云南某冶炼废渣堆渗滤液产生及其影响因素研究

渗滤液作为渣堆对周边水土的主要污染源,是污染场地原位风险管控的关键对象。云南某历史遗留冶炼废渣堆出现了渗滤液产生量少、空间分布位置有限的特殊现象。为研究该冶炼废渣堆渗滤液产生的控制条件和影响因素,基于详细勘察和野外现场调查试验结果,构建了渣体包气带水文地质概念模型,并结合HYDRUS软件分析了不同条件下渣体包气带的水分变化。结果表明：该厚层渣体包气带水分运移深度有限,正常降雨条件下该渣体产生渗滤液的临界深度为8.8 m;暴雨条件下熔炼渣相较于石膏渣和生活垃圾更易产生渗滤液;渣体包气带越厚、初始体积含水率越低、渣体物质组成及其结构越复杂、覆土层越厚的条件下,渣体越难产生渗滤液。该研究结果对我国类似冶炼废渣堆原位风险管控处置具有重要的参考价值。     

Analyzing the Variability of Remote Sensing and Hydrologic Model Evapotranspiration Products in a Watershed in Michigan

The goal of this paper was to statistically explore the spatiotemporal performance of remotely sensed actual evapotranspiration (ETa) datasets and a remotely sensed ensemble in a region that lacks observed data. The remotely sensed datasets were further compared with ETa results from a physically based hydrologic model (Soil and Water Assessment Tool) to examine the differences and determine the level of agreement between the ETa datasets and the model outputs. ETa datasets were compared on temporal (i.e., monthly and seasonal basis) and spatial (i.e., landuse) scales at both watershed and subbasin levels. The results showed a lack of consistent similarities and differences among the datasets when evaluating the monthly ETa variations; however, the seasonal aggregated data presented more consistent similarities and differences during the spring and summer compared to the fall and winter. Meanwhile, spatial analysis of the datasets showed the MOD16A2 500 m ETa product was the most versatile of the tested datasets, being able to differentiate between landuses during all seasons. Furthermore, the use of an averaging ensemble was able to improve overall ETa performance in the study area. This study showed that the remotely sensed ETa products are not similar throughout the year, but the appropriate application periods for different ETa products were identified. Finally, spatial variabilities of the ETa products are more in tune with landuse and climate characteristics.     

Estimating Long-Term Ground Level Concentrations of SO2 from Short-Term Peak Data

Maximum concentrations of sulfur dioxide vary approximately inversely as the square root of the averaging time for periods up to a year, a much longer time period than those reported in previously published studies. This finding is based on analyses of SO₂ and tracer gas concentrations measured in the vicinities of a test stack, a petrochemical complex, and eight power plants. Therefore, for a given set of emission conditions, long-term concentrations of SO₂ and other conservative pollutants emitted by well-defined sources can be rapidly estimated from maximum short-term concentrations, and vice versa. The scatter in the data corresponds to an estimation error of about a factor of three for averaging time conversions of one day to one year. This is approximately the same error associated with conventional calculations. Therefore, the use of averaging time conversions is justified as a rapid screening technique to estimate compliance with ambient air quality standards.     

From Global to Local: Providing Actionable Flood Forecast Information in a Cloud‐Based Computing Environment

Global and continental scale flood forecast provide coarse resolution flood forecast, but from the perspective of emergency management, flood warnings should be detailed and specific to local conditions. The desired refinement can be provided by the use of downscaling global scale models and through the use of distributed hydrologic models to produce a high‐resolution flood forecast. Three major challenges associated with transforming global flood forecasting to a local scale are addressed in this work. The first is using open‐source software tools to provide access to multiple data sources and lowering the barriers for users in management agencies at local level. This can be done through the Tethys Platform that enables web water resources modeling applications. The second is finding a practical solution for the computational requirements associated with running complex models and performing multiple simulations. This is done using Tethys Cluster that manages distributed and cloud computing resources as a companion to the Tethys Platform for web app development. The third challenge is discovering ways to downscale the forecasts from the global extent to the local context. Three modeling strategies have been tested to address this, including downscaling of coarse resolution global runoff models to high‐resolution stream networks and routing with Routing Application for Parallel computatIon of Discharge (RAPID), the use of hierarchical Gridded Surface and Subsurface Hydrologic Analysis (GSSHA) distributed models, and pre‐computed distributed GSSHA models.     

AERCOARE: An overwater meteorological preprocessor for AERMOD

AERCOARE is a meteorological data preprocessor for the American Meteorological Society and U.S Environmental Protection Agency (EPA) Regulatory Model (AERMOD). AERCOARE includes algorithms developed during the Coupled-Ocean Atmosphere Response Experiment (COARE) to predict surface energy fluxes and stability from routine overwater measurements. The COARE algorithm is described and the implementation in AERCOARE is presented. Model performance for the combined AERCOARE-AERMOD modeling approach was evaluated against tracer measurements from four overwater field studies. Relatively better model performance was found when lateral turbulence measurements were available and when several key input variables to AERMOD were constrained. Namely, requiring the mixed layer height to be greater than 25 m and not allowing the Monin Obukhov length to be less than 5 m improved model performance in low wind speed stable conditions. Several options for low wind speed dispersion in AERMOD also affected the model performance results. Model performance for the combined AERCOARE-AERMOD modeling approach was found to be comparable to the current EPA regulatory Offshore Coastal Model (OCD) for the same tracer studies. AERCOARE-AERMOD predictions were also compared to simulations using the California Puff-Advection Model (CALPUFF) that also includes the COARE algorithm. Many model performance measures were found to be similar, but CALPUFF had significantly less scatter and better performance for one of the four field studies. For many offshore regulatory applications, the combined AERCOARE-AERMOD modeling approach was found to be a viable alternative to OCD the currently recommended model.

Implications: A new meteorological preprocessor called AERCOARE was developed for offshore source dispersion modeling using the U.S. Environmental Protection Agency (EPA) regulatory model AERMOD. The combined AERCOARE-AERMOD modeling approach allows stakeholders to use the same dispersion model for both offshore and onshore applications. This approach could replace current regulatory practices involving two completely different modeling systems. As improvements and features are added to the dispersion model component, AERMOD, such techniques can now also be applied to offshore air quality permitting.     

太湖叶绿素a浓度时空分异及其定量反演

利用2005年实测叶绿素a浓度数据分析了太湖叶绿素a浓度的时空分布特征,并利用同步光谱数据,分季节对太湖叶绿素a浓度的反演模型进行研究,从而分析叶绿素a的时空变化对反演模型的影响.首先分析1a内叶绿素a浓度随时间的变化规律,然后利用反距离加权插值法绘制叶绿素a浓度不同季节空间分布图,分析叶绿素a浓度在不同季节的空间分布规律,在此基础上分春、夏、秋3个季节和中营养化、轻度富营养化、中度富营养化、重度富营养化4个营养状态进行叶绿素a浓度定量反演模型研究.结果表明,太湖叶绿素a浓度具有明显的时空分布特征.夏季叶绿素a浓度最高,冬季最低,平均浓度分别为56.29μg/L、13.61 μg/L.秋季由于受到夏季高浓度的影响,叶绿素a浓度高于春季,平均值分别为26.43μg/L、34.78μg/L;夏季叶绿素a浓度空间变化最大,冬季全湖叶绿素a浓度含量较为均一,空间变化不明显,秋季空间差异要大于春季;全年北部湖区的空间差异较大,而南部湖区相对较小.不同季节叶绿素a反演算法模型不同,春、秋季波段比值法反演效果较好;而夏季微分法反演效果明显好于其它反演算法,不同营养状态条件下反演算法差异相对较小.     

巢湖水体散射和后向散射特性研究

湖泊水体散射特性的研究对湖泊水色要素遥感反演模型的发展具有重要的意义.本研究利用AC-S和ECO-BB9实测了巢湖水体的散射系数和后向散射系数,在分析光谱变化特性的基础上,构建了悬浮颗粒物散射系数和后向散射系数的幂函数光谱模型,获得的光谱指数分别为0.86和3.24.研究发现悬浮颗粒物散射系数与TSM和ISM都存在较好的线性函数关系,进而提出水体中总悬浮颗粒物的比散射系数为0.6364(10-3m2·mg-1),无机悬浮颗粒物的比散射系数为0.9108(10-3m2·mg-1).同时,分析了悬浮颗粒物后向散射率和折射指数的变化,其变化范围分别为0.003～0.026和1.02～1.06.     

利用海上测量光谱进行赤潮监测

利用太平洋东海岸加拿大温哥华海域56个观测站位现场实测的海洋表面光谱（400-800hm）反射率值和叶绿索、泥沙浓度资料，研究了赤潮发生时海面水体光谱反射率的变化趋势，以了解清洁水体与赤潮水体的不同特征。经过多组数据的比较分析，发现相对于清洁海水的海面光谱反射率，赤潮发生时海面光谱反射率曲线的荧光峰从685nm波长向710hm的红光波长位移；清洁海水海洋表面光谱反射率平均值在400-588nm之间比赤潮海水的平均反射率值大，在波长588nm处两值相交后，清洁海水的反射率值小于赤潮水体的反射率值，而在688nm处清洁海水和赤潮水体反射率值大小相等（大约为0．25），其后保持赤潮海水的反射率值在688—756nm之间一直高于清洁海水的平均反射率值。清洁海水和赤潮水体不同的荧光峰值以及不同的光谱反射率特征之间的差异，可以用于监测赤潮的最佳波段选择。