Watershed delineation using hydrographic features and a DEM in plain river network region

Watershed delineation is a required step when conducting any spatially distributed hydrological modelling. Automated approaches are often proposed to delineate a watershed based on a river network extracted from the digital elevation model (DEM) using the deterministic eight‐neighbour (D8) method. However, a realistic river network cannot be derived from conventional DEM processing methods for a large flat area with a complex network of rivers, lakes, reservoirs, and polders, referred to as a plain river network region (PRNR). In this study, a new approach, which uses both hydrographic features and DEM, has been developed to address the problems of watershed delineation in PRNR. It extracts the river nodes and determines the flow directions of the river network based on a vector‐based hydrographic feature data model. The river network, lakes, reservoirs, and polders are then used to modify the flow directions of grid cells determined by D8 approach. The watershed is eventually delineated into four types of catchments including lakes, reservoirs, polders, and overland catchments based on the flow direction matrix and the location of river nodes. Multiple flow directions of grid cells are represented using a multi‐direction encoding method, and multiple outflows of catchments are also reflected in the topology of catchments. The proposed approach is applied to the western Taihu watershed in China. Comparisons between the results obtained from the D8 approach, the ‘stream burning’ approach, and those from the proposed approach clearly demonstrate an improvement of the new approach over the conventional approaches. This approach will benefit the development of distributed hydrological models in PRNR for the consideration of different types and multiple inlets and outlets of catchments. Copyright © 2015 John Wiley & Sons, Ltd.     

基于CMIP5模式的中国气候变化敏感性预估与分析

以CMIP5提供的26个全球气候系统模式的温度和降水数据为基础,采用区域气候变化指数(Regional Climate Change Index,RCCI)分析中国的不同区域对21世纪气候变化响应的敏感性。结果表明,三种排放情景(RCP 2.6、RCP 4.5、RCP 8.5)下,21世纪全期,气候变化最敏感的区域分布在西藏地区,其次为我国西北地区以及东北地区,气候变化敏感性最低的区域分布在我国内蒙古中东部、华北地区以及长江中下游一带,且高排放情景对应更高的气候变化敏感性。对RCCI指数贡献因子分析结果表明,对中国气候变化敏感性贡献的大小依次为Δσ_TΔσ_pΔRRWAF。冬夏两季温度变化的大值区与RCCI指数的大致区分布一致,RCCI大小的分布很大程度上由温度变化的敏感性决定。而夏季降水变化的大值区主要出现在西藏地区、华南地区和东北地区,冬季降水变化的大值区则主要出现在黄河以南长江以北的中原地区以及东北地区。     

FDR土壤水分传感器原状土壤标定方法研究

为获得测站准确的土壤水分传感器标定参数,利用自动土壤水分站点的大型原状土壤为样本,在实验室同时进行人工称重观测和仪器自动对比观测,得到一系列的人工自动测量数据,以人工称重数据为准对自动土壤水分传感器进行订正。由于采用原状土壤,样本土壤的质地、密度、土壤颗粒和结合紧密度基本没有受到破坏,订正后的自动土壤体积含水量值能更加真实反映台站实际土壤墒情,能够修订人工对比观测期间由于样本空间不足导致的不合理的田间标定方程。     

FDR自动土壤水分数据标定问题及解决方法

针对目前FDR自动土壤水分数据可用性低的实际情况,本文从FDR自动土壤水分站传感器原理出发,结合数据处理流程与方法对湖南60个站点不同层次的标定参数及部分站点的相关观测数据进行了分析,指出目前田间标定法在自然条件下几乎无法得到覆盖土壤各个湿度区间的均匀样本数据,导致二次标定参数不合理是造成FDR自动土壤水分站数据可用性差的根本原因。二次标定方程参数不合理主要表现为方程斜率过大、过小、负值3种情况,导致观测数据增幅过大、常年不变、与实际土壤湿度变化趋势完全相反等问题。最后针对该问题提出了大样本原状取土,实验室标定的解决方法,并对方法进行了初步验证,结果表明该方法能从源头上有效改善土壤水分站观测数据质量。     

空间层次聚类显著性判别的重排检验方法

同时顾及空间邻近与专题属性相似的空间层次聚类是挖掘空间分布模式的一种有效手段。空间层次聚类方法虽然可以获得多层次的聚集结构,但聚类结果显著性的统计判别依然是一个尚未解决的难题。为此,本文提出了一种空间层次聚类结果显著性的统计判别方法,用于确定空间层次聚类的停止准则,减少聚类过程对参数设置的依赖。通过试验分析与比较发现,该方法能够有效判别空间层次聚类结果的显著性和确定层次聚类合并过程的停止条件,同时具有很好的抗噪性,避免随机结构的干扰。     

基于OS071X测波雷达的波浪探测分析

文章利用舟山海洋环境监测站2014年第16号台风"凤凰"过境影响期间,对OS071X测波雷达和3m波浪浮标在同一海域内的波浪探测资料进行了对比验证。通过分析,OS071X测波雷达探测反演的有效波高、周期与3m波浪浮标探测结果对比,二者按先后顺序的均方根误差分别为0.27m和0.29m,相关系数分别为0.93和0.90。结果表明,OS071X测波雷达系统的探测精度得到了验证,能够满足实时探测近岸海域波浪的需求。     

Extreme deformation characteristics and countermeasures for a tunnel in difficult grounds in southern Shaanxi,China

The Qingling–Bashan (QB) mountain region in southern Shaanxi mainly consists of strongly compressive zones from east to west, with tight folds and compressive fractures. There is a wide distribution of soft rocks of various types, such as phyllite and slate, accompanied by complex geological structures. Ironically, tunnel construction in these difficult grounds with complicated geological conditions embraces a high risk of extreme deformation due to various unpredictable reasons, which can frequently cause collapse and result in budget overruns during the construction period. Therefore, it is crucial to conduct effective countermeasures to eliminate or avoid such adverse impacts. This paper provides a case study on the “Yingfeng tunnel” (a tunnel constructed in soft rock consisting of a slate ground) based on a geological survey, indoor experiments and in situ monitoring. A successive rock mass deformation resulted in the tunnel lining seriously intruding into construction clearance and some other sections, even collapsing during the construction. The maximum displacement amount was 62.5 cm, while the maximum deformation speed reached as high as 34.18 mm/day. Additionally, to evaluate the construction impacts of tunnelling-induced geo-hazards, an investigation on extreme deformation was conducted. Considering the time-dependent features of the rock mass deformation, the constraint-convergence method was used to put forward applicable countermeasures in this paper. Finally, from the feedbacks of monitoring results, extreme deformation of the Yingfeng tunnel was effectively controlled.     

School vulnerability to disaster: examination of school closure,demographic, and exposure factors in Hurricane Ike’s wind swath

Damage and destruction to schools from climate-related disasters can have significant and lasting impacts on curriculum and educational programs, educational attainment, and future income-earning potential of affected students. As such, assessing the potential impact of hazards is crucial to the ability of individuals, households, and communities to respond to natural disasters, extreme events, and economic crises. Yet, few studies have focused on assessing the vulnerability of schools in coastal regions of the USA. Using Hurricane Ike’s tropical storm wind swath in the State of Texas as our study area, we: (1) assessed the spatial distribution patterns of school closures and (2) tested the relationship between school closure and vulnerability factors (namely physical exposure and school demographics) using zero-inflated negative binomial regression models. The regression results show that higher probabilities of hurricane strikes, more urbanized school districts, and school districts located in coastal counties on the right side of Ike’s path have significant positive associations with an increase in the number of school closure days. Socioeconomic characteristics were not significantly associated with the number of days closed, with the exception of proportion of Hispanic youth in schools, a result which is not supported by the social vulnerability literature. At a practical level, understanding how hurricanes may adversely impact schools is important for developing appropriate preparedness, mitigation, recovery, and adaptation strategies. For example, school districts on the right side of the hurricane track can plan in advance for potential damage and destruction. The ability of a community to respond to future natural disasters, extreme events, and economic crises depends in part on mitigating these adverse effects.