北京市开展区域水环境合作探究

通过分析北京市地表水资源、水环境质量现状及存在的问题,得出生态环境用水严重短缺是制约北京市水环境质量全面改善的根本原因,并对此提出全面加强区域水环境合作、改善北京市水环境的基本思路,及与周边地区开展水环境合作的途径及建议。     

河北省地表水环境污染特征及分析

河北省1998年-2005年的水环境质量监测数据分析表明：河北省地表水污染恶化趋势基本得到遏制,但部分地区水污染矛盾仍很突出;水体总体污染减轻,但氨氮污染有加重趋势;主要湖（库）水水质稳定,但普遍呈不同程度的富营养化。在此基础上,分析了地表水污染的原因,并提出了河北省改善地表水环境污染的对策与措施。     

Sensitivity and Uncertainty of Ground‐Water Discharge Estimates for Semiarid Shrublands1

Abstract: We proposed a step‐by‐step approach to quantify the sensitivity of ground‐water discharge by evapotranspiration (ET) to three categories of independent input variables. To illustrate the approach, we adopt a basic ground‐water discharge estimation model, in which the volume of ground water lost to ET was computed as the product of the ground‐water discharge rate and the associated area. The ground‐water discharge rate was assumed to equal the ET rate minus local precipitation. The objective of this study is to outline a step‐by‐step procedure to quantify the contributions from individual independent variable uncertainties to the uncertainty of total ground‐water discharge estimates; the independent variables include ET rates of individual ET units, areas associated with the ET units, and precipitation in each subbasin. The specific goal is to guide future characterization efforts by better targeting data collection for those variables most responsible for uncertainty in ground‐water discharge estimates. The influential independent variables to be included in the sensitivity analysis are first selected based on the physical characteristics and model structure. Both regression coefficients and standardized regression coefficients for the selected independent variables are calculated using the results from sampling‐based Monte Carlo simulations. Results illustrate that, while as many as 630 independent variables potentially contribute to the calculation of the total annual ground‐water discharge for the case study area, a selection of seven independent variables could be used to develop an accurate regression model, accounting for more than 96% of the total variance in ground‐water discharge. Results indicate that the variability of ET rate for moderately dense desert shrubland contributes to about 75% of the variance in the total ground‐water discharge estimates. These results point to a need to better quantify ET rates for moderately dense shrubland to reduce overall uncertainty in estimates of ground‐water discharge. While the approach proposed here uses a basic ground‐water discharge model taken from an earlier study, the procedure of quantifying uncertainty and sensitivity can be generalized to handle other types of environmental models involving large numbers of independent variables.     

Modeling the Hydrology of Climate Change in California’s Sierra Nevada for Subwatershed Scale Adaptation1

Young, Charles A., Marisa I. Escobar‐Arias, Martha Fernandes, Brian Joyce, Michael Kiparsky, Jeffrey F. Mount, Vishal K. Mehta, David Purkey, Joshua H. Viers, and David Yates, 2009. Modeling the Hydrology of Climate Change in California’s Sierra Nevada for Subwatershed Scale Adaptation. Journal of the American Water Resources Association (JAWRA) 45(6):1409‐1423. Abstract: The rainfall‐runoff model presented in this study represents the hydrology of 15 major watersheds of the Sierra Nevada in California as the backbone of a planning tool for water resources analysis including climate change studies. Our model implementation documents potential changes in hydrologic metrics such as snowpack and the initiation of snowmelt at a finer resolution than previous studies, in accordance with the needs of watershed‐level planning decisions. Calibration was performed with a sequence of steps focusing sequentially on parameters of land cover, snow accumulation and melt, and water capacity and hydraulic conductivity of soil horizons. An assessment of the calibrated streamflows using goodness of fit statistics indicate that the model robustly represents major features of weekly average flows of the historical 1980‐2001 time series. Runs of the model for climate warming scenarios with fixed increases of 2°C, 4°C, and 6°C for the spatial domain were used to analyze changes in snow accumulation and runoff timing. The results indicated a reduction in snowmelt volume that was largest in the 1,750‐2,750 m elevation range. In addition, the runoff center of mass shifted to earlier dates and this shift was non‐uniformly distributed throughout the Sierra Nevada. Because the hydrologic model presented here is nested within a water resources planning system, future research can focus on the management and adaptation of the water resources system in the context of climate change.     

MODIS Biophysical States and NEXRAD Precipitation in a Statistical Evaluation of Antecedent Moisture Condition and Streamflow1

Abstract: The potential of remotely sensed time series of biophysical states of landscape to characterize soil moisture condition antecedent to radar estimates of precipitation is assessed in a statistical prediction model of streamflow in a 1,420 km² watershed in south‐central Texas, Moderate Resolution Imaging Spectroradiometer (MODIS) time series biophysical products offer significant opportunities to characterize and quantify hydrologic state variables such as land surface temperature (LST) and vegetation state and status. Together with Next Generation Weather Radar (NEXRAD) precipitation estimates for the period 2002 through 2005, 16 raw and deseasoned time series of LST (day and night), vegetation indices, infrared reflectances, and water stress indices were linearly regressed against observed watershed streamflow on an eight‐day aggregated time period. Time offsets of 0 (synchronous with streamflow event), 8, and 16 days (leading streamflow event) were assessed for each of the 16 parameters to evaluate antecedent effects. The model results indicated a reasonable correlation (r² = 0.67) when precipitation, daytime LST advanced 16 days, and a deseasoned moisture stress index were regressed against log‐transformed streamflow. The estimation model was applied to a validation period from January 2006 through March 2007, a period of 12 months of regional drought and base‐flow conditions followed by three months of above normal rainfall and a flood event. The model resulted in a Nash‐Sutcliffe estimation efficiency (E) of 0.45 for flow series (in log‐space) for the full 15‐month period, ?0.03 for the 2006 drought condition period, and 0.87 for the 2007 wet condition period. The overall model had a relative volume error of ?32%. The contribution of parameter uncertainties to model discrepancy was evaluated.     

Social Acceptability of Water Resource Management: A Conceptual Approach and Empirical Findings from Portland,Oregon1

Abstract: Surface water resources in urban areas serve multiple functions ranging from recreation to wildlife habitat. As a result, diverse values influence people’s views about resource protection, potentially leading to conflicting interests. In metropolitan Portland, Oregon, natural resource planning has recently focused on habitat restoration as well as stormwater and pollution mitigation, especially through the protection of riparian areas. Due to opposition over proposed regulations in the study region, this research examines public attitudes about an array of resource management efforts. The primary research question is: what is the extent of positive–negative attitudes about water resource protection, and what theoretical dimensions underlie diverse judgments? After empirical survey results are presented, I outline a conceptual approach for future assessments of environmental attitudes while highlighting important value‐based dimensions of judgments. Although flexible, the framework allows broad comparisons to advance knowledge about the social acceptability of varied water resource management approaches across diverse places and contexts.     

人工神经网络方法在拟建小区域环境质量评价中的应用

人工神经网络的评价方法用于小区域环境质量评价中,根据本地区特点因地制宜地选择环境质量参数,代入模型中进行环境质量评价及预测,对用于环境质量评价的BP人工神经网络模型进行了改进,即对网络模型的训练样本进行了扩充,从而提高了模型的抗干扰能力和准确性.将改进了的BP人工神经网络模型应用于四川省资阳市沱江二桥拟建项目小区域的大气、地表水环境质量评价中, 对该市小区域大气、地表水环境质量状况进行评价,评价结果表明,BP人工神经网络模型用于环境质量评价是可行的,且评价结论客观,评价模型普遍适用.     

江河水源地突发性水污染事故风险评价

近年来,我国江河饮用水水源地突发性水质污染事故频发,成为我国面临的最严重的环境问题之一.江河水源地突发性水质污染事件的风险评价是确保饮用水源地水质安全的重要手段,对突发性水质污染事故,采取适当的应急处理措施.     

信息可视化在化工企业水环境安全影响评价中的研究及应用

运用data system.exe技术,对水环境评价系统功能模块进行设计;提出水环境影响评价信息可视化软件的设计方法;建立水环境污染因子数据信息可视化软件,并应用该软件对石油化工企业的水环境进行了初步的风险评价。结果表明:该软件能在识别污染因子数据信息的同时生成与之相匹配的直观的模拟环境图像,有助于管理者进行及时分析与决策;通过输入水环境污染因子监测值后,系统可以自动判定环境的污染的程度,并把对应环境质量的级别、环境的安全程度以及污染对人体与生物的影响程度在图中显示出来,能够有效地提高环境影响评价的可靠度;评价示意图中的评价因子可以根据需要进行增加或更换,有助于该系统的推广应用,建立的环境污染因子数据信息可视化模型具有很强的适用性。