Predictive uncertainty of peak outflow relations for landslides dam breach

Risk assessment development considering the failure of landslide dams often requires the estimation of peak outflow through the breach. The empirical equations based on data from case studies tend to be the first direct approach. This paper conducted an uncertainty analysis when these empirical relations were utilized to predict the peak outflow of a breached landslide dam. The results suggest that the relations derived from manmade dams or embankments typically overestimate the peak outflow about 1/5 to 3/4 of an order of magnitude; and the relations derived from the database of landslide dams have much smaller mean prediction errors and also exhibit broad uncertainty bands. Application of the uncertainly analysis was illustrated by the Tangjiashan landslide dammed lake, formed during 2008 Wenchuan earthquake. In addition, the predicted results from Eq. 1 deduced herein were considered to be the reliable estimate of peak outflow through the breach of landslide dam.     

安徽淮北平原冬小麦气候适宜度分析及作物年景评估

选取安徽省淮北平原37个气象站1960-2016年逐日气象资料,构建气温、降水、日照及气候适宜度模型,分析气候变暖背景下冬小麦气候适宜度时空演变特征,揭示冬小麦生育期气候风险,评判农业气候年景。结果表明：淮北平原冬小麦不同生育期对气候因子适宜程度不同,单要素各生育期适宜度均为灌浆-乳熟期较高,返青-拔节期较低,其中降水适宜度分蘖期最低;全生育期温度适宜度最高、日照适宜度次之、降水适宜度最低,水分是冬小麦生长的限制因子。气候综合适宜度灌浆-乳熟期最高,分蘖期降水适宜度最低,并且其序列变异系数大,常遭遇秋冬连旱,引起产量波动;全生育期气候适宜度呈东高西低分布,淮北中东部较高,而淮北西部及沿淮地区较低,冬小麦生产风险相对较高。1961-2016年全生育期温度适宜度线性增大趋势显著,降水适宜度线性趋势不明显,而日照适宜度呈显著的线性减小趋势;综合来看,全生育期气候适宜度无明显线性增减趋势,空间上淮北东部略有增大,而西部及沿淮地区略有减小,气候风险增加。淮北平原多数年份气候适宜度适中,适宜性偏差年发生概率高于偏好年。基于气候适宜度评判冬小麦气候年景等级,评估结果与实际产量增减情况基本相符,表明农业气候年景模型评估精度能满足业务服务需求,具有推广应用价值。     

A new SPH-based approach to simulation of granular flows using viscous damping and stress regularisation

The smoothed particle hydrodynamics (SPH) method was recently extended to simulate granular materials by the authors and demonstrated to be a powerful continuum numerical method to deal with the post-flow behaviour of granular materials. However, most existing SPH simulations of granular flows suffer from significant stress oscillation during the post-failure process, despite the use of an artificial viscosity to damp out stress fluctuation. In this paper, a new SPH approach combining viscous damping with stress/strain regularisation is proposed for simulations of granular flows. It is shown that the proposed SPH algorithm can improve the overall accuracy of the SPH performance by accurately predicting the smooth stress distribution during the post-failure process. It can also effectively remove the stress oscillation issue in the standard SPH model without having to use the standard SPH artificial viscosity that requires unphysical parameters. The predictions by the proposed SPH approach show very good agreement with experimental and numerical results reported in the literature. This suggests that the proposed method could be considered as a promising continuum alternative for simulations of granular flows.