Efficient Delineation of Nested Depression Hierarchy in Digital Elevation Models for Hydrological Analysis Using Level‐Set Method

In terrain analysis and hydrological modeling, surface depressions (or sinks) in a digital elevation model (DEM) are commonly treated as artifacts and thus filled and removed to create a depressionless DEM. Various algorithms have been developed to identify and fill depressions in DEMs during the past decades. However, few studies have attempted to delineate and quantify the nested hierarchy of actual depressions, which can provide crucial information for characterizing surface hydrologic connectivity and simulating the fill‐merge‐spill hydrological process. In this paper, we present an innovative and efficient algorithm for delineating and quantifying nested depressions in DEMs using the level‐set method based on graph theory. The proposed level‐set method emulates water level decreasing from the spill point along the depression boundary to the lowest point at the bottom of a depression. By tracing the dynamic topological changes (i.e., depression splitting/merging) within a compound depression, the level‐set method can construct topological graphs and derive geometric properties of the nested depressions. The experimental results of two fine‐resolution Light Detection and Ranging‐derived DEMs show that the raster‐based level‐set algorithm is much more efficient (~150 times faster) than the vector‐based contour tree method. The proposed level‐set algorithm has great potential for being applied to large‐scale ecohydrological analysis and watershed modeling.     

Biological Connectivity of Seasonally Ponded Wetlands across Spatial and Temporal Scales

Many species that inhabit seasonally ponded wetlands also rely on surrounding upland habitats and nearby aquatic ecosystems for resources to support life stages and to maintain viable populations. Understanding biological connectivity among these habitats is critical to ensure that landscapes are protected at appropriate scales to conserve species and ecosystem function. Biological connectivity occurs across a range of spatial and temporal scales. For example, at annual time scales many organisms move between seasonal wetlands and adjacent terrestrial habitats as they undergo life‐stage transitions; at generational time scales, individuals may disperse among nearby wetlands; and at multigenerational scales, there can be gene flow across large portions of a species’ range. The scale of biological connectivity may also vary among species. Larger bodied or more vagile species can connect a matrix of seasonally ponded wetlands, streams, lakes, and surrounding terrestrial habitats on a seasonal or annual basis. Measuring biological connectivity at different spatial and temporal scales remains a challenge. Here we review environmental and biological factors that drive biological connectivity, discuss implications of biological connectivity for animal populations and ecosystem processes, and provide examples illustrating the range of spatial and temporal scales across which biological connectivity occurs in seasonal wetlands.     

Does Wetland Location Matter When Managing Wetlands for Watershed‐Scale Flood and Drought Resilience?

Wetland protection and restoration strategies that are designed to promote hydrologic resilience do not incorporate the location of wetlands relative to the main stream network. This is primarily attributed to the lack of knowledge on the effects of wetland location on wetland hydrologic function (e.g., flood and drought mitigation). Here, we combined a watershed‐scale, surface–subsurface, fully distributed, physically based hydrologic model with historical, existing, and lost (drained) wetland maps in the Nose Creek watershed in the Prairie Pothole Region of North America to (1) estimate the hydrologic functions of lost wetlands and (2) estimate the hydrologic functions of wetlands located at different distances from the main stream network. Modeling results showed wetland loss altered streamflow, decreasing baseflow and increasing stream peakflow during the period of the precipitation events that led to major flooding in the watershed and downstream cities. In addition, we found that wetlands closer to the main stream network played a disproportionately important role in attenuating peakflow, while wetland location was not important for regulating baseflow. The findings of this study provide information for watershed managers that can help to prioritize wetland restoration efforts for flood or drought risk mitigation.     

Application of response surface methodology for the optimization of biodiesel production from yellow mustard (Sinapis alba L.) seed oil

In the present study, response surface methodology (RSM) involving central composite design (CCD) was applied to optimize the reaction parameters of biodiesel production from yellow mustard (Sinapis alba L.) seed oil during the single-step transesterification process. A total of 30 experiments were designed and performed to determine under the effects of variables on the biodiesel yield such as methanol to oil molar ratio (2:1–10:1), catalyst concentration (0.2–1.0 wt.% NaOH), reaction temperature (50–70°C), and reaction time (30–90 min). The second order polynomial model was used to predict the biodiesel yield and coefficient of determination (R²) was found to be at 0.9818. The optimum biodiesel yield was calculated as 96.695% from the model with the following reaction conditions: 7.41:1 of methanol to oil molar ratio, 0.63 wt. % NaOH of catalyst concentration, 61.84°C of reaction temperature, and 62.12 min of reaction time. It is seen that the regression model results were in agreement with the experimental data. The results showed that RSM is a suitable statistical technique for optimizing the reaction parameters in the transesterification process in order to maximize the biodiesel yield.     

不同配置人工湿地对分散性生活污水的处理效能研究

为研究不同植物及组合(美人蕉+黄菖蒲、花叶芦竹、黄菖蒲、旱伞草)与不同填料(陶粒、沸石、改性沸石、改性钢渣)对系统处理分散性生活污水效能的影响,建立了8种不同配置的潜流式人工湿地中试系统。结果表明,各湿地对COD均具有较好的去除效果(去除率大于70%)。旱伞草、黄菖蒲+美人蕉、黄菖蒲和花叶芦竹四植物系统对TN的去除率均呈先降低后上升的趋势,最终平均去除率分别为57.8%、51.1%、50.4%和45.5%。改性沸石、沸石、陶粒和改性钢渣填料系统对TN平均去除率分别为96.4%、83.7%、34.6%和26.6%。各植物系统对TP的去除效果差异不显著,其中旱伞草系统TP平均去除负荷最大(0.63 g/(d·m2))。各填料对TP的去除效果从大到小依次为改性钢渣、改性沸石、陶粒、沸石,改性钢渣和改性沸石对TP的去除能力显著高于陶粒和沸石,平均去除率达86.3%和78.8%。研究表明,分别采用旱伞草和改性沸石为湿地植物和填料具有较好的应用前景。     

一株苯酚降解菌的筛选鉴定及响应面法优化其降解

从某化工厂污水处理车间活性污泥中分离、筛选到一株能以苯酚为唯一碳源和能源生长的菌株YH8.基于形态特征、生理生化特性、BIOLOG细菌自动鉴定系统、16S rDNA和gyrB基因序列同源性分析鉴定菌株YH8,鉴定菌株YH8为Acinetobacter guillouiae.在苯酚浓度低于1200 mg·L-1,温度为26~34℃,pH为7.0~10.0时,菌株YH8培养60 h对苯酚的降解率达70%以上.运用单因素实验初步确定苯酚降解的最适外加碳源和氮源分别为山梨醇和NaNO3,最适温度为30℃,最适初始pH为9.0,最适接种量为5%.为了提高菌株YH8的降解率,首先利用Plackett-Burman实验设计评估并筛选出影响苯酚降解的3个关键因素为初始pH、苯酚浓度、山梨醇浓度.用最陡爬坡实验逼近以上3个因子的最大响应区域,采用Box-Behnken实验设计及响应面法分析,确定其最优降解条件为初始pH 9.26、苯酚浓度1163.63 mg·L-1、山梨醇浓度7.81%、接种量5%、NaNO_3浓度2%、温度30℃、培养时间96 h,在此条件下苯酚降解率可达98.95%.苯酚降解酶活性及酶定域实验表明,菌株YH8相关降解酶为胞内酶,且苯酚可诱导苯酚羟化酶(LmPH)和邻苯二酚1,2-双加氧酶(C_(12)O)的合成.通过降解酶特异性引物从菌株YH8扩增得到LmPH和C12O基因片段,经质粒检测和消除实验发现菌株YH8相关降解基因位于质粒上.此外,菌株YH8能耐受高浓度NaCl和多种重金属离子,对多种抗生素具有抗性.     

宜兴市土地利用类型与水生态健康相关性研究

利用宜兴市2012年-2014年土地利用数据、水生态健康等相关数据,引用土地利用动态度和土地利用综合程度指数,对土地利用变化和水生态健康现状进行分析,运用相关性分析法测算土地利用类型比例与水生态健康主要指标的相关性.结果表明:耕地、建设用地比例与水生态健康综合指标负相关,湿地、草地、园地、林地用地比例与水生态健康综合指标正相关;建设用地比例与底栖动物负相关;湿地用地比例与营养、底栖动物指标正相关较强.     

黄河三角洲新生湿地土壤碳氮磷分布及其生态化学计量学意义

河口湿地是连接陆地生态系统和海洋生态系统的纽带。土壤碳(C)、氮(N)、磷(P)元素是湿地生态系统营养水平的重要指示物,显著影响湿地生态系统的生产力。本文研究了黄河三角洲新生湿地不同植被下土壤C、N、P的分布特征和生态化学计量特征。结果表明,1)黄河三角洲新生湿地C、N、P含量分别为1.2~8.4、0.2~0.8、0.4~0.6g/kg,平均值分别为3.5、0.4、0.5g/kg;土壤表层的C、N、P含量显著高于亚表层。2)黄河三角洲新生湿地C/N、C/P、N/P比值分别为4.62~12.67、2.02~16.39、0.22~1.53,平均值分别为8.77、6.81、0.77。土壤C/N、C/P、N/P比值随土壤剖面深度向下递减,不同植被土壤之间的C/N、C/P、N/P比值有所不同。土壤生态化学计量比值显示黄河三角洲新生湿地土壤有机质分解快,氮的矿化度高。因此,提高该地区土壤有机质的归还,同时适当增加氮肥使用成为湿地生态恢复的优先选项。     

石英灯辐射式瞬态热环境试验关键技术分析

结合石英灯辐射式加热器的特性,从传感器弱信号传输、无功补偿、智能控制、仿形加热器、开环试验技术等角度出发,分析了对型号瞬态热试验性能的影响。结合瞬态热试验的实施,给出了上述几个角度制约热试验实施的改进措施,以期提高试验系统瞬态热试验的有效性。     

污泥水磷和有机物同步混凝去除的多目标优化技术研究

通过引入多响应值的归一化评分法进行了污泥水磷和有机物同步混凝去除的多目标优化,并利用响应面(RSM)技术考察了Al/P比、聚丙烯酰胺(PAM)投加量和悬浮固体(SS)浓度对污染物去除的单独效应和联合效应.结果表明,复合投加聚合氯化铝和PAM能同步去除污泥水中磷和有机物,并改善沉降效果.归一化后单目标RSM优化显示,对污泥水中磷和有机物同步去除的贡献为Al/P比SS浓度PAM投加量.在最优条件Al/P比为3、PAM浓度为1.22 mg·L~(-1)、SS浓度为3.58 g·~(L-1)的条件下,正磷和总有机碳去除率分别为93.1%和53.9%.与多响应变量优化相比,引入归一化评分法有效解决了变量间数值量级差异的问题,使结果的分析计算变得简单方便.