Water system characteristics of Karst river basins in South China and their driving mechanisms of hydrological drought

Natural Hazards - It is common knowledge that drought is considered one of the most damaging natural disasters in terms of economic costs, societal problems, and ecological impacts. In this study,...     

The Derivation and Validation of TBM Disc Cutter Wear Prediction Model

The problem of disc cutter wear is inevitable when shield or TBM excavating hard rock for a long distance, thus, the study of disc cutter wear model has an important project value on predicting its service life and replacement opportunity. It is put forward by analyzing disc cutter wear mechanism that the main wear form is abrasive wear, which is based on plastic removal mechanism. Then, disc cutter wear rate and linear wear rate prediction models are obtained by approximate calculation and mathematical deduction, which are based on Rabinowicz equation and CSM model. At last, the two models are verified through field test data from three projects, and the results show that the prediction model can accurately reflect the real wear situation of disc cutter.     

Dynamic Response to Seismic Waves at the Shallow Slope Supported by Bolts

In the soil slope supported by bolts, longitude waves instead of transverse waves, generated by earthquakes, first reach the slope surface. With the dynamic response of the P (pressure) wave along the anchorage structure, first, a theoretical study was conducted to investigate the propagation characteristics of the interference superposition, generated by the SV (shear-vertical) and the P waves. The SV wave was formed by the wave, originating from the bottom and reflected from the free surface of the slope, whereas the latter was the incident P wave, propagating in the slope. In addition, the structural measures, restraining the seismic wave, and the characteristics of the restraint effect at the free segment of the bolt were investigated. According to the wave-way difference between the incident P wave and the reflected SV wave, the minimum critical slope angle, influenced by the interference at the shallow slope, and the maximum influencing depth of the dynamic response, acting vertically to the slope surface, were obtained. The results indicate that the maximum influencing depth linearly correlated with the slope angle. Furthermore, based on the propagation characteristics of the P wave along the bolt, and the coupled relation between the wave length and the anchorage design parameters, the axial acceleration of the wave propagating along the bolt axis was obtained. Then, the theoretical length of the anti-seismic bolt, subjected to seismic waves, and the compensation force of the anchorage structure were obtained. Finally, a numerical study, based on FlAC3D, properly verified the theoretical conclusions.     

高密度电法在草炭土分布特征调查中的应用

为了更好的研究草炭土湿地基本信息,获取草炭土分布特征,选择吉林省东部沼泽草炭土湿地为研究对象,运用高密度电阻率法,对比不同装置下探测结果的差异,再与已知的探槽资料做对比,得出温纳—施伦贝格装置为最可靠、最合理的探测装置。再将该装置运用到其他草炭土地区,得出对草炭土湿地的探测为浅层地质问题,草炭土的视电阻率为50~300Ω·m,深度为1.2~3.9 m,在反演图像中表现为低阻体部分,各地层间层状结构明显,电性界限分明。     

香溪河流域岩溶洞穴发育与分布特征

结合1∶5万水文地质调查,对香溪河岩溶流域溶洞特征进行了探究,统计其溶洞的规模、形态、发育地层、发育方向及分布高程,结果表明:该区洞穴规模中等,受岩性的控制,溶洞的发育表现出对碳酸盐岩岩组类型的选择性,其中寒武-奥陶系地层溶洞发育程度最高;溶洞的发育方向多为北北东和北北西向,与区域构造线一致,同时受本区构造运动间歇性抬升的影响,溶洞集中发育于4个高程区;从溶洞发育的构造部位来看,溶洞主要分布在宽缓向斜的东南翼及向斜核部,平面分布表现出分带性;该区溶洞多发育至早期就停止进一步发育,其规模、类型、分布特征等与鄂西南地区溶洞均存在差异。      

华蓥山中段地区地下水资源量评价

四川华蓥山中段地区水流失比较严重,供需矛盾突出,水环境持续恶化,不但影响到居民正常的生产和生活,而且严重影响了该地区国民经济的建设和发展。通过野外调查和综合分析现场收集的资料,总结出华蓥山中段地区地下水资源量流失情况:该区每年流失的水资源量约为0.914 4亿m3,且华蓥山褶皱西翼水流失总量大于东翼,而西翼北端是区内水流失量最严重的区域,其水资源量流失的影响因素主要为气候、社会发展及人类活动等。      

2021年6-9月广西异常高温成因分析

2021年6-9月广西经历了1951年以来最高的月平均气温,大范围高温天气频发.利用1961-2021年广西国家地面气象观测站日平均气温和日最高气温观测资料、1991-2021年ERA5再分析资料和西太平洋副热带高压指数资料,对此次广西异常高温的特征和成因进行了研究分析.结果 表明,气候变暖是导致此次高温事件的重要气候背景,西太平洋副热带高压异常偏强位置偏西偏北、中纬度西风带扰动影响偏北以及热带气旋影响偏弱是造成广西气温异常偏高的主要原因.     

Modelling coastal land use change by incorporating spatial autocorrelation into cellular automata models

This paper presents a spatial autoregressive (SAR) method-based cellular automata (termed SAR-CA) model to simulate coastal land use change, by incorporating spatial autocorrelation into transition rules. The model captures the spatial relationships between explained and explanatory variables and then integrates them into CA transition rules. A conventional CA model (LogCA) based on logistic regression (LR) was studied as a comparison. These two CA models were applied to simulate urban land use change of coastal regions in Ningbo of China from 2000 to 2015. Compared to the LR method, the SAR model yielded smaller accumulated residuals that showed a random distribution in fitting the CA transition rules. The better-fitting SAR model performed well in simulating urban land use change and scored an overall accuracy of 85.3%, improving on the LogCA model by 3.6%. Landscape metrics showed that the pattern generated by the SAR-CA model has less difference with the observed pattern.     

Mapping fine‐scale urban housing prices by fusing remotely sensed imagery and social media data

The accurate mapping of urban housing prices at a fine scale is essential to policymaking and urban studies, such as adjusting economic factors and determining reasonable levels of residential subsidies. Previous studies focus mainly on housing price analysis at a macro scale, without fine‐scale study due to a lack of available data and effective models. By integrating a convolutional neural network for united mining (UMCNN) and random forest (RF), this study proposes an effective deep‐learning‐based framework for fusing multi‐source geospatial data, including high spatial resolution (HSR) remotely sensed imagery and several types of social media data, and maps urban housing prices at a very fine scale. With the collected housing price data from China's biggest online real estate market, we produced the spatial distribution of housing prices at a spatial resolution of 5 m in Shenzhen, China. By comparing with eight other multi‐source data mining techniques, the UMCNN obtained the highest housing price simulation accuracy (Pearson R = 0.922, OA = 85.82%). The results also demonstrated a complex spatial heterogeneity inside Shenzhen's housing price distribution. In future studies, we will work continuously on housing price policymaking and residential issues by including additional sources of spatial data.     

基于生态足迹的孟连县土地利用结构优化研究

采用生态足迹法对云南孟连县2005—2011年生态足迹进行计算,根据2005—2011年数据运用GM(1,1)灰色预测模型对2020年生态足迹进行预测,得到2020年人均生态赤字将达到2.762 hm2/人,土地利用结构急需调整优化。在此背景下建立以生态赤字最小化和经济效益、社会效益最大化为目标函数的多目标线性规划模型,设置了8个变量和13个约束条件。根据模型求解优化方案,对孟连县2020年土地利用结构进行优化调整,结果表明:相比于优化前,人均生态赤字减少10.87%,经济效益增加0.52亿元,社会效益增加0.001 hm2。优化后的土地利用结构基本上实现了经济、社会、生态效益的统一。