Coupling the WRF model with a temperature index model based on remote sensing for snowmelt simulations in a river basin in the Altay Mountains,north‐west China

Snowmelt water is an important freshwater resource in the Altay Mountains in north‐west China; however, warming climate and rapid spring snowmelt can cause floods that endanger both public and personal property and safety. This study simulates snowmelt in the Kayiertesi River catchment using a temperature index model based on remote sensing coupled with high‐resolution meteorological data obtained from National Centers for Environmental Prediction (NCEP) reanalysis fields that were downscaled using the Weather Research Forecasting model and then bias corrected using a statistical downscaled model. Validation of the forcing data revealed that the high‐resolution meteorological fields derived from the downscaled NCEP reanalysis were reliable for driving the snowmelt model. Parameters of the temperature index model based on remote sensing were calibrated for spring 2014, and model performance was validated using Moderate Resolution Imaging Spectroradiometer snow cover and snow observations from spring 2012. The results show that the temperature index model based on remote sensing performed well, with a simulation mean relative error of 6.7% and a Nash–Sutcliffe efficiency of 0.98 in spring 2012 in the river of Altay Mountains. Based on the reliable distributed snow water equivalent simulation, daily snowmelt run‐off was calculated for spring 2012 in the basin. In the study catchment, spring snowmelt run‐off accounts for 72% of spring run‐off and 21% of annual run‐off. Snowmelt is the main source of run‐off for the catchment and should be managed and utilized effectively. The results provide a basis for snowmelt run‐off predictions, so as to prevent snowmelt‐induced floods, and also provide a generalizable approach that can be applied to other remote locations where high‐density, long‐term observational data are lacking. Copyright © 2016 John Wiley & Sons, Ltd.     

Observations of late winter Canadian tundra snow cover properties

Tundra snow cover is important to monitor as it influences local, regional, and global‐scale surface water balance, energy fluxes, as well as ecosystem and permafrost dynamics. Observations are already showing a decrease in spring snow cover duration at high latitudes, but the impact of changing winter season temperature and precipitation on variables such as snow water equivalent (SWE) is less clear. A multi‐year project was initiated in 2004 with the objective to quantify tundra snow cover properties over multiple years at a scale appropriate for comparison with satellite passive microwave remote sensing data and regional climate and hydrological models. Data collected over seven late winter field campaigns (2004 to 2010) show the patterns of snow depth and SWE are strongly influenced by terrain characteristics. Despite the spatial heterogeneity of snow cover, several inter‐annual consistencies were identified. A regional average density of 0.293 g/cm³ was derived and shown to have little difference with individual site densities when deriving SWE from snow depth measurements. The inter‐annual patterns of SWE show that despite variability in meteorological forcing, there were many consistent ratios between the SWE on flat tundra and the SWE on lakes, plateaus, and slopes. A summary of representative inter‐annual snow stratigraphy from different terrain categories is also presented. © 2013 Her Majesty the Queen in Right of Canada. Hydrological Processes. © 2013 John Wiley & Sons, Ltd.     

Evaluation of snow products over the Tibetan Plateau

Four satellite‐based snow products are evaluated over the Tibetan Plateau for the 2007–2010 snow seasons. The Moderate Resolution Imaging Spectroradiometer (MODIS) Terra and Aqua snow cover daily L3 Global 500‐m grid products (MOD10A1 and MYD10A1), the National Oceanic and Atmospheric Administration Interactive Multisensor Snow and Ice Mapping System (IMS) daily Northern Hemisphere snow cover product and the Advanced Microwave Scanning Radiometer – Earth Observing System Daily Snow Water Equivalent were validated against Thematic Mapper (TM) snow cover maps of Landsat‐5 and meteorological station snow depth observations. The overall accuracy of MOD10A1, MYD10A1 and IMS is higher than 91% against stations observations and than 79% against Landsat TM images. In general, the daily MODIS snow cover products show better performance than the multisensor IMS product. However, the IMS snow cover product is suitable for larger scale (~4km) analysis and applications, with the advantage over MODIS to allow for mitigation for cloud cover. The accuracy of the three products decreases with decreasing snow depth. Overestimation errors are most common over forested regions; the IMS and Advanced Microwave Scanning Radiometer – Earth Observing System Snow Water Equivalent products also show poorer performance that the MODIS products over grassland. By identifying weaknesses in the satellite products, this study provides a focus for the improvement of snow products over the Tibetan plateau. The quantitative evaluation of the products proposed here can also be used to assess their relative weight in data assimilation, against other data sources, such as modelling and in situ measurement networks. Copyright © 2015 John Wiley & Sons, Ltd.     

Quantifying snow water equivalent using terrestrial ground penetrating radar and unmanned aerial vehicle photogrammetry

This study demonstrates the potential value of a combined unmanned aerial vehicle (UAV) Photogrammetry and ground penetrating radar (GPR) approach to map snow water equivalent (SWE) over large scales. SWE estimation requires two different physical parameters (snow depth and density), which are currently difficult to measure with the spatial and temporal resolution desired for basin-wide studies. UAV photogrammetry can provide very high-resolution spatially continuous snow depths (SD) at the basin scale, but does not measure snow densities. GPR allows nondestructive quantitative snow investigation if the radar velocity is known. Using photogrammetric snow depths and GPR two-way travel times (TWT) of reflections at the snow-ground interface, radar velocities in snowpack can be determined. Snow density (RSN) is then estimated from the radar propagation velocity (which is related to electrical permittivity of snow) via empirical formulas. A Phantom-4 Pro UAV and a MALA GX450 HDR model GPR mounted on a ski mobile were used to determine snow parameters. A snow-free digital surface model (DSM) was obtained from the photogrammetric survey conducted in September 2017. Then, another survey in synchronization with a GPR survey was conducted in February 2019 whilst the snowpack was approximately at its maximum thickness. Spatially continuous snow depths were calculated by subtracting the snow-free DSM from the snow-covered DSM. Radar velocities in the snowpack along GPR survey lines were computed by using UAV-based snow depths and GPR reflections to obtain snow densities and SWEs. The root mean square error of the obtained SWEs (384 mm average) is 63 mm, indicating good agreement with independent SWE observations and the error lies within acceptable uncertainty limits.     

基于抗差最小二乘估计的载体速度计算方法

针对相位率值的特点,引入抗差最小二乘估计进行速度计算,根据IGGⅢ方案选取合适的等价权因子来降低存在小周跳影响的观测值对结果的贡献,利用航空飞行实验的数据进行了计算分析,结果表明经过抗差后的速度仍可保持在mm/s的量级。     

Quantification of fundamental frequency drop for unreinforced masonry buildings from dynamic tests

The knowledge of fundamental frequency and damping ratio of structures is of uppermost importance in earthquake engineering, especially to estimate the seismic demand. However, elastic and plastic frequency drops and damping variations make their estimation complex. This study quantifies and models the relative frequency drop affecting low‐rise modern masonry buildings and discusses the damping variations based on two experimental data sets: Pseudo‐dynamic tests at ELSA laboratory in the frame of the ESECMaSE project and in situ forced vibration tests by EMPA and EPFL. The relative structural frequency drop is shown to depend mainly on shaking amplitude, whereas the damping ratio variations could not be explained by the shaking amplitude only. Therefore, the absolute frequency value depends mostly on the frequency at low amplitude level, the amplitude of shaking and the construction material. The decrease in shape does not vary significantly with increasing damage. Hence, this study makes a link between structural dynamic properties, either under ambient vibrations or under strong motions, for low‐rise modern masonry buildings. A value of 2/3 of the ambient vibration frequency is found to be relevant for the earthquake engineering assessment for this building type. However, the effect of soil–structure interaction that is shown to also affect these parameters has to be taken into account. Therefore, an analytical methodology is proposed to derive first the fixed‐base frequency before using these results. Copyright © 2010 John Wiley & Sons, Ltd.     

裂隙参数对衰减各向异性影响的数值模拟

理论、观测和实验均证实,在地壳和上地幔存在对应力变化敏感的直立裂隙,在整体上呈现方位各向异性.在Hudson裂隙理论基础上,系统全面地数值模拟了裂隙介质几何、物性和弹性波频率等参数对各向异性衰减的影响.结果显示,裂隙密度、裂隙纵横比、泊松比、裂缝填充物、弹性波频率和未破裂岩石母体纵横波速度等对各向异性衰减有着显著影响,...     

基础隔震结构抗震可靠度简化分析方法

选用胡聿贤平稳地震地面运动模型作为基础隔震结构的随机地震动输入,采用Bouc-Wen模型描述隔震结构的层间滞变位移,将滞变体系动力特性矩阵随机等效线性化,并建立等价线性状态方程。引入左右特征向量系,对振动微分方程进行解耦,推导了基础隔震结构随机地震响应的统计矩解析解。采用变形失效准则,定义了上部结构和隔震层的功能状态极限函数。在此基础上,采用首次超越破坏模型,基于Possion分布假设和串联系统可靠度模型,建立了从整体上评价基础隔震体系抗震可靠度的简化分析方法。最后,通过一个基础隔震框架结构计算实例,说明了这种方法的运用。     

铅芯橡胶支座力学性能及在清澜大桥的应用研究

本文首先分析了铅芯橡胶支座的力学性能,并结合一个实际工程,用大型通用结构分析程序ANSYS进行时程分析,通过对比考虑和不考虑铅芯橡胶支座恢复力耦合作用的连续梁桥模型的自振周期和最大剪力、弯矩,结果证明铅芯橡胶支座具有良好的减震、隔震性能。本文的计算结果为铅芯橡胶支座在连续梁桥的应用和设计提供了参考。     

结构参数对双链式悬索桥地震响应的影响

以某双链式悬索桥为工程背景,建立了空间有限元计算模型.运用几何非线性时程分析方法,分析并探讨了不同垂跨比、阻尼比,塔桥不同连接方式和双链位置对双链式悬索桥地震响应的影响.分析表明,竖向地震动分量使桥塔轴力迅速增大,加劲梁采用钢筋混凝土边梁可有效减小地震响应;塔梁间采用简支连接方案其抗震性能比固定支座连接方案、滑动支座连接方案要好;双链式悬索桥横向抗震性能优于单链式悬索桥.对双链式悬索桥抗震性能的研究,为此类悬索结构的设计选型,乃至减震、隔震及抗震加固提供了参考.