DEVELOPMENT OF LARGE SCALE GRIDDED RIVER NETWORKS FROM VECTOR STREAM DATA1

ABSTRACT: The Network Tracing Method (NTM) has been developed to determine gridded coarse river networks for modeling large hydrologic systems. For a coarse resolution grid, the NTM determines the downstream cell of each cell and the distance along the actual meandering flow paths between them. Unlike previously developed methods, the NTM uses fine resolution vector river networks as the source of information of the flow patterns rather than digital elevation models. The main advantage of using vector river networks as input is that they capture the hydrologic terrain features better than topographic data do, particularly in areas of low topographic relief. The NTM was applied to South America with a grid resolution of 1 degree by 1 degree and to the globe with a resolution of 2.815 degrees by 2.8125 degrees. Overall, the method captured the flow patterns well. Generated digital river networks and drainage divides showed minor disagreement with those obtained from existing maps, and most of them were consistent with the resolution of the coarse river network. The majority of estimated basin areas were also close to documented values. River lengths calculated with the NTM, however, were consistently underpredicted.     

城市土壤和地表灰尘重金属污染研究进展与展望

随着城市化和工业化的不断推进,城市土壤和地表灰尘重金属污染日趋严重,对城市环境和人类健康构成威胁,已成为国内外城市环境研究的热点问题.从重金属污染水平及其时空特征、污染源解析方法、生态和健康风险这3个主要方面,对国内外城市土壤和地表灰尘重金属研究成果进行了梳理和归纳.分析了当前研究存在的不足,并对未来研究进行了展望,即研究土壤和地表灰尘重金属在不同条件下的相互影响机制,通过丰富验证方法加强重金属来源解析模型结果的可靠性研究,加强来源驱动下重金属化学形态差异和地表灰尘短期累积污染过程的研究,完善暴露参数并深入探究重金属的化学形态对其生态和健康风险的影响,以提高风险预测水平.     

Adsorption of picloram on clays nontronite,illite and kaolinite: equilibrium and herbicide-clays surface complexes

The picloram (PCM) adsorption on nontronite, illite and kaolinite was studied at pH 3, 5 and 7. The adsorption isotherms had well-fitted to Langmuir and Freundlich models equations. The interactions of PCM with the clay mineral surfaces exhibited an anionic profile adsorption, with a decrease in adsorption when the pH increases. The PCM adsorption capacity increases in the following order: kaolinite?<?illite?<?nontronite. The X-ray diffraction (XRD) analysis of PCM-clay samples revealed that the picloram molecule does not enter into the clays basal space. The interaction of PCM with clays surface sites through nitrogen of the pyridine ring was confirmed by X-ray photoelectron spectroscopy (XPS). Due to the anionic form of PCM, the adsorption onto the external and edges surface sites of the clay minerals was proposed.     

大气磷干沉降采样方法对比分析

以四川农业大学成都校区为监测点,采用大气主动采样法(AA)、大气干表面法(ADS)及大气湿表面法(AWS)3种常用干沉降采集方法做大气磷干沉降通量对比试验。结果表明,3种采样方法获得的大气磷干沉降通量间具有显著的差异性及相关性(P0.05),三者间可以进行换算统一;AA法适用于较短采样周期的连续性监测研究,ADS法适用于较长采样周期(5 d)的监测研究,而AWS法更适用于在长采样周期(月)内选取一段时间作为干沉降监测的研究。     

基于健康风险的三氯杀螨醇生产设备表面污染物筛选值推算的初步研究

运用确定性和概率性人体健康风险评估的方法,推算一般工业暴露情景和拆卸清理暴露情景下三氯杀螨醇生产设备表面污染物的筛选值.结果表明:p,p'-滴滴涕、p,p'-滴滴滴和p,p'-滴滴依基于确定性风险评估的设备表面筛选值在一般工业暴露情景下分别为0.224 mg/m2、0.214 mg/m2和0.151 mg/m2,在拆卸...     

MnO_2陶粒臭氧氧化催化剂的制备及其性能

以凹凸棒土为载体、MnO_2为活性组分,制备了MnO_2陶粒臭氧氧化催化剂,并以草酸为模拟污染物,采用响应面法对催化剂的制备条件进行了优化。实验结果表明:各因素对草酸去除率影响的显著性顺序为MnO_2投加量盐酸溶液质量分数煅烧时间煅烧温度。催化剂的最佳制备条件为:MnO_2投加量200 mg/g,盐酸溶液质量分数20%,煅烧时间2 h,煅烧温度400℃。在初始草酸质量浓度150 mg/L、溶液pH 3.11、臭氧投加量8.10 mg/min、臭氧-氧气曝气量400 m L/min的条件下,最佳条件制备的催化剂在反应30 min时的草酸去除率达66.99%。催化剂具有良好的活性稳定性,且催化过程中Mn~(2+)溶出量低。催化剂具有较大的比表面积,负载的MnO_2类型为α-MnO_2和β-MnO_2。     

环境标准样品在国家地表水采测分离工作中的应用

按照《国家地表水环境质量监测网监测任务作业指导书(试行)》中实验室分析测试的质量保证和质量控制要求,结合江苏省南京环境监测中心的实际工作,综合分析2017年10月—2018年8月间国家地表水采测分离工作中环境标准样品在样品测试准确度验证、检测人员能力确认、检测设备期间核查及关键化学试剂检查等方面的应用情况。为保障环境监测结果量值溯源的统一性、准确性、一致性和可比性,提出丰富水环境标准样品的浓度水平、解决标准样品供需不平衡问题、改善消耗量大的标准样品操作方法、建立环境标准样品使用信息共享平台等实践建议,为合理提升环境标准样品应用效能、有效保证水环境监测数据质量提供参考。     

玻璃表面PAHs垂向分布特征与室内外对比研究

利用GC-MS对上海市玻璃表面有机膜中PAHs浓度进行了定量分析。结果表明随着楼层的增加,10层居民楼玻璃表面PAHs浓度出现先增加后减少的趋势,最高浓度出现在3层(736 ng/m~2),最低在9层(346 ng/m2);17层公寓楼PAHs浓度则是先减少后增加再减少的趋势,最高浓度出现在9层(2 338 ng/m~2),最低在16层(564 ng/m~2)。TOC与PAHs相关性分析暗示除TOC外,玻璃表面PAHs富集可能还受控于其他因素。10层居民楼主要以3环和4环PAHs为主;而17层公寓楼则以4环为主。玻璃外表面PAHs浓度(555 ng/m~2)远高于内表面(308 ng/m~2);外表面主要以Phe、Pyr、Chry、Fluo和Fl为主;内外表面低环PAHs比值接近于1,高环比值基本上低于0.6。TEQ值虽然较低,但生态风险仍不能忽视。     

The Watershed Flow and Allocation Model: An NHDPlus‐Based Watershed Modeling Approach for Multiple Scales and Conditions

The Watershed Flow and Allocation model (WaterFALL^®) provides segment‐specific, daily streamflow at both gaged and ungaged locations to generate the hydrologic foundation for a variety of water resources management applications. The model is designed to apply across the spatially explicit and enhanced National Hydrography Dataset (NHDPlus) stream and catchment network. To facilitate modeling at the NHDPlus catchment scale, we use an intermediate‐level rainfall‐runoff model rather than a complex process‐based model. The hydrologic model within WaterFALL simulates rainfall‐runoff processes for each catchment within a watershed and routes streamflow between catchments, while accounting for withdrawals, discharges, and onstream reservoirs within the network. The model is therefore distributed among each NHDPlus catchment within the larger selected watershed. Input parameters including climate, land use, soils, and water withdrawals and discharges are georeferenced to each catchment. The WaterFALL system includes a centralized database and server‐based environment for storing all model code, input parameters, and results in a single instance for all simulations allowing for rapid comparison between multiple scenarios. We demonstrate and validate WaterFALL within North Carolina at a variety of scales using observed streamflows to inform quantitative and qualitative measures, including hydrologic flow metrics relevant to the study of ecological flow management decisions.     

Modeling Summer Month Hydrological Drought Probabilities in the United States Using Antecedent Flow Conditions

Climate change raises concern that risks of hydrological drought may be increasing. We estimate hydrological drought probabilities for rivers and streams in the United States (U.S.) using maximum likelihood logistic regression (MLLR). Streamflow data from winter months are used to estimate the chance of hydrological drought during summer months. Daily streamflow data collected from 9,144 stream gages from January 1, 1884 through January 9, 2014 provide hydrological drought streamflow probabilities for July, August, and September as functions of streamflows during October, November, December, January, and February, estimating outcomes 5‐11 months ahead of their occurrence. Few drought prediction methods exploit temporal links among streamflows. We find MLLR modeling of drought streamflow probabilities exploits the explanatory power of temporally linked water flows. MLLR models with strong correct classification rates were produced for streams throughout the U.S. One ad hoc test of correct prediction rates of September 2013 hydrological droughts exceeded 90% correct classification. Some of the best‐performing models coincide with areas of high concern including the West, the Midwest, Texas, the Southeast, and the Mid‐Atlantic. Using hydrological drought MLLR probability estimates in a water management context can inform understanding of drought streamflow conditions, provide warning of future drought conditions, and aid water management decision making.