松动岩体工程特性研究——以雅砻江楞古水电站松动岩体为例

为了对松动岩体的工程特性进行系统研究,以楞古水电站厂址区边坡为例,对该边坡岩体进行了详细的地质编录和物理勘探试验,重点对节理裂隙的空间发育规律、镶嵌结构和碎裂结构岩体的发育深度及空间分布、软弱结构面发育分布规律以及边坡已有变形破坏特征这四个方面进行了系统的统计和分析,认为松动岩体是区域断裂活动和浅表生改造的结果,岩体工程效应差、变形模量低;同时结合应力测试、声波测速、高密度电磁勘探等试验成果进行分析,结果显示松动岩体具低波速（波速大部分小于3 000 m/s）、低应力（最大主应力不超过20 MPa）、强透水性（透水性系数大于10 L/（min·m·m））。认为岩体破碎主要受断层及节理裂隙影响,分析了岩体破裂松动的演化过程及特征。     

宿南矿区不同时期塌陷塘水环境质量评价

以宿南矿区不同时期形成的采煤塌陷塘(芦岭塘、朱仙庄#1塘和#2塘)为研究对象,于2017年先后采集夏季和冬季水样,运用piper三线图、相关性分析、改进模糊综合评价法等,对其水环境质量进行分析评价与比较,得到以下结论:①芦岭塘、朱仙庄#1塘夏、冬两季水化学类型均为HCO_3―Na·Mg型,朱仙庄#2塘为SO_4―Na·Mg·Ca型。②三个塌陷塘水的TDS、pH、EC变化趋势为朱仙庄#1塘>朱仙庄#2塘>芦岭塘,其季节变化趋势均为夏季>冬季; ORP变化趋势为朱仙庄#2塘>芦岭塘>朱仙庄#1塘,其季节性变化趋势为冬季>夏季。③改进的模糊综合评价结果表明,三个塌陷塘夏季水质较差,主要受人为污染影响;冬季芦岭塘、朱仙庄#1塘水质良好,受污染小;朱仙庄#2塘冬季水质与夏季相近,均较差,主要受投加鱼食料的影响。     

北极斯瓦尔巴德群岛中部海域表层海水水质研究

掌握北极海水水质特征及地域分布等第一手数据对北极科考意义重大。该项研究工作是全国青少年北极科考子任务,于2017年夏季在北极斯瓦尔巴德群岛中部海域对表层海水水质特征、地域差异及相关控制因素进行了研究。选取了6个区域共40个采样点采集表层海水样本,从温度、酸碱度、电导率、溶解性总固体量、实际盐度和溶解氧饱和度等方面进行了水质特征测量分析,发现该海域6个区域在海水温度、电导率、溶解性总固体量、实际盐度及溶解氧饱和度等方面均有较大差异,而酸碱度差异不大: 北部冰区水温最低,溶解性总固体量最低,溶解氧含量较高; 西北部海湾溶解氧饱和度最高; 中部海峡溶解性总固体量最高,盐度和电导率最低; 南部海域水温最高,实际盐度和电导率最高,溶解氧饱和度最低; 东部沿海水温偏低。采样点地理位置、洋流情况、地形地貌等因素对表层海水水质均有影响。这些研究成果对补充我国在北极地区的第一手科考数据和进行深入的科考研究具有重要意义。     

Evolution trend of the water quality in Dongping Lake after South-North Water Transfer Project in China

To investigate the evolution trend of water quality in Dongping Lake after South-North Water Transfer Project operation as well as to ensure the safe usage of the water receiving areas, water samples were collected and determined before and after water delivery in different hydrological seasons. Then, comprehensive pollution index method, comprehensive nutrition state index method and health risk assessment model were utilized to evaluate the quality, nutrition, and health risk of Dongping Lake water. Results showed that the quality of Dongping Lake water still met level Ⅲ (light pollution) no matter before or after water delivery. The nutrition state was improved from light eutropher before water delivery to mesotropher after water delivery. The health risk level was reduced from high-medium before water delivery to medium level after water delivery. In summary, the operation of the eastern route of South-North Water Transfer Project is beneficial for water environment improvement of Dongping Lake.     

基于CSA-PLS算法的养殖水体水质快速高光谱预测反演模型研究

养殖水体水质的优劣直接影响养殖对象的成长,准确、快速、全面地掌控养殖水环境的水质参数变化情况具有重要意义。传统的水质指标监测方法都通过人工采样的方式,不仅耗费时间长,且只能体现局部水体情况。针对这些问题,提出了一种乌鸦搜索算法(CSA)结合偏最小二乘回归(PLSR)的高光谱特征波段筛选方法,快速构建回归模型,实现光谱数据的精准预测反演。以连片的养殖小区为研究对象,采集养殖水体样本并拍摄同时期的高光谱影像数据。首先对提取的采样点光谱数据利用多种数据变换方法分别预处理;其次利用这些数据,对水质指标总氮(TN)、氨氮(NH₄⁺-N)、总磷(TP)和化学需氧量(COD)分别构建全波段的SVR和AdaBoost回归模型,同时与提出的CSA-PLS自动筛选波段方法和传统的连续投影算法(SPA)筛选波段后构建的模型进行比较分析;最后根据决定系数(R²)和均方根误差(REMS)选出适合各水质指标的最优模型。从实验结果可以看出,所提波段筛选方法的AdaBoost模型预测结果优于SVR和传统SPA方法提取特征波段后构建的模型,与全波段最优模...     

城市规划对大气环境变化及空气质量的影响

采用北京大学三维复杂地形中尺度数值模式,利用Landsat-TM卫星影像图和"北京海淀区北部地区总体规划--用地规划图",分别模拟了北京海淀区北部规划完成后和目前情况下的气象场和大气环境,并分析了规划区的建成对本地和整个海淀区的影响.通过将观测的直径小于10 μm的粒子即PM10总量加权分配得到源强分布,计算海淀区的PM10浓度分布,在目前源强分布调查很困难的情况下不失为一种较为合理可行的方法.试验表明规划区的建成会增加当地和其下风方向的热岛强度和PM10浓度.对规划区进行较为合理的布局,如相对增加树木减少建筑物的面积将会缓和上述影响.     

日照万平口沙滩质量评价及“蓝旗沙滩”建设建议

沙滩质量评价是有效的沙滩管理工具。“蓝旗”标准是目前世界上认可度最高的沙滩评价标准。文章基于“蓝旗”标准,根据国内外已有沙滩质量评价体系,结合实地调研和问卷调查,构建适用于万平口沙滩的质量评价体系。评价结果表明：(1)万平口环境因素、安全与教育和环境管理准则层评价结果均为良好,社会因素准则层达到优质等级,说明万平口风景区作为旅游地,其气候条件适宜,服务水平和安全及教育水平都较为发达。(2）万平口沙滩的自然条件本底优良,是最能体现日照“蓝天、碧海、金沙滩”的特色景区。但由于自然及人为因素造成的沙滩侵蚀退化现象严重,影响了沙滩的可持续发展。根据评价结果及万平口与“蓝旗沙滩”的对比差异,认为万平口建设“蓝旗沙滩”,需要完善景区水质监测、加强景区内及周边环境管理、重视沙滩养护、完善基础设施的投放、进一步提高景区的服务水平、重视景区内安全保障及加强景区的宣传,提高公众对“蓝旗”的认知度。     

炎可宁丸质量评价研究

目的：建立炎可宁丸质量标准。方法：采用显微鉴别法鉴别黄连。采用薄层色谱法（TLC）鉴别黄柏、大黄、黄芩、板蓝根、黄连。采用高效液相色谱（HPLC）法测定大黄素与大黄酚的含量,使用Phenomenex Luna C₁₈色谱柱（4.6 mm ×250 mm,5μm）,以甲醇-0.1%磷酸溶液（85∶15）为流动相,流速为1.0 ml/min,柱温为30℃,检测波长为254 nm。采用HPLC法测定黄芩苷的含量,使用CAPCELL PAK C₁₈色谱柱（4.6 mm×250 mm,5μm）,以甲醇-0.1%磷酸溶液(45∶55)为流动相,流速为1.0 ml/min,柱温为30℃,检测波长为280 nm。结果:薄层色谱斑点清晰;大黄素和大黄素酚的线性范围分别为9.3～465.0 ng、11.6～580.0 ng,加样回收率分别为93.3%、98.0%,RSD分别为1.8%、2.7%;黄芩苷的线性范围为68～3400 ng,加样回收率为97.2%,RSD为1.2%。结论:本法简便可靠、结果准确,可用于该制剂的质量控制。     

Watershed-scale vegetation,water quantity,and water quality responses to wildfire in the southern Appalachian mountain region,United States

Wildfires are landscape scale disturbances that can significantly affect hydrologic processes such as runoff generation and sediment and nutrient transport to streams. In Fall 2016, multiple large drought-related wildfires burned forests across the southern Appalachian Mountains. Immediately after the fires, we identified and instrumented eight 28.4–344 ha watersheds (four burned and four unburned) to measure vegetation, soil, water quantity, and water quality responses over the following two years. Within burned watersheds, plots varied in burn severity with up to 100% tree mortality and soil O-horizon loss. Watershed scale high burn severity extent ranged from 5% to 65% of total watershed area. Water quantity and quality responses among burned watersheds were closely related to the high burn severity extent. Total water yield (Q) was up to 39% greater in burned watersheds than unburned reference watersheds. Total suspended solids (TSS) concentration during storm events were up to 168 times greater in samples collected from the most severely burned watershed than from a corresponding unburned reference watershed, suggesting that there was elevated risk of localized erosion and sedimentation of streams. NO₃-N concentration, export, and concentration dependence on streamflow were greater in burned watersheds and increased with increasing high burn severity extent. Mean NO₃-N concentration in the most severely burned watershed increased from 0.087 mg L⁻¹ in the first year to 0.363 mg L⁻¹ (+317%) in the second year. These results suggest that the 2016 wildfires degraded forest condition, increased Q, and had negative effects on water quality particularly during storm events.     

Quality and timing of crowd-based water level class observations

Crowd-based hydrological observations can supplement existing monitoring networks and allow data collection in regions where otherwise no data would be available. In the citizen science project CrowdWater, repeated water level observations using a virtual staff gauge approach result in time series of water level classes (WL-classes). To investigate the quality of these observations, we compared the WL-class data with “real” (i.e., measured) water levels from the same stream at a nearby gauging station. We did this for nine locations where citizen scientists reported multiple observations using a smartphone app and at 12 locations where signposts were set up to ask citizens to record observations on a paper form that could be left in a letterbox. The results indicate that the quality of the data collected with the app was better than for the forms. A possible explanation is that for each app location, a single person submitted the vast majority of the observations, whereas at the locations of the forms almost every observation was made by a different person. On average, there were more contributions between May and September than during the other months. Observations were submitted for a range of flow conditions, with a higher fraction of high flow observations for the locations were data were collected with the app. Overall, the results are encouraging for citizen science approaches in hydrology and demonstrate that the smartphone application and the virtual staff gauge are a promising approach for crowd-based water level class observations.