油田作业废水处理技术研究进展

文章讨论了作业废水的组成与特点,并对近年来钻井废水处理工艺,酸化废水处理工艺,压裂废水处理工艺进行了总结与评述。根据作业废水的处理现状,对未来作业废水的处理技术进行了展望。油田废水处理主要向以下三个方面发展:开发新型处理药剂;建立高效处理工艺流程;从污水源头开始控制。     

微电解-Fenton联合工艺预处理煤层气井压裂废水

利用Fenton强化微电解工艺对煤层气井压裂废水展开预处理研究,以COD去除率和可生化性(B/C)为考察指标,单独工艺正交实验结果表明pH为3、反应时间为90 min、铁碳体积比为1.5∶1和pH为4、反应时间为80 min、H2O2投加量为4 mL/L分别是微电解与Fenton反应的最优条件,各可获得48.1%和44.9%的COD去除率。在最优条件下进行微电解-Fenton联合运行实验,连续61 h内COD去除率均稳定在65%以上,B/C由0.158上升到0.3以上,有利于后续生化处理的运行。     

新型结构ABR的设计与水力特性研究

针对ABR自身的缺点,设计出一种新型结构的ABR.该反应器为双层结构,共有5部分组成,各部分容积各不相同.该反应器的设计思想是将ABR与生物滤池以及活性炭吸附等工艺相联合.这种设计能够最大程度地发挥各工艺的优势,进而达到更好的处理效果.通过脉冲响应实验对该反应器的水力特性进行研究,得出不同水力停留时间(HRT)下的停留...     

水力条件对复合人工湿地处理城市受污染河水效果的影响

通过对水力负荷、水力停留时间等水力条件的控制,观察其对复合垂直上行流人工湿地处理城市受污染河水效果的影响.一年多来的运行结果表明:水力条件对复合垂直上行流人工湿地去除其他污染物的影响显著,但对总氮去除的影响不大.水力停留时间的延长可提高总磷、氨氮、COD的去除效果;随着水力负荷的增加,总磷、氨氮、COD去除率都有所增加...     

垂直流人工湿地水力学特性研究

通过示踪剂实验从停留时间分布（RTD）曲线及其统计特征值等方面对垂直流人工湿地的水力学特性进行了定性和定量的分析。研究表明水流在垂直流人工湿地中的流动是一种非理想的不均匀流动,存在一定的死区和水流的扩散;垂直流人工湿地较大的死区率与其表面布水的不均匀性有关,这也可能是其死区率大于表流人工湿地的最主要的原因。实验还表明,进水流量对垂直流人工湿地停留时间分布影响较大,随着进水流量的增加,平均停留时间减小,但标准平均停留时间增大,死区率减小;当进水流量为15L／h（水力负荷为620mm／d）时,水流在湿地中的散度最大,水流更接近全混流,不利于污染物的降解。     

Probabilistic Flood Inundation Forecasting Using Rating Curve Libraries

One approach for performing uncertainty assessment in flood inundation modeling is to use an ensemble of models with different conceptualizations, parameters, and initial and boundary conditions that capture the factors contributing to uncertainty. However, the high computational expense of many hydraulic models renders their use impractical for ensemble forecasting. To address this challenge, we developed a rating curve library method for flood inundation forecasting. This method involves pre‐running a hydraulic model using multiple inflows and extracting rating curves, which prescribe a relation between streamflow and stage at various cross sections along a river reach. For a given streamflow, flood stage at each cross section is interpolated from the pre‐computed rating curve library to delineate flood inundation depths and extents at a lower computational cost. In this article, we describe the workflow for our rating curve library method and the Rating Curve based Automatic Flood Forecasting (RCAFF) software that automates this workflow. We also investigate the feasibility of using this method to transform ensemble streamflow forecasts into local, probabilistic flood inundation delineations for the Onion and Shoal Creeks in Austin, Texas. While our results show water surface elevations from RCAFF are comparable to those from the hydraulic models, the ensemble streamflow forecasts used as inputs to RCAFF are the largest source of uncertainty in predicting observed floods.     

Framing Dynamics and Political Gridlock: The Curious Case of Hydraulic Fracturing in New York

‘Fracking’ was on New York's agenda since 2008, yet no decision was made about it until late 2014. The gridlock is an intriguing puzzle given that the Marcellus shale is considered a ‘world class’ energy supply, and development has been aggressive in other US states. While policy scholars typically conceptualize gridlock as policy stability, this paper examines it as a dynamic process by which competing discourse coalitions engage in interactive framing processes that (re)structure the discussion. This suggests that the interaction between contending coalitions influences gridlock. Yet, we lack knowledge about interactive framing between competing coalitions during policy controversies. Our main finding is that a central mechanism of gridlock is the production of conflict through interactive framing dynamics that deny a shared discursive space capable of ushering in a consensus, or reasoned agreement. In New York, this contest evolved from a policy consensus about the economic benefits of fracking to policy negotiation that incorporated environmental threats, and to prolonged policy controversy in which competing discourse coalitions contested notions of fracking in relation to energy production, environmental protection, public health, economic development, and governance. While a ban has been instituted, the failure to bridge discourse coalitions suggests that controversy will persist unless meaning disputes are resolved.     

基于震后低压变化的供水管网功能可靠度分析

供水管网的抗震功能是指供水管网在地震作用下能够满足震后城市特定用水需要(需水量和水压)的能力。地震发生后,供水管网一般处于低压供水状态,使得管网中部分用户的水压和水量不能得到全部满足,导致管网部分节点的实际配水量小于需水量。为此,在传统的管网水力分析基础上考虑节点流量随节点水压的动态变化,通过求解非线性水力方程组,得到管网节点实际流量和水压;同时,借鉴结构可靠度分析方法,引入供水管网系统随机水力模型,给出了震后供水管网功能可靠度分析的一次二阶矩方法。以一实际管网为例,演示了震后低压供水时管网功能可靠度分析的应用方法。     

Monte Carlo analysis of field water flow comparing uni- and bimodal effective hydraulic parameters for structured soil

Soil structure critically affects the hydrological behaviour of soils. In this paper, we examined the impact of areal heterogeneity of hydraulic properties of a structured soil on soil ensemble behaviour for various soil water flow processes with different top boundary conditions (redistribution and drainage plus evaporation and infiltration). Using a numerical solution of the Richards' equation in a stochastic framework, the ensemble characteristics and flow dynamics were studied for drying and wetting processes observed during a time interval of ten days when a series of relatively intense rainfall events occurred. The effects of using unimodal and bimodal interpretative models of hydraulic properties on the ensemble hydrological behaviour of the soil were illustrated by comparing predictions to mean water contents measured over time in several sites at field scale. Although the differences between unimodal and bimodal fitting are not significant in terms of goodness of fit, the differences in process predictions are considerable with the bimodal soil simulating water content measurements much better than unimodal soil. We also investigated the relative contribution of the soil variability of each parameter on the variance of the water contents obtained as the main output of the stochastic simulations. The variability of the structural parameter, weighting the two pore space fractions in the bimodal interpretative model, has the largest contribution to water content variance. The contribution of each parameter depends only partly on the coefficient of variation, much more on the sensitivity of the model to the parameters and on the flow process being observed. We observed that the contribution of the retention parameters to uncertainty increases during drainage processes; the opposite occurs with the hydraulic conductivity parameters.     

Adaptive Management of Stream Channel Maintenance at Bridge Crossings in the Northern Tier Region,Pennsylvania1

Abstract: An adaptive management framework is applied to the problem of identifying mitigation measures for sediment deposition near bridge crossings in small streams in the Northern Tier region of northern Pennsylvania. The presence of the rigid bridge infrastructure introduces a challenge for applying adaptive management practices, because the integrity of the bridge structure itself has to be maintained regardless of the mitigation practices used in the stream channel near the bridge. In an effort to overcome the unacceptable risk that field‐scale adaptive management experiments present to rigid bridge infrastructure, an adaptive management approach for laboratory‐scale experimentation of mitigation methods at bridge crossings in the Northern Tier region is presented as a way to decrease the level of uncertainty about channel response to mitigation measures and increase the rate of learning about the effectiveness of these measures. Four cycles of adaptive management experiments are discussed to demonstrate that this approach results in fast and efficient learning about channel response to mitigation methods for the given conditions. The value of monitoring and of assessment of monitored data in the overall efficiency of the adaptive management approach is highlighted. Assessment of what was learned in the adaptive management experiment cycles presented here leads to new directions to continually improve management policies and practices in stream channels at bridge crossings in the Northern Tier region. The adaptive management process, rather than continuing with a normally risk‐averse management approach, results in opportunities for learning new information about a system’s response.