Spatiotemporal Variability of Snow Depletion Curves Derived from SNODAS for the Conterminous United States, 2004‐2013

Assessment of water resources at a national scale is critical for understanding their vulnerability to future change in policy and climate. Representation of the spatiotemporal variability in snowmelt processes in continental‐scale hydrologic models is critical for assessment of water resource response to continued climate change. Continental‐extent hydrologic models such as the U.S. Geological Survey National Hydrologic Model (NHM) represent snowmelt processes through the application of snow depletion curves (SDCs). SDCs relate normalized snow water equivalent (SWE) to normalized snow covered area (SCA) over a snowmelt season for a given modeling unit. SDCs were derived using output from the operational Snow Data Assimilation System (SNODAS) snow model as daily 1‐km gridded SWE over the conterminous United States. Daily SNODAS output were aggregated to a predefined watershed‐scale geospatial fabric and used to also calculate SCA from October 1, 2004 to September 30, 2013. The spatiotemporal variability in SNODAS output at the watershed scale was evaluated through the spatial distribution of the median and standard deviation for the time period. Representative SDCs for each watershed‐scale modeling unit over the conterminous United States (n = 54,104) were selected using a consistent methodology and used to create categories of snowmelt based on SDC shape. The relation of SDC categories to the topographic and climatic variables allow for national‐scale categorization of snowmelt processes.     

PREDICTING WILDERNESS SNOW WATER EQUIVALENT WITH NONWILDERNESS SNOW SENSORS1

ABSTRACT: Ten pairs of snow sensors were analyzed to investigate the feasibility of predicting snow water equivalent at high-elevation, telemetered snow sensor sites from lower-elevation sensors. The need for this analysis stems from an agreement between the California Department of Water Resources and the USDA Forest Service to temporarily allow snow sensors in California's wilderness areas so that a predictive relationship can be developed. After 10 or 15 years, the agreement calls for the sensors to be removed. Initial efforts to a priori select sensor pairs were based on proximity, colocation within a basin, and annual precipitation amount, but regression yielded poor fits (R² < 0.65) and high standard errors in eight of the ten cases. Analysis of the results suggested that eleva-tional similarity was the most important selection criteria, and that all available sensors near the target site should be analyzed via a regression screening. Using elevation for selection and the regression screening, five sensors that initially had poor fits were reanalyzed. Each of the five sensors was paired with between two and five new sensors, and R² values improved between 27 and 46 percent. Various data smoothing and editing algorithms were evaluated, but they rarely resulted in improved fits.     

Reducing non-point source pollution with enhancing infiltration

The rainfall system was set up on a slope land, which was used with some materials to enhance soil infiltration. The results showed that it was effective to enhance the infiltration of rainwater in soil and reduce the pollutants of surface runoff. After the soil meliorated by the lignin polymer and zeolite, runoff was delayed about 10 min and reduced by 44.40%--50.00%, synchronously, the pollutant loads, such as total suspended solids （TSS）, chemical oxygen demand by ditromate （CODCr）, total nitroger （TN） and total phosphorus （TP）, were reduced on averages by 44.58%, 37.80%, 51.62% and 44.11%, respectively. It is an available technique to control the pollution of non-point source from sources.     

Telemetric System for Hydrology and Water Quality Monitoring in Watersheds of Northern New Mexico, Usa

This study utilized telemetric systems to sample microbes and pathogens in forest, burned forest, rangeland, and urban watersheds to assess surface water quality in northern New Mexico. Four sites included remote mountainous watersheds, prairie rangelands, and a small urban area. The telemetric system was linked to dataloggers with automated event monitoring equipment to monitor discharge, turbidity, electrical conductivity, water temperature, and rainfall during base flow and storm events. Site data stored in dataloggers was uploaded to one of three types of telemetry: 1) radio in rangeland and urban settings; 2) a conventional phone/modem system with a modem positioned at the urban/forest interface; and 3) a satellite system used in a remote mountainous burned forest watershed. The major variables affecting selection of each system were site access, distance, technology, and cost. The systems were compared based on operation and cost. Utilization of telecommunications systems in this varied geographic area facilitated the gathering of hydrologic and water quality data on a timely basis.     

Role of Geographic Information System (GIS) in Watershed Simulation By Winvast Model

The uncertainty of modeling input will increase the simulation error, and this situation always happens in a model without user-friendly interface. WinVAST model, developed by the University of Virginia in 2003, treats an entire multi-catchment by a tree-view structure. Its extra computer programs can connect geographic information system (GIS). Model users can prepare all the necessary information in ArcGIS. Extracting information from GIS interface can not only decrease the inconvenience of data input, but also lower the uncertainty due to data preparation. The Daiyuku Creek and Qupoliao Creek in the Fei-tsui reservoir watershed in Northern Taiwan provided the setting for the case study reported herein. The required information, including slope, stream length, subbasin area, soil type and land-use condition, for WinVAST model should be prepared in a Microsoft Access database, which is the project file of WinVAST with extension mdb. In ArcGIS interface, when the soil layer, land-use layer, and Digital Elevation Model (DEM) map are prepared, all the watershed information can be created as well. This study compared the simulation results from automatically generated input and manual input. The results show that the relative simulation error resulting from the rough process of data input can be around 30% in runoff simulation, and even reach 70% in non-point source pollution (NPSP) simulation. It could conclude that GIS technology is significant for predicting watershed responses by WinVAST model, because it can efficiently reduce the uncertainty induced by input errors.     

Environmental and economic analysis of switchgrass production for water quality improvement in northeast Kansas

The primary objectives of this research were to determine SWAT model predicted reductions in four water quality indicators (sediment yield, surface runoff, nitrate nitrogen (NO(3)-N) in surface runoff, and edge-of-field erosion) associated with producing switchgrass (Panicum virgatum) on cropland in the Delaware basin in northeast Kansas, and evaluate switchgrass break-even prices. The magnitude of potential switchgrass water quality payments based on using switchgrass as an alternative energy source was also estimated. SWAT model simulations showed that between 527,000 and 1.27 million metric tons (Mg) of switchgrass could be produced annually across the basin depending upon nitrogen (N) fertilizer application levels (0-224 kg N ha(-1)). The predicted reductions in sediment yield, surface runoff, NO(3)-N in surface runoff, and edge-of-field erosion as a result of switchgrass plantings were 99, 55, 34, and 98%, respectively. The average annual cost per hectare for switchgrass ranged from about 190 US dollars with no N applied to around 345 US dollars at 224 kg N ha(-1) applied. Edge-of-field break-even price per Mg ranged from around 41 US dollars with no N applied to slightly less than 25 US dollars at 224 kg N ha(-1) applied. A majority of the switchgrass produced had an edge-of-field break-even price of 30 Mg(-1) US dollars or less. Savings of at least 50% in each of the four water quality indicators could be attained for an edge-of-field break-even price of 22-27.49 US dollars Mg(-1).     

城市雨水口地面暴雨径流浓度模型研究

在假设每一雨水口集水流域产生的地面暴雨径流均汇入该雨水口的条件下,通过研究雨水口入流污染物浓度随入流流量变化的规律,建立城市雨水口地面暴雨径流浓度模型,并采用2000年7￣9月间重庆市两个雨水口的测量数据,对模型的模拟精度进行验证。     

滇池东南岸农业和富磷区入湖河流地表径流及污染特征

应用聚类分析与因子分析方法,通过8次常规监测,对滇池东南岸10条以农业面源和受磷矿开采区影响的入湖河流的地表径流及其水质污染特征进行了分析,并探讨了其空间差异性。在南岸选取降雨过程相同的3条河流,开展暴雨径流监测,探讨污染物在降雨过程中的流失特征。结果表明,新宝象河的平均流量为2.6 m3/s,占总入湖流量的26.5%;总氮、总磷、化学需氧量、悬浮物是滇池的主要污染指标,许多河流均已严重超标。河流水质在空间上可分为3类,具有明显的空间差异性。总氮、总磷、溶解磷、硝态氮对水质污染的贡献率达到了53.636%,氮、磷含量是河流水质污染的主要贡献因子。降雨条件下化学需氧量、悬浮物浓度增长迅速,流量、悬浮物与大多数水质指标均有相关性,磷矿开采对河流水质的影响在降雨条件下更加明显,其悬浮物浓度在降雨条件下比只受农业面源影响的河流最高高出1.9倍。     

施工扬尘环境下短时强降雨屋面径流中砷、汞、铅、镉、锌的污染特征研究

以南京北郊为例,测量分析了屋面径流中砷(As)、汞(Hg)、铅(Pb)、镉(Cd)和锌(Zn)5种元素的浓度、形态特征。结果表明:短时强降雨过程中这5种元素浓度在较大范围内无规则波动,且不同元素间浓度分布存在较大差异;Zn与Pb的平均浓度分别高于《地表水环境质量标准》(GB 3838—2002)的Ⅴ类和Ⅳ类标准限值,污染程度从大到小依次为ZnPbAsHgCd。元素形态分析表明,径流中除Hg外其他4种元素主要以颗粒态形式存在,各元素颗粒态占总形态的平均分数分别为:As,64.5%;Hg,43.7%;Pb,76.5%;Cd,54.6%;Zn,54.3%。     

常见基质对暴雨径流中磷素去除效果的比较研究

选取沙子、土壤、沸石、白矾石、陶粒、钢渣、石灰石、蛭石和碎石9种常见的基质,通过吸附和解吸实验、静态吸附实验和动态模拟实验,较为系统地研究了这些基质的吸附特性以及去除暴雨径流中低浓度磷素污染物的特性,并分析了影响基质去除磷素的影响因子.结果表明,9种供试基质对磷酸盐的动态去除效率要比其他形态磷高,对磷素的平衡吸附量大小顺序为：沸石、土壤、蛭石 ＞陶粒、钢渣、石灰石 ＞碎石、沙子、白矾石,对磷素的动态吸附能力为：沸石、石灰石、白矾石、土壤＞钢渣、碎石、沙子＞陶粒、蛭石.另外,蛭石、陶粒和钢渣在对暴雨径流中磷素的静态和动态吸附过程中出现了磷释放现象,其它基质对磷酸盐的动态吸附能力较强,去除率介于30%～87%.综合分析以上多种因素,为了去除暴雨径流中的低浓度磷素,沸石、石灰石和土壤是比较理想的工程基质材料.