Heterogeneity of Hydrologic Response in Urban Watersheds1

Meierdiercks, Katherine L., James A. Smith, Mary Lynn Baeck, and Andrew J. Miller, 2010. Heterogeneity of Hydrologic Response in Urban Watersheds. Journal of the American Water Resources Association (JAWRA) 46(6):1221–1237. DOI: 10.1111/j.1752-1688.2010.00487.x Abstract: The changing patterns of streamflow associated with urbanization are examined through analyses of discharge and rainfall records for the study watersheds of the Baltimore Ecosystem Study (BES). Analyses utilize a decade (1999-2008) of observations from a dense U.S. Geological Survey stream gaging network and Hydro-NEXRAD radar rainfall fields. The principal study watershed of the BES is Gwynns Falls (171 km²). Focus is given to two Gwynns Falls basins with contrasting patterns and histories of development, Dead Run and Upper Gwynns Falls. The sharp contrasts in streamflow properties between the basins reflect the differences in urban development prior to implementation of stormwater management regulations (much of Dead Run) and development for which stormwater management is an integral part of the hydrologic system (Upper Gwynns Falls). The mean annual runoff in Dead Run (558 mm) is 35% larger than that of Upper Gwynns Falls; larger contrasts in runoff properties typify the “warm season” and are linked to storm event hydrologic response. Spatial heterogeneities in storm event response are reflected in seasonal and diurnal properties of streamflow. Analyses of storm event response are presented for June 2006, during which monthly rainfall over the BES region ranged from less than 150 to more than 500 mm. Baisman Run, the BES forest reference watershed, and Moores Run, a highly urbanized watershed in Baltimore City, provide “end-member” representations of urban impacts on streamflow.     

基于FY2C卫星数据的藏北高原降水估算研究

如何确切的掌握降水的时空分布,对区域气候、水文和生态应用等至关重要。以藏北高原典型区为研究区,在大量地面实况降水观测数据与对长时间序列FY 2C 影像光谱特征和云图特征分析的基础上,获取卫星降水模拟参数特征集以刻画云降水的发生与发展过程,选用最值归一化方法对不同量纲云图特征参数进行归一化处理。构建基于三层前向型反向传播神经网络的卫星降水估算模型,用于该地域降水估算,并采用多指标体系分析模型的降水模拟精度。结果表明：静止气象卫星红外波段能较精确地揭示云的降水机理,较高时间分辨率遥感图像可以监测云图的变化细节,并获取能够反映云图降水特征的降水模拟参数;人工神经网络能较好地刻画该地域卫星降水特征的非线性规律;三层前向型反向传播神经网络卫星降水估算模型的估算结果与雨量计实测值间的相关性可以达到0.57。模型估算结果系统性的低估偏小,预示着对该地域弱降水强度将有较好的指示性     

上海城市河岸带对降雨径流氮垂直去除研究

在上海市城市河岸带人工绿地建设了微区径流场,进行了5次模拟降雨径流实验,研究了人工绿地岸带下渗流中氮浓度和去除率的时空变化。结果表明：人工绿地岸带对垂直下渗流中氮有显著的净化作用,且主要集中于土壤的0~30 cm以内,TN和NH4+去除率在399%和398%以上,NO3-+NO2-去除率除11月为负值外,其余月份均在100%以上;在30~60 cm深度,由于土壤氮的析出导致径流中氮浓度增加,去除率降低;而60~90 cm深度的去除率增加。径流场内下渗流中氮浓度具有明显的水平空间变化,随距入水端距离的增加,30 cm深度下渗流中氮浓度先上升后下降;人工绿地岸带对下渗流中氮的净化作用均随淹水时间的延长呈降低趋势,且季节变化明显,在10月和4月具有较高的去除率,0~30 cm内TN、NH4+和NO3-+NO2-的去除率可分别达635%、891%和416%以上     

三种常用氨基甲酸酯类农药人工抗原合成方法的设计与优选

农药人工抗原的合成直接影响制备抗体的质量,是建立农药分子特异性强、灵敏度高的免疫分析方法的关键。本文综述了国内外对于氨基甲酸酯类广泛使用的3种农药甲萘威、克百威、涕灭威人工抗原合成过程中的农药分子半抗原的设计原则、合成方法,人工抗原的设计、优选及影响因素等方面的研究进展。     

人工增雨指挥系统构建与研究

为增加有效降水,降低干旱和雾霾等环境污染的影响,保护生态环境安全,研制了以提高开发空中水资源能力为主要目的、基于GIS技术的人工增雨作业决策指挥系统,依托新一代多普勒天气雷达、Micaps数据资料和自动站数据库,应用Microsoft C#语言开发了增雨作业预警和指挥功能、指挥信息和作业信息收集互传功能、增雨效果评估功能、常规业务管理功能,构建了功能较为完善的业务系统。     

秦皇岛地区干旱趋势分析及人工增雨条件

通过分析秦皇岛地区水资源及人均占有率、气候干旱化之现状及秦皇岛地区降水的特点,发现秦皇岛降水有明显日变化特征（凌晨1～2时和傍晚17～18时降水量较大）。从化学制剂的选择、碘化银成核环境确定、积云增雨的高度判断三个方面提出了人工增雨作业条件,在作业实践中取得了良好效果。     

Estimation of Evapotranspiration Across the Conterminous United States Using a Regression With Climate and Land‐Cover Data1

Sanford, Ward E. and David L. Selnick, 2012. Estimation of Evapotranspiration Across the Conterminous United States Using a Regression with Climate and Land‐Cover Data. Journal of the American Water Resources Association (JAWRA) 1‐14. DOI: 10.1111/jawr.12010 Abstract: Evapotranspiration (ET) is an important quantity for water resource managers to know because it often represents the largest sink for precipitation (P) arriving at the land surface. In order to estimate actual ET across the conterminous United States (U.S.) in this study, a water‐balance method was combined with a climate and land‐cover regression equation. Precipitation and streamflow records were compiled for 838 watersheds for 1971‐2000 across the U.S. to obtain long‐term estimates of actual ET. A regression equation was developed that related the ratio ET/P to climate and land‐cover variables within those watersheds. Precipitation and temperatures were used from the PRISM climate dataset, and land‐cover data were used from the USGS National Land Cover Dataset. Results indicate that ET can be predicted relatively well at a watershed or county scale with readily available climate variables alone, and that land‐cover data can also improve those predictions. Using the climate and land‐cover data at an 800‐m scale and then averaging to the county scale, maps were produced showing estimates of ET and ET/P for the entire conterminous U.S. Using the regression equation, such maps could also be made for more detailed state coverages, or for other areas of the world where climate and land‐cover data are plentiful.     

Assessing Linkages in Stream Habitat,Geomorphic Condition,and Biological Integrity Using a Generalized Regression Neural Network

Watershed managers often use physical geomorphic and habitat assessments in making decisions about the biological integrity of a stream, and to reduce the cost and time for identifying stream stressors and developing mitigation strategies. Such analysis is difficult since the complex linkages between reach‐scale geomorphic and habitat conditions, and biological integrity are not fully understood. We evaluate the effectiveness of a generalized regression neural network (GRNN) to predict biological integrity using physical (i.e., geomorphic and habitat) stream‐reach assessment data. The method is first tested using geomorphic assessments to predict habitat condition for 1,292 stream reaches from the Vermont Agency of Natural Resources. The GRNN methodology outperforms linear regression (69% vs. 40% classified correctly) and improves slightly (70% correct) with additional data on channel evolution. Analysis of a subset of the reaches where physical assessments are used to predict biological integrity shows no significant linear correlation, however the GRNN predicted 48% of the fish health data and 23% of macroinvertebrate health. Although the GRNN is superior to linear regression, these results show linking physical and biological health remains challenging. Reasons for lack of agreement, including spatial and temporal scale differences, are discussed. We show the GRNN to be a data‐driven tool that can assist watershed managers with large quantities of complex, nonlinear data.     

人工冻结法调控多年冻土区桩基础地温场的效果分析*

为了解决青藏铁路运营过程中,由于多年冻土地基的升温退化,部分多年冻土区桥梁桩基础承载性能下降,产生有害沉降变形,进而造成桥梁上部结构移位破坏,甚至部分桥梁桩基础在短时间内产生较大的沉降变形这一严重问题。基于当前多年冻土区桥梁桩基础沉降病害快速抢修技术空缺,提出人工冻结技术处置多年冻土区桥梁桩基础沉降病害的新设想,利用数值软件建立冻结管-桩基础三维模型分析该技术的可行性与调控效果,分析冻结参数、场地冻土条件等对冻结效果的影响。研究结果表明:人工冻结法可以快速降低桩周多年冻土温度;同时,冻结96 h可以对桩基地温场起到较好的冷却效果;冻结管至桩的距离对冻结效果的影响最为显著,冻土的含冰量越大,则降温速率越慢。     

A Framework to Develop Nationwide Flooding Extents Using Climate Models and Assess Forecast Potential for Flood Resilience

The methods used to simulate flood inundation extents can be significantly improved by high‐resolution spatial data captured over a large area. This paper presents a hydraulic analysis methodology and framework to estimate national‐level floodplain changes likely to be generated by climate change. The hydraulic analysis was performed using existing published Federal Emergency Management Agency 100‐year floodplains and estimated 100‐ and 10‐year return period peak flow discharges. The discharges were estimated using climate variables from global climate models for two future growth scenarios: Representative Concentration Pathways 2.6 and 8.5. River channel dimensions were developed based on existing regional United States Geological Survey publications relating bankfull discharges with channel characteristics. Mathematic relationships for channel bankfull topwidth, depth, and side slope to contributing drainage area measured at model cross sections were developed. The proposed framework can be utilized at a national level to identify critical areas for flood risk assessment. Existing hydraulic models at these “hot spots” could be repurposed for near–real‐time flood forecasting operations. Revitalizing these models for use in simulating flood scenarios in near–real time through the use of meteorological forecasts could provide useful information for first responders of flood emergencies.