, spatial and volumetric features of debris flows are difficult to predict, and it is of utmost importance that achievable management solutions are found to reduce the impact of these catastrophic events. The emotional and economic toll of these debris flows on this increasingly densely populated capital city in South America is devastating where communities must live in such inadequate and dangerous conditions. To address this problem, the application of advanced Japanese technology, Sustainable Actions Basin Orientation (SABO), has been investigated using a geomorphological modelling to develop an implementation plan. Rayos de Sol stream basin in Chosica, was selected as a pilot to develop the proposal, as it is considered high risk due to the presence of ancient debris flows and recent flows in 2012, 2015 and 2017. The recurrence of debris flows in this location has resulted in numerous deaths and catastrophic property losses. This study combines geologic and geomorphic mapping and hydraulic and landform evolution numerical modelling. The implementation of a SABO Master Plan based on the multidisciplinary assessment hazard scenarios, will allow the implementation of feasible mitigation actions. The SABO technology has been applied successfully in Japan and other countries in areas with steep short slopes, similar to the conditions surrounding the Peruvian capital. Results from this study will be presented to the Peruvian Government as part of an action plan to manage debris-flow impact.

1. KEY POINTS

2. High-risk mass slope failure is linked to poor urban planning in urban developing regions of Lima the capital of Peru.

3. A multidisciplinary study including geotechnical and hydrological analysis, engineering design, and socio-economic research is required to implement a SABO Master Plan, and this basin is pilot study basin.

4. At the present time, a maintenance programme for existing hydraulic structures should be implemented, and a flood risk management plan developed may propose the relocation of some communities and infrastructure.

     

A hybrid integrated deep learning model for the prediction of citywide spatio-temporal flow volumes

ABSTRACT

The spatio-temporal residual network (ST-ResNet) leverages the power of deep learning (DL) for predicting the volume of citywide spatio-temporal flows. However, this model, neglects the dynamic dependency of the input flows in the temporal dimension, which affects what spatio-temporal features may be captured in the result. This study introduces a long short-term memory (LSTM) neural network into the ST-ResNet to form a hybrid integrated-DL model to predict the volumes of citywide spatio-temporal flows (called HIDLST). The new model can dynamically learn the temporal dependency among flows via the feedback connection in the LSTM to improve accurate captures of spatio-temporal features in the flows. We test the HIDLST model by predicting the volumes of citywide taxi flows in Beijing, China. We tune the hyperparameters of the HIDLST model to optimize the prediction accuracy. A comparative study shows that the proposed model consistently outperforms ST-ResNet and several other typical DL-based models on prediction accuracy. Furthermore, we discuss the distribution of prediction errors and the contributions of the different spatio-temporal patterns.     

The recognition of former melt flux through high‐strain zones

High‐strain zones are potential pathways of melt migration through the crust. However, the identification of melt‐present high‐strain deformation is commonly limited to cases where the interpreted volume of melt “frozen” within the high‐strain zone is high (>10%). In this contribution, we examine high‐strain zones in the Pembroke Granulite, an otherwise low‐strain outcrop of volcanic arc lower crust exposed in Fiordland, New Zealand. These high‐strain zones display compositional layering, flaser‐shaped mineral grains, and closely spaced foliation planes indicative of high‐strain deformation. Asymmetric leucosome surrounding peritectic garnet grains suggest deformation was synchronous with minor amounts of in situ partial melting. High‐strain zones lack typical mylonite microstructures and instead display typical equilibrium microstructures, such as straight grain boundaries, 120° triple junctions, and subhedral grain shapes. We identify five key microstructures indicative of the former presence of melt within the high‐strain zones: (a) small dihedral angles of interstitial phases; (b) elongate interstitial grains; (c) small aggregates of quartz grains with xenomorphic plagioclase grains connected in three dimensions; (d) fine‐grained, K‐feldspar bearing, multiphase aggregates with or without augite rims; and (e) mm‐ to cm‐scale felsic dykelets. Preservation of key microstructures indicates that deformation ceased as conditions crossed the solidus, breaking the positive feedback loop between deformation and the presence of melt. We propose that microstructures indicative of the former presence of melt, such as the five identified above, may be used as a tool for recognising rocks formed during melt‐present high‐strain deformation where low (<5%) volumes of leucosome are “frozen” within the high‐strain zone.