中巴公路沿线冰川泥石流的形成与危险性评估

中巴公路是一条连接中国西北部与巴基斯坦北部的高原公路。根据野外考察与统计分析,选取暴发频率、流域面积、堆
积扇体积、估计一次冲出量、植被覆盖率、沟道坡角及海拔7个主要控制因素,采用多因子综合评价法对公路沿线的8条典型冰川
泥石流沟的危险性进行了评估,并将评估结果与它们在2010及2011的两年里实际发生冰川泥石流情况进行了对比。对比结果
表明:多因素综合评估法评估的中巴公路沿线典型冰川泥石流沟的危险等级与实际发生情况吻合较好,因而多因素综合评估法在
灾害危险性评估方面具有很好的应用前景。      

中巴地球资源卫星数据的推广应用

1999年10月14日,中巴地球资源卫星01号升空,2006年中国资源卫星应用中心自主研发的数据处理实验系统投产,迅速提高了数据产品的生产能力和效率。通过对IRMSS图像的去噪声干扰,CCD图像的M IF补偿。在敦煌定标场连续两年开展CBERS-02星CCD与法国SPOT-4 HRVIR1的交叉定标试验,及时将结果上网公布,拓展了数据定量化应用的广度和深度。2007年7月数据产品分发已突破20万景①。在CBERS图像应用中,贵阳市率先应用于1∶10万森林调查,扬州市开展了主要农作物的长势监测,北京市进行了密云水库蓄水面积的变化监测,北京市绿地动态监测等。     

中巴公路泥石流灾害破坏及防治优化

中巴公路沿线活跃的地质构造运动、陡峭的地形地貌与冰川气候造成泥石流广泛发育,威胁中巴公路扩建与建成后的
运营。分布在中巴公路北段冰川泥石流对该公路的威胁最为严重。根据2008-2011年期间雨季前后泥石流的活动状况,采用沿
线普查与重点详查的研究方式,总结中巴公路沿线泥石流灾害的主要危害类型;并结合设计图纸,对2009年以前原中巴公路防治
工程进行简要的损毁评估;通过分析中巴公路的防治现状提出相应的防治对策,最终针对典型的病害提出具有代表性的改进措
施,以期为高海拔区公路灾害的防治提供一定的参考。研究表明:中巴公路泥石流的危害类型有5种,即淤积、侵蚀、冲击、漫流改
道与堵江;损毁评估结果显示原有小型泥石流防治工程基本失效;原大型桥梁工程配套防治工程需要新建或加固;而新建桥梁工
程运行良好;泥石流防治工程应考虑以下5个现状:援建工程的性质、不良工程地质条件、公路短期安全与灾害发展趋势的统一、
主动工程被动防治及建立灾害管理与公路养护机构;鉴于中巴公路防治工程所面临的“技术经济性”问题,典型防治工程应根据泥
石流的分布特征、性质特点与公路的交汇关系,采取因地制宜的防治方案。      

中巴地球资源卫星用户大会在京隆重召开

中巴地球资源卫星 ( CBERS- 1 )于 1 999年 1 0月 1 4日成功发射 ,2 0 0 0年 3月 2日正式交付使用。其在轨运行了 3年多 ,已接收 CCD传感器等多种数据共计 40万余景。目前 ,中国资源卫星应用中心已向全国1 4 0多个用户单位分发了 80 0 0余景 CBERS- 1数据产品 ,它们的应用涉及农、林、水、土、地矿、城市规划、环保、自然灾害、地理、测绘和全球变化应用等众多领域。     

“碟溜儿”旋转里的童年

在禹州乡下,人们把陀螺称作“碟溜儿”。在我童年的记忆里,碟溜儿、木枪、弹弓和纸叠的“四角”是农村孩子过年必备的“四大件”,其中以碟溜儿最具技术含量且刺激好玩。我们玩的碟溜儿多是自制的,这对富于创造性的农村孩子来说不算什么难事,只是制作碟溜儿的木头有些讲究。俗话说:“榆木疙瘩不开窍。”榆木质地坚硬且不易炸裂,自然是制作碟溜儿的好材料。枣树和柿树的木质稍稍次之,因为暗藏花纹的缘故,深受孩子们喜爱,再有就是据说能够辟邪的桃木了。     

"碟溜儿"旋转里的童年

在禹州乡下,人们把陀螺称作碟溜儿.在我童年的记忆里,碟溜儿、木枪、弹弓和纸叠的四角是农村孩子过年必备的四大件,其中以碟溜儿最具技术含量且刺激好玩.我们玩的碟溜儿多是自制的,这对富于创造性的农村孩子来说不算什么难事,只是制作碟溜儿的木头有些讲究.俗话说:榆木疙瘩不开窍.榆木质地坚硬且不易炸裂,自然是制作...     

《中巴地球资源卫星影像图集》即将出版

由中国与巴西联合研制的"中巴地球资源卫星"(简称CBERS-1或中国资源一号卫星)分别于1999年10月、2003年10月成功发射了两颗同性能的遥感卫星,获取了大量的遥感资料,并得到广泛应用。由中国资源卫星应用中心研制的《中巴地球资源卫星影像图集》(暂名)即将出版。该图集8开本240页,图集将以形象生动、可靠的信息,经处理简明分析的图像,奉献给读者。     

中巴资源卫星CBERS-1数据在巴西的应用

本文重点介绍了当前巴西以用户为导向的 CBERS数据的应用项目 ,并对今后利用中巴地球资源卫星开展国家项目发表了一些看法。     

中巴合作研制资源1号卫星成功发射和正常运作

资源1号卫星(ZY-1)是一项巨大的系统工程.它是由中国和巴西合作研制而成.1999年10月14日在太原卫星发射基地成功升天.上午10点15分,由指挥部发出“点火”令后,庞大的火箭如巨雷震天般将卫星送上天,几秒中后冲进云霄,只见闪闪的星点.     

Landslide mapping and analysis along the China-Pakistan Karakoram Highway based on SBAS-InSAR detection in 2017

The Karakoram Highway(KKH), a part of the China–Pakistan Economic Corridor(CPEC), is a major highway connecting northern Pakistan to China. The inventorying and analysis of landslides along KKH are challenging because of poor accessibility, vast study area, limited availability of ground-based datasets, and the complexity of landslide processes in the region. In order to preserve life, property, and infrastructure, and to enable the uninterrupted and efficient operation of the KKH, it is essential to strengthen measures for the prevention and control of geological disasters. In the present study, SBASInSAR(Small Baseline Subsets-Interferometric Synthetic Aperture Radar) was used to process 150 scenes of Sentinel 1-A images in the year 2017 along the Karakoram Highway. A total of 762 landslides, including 57 complex landslides, 126 rock falls, 167 debris slides, and 412 unstable slopes, ranging in size between 0.0017 and 10.63 km2 were identified. Moreover, this study also gains an inventory of 40 active glacier movements in this region. Landslide categorization, displacements characteristics, spatial distribution, and their relationship with various contributing factors have been successfully investigated along the entire KKH using image interpretation and frequency-area statistics. The criteria adopted for landslides categorization is presented in the study. The results showed that the 2-D ground deformation derived in Hunza valley echoes well with the general regional landslides characteristics. The spatial distribution analysis revealed that there are clumped distributions of landslides in the Gaizi, Tashkurgan, and Khunjerab in China, as well as in Hunza valley, and north of Chilas city in Pakistan. Statistical results indicated that these landslides mainly occur on south-facing slopes with a slope angle of 20°– 45° and elevation relief of 550 – 2,100 m. Landslide development is also related to low vegetation cover and weathering effects in mountain gullies. Overall, our study provides scientific data support and theoretical references for prevention, control, and mitigation of geological disasters in the Karakoram region.     

Risk assessment of glacial debris flow on alpine highway under climate change: A case study of Aierkuran Gully along Karakoram Highway

Glacial debris flows(GDFs) often occur in alpine regions that are subject to rapid climate change, and pose a serious threat to road systems. However, the ways that climate change impacts GDF risks along road systems remain poorly understood. Aierkuran Gully, located in eastern Pamir along Karakoram Highway(KKH), is a hotspot for GDF activity and climate change, and was thus selected to investigate the GDF risk to road systems under climate change conditions. Reg CM4.6 climate data for northwestern China were selected as climate projections during baseline(2011–2020) and future periods(2031–2040) under the Representative Concentration Pathway(RCP) 8.5. To reflect the coupling effect of rainfall and melt water that triggers GDF, a glacial hydrological model DETIM that considers both factors was applied to calculate the peak debris flow discharge. A FLO-2 D model was calibrated based on high-quality data collected from a detailed field investigation and historical debris flow event. The FLO-2 D model was used to simulate the debris flow depth and velocity during baseline and future periods under RCP8.5. The debris flow hazard was analyzed by integrating the maximum flow depth and momentum. Road structure vulnerability was further determined based on the economic value and susceptibility of hazard-affected objects. The GDF risk along KKH was assessed based on the GDF hazard and vulnerability analysis. Our results show that climate change would lead to amplified peak debris flow discharge, trigger highermagnitude GDF, and induce more severe damage and threats to the road system. Compared with the baseline period, the debris flow damage risk for culverts and bridges would increase and the areas that inundate the road and pavement would expand. Our findings provide valuable insights for the development of mitigation strategies to adapt road systems to climate change, especially in alpine regions with highly active GDFs.     

公路弃土场边坡的稳定影响因素敏感性分析

以日照市岚山区某弃土场为研究对象,通过对现场调研并采样开展直剪试验,在压实度分别为90%、92%和95%的情况下取得不同的黏聚力c和内摩擦角φ值,通过MIDAS GTS NX进行数据模拟,选取MohrCoulomb模型,采用有限元强度折减法(SRM)算出边坡的等效应变塑性区及安全系数,以此分析边坡稳定性。利用数值模拟的结果,分别绘制坡高、坡比与安全系数的关系图,归类分析不同坡高和坡度对边坡稳定性系数的变化规律。通过边坡稳定影响因素的敏感性分析,分析影响边坡稳定性各因素与边坡安全系数之间的相关性,即分析各因素的变化对于边坡安全系数的影响程度。     

Landslide inventory and susceptibility assessment using multiple statistical approaches along the Karakoram highway,northern Pakistan

China-Pakistan Economic Corridor(CPEC)is a framework of regional connectivity,which will not only benefit China and Pakistan but will have positive impact on Iran,Afghanistan,India,Central Asian Republic,and the region.The surrounding area in CPEC is prone to frequent disruption by geological hazards mainly landslides in northern Pakistan.Comprehensive landslide inventory and susceptibility assessment are rarely available to utilize for landslide mitigation strategies.This study aims to utilize the high-resolution satellite images to develop a comprehensive landslide inventory and subsequently develop landslide susceptibility maps using multiple techniques.The very high-resolution(VHR)satellite images are utilized to develop a landslide inventory using the visual image classification techniques,historic records and field observations.A total of 1632 landslides are mapped in the area.Four statistical models i.e.,frequency ratio,artificial neural network,weights of evidence and logistic regression were used for landslide susceptibility modeling by comparing the landslide inventory with the topographic parameters,geological features,drainage and road network.The developed landslides susceptibility maps were verified using the area under curve(AUC)method.The prediction power of the model was assessed by the prediction rate curve.The success rate curves show 93%,92.8%,92.7%and 87.4%accuracy of susceptibility maps for frequency ratio,artificial neural network,weights of evidence and logistic regression,respectively.The developed landslide inventory and susceptibility maps can be used for land use planning and landslide mitigation strategies.     

Assessment of rock slope stability by probabilistic-based Slope Stability Probability Classification method along highway cut slopes in Adilcevaz-Bitlis (Turkey)

Rock slope stability is of great concern along highway routes as stability problems on cut slopes may cause fatal events as well as loss of property. In rock slope engineering, stability evaluations are commonly performed by means of analytical or numerical analyses, principally considering the factor of safety concept. As a matter of fact, the probabilistic assessment of slope stability is progressively getting popularity due to difficulties in assigning the most appropriate values to design parameters in analytical or numerical methods. Additionally, the effect of heterogeneities in rock masses and discontinuities on the analysis results is minimized through the probabilistic concept. In this study, slope stability of high and steep sedimentary rock cut slopes along a state highway in Adilcevaz-Bitlis (Turkey) was evaluated on the basis of probabilistic approach using the Slope Stability Probability Classification (SSPC) system. The probabilistic assessment indicates major slope stability problems because of discontinuity controlled and discontinuity orientation independent mass movements. Almost all studied cut slopes suffer from orientation-independent stability problems with very low stability probabilities. Additionally, the probability of planar and toppling failures is significantly high with respect to the SSPC system. The stability problems along the investigated rock slopes were also verified by field reconnaissance. Remedial measures such as slope re-design and reinforcement at the studied locations should be taken to prevent hazardous events along the highway. On the other hand, the probabilistic approach may be a useful tool during rock slope engineering to overcome numerous uncertainties when probabilistic and analytic results are compared.     

Evaluation of spatiotemporal variability of temperature and precipitation over the Karakoram Highway region during the cold season by a Regional Climate Model

Precipitation and temperature are two important factors associated to snow hazards which block the transport infrastructure and cause loss of life and properties in the cold season. The in-situ observations are limited in the alpine with complex topographic characteristics, while coarse satellite rainfall estimates, reanalysis rain datasets, and gridded in-situ rain gauge datasets obscure the understanding of the precipitation patterns in hazardprone areas. Considering the Karakoram Highway(KKH) region as a study area, a double nestedWeather Research and Forecasting(WRF) model with the high resolution of a 10-km horizontal grid was performed to investigate the spatial and temporal patterns of temperature and precipitation covering the Karakoram Highway region during the cold season. The results of WRF were compared with the in-situ observations and Multi-Source WeightedEnsemble Precipitation(MSWEP) datasets. The results demonstrated that the WRF model well reproduced the observed monthly temperature(R =0.96, mean bias =-3.92°C) and precipitation(R =0.57, mean bias = 8.69 mm). The WRF model delineated the essential features of precipitation variability and extremes, although it overestimatedthe wet day frequency and underestimated the precipitation intensity. Two rain bands were exhibited in a northwest-to-southeast direction over the study area. High wet day frequency was found in January,February, and March in the section between Hunza and Khunjerab. In addition, the areas with extreme values are mainly located in the Dasu-Islamabad section in February, March, and April. The WRF model has the potential to compensate for the spatial and temporal gaps of the observational networks and to provide more accurate predictions on the meteorological variables for avoiding common coldweather hazards in the ungauged and high altitude areas at a regional scale.     

Projection of future streamflow of the Hunza River Basin,Karakoram Range (Pakistan) using HBV hydrological model

Hydrologiska Byrans Vattenbalansavdeling(HBV) Light model was used to evaluate the performance of the model in response to climate change in the snowy and glaciated catchment area of Hunza River Basin. The study aimed to understand the temporal variation of streamflow of Hunza River and its contribution to Indus River System(IRS). HBV model performed fairly well both during calibration(R2=0.87, Reff=0.85, PBIAS=-0.36) and validation(R2=0.86, Reff=0.83, PBIAS=-13.58) periods on daily time scale in the Hunza River Basin. Model performed better on monthly time scale with slightly underestimated low flows period during bothcalibration(R2=0.94, Reff=0.88, PBIAS=0.47) and validation(R2=0.92, Reff=0.85, PBIAS=15.83) periods. Simulated streamflow analysis from 1995-2010 unveiled that the average percentage contribution of snow, rain and glacier melt to the streamflow of Hunza River is about 16.5%, 19.4% and 64% respectively. In addition, the HBV-Light model performance was also evaluated for prediction of future streamflow in the Hunza River using future projected data of three General Circulation Model(GCMs) i.e. BCC-CSM1.1, CanESM2, and MIROCESM under RCP2.6, 4.5 and 8.5 and predictions were made over three time periods, 2010-2039, 2040-2069 and 2070-2099, using 1980-2010 as the control period. Overall projected climate results reveal that temperature and precipitation are the most sensitiveparameters to the streamflow of Hunza River. MIROC-ESM predicted the highest increase in the future streamflow of the Hunza River due to increase in temperature and precipitation under RCP4.5 and 8.5 scenarios from 2010-2099 while predicted slight increase in the streamflow under RCP2.6 during the start and end of the 21 th century. However, BCCCSM1.1 predicted decrease in the streamflow under RCP8.5 due to decrease in temperature and precipitation from 2010-2099. However, Can ESM2 predicted 22%-88% increase in the streamflow under RCP4.5 from 2010-2099. The results of this study could be useful for decision making and effective future strategic plans for water management and their sustainability in the region.     

Characteristics of Permafrost along Highway G214 in the Eastern Qinghai-Tibet Plateau

The characteristics of the permafrost along National Highway No. 214(G214) in Qinghai province(between kilometer markers K310 and K670),including the distribution patterns of permafrost and seasonally frozen ground(SFG), ground ice content and mean annual ground temperature(MAGT), were analyzed using a large quantity of drilling and measured ground temperature data. Three topographic units can be distinguished along the highway: the northern mountains, including Ela Mountain and Longstone Mountain; the medial alluvial plain and the southern Bayan Har Mountains.The horizontal distribution patterns of permafrost can be divided into four sections, from north to south: the northern continuous permafrost zone(K310-K460),the island permafrost zone(K460-K560), the southern continuous permafrost zone(K560-K630),and the discontinuous permafrost zone(K630-K670).Vertically, the permafrost lower limits(PLLs) of the discontinuous zone were 4200/4325 m, 4230/4350 m,and 4350/4450 m on the north-facing/south-facing slopes of Ela Mountain, Longstone Mountain and Bayan Har Mountains, respectively. The permafrost was generally warm, with MAGTs between-1.0°C and0°C in the northern continuous permafrost zone,approximately-0.5°C in the island permafrost zone,between-1.5°C and 0°C in the southern continuous permafrost zone, and higher than-0.5°C in the discontinuous permafrost zone. In contrast, the spatial variations in ground ice content were mainly controlled by the local soil water content and lithology.The relationships between the mean annual air temperature(MAAT) and the PLLs indicated that the PLLs varied between-3.3°C and-4.1°C for the northern Ela and Longstone Mountains and between-4.1°C and-4.6°C in the southern Bayan Har Mountains.