Application of Satellite Microwave Images in Estimating Snow Water Equivalent1

Abstract: Flood forecast and water resource management requires reliable estimates of snow pack properties [snow depth and snow water equivalent (SWE)]. This study focuses on application of satellite microwave images to estimate the spatial distribution of snow depth and SWE over the Great Lakes area. To estimate SWE, we have proposed the algorithm which uses microwave brightness temperatures (Tb) measured by the Special Sensor Microwave Imager (SSM/I) radiometer along with information on the Normalized Difference Vegetation Index (NDVI). The algorithm was developed and tested over 19 test sites characterized by different seasonal average snow depth and land cover type. Three spectral signatures derived from SSM/I data, namely T19V‐T37V (GTV), T19H‐T37H (GTH), and T22V‐T85V (SSI), were examined for correlation with the snow depth and SWE. To avoid melting snow conditions, we have used observations taken only during the period from December 1‐February 28. It was found that GTH, and GTV exhibit similar correlation with the snow depth/SWE and are most should be used over deep snowpack. In the same time, SSI is more sensitive to snow depth variations over a shallow snow pack. To account for the effect of dense forests on the scattering signal of snow we established the slope of the regression line between GTV and the snow depth as a function of NDVI. The accuracy of the new technique was evaluated through its comparison with ground‐based measurements and with results of SWE analysis prepared by the National Operational Hydrological Remote Sensing Center (NOHRSC) of the National Weather Service. The proposed algorithm was found to be superior to previously developed global microwave SWE retrieval techniques.     

Influences of air temperature change on leisure industries – case study on ski activities –

To evaluate the influences of air temperature change on ski activities, thechanges in the numbers of skiers visiting seven ski areas in Japan were predicted in conjunction with climate change. First, having built a model forpredicting snow depth based on the budgets of water and heat using the air temperature and precipitation data collected nationwide, we demonstrated goodagreement between the predicted and observed snow depths (p < 0.01 and the ratios for more than 81% cases ranged from 0.5 to 2). Second, the relationshipbetween the number of skiers and the depth of snow at one of the seven ski areaswas analyzed statistically on a daily basis. In addition, we did the same on amonthly basis at six other ski areas and compared the observed and predictednumbers of skiers (p < 0.01 and the ratios for more than 94% cases ranged from 0.5 to 2). Using this model and the relationship between daily snow depth andnumber of skiers, the changes in skier numbers in the seven ski areas werepredicted for several scenarios with respect to air temperature changes; e.g. a more than 30% drop in visiting skiers was forecast in almost all ski areas in Japan except northern region (Hokkaido) and/or high altitude regions (center of the Main Island) under the condition of a 3 ^°C increase in air temperature. The vulnerability of the ski industry and its adaptationto climate change are discussed.     

REGIONAL RUNOFF SIMULATION FOR SOUTHEAST MICHIGAN1

ABSTRACT: The feasibility of simulating monthly runoff for southeast Michigan, which comprises four major river basins, was evaluated with the Streamflow Synthesis and Reservoir Regulation watershed model. The evaluation covered a 13-year period (1961–73), which encompassed a complete runoff cycle. Results indicate it is feasible to simulate monthly runoff volumes on a regional scale with a single equivalent watershed by using daily precipitation and temperature data. Simulation of regional flows appears particularly attractive for the Great Lakes basin, since the basin consists of many relatively small watersheds. This method also appears promising for development of monthly runoff forecasts by employing average monthly meteorological data distributed on a daily basis. Tests of six-month runoff forecasts show relatively small deterioration with time and offer considerable improvement over climatology.     

南京市雪水中有机磷阻燃剂的污染特征及健康风险评价

采用超高效液相色谱-串联质谱仪（HPLC-MS/MS）分析了南京雪水中的13种有机磷酸酯阻燃剂（Organophosphate esters,OPEs）,研究了其浓度水平及污染特征,利用主成分分析阐述了OPEs可能的来源,并评估了其健康风险.结果表明,雪水中共检出11种OPEs,11种检出OPEs总浓度水平范围为229.1~1175.0ng/L,平均浓度为746.0ng/L,其中∑₁₁OPEs的最大值区域为商业区和住宅区密集的马群,最小值区域为城郊的化工园区.磷酸三（1,3-二氯-2-丙基）酯（Tris（1,3-dichloropropyl）phosphate,TDCPP）和磷酸三（2-丁氧基乙基）酯（Tris（2-butoxyethyl）phosphate,TBEP）是雪水中主要的OPEs污染单体,两者的贡献率分别为26.6%、20.4%.主成分分析表明雪水中TBEP与磷酸三（2-氯异丙基）酯（Tris（1-chloro-2-propyl）phosphate,TCPP）、磷酸三甲酯（TriMethyl Phosphate,TMP）与磷酸三乙酯（Triethyl phosphate,TEP）两两之间可能存在共同的来源,大气的远距离迁移和干湿沉降可能是雪水中附着OPEs的重要原因.不同人群通过饮水摄入11种OPEs的日均暴露量范围为26.6~39.0ng/（kg·d）,通过饮水摄入的OPEs的非致癌风险和致癌风险均低于理论风险值,研究区内雪水中OPEs所致人体健康风险处于较低水平.     

暴雨径流潜流过程及其对分层水库水质的影响

为探究汛期暴雨径流潜入演变过程及其对分层水库水质的影响,以西安金盆水库为研究对象,对2015年6月和2017年10月2次暴雨径流过程中各监测点水温、溶解氧、浊度、总氮、总磷和COD_Mn等水质指标进行持续监测.结果表明：径流量在300~400m³/s时,潜流经历全断面径流-底部潜流-中部潜流3个阶段,最终潜入主库区中部水体.暴雨径流的汇入使水库热分层结构稳定性受到一定破坏,中下部水体溶解氧得到补充.暴雨径流携带的大量泥沙及氮、磷营养盐等污染物质会对水库水质造成较大冲击,2015年6月暴雨径流使水库中层水体总氮、总磷、COD_Mn和浊度从1.60,0.021,3.70mg/L和5NTU增大为2.37,0.100,5.80mg/L和93NTU,水质污染特征为短时高污染负荷.     

北京城市主干道降雨径流污染负荷分析

为了解城市主干道径流污染特征,于2018年6—9月对北京城市主干道降雨径流进行取样监测,运用EXCEL和SPSS软件统计分析径流污染物TSS、EC、COD、TN、TP、Zn和Ni之间的污染特性,并在此基础上估算污染物年污染负荷.研究结果表明,北京城市主干道径流水质为劣Ⅴ类;污染物浓度与降雨量、平均降雨强度、降雨历时和雨前干期长度存在一定的相关关系,依据冲刷作用与稀释作用的强弱变化,相关性有一定变化;用TSS和EC表征污染物在径流中的存在状态,发现COD、TN、Zn和Ni在径流中主要以溶解态存在,TP主要以颗粒吸附的形式存在;据实际监测数据估算,北京城市主干道年污染负荷TSS、COD、TN、TP、Zn和Ni分别为3273.15、266.86、16.24、1.89、0.097和0.008 kg·hm~(-2)·a~(-1).城市主干道径流污染特征研究可以为城市道路径流污染防控与管理提供科学依据.     

哈尔滨市融雪径流中重金属污染空间分布及源解析

根据2018年哈尔滨市融雪径流中重金属(Fe、Pb、Cr、Cd、Hg和Zn)监测数据,结合气象数据,运用暴雨洪水管理模型(SWMM)构建了城市融雪过程水文及水质模型.对各排水口及汇水区融雪径流产出量、单位面积重金属负荷量进行了计算,并在此基础上分析了融雪径流中重金属污染的空间分布特征及主要来源.结果表明:在采集的融雪径流样品中,Fe浓度最大,平均值为4.95 mg·L~(-1);Hg浓度最小,平均值为0.542μg·L~(-1);Pb浓度变化范围最大,在32.14～254.36μg·L~(-1)之间;Hg浓度变化范围最小,为0.038～0.841μg·L~(-1).在空间分布上, Fe、Pb、Cr、Cd和Zn 5种重金属浓度的高值区均分布在人口密集的居民区、商业区及主要交通道路周围.排水口重金属污染产出量与径流量成正比,总产出量FePbCrCdHgZn. Zn产出量由高到低的排放口依次为马家沟、阿什河、松北区排放口、何家沟、道里区排放口和道外区排放口,其它5种重金属产污量总体呈现阿什河马家沟何家沟松北区排放口道里区排放口道外区排放口的趋势.Fe的单位面积负荷总量最大,为2405.94μg·m~(-2);Pb和Cr次之,为36.36μg·m~(-2)和14μg·m~(-2).主成分分析结果表明哈尔滨市春季融雪径流中重金属的主要来源依次为工业源、生活与机动车源和燃煤源,贡献率分别为43.237%、23.598%和12.012%.     

水源水库暴雨径流过程水体锰的迁移及其影响

针对西安金盆水库2017年汛期出现的锰浓度超标问题,对水库上游至主库区沿程多个监测点垂向锰浓度及其赋存形态进行监测,研究暴雨径流对水中锰含量的影响以及径流中锰的形态,估算单次典型暴雨径流过程水库水体锰的汇入、输出与沉积量,根据实测数据与计算结果,从运行调度角度提出了暴雨时期高浊、高负荷径流入库的规避方案.结果表明,强降雨过程引起的高浊径流汇入显著增加了西安金盆水库水体总锰浓度,导致水库水质严重恶化,2017年10月12日至2017年10月14日单次降雨径流总锰的输入负荷为9. 11 t,泄洪和出水输出的总锰为6. 22 t,净沉积量(锰)为1. 47 t.水库上游沿程水体锰含量及形态变化表明,连续降雨过程对土壤的冲刷和侵蚀作用导致大量颗粒态污染物随径流汇入水体,占水体中总锰的质量分数大于70%,铁锰氧化物结合态为其主要形态.通过与不同粒径范围的颗粒进行相关性分析,颗粒态锰粒径约为2～20μm.暴雨径流入库时期采取泄洪排浊的措施可以有效减小锰的污染负荷,降低供水安全风险.     

高塔熔体造粒生产硝基复合肥工艺危险性分析

针对多起硝酸铵燃爆事故进行了调研,在此基础上对高塔熔体造粒生产硝基复合肥工艺的危险因素进行了分析,并且对此工艺涉及的物料进行了热危险性实验研究;根据调研、分析、研究的结果,提出了保障高塔熔体造粒生产硝基复合肥工艺安全生产的改造建议和生产控制参数。     

降雨时间分辨率对SWAT水文模拟的影响

分别基于13个雨量站的日降雨量和小时降雨量,在率水流域建立SWAT（Soil and Water Assessment Tool）水文模型,对基于不同降雨时间分辨率的SWAT模型进行独立的参数率定和验证,在此基础上分析降雨时间分辨率对率水流域SWAT模拟性能的影响.结果表明,降雨输入的时间分辨率对率水流域SWAT模型的水文模拟性能有显著影响.小时降雨输入SWAT模型的纳什系数（NSE）和决定系数（R²）在率定期分别为0.89、0.90,在验证期分别为0.86、0.88,均显著高于日降雨输入SWAT模型对应的模型评价统计量值.究其原因,小时降雨输入SWAT模型对于峰值流量的模拟要明显优于日降雨输入SWAT模型.建议应在不同气候与自然环境条件的流域内开展类似的降雨时间分辨率对水文模型模拟性能的影响研究.