Modeling Flow,Nutrient, and Sediment Delivery from a Large International Watershed Using a Field‐Scale SWAT Model

A large international watershed, the St. Clair‐Detroit River System, containing both extensive urban and agricultural areas, was modeled using the Soil and Water Assessment Tool (SWAT) model. The watershed, located in southeastern Michigan, United States, and southwestern Ontario, Canada, encompasses the St. Clair, Clinton, Detroit (DT), Sydenham (SY), Upper, and Lower Thames subwatersheds. The SWAT input data and model resolution (i.e., hydrologic response units, HRUs), were established to mimic farm boundaries, the first time this has been done for a watershed of this size. The model was calibrated (2007–2015) and validated (2001–2006) with a mix of manual and automatic methods at six locations for flow and water quality at various time scales. The model was evaluated using Nash–Sutcliffe efficiency and percent bias and was used to explore major water quality issues. We showed the importance of allowing key parameters to vary among subwatersheds to improve goodness of fit, and the resulting parameters were consistent with subwatershed characteristics. Agricultural sources in the Thames and SY subwatersheds and point sources from DT subwatershed were major contributors of phosphorus. Spatial distribution of phosphorus yields at HRU and subbasin levels identified locations for potential management targeting for both point and nonpoint sources and revealed that in some subwatersheds nonpoint sources are dominated by urban sources.     

Modeling Hydrological and Environmental Consequences of Climate Change and Urbanization in the Boise River Watershed,Idaho

The potential impacts driven by climate variability and urbanization in the Boise River Watershed (BRW), located in southwestern Idaho, are evaluated. The outcomes from Global Circulation Models (GCMs) and land use and land cover (LULC) analysis have been incorporated into a hydrological and environmental modeling framework to characterize how climate variability and urbanization can affect the local hydrology and environment at the BRW. The combined impacts of future climate and LULC change are also evaluated relative to the historical baseline conditions. For modeling exercises, Hydrological Simulation Program‐Fortran (HSPF) is used in parallel computing and statistical techniques, including spatial downscaling and bias correlation, are employed to evaluate climate consequences derived from GCMs as well. The implications of climate variability and land use change driven by urbanization are then observed to evaluate how these overall global challenges can affect water quantity and quality conditions at the BRW. The results show the combined impacts of both climate change and urbanization can lead to more seasonal variability of streamflow (from ?27.5% to 12.5%) and water quality, including sediment (from ?36.5% to 49.3%), nitrogen (from ?24% to 124.2%), and phosphorus (from ?13.3% to 21.2%) during summer and early fall over the next several decades.     

Spatial assessment of groundwater quality in Guna Tana landscape

This study focuses on investigating the quality of groundwater for irrigation and drinking water purposes. Spatial distribution of physicochemical and microbiological parameters was assessed from samples collected from springs, hand‐dug wells, and boreholes found the Guna Tana landscape. A total of 70 samples were considered for physical, chemical, and bacteriological water quality determination. The results revealed that most of the groundwater quality index (WQI) values lie between good and excellent. The maximum, minimum, mean, and standard deviation of each water quality parameter were prepared for evaluating groundwater quality. According to the WQI values, more than 83% of the water samples were classified as excellent water for drinking. More than 92% of the water samples showed low sodium hazards for irrigation and about 48% and 46% of the water samples were classified as within the excellent and good water classes for irrigation based on their electrical conductance levels. Therefore, the groundwater that is found in the Guna Tana landscape could be used for drinking and irrigation purposes without any advanced treatment.     

2013年成都财富论坛期间空气质量状况分析研究

利用2013年5月20日-6月20日成都市区7个环境质量监测站点可吸入颗粒物(PM₁₀)、细颗粒物(PM_2.5)、SO₂、NO₂、CO和臭氧的实测资料及地面气象观测资料,对成都举办财富全球论坛期间及前后的空气质量变化特征和成因进行分析.结果表明,由于市政府采取交通管制措施,使机动车尾气排放的NO₂浓度与财富论坛前后相比降幅达27.2%;财富论坛期间臭氧前体物质浓度的降低,使地面臭氧日均浓度在相同太阳日辐射值下与财富论坛前后相比较低;对城区扬尘控制和周边重污染企业限产停产,分别对PM₁₀和SO₂的排放起到了明显的削减作用;后向轨迹分析表明市区SO₂浓度累积与来自东南部低空的气团有关.当相对湿度小于60%时颗粒物容易吸湿增长,而当相对湿度大于60%时降雨概率增大,颗粒物容易被清除.综合分析,成都市区财富论坛期间空气质量改善是政府减排举措的有效实施和较好的气象条件共同作用的结果.     

城市环境系统质量评价方法比较及实证研究

根据城市环境系统的内涵,从环境质量、资源利用、污染控制、生态建设四个方面构建了城市环境系统质量评价指标体系,并运用竞争性评价模型对十个沿海城市2012年的环境系统质量状况进行了综合评价和排序.为了判定竞争性评价模型的可靠性,采用传统的综合指数法进行验证性评价,结果表明:两种方法的评价结果具有较好的一致性,得分排在前6位的城市完全相同,其它城市的排序相差不大,因此,竞争性评价模型用于城市环境系统质量评价具有较好的可靠性.     

西安市大气环境质量评价及变化趋势预测

选用SO2、NO2、PM10作为评价因子,采用时间序列的方法对西安市2009年-2014年大气环境质量进行分析评价.结果表明:2009年-2012年西安市空气质量达到了国家二级标准,SO2和NO2的年平均含量下降,2013年都略有上升,但总体上呈下降趋势,而颗粒物的年平均含量呈上升趋势且为影响该市空气质量的主要污染物,主要污染时间为1季度和4季度;利用GM(1,1)模型,预测2015年空气质量变化趋势,提出2015年应该采取措施降低颗粒物的含量,提高本市空气质量.     

卫星遥感技术在空气点位布设评估工作中的应用研究

以苏州市为例,利用2013-2014年MODIS高分辨率大气气溶胶卫星遥感产品对国控空气监测点位布设调整方案进行评估论证,通过提取2 km和5km半径范围的PM2.5遥感观测数据,与现有国控布设点位的地面监测数据进行相关性分析后,确定卫星产品用于评估验证是可靠的;通过不同天气场下PM2.5月均值浓度分布的比较,表明调整后空气点位布设具有很好的代表性.     

白洋淀上游城市内河浮游动物群落调查与水质评价

对处于白洋淀上游的保定市城区府河设点调查监测,分析其浮游动物群落结构特征及变化规律。通过计算Shannon-Wiener多样性指数、Margalef指数和Pielou均匀度指数进行了府河水质评价。结果显示:监测期内在监测河段共检出浮游动物81个种属(原生动物未计入);优势种8种,且大多数为生活在中污性水体中的种类;ShannonWiener指数月平均值波动范围为1.38~2.64;Margalef指数月平均值波动范围为1.69~2.83;Pielou均匀度指数月平均值波动范围为0.47~0.58。依据生物多样性指数对监测河段进行水质评价结果表明其水体为中污染。     

聚类分析和标识指数法在苏州城区河道的应用

选取2013—2014年苏州市古城区河道8个监测断面的水质监测数据,应用层次聚类分析法和改进的综合水质标识指数法对苏州市古城区河道水质进行综合评价,并对各监测断面综合水质达标率进行计算。结果表明:苏州市古城区主河道水质在2013年5月份后明显好转,但小河道水质改善较小;在空间上呈现出城北河道水质较城南好,纵向河道水质比横向好的特点。根据评价结果与实际工程情况对比发现,层次聚类分析和水质标识指数法可以有效、准确地对城区河道水质进行总体评价。     

回归模型法推导油菜田土壤Cd限值的不确定性

为研究土壤-作物迁移模型推导农田土壤环境基准的不确定性,以油菜为例,通过贵州省4种典型微酸性土壤——红壤、黄壤、石灰土和黄棕壤进行Cd盐添加的盆栽试验,除全量Cd外,选择5种有效态提取剂,分别与油菜籽w(Cd)建立土壤-作物迁移模型. 参照GB 13078—2001《饲料卫生标准》w(Cd)限值(0.5 mg/kg),采用模型预测中位值和95%预测上限进行土壤Cd限值推导并分析模型的不确定性. 结果表明:全量和各提取态Cd质量分数与油菜籽w(Cd)均能建立极显著的一元(R2为0.907~0.946)或多元(考虑pH)回归模型(R2为0.875~0.962). 5.550(以多元模型中位值推导的农田安全种植油菜的Cd限值)随pH的升高从0.93 mg/kg增至1.45 mg/kg,HNO₃提取态、HCl提取态、DTPA提取态的Cd的质量分数也分别从0.81、0.97、0.73 mg/kg升至1.39、1.79、1.66 mg/kg. 基于CaCl₂提取态Cd的一元模型对pH不敏感,SEQS₅₀不受其影响. 对所有模型而言,SEQS₅₀是SEQS₉₅(基于模型95%的预测上限推导的限值)的1.1倍左右. 其中,CaCl₂提取态Cd的SEQS₅₀和SEQS₉₅分别为0.052和0.049 mg/kg,小于福建省CaCl₂提取态Cd标准限值(0.15 mg/kg). 为降低不确定性,需要选择合适的提取剂,使用全量Cd,HNO₃、HCl或DTPA 3种提取态Cd建模时须兼顾pH的影响. 研究显示,SEQS₉₅能够降低土壤Cd限值达标而作物Cd含量超标的可能性.