A two-layer model for studying 2D dissolved pollutant runoff over impermeable surfaces

Dissolved pollutants in stormwater are a main contributor to water pollution in urban environments. However, many existing transport models are semi-empirical and only consider one-dimensional flows, which limit their predictive capacity. Combining the shallow water and the advection–diffusion equations, a two-dimensional physically based model is developed for dissolved pollutant transport by adopting the concept of a ‘control layer’. A series of laboratory experiments has been conducted to validate the proposed model, taking into account the effects of buildings and intermittent rainfalls. The predictions are found to be in good agreement with experimental observations, which supports the assumption that the depth of the control layer is constant. Based on the validated model, a parametric study is conducted, focusing on the characteristics of the pollutant distribution and transport rate over the depth. The hyetograph, including the intensity, duration and intermittency, of rainfall event has a significant influence on the pollutant transport rates. The depth of the control layer, rainfall intensity, surface roughness and area length are dominant factors that affect the dissolved pollutant transport. Finally, several perspectives of the new pollutant transport model are discussed. This study contributes to an in-depth understanding of the dissolved pollutant transport processes on impermeable surfaces and urban stormwater management.     

Characterizing spatial and temporal variation in 18O and 2H content of New Zealand river water for better understanding of hydrologic processes

Time series of hydrogen and oxygen stable isotope ratios (δ²H and δ¹⁸O) in rivers can be used to quantify groundwater contributions to streamflow, and timescales of catchment storage. However, these isotope hydrology techniques rely on distinct spatial or temporal patterns of δ²H and δ¹⁸O within the hydrologic cycle. In New Zealand, lack of understanding of spatial and temporal patterns of δ²H and δ¹⁸O of river water hinders development of regional and national-scale hydrological models. We measured δ²H and δ¹⁸O monthly, together with river flow rates at 58 locations across New Zealand over a two-year period. Results show: (a) general patterns of decreasing δ²H and δ¹⁸O with increasing latitude were altered by New Zealand's major mountain ranges; δ²H and δ¹⁸O were distinctly lower in rivers fed from higher elevation catchments, and in eastern rain-shadow areas of both islands; (b) river water δ²H and δ¹⁸O values were partly controlled by local catchment characteristics (catchment slope, PET, catchment elevation, and upstream lake area) that influence evaporation processes; (c) regional differences in evaporation caused the slope of the river water line (i.e., the relationship between δ²H and δ¹⁸O in river water) for the (warmer) North Island to be lower than that of the (cooler, mountain-dominated) South Island; (d) δ²H seasonal offsets (i.e., the difference between seasonal peak and mean values) for individual sites ranged from 0.50‰ to 5.07‰. Peak values of δ¹⁸O and δ²H were in late summer, but values peaked 1 month later at the South Island sites, likely due to greater snow-melt contributions to streamflow. Strong spatial differences in river water δ²H and δ¹⁸O caused by orographic rainfall effects and evaporation may inform studies of water mixing across landscapes. Generally distinct seasonal isotope cycles, despite the large catchment sizes of rivers studied, are encouraging for transit time analysis applications.     

中学地理科学实验的六大类型及其案例分析

依据实验的根本目的,为拓展学生对地理过程的理解,体验真实的地理原理,笔者将中学地理科学实验划分为经典实验室实验、时间变化模型实验、类比实验、空间变化模型实验、物理模型实验以及计算机模型实验六大类型,并对每一类型实验进行举例分析,希望以此深化地理科学实验的理论研究、丰富地理科学实验的实践案例、培养学生的地理核心素养,为地理科学实验教学研究提供新的视角。     

地理试题透视六大解题思维——以浙江省选考试题为例

思维是指人脑借助于语言对客观事物的概括和间接反应的过程,以感知为基础,又超越感知的界限,它探索与发现事物的内部本质联系和规律性,是认识过程的高级阶段。目前国内针对地理解题的思维研究相对较少,本文以浙江省历年选考地理试题为例,总结和提炼出六大解题思维,即:逆向思维、收支平衡思维、比较思维、发散思维、空间思维、辩证思维,旨在帮助学生掌握分析和解答地理问题的方法,从而有效提升高中地理学习和复习效果,增强学生学习地理的兴趣。同时在培养学生的地理解题思维过程中,落实地理学科核心素养的培育。     

科尔沁湿草甸参考作物蒸散发模拟分析

为探明气候变化下干旱半干旱地区湿草甸参考作物蒸散发(ET₀)影响因子,使用FAO 56 P-M模型对科尔沁湿草甸ET₀进行模拟,利用涡度相关系统对模型的适用性进行评价,并通过通径分析及指标敏感性分析对ET₀的影响因子进行辨识。结果表明:(1)小时尺度模拟精度最高,日尺度次之,月尺度较差,小时尺度上晴、阴、雨3种天气条件下模拟效果不同,晴天最优,阴雨天较差。(2)ET₀年内变化呈单峰曲线状,生长季明显高于非生长季,集中在3—10月,占全年89.79%。生长季典型晴天ET₀逐小时分布特征遵循倒“U”单峰型变化规律。(3)通径分析结果显示,对ET₀的通径系数以及对回归方程估测可靠程度E的总贡献均表现为VPD(饱和水汽压差) > T_min(最低气温) > R_n(冠层表面净辐射)>u₂(2 m高度风速),即VPD为影响ET₀最重要的因子;指标敏感性分析中,在去除VPD后引起的E变化最大,说明ET₀对VPD的变化最为敏感,其次为u₂、T_min和R_n。     

居住迁移对居民健康的影响研究进展述评

进入城市时代以来,居住环境与居民健康的联系愈发密切,尤其在“流动性"增强的大背景下,居住迁移对居民健康的影响问题受到广泛关注。论文结合知识图谱分析和文献研究法,系统评述居住迁移影响居民健康问题的最新进展。研究发现：① 近15 a来,该领域的文献数量逐年增多,关注度持续上升;文献空间分布主要集中在发达国家,但不同地区的研究内容存在显著差异。② 主要研究对象由“同质性群体”向“异质性群体”转变,从“一般性群体”向“特殊群体”转变;研究方法由数理统计向混合研究、综合应用转变。③ 研究视角经历“人口迁移—个体健康”“居住迁移—环境—个体健康”与“迁居轨迹—环境演变—个体健康发展”等3个演变阶段。④ 近期研究重点有：迁居行为与儿童健康,迁居时空特征与身心健康,住房生涯与身心健康,邻里环境、累积剥夺与健康发展等。结合以上分析,提出如下建议：注重“整合性”分析;关注城市内部迁居行为和多次迁居轨迹对居民健康的影响;扩大迁居引发的“环境”因素(如居住隔离、社会分异、职住空间错位等)研究;更多关注迁居对二代流动人口儿童健康的影响,侧重对非正规居住空间如“城中村”等的研究。     

南极罗斯海沉积物中可培养菌株的分离及胞外水解酶活性检测

研究了南极罗斯海地区沉积物中可培养微生物多样性,并检测了菌株胞外酶活性,为开发利用南极资源奠定基础。采用Zobell2216E培养基、土豆培养基(PDA)及稀释平板划线法分离并获得纯培养的细菌和真菌,分别通过16SrDNA、18S/ITS序列鉴定分析了可培养微生物的多样性和系统发育。从南极罗斯海沉积物样品中获得78株细菌和54株真菌,细菌、真菌的优势菌株分别为嗜冷杆菌属(Psychrobacter)、枝孢属(Cladosporium);78株细菌菌株中有2株与模式菌株的16SrDNA基因序列相似性小于97%,可能是潜在的细菌新物种。细菌API20NE生理生化和真菌产胞外酶活性结果表明,获得的细菌和真菌大多数可检测到胞外水解酶活性。本研究丰富了南极可培养微生物资源,为南极罗斯海地区可培养微生物的多样性研究以及南极微生物资源的应用研究奠定了基础。     

China’s rural revitalization and development: Theory,technology and management

Journal of Geographical Sciences - The urban-rural transformation from dichotomy to integration is a gradual process. Like rural areas in many countries, Chinese rural society is experiencing a...     

Identifying primary public transit corridors using multi-source big transit data

ABSTRACT

Effective public transit planning needs to address realistic travel demands, which can be illustrated by corridors across major residential areas and activity centers. It is vital to identify public transit corridors that contain the most significant transit travel demand patterns. We propose a two-stage approach to discover primary public transit corridors at high spatio-temporal resolutions using massive real-world smart card and bus trajectory data, which manifest rich transit demand patterns over space and time. The first stage was to reconstruct chained trips for individual passengers using multi-source massive public transit data. In the second stage, a shared-flow clustering algorithm was developed to identify public transit corridors based on reconstructed individual transit trips. The proposed approach was evaluated using transit data collected in Shenzhen, China. Experimental results demonstrated that the proposed approach is a practical tool for extracting time-varying corridors for many potential applications, such as transit planning and management.