Estimating pesticide runoff in small streams

Surface runoff is one of the most important pathways for pesticides to enter surface waters. Mathematical models are employed to characterize its spatio-temporal variability within landscapes, but they must be simple owing to the limited availability and low resolution of data at this scale. This study aimed to validate a simplified spatially-explicit model that is developed for the regional scale to calculate the runoff potential (RP). The RP is a generic indicator of the magnitude of pesticide inputs into streams via runoff. The underlying runoff model considers key environmental factors affecting runoff (precipitation, topography, land use, and soil characteristics), but predicts losses of a generic substance instead of any one pesticide. We predicted and evaluated RP for 20 small streams. RP input data were extracted from governmental databases. Pesticide measurements from a triennial study were used for validation. Measured pesticide concentrations were standardized by the applied mass per catchment and the water solubility of the relevant compounds. The maximum standardized concentration per site and year (runoff loss, R_Loss) provided a generalized measure of observed pesticide inputs into the streams. Average RP explained 75% (p < 0.001) of the variance in R_Loss. Our results imply that the generic indicator can give an adequate estimate of runoff inputs into small streams, wherever data of similar resolution are available. Therefore, we suggest RP for a first quick and cost-effective location of potential runoff hot spots at the landscape level.     

边坡变形时序非线性判定及混沌预测研究

以探讨边坡变形性质及混沌预测可行性为目的,基于混沌理论利用相空间重构技术对其变形时间序列进行混沌特征判定,试验显示变形系统具有混沌特性,可用混沌相关理论进行研究;基于混沌相空间重构技术,笔者构建了多种混沌预测模型进行混沌预计研究,分析各类模型的工程实际应用效果;针对单次监测时序预测精度较低的问题,提出累加时序预测方案,训练结果显示,短期预测精度变形累计值基本控制在5%以内,高程值预测相对误差均低于1%,预测精度较高,可以用于工程实际。     

基于人工神经网络理论的建筑物火灾安全评价研究

依据建筑物火灾危险性的影响因素,应用人工神经网络理论及系统安全方法,建立了建筑物火灾危险性的评价指标体系,该方法摆脱了评价过程中的随机性和参评人员主观上的不确定性及其认识上的模糊性等缺点,大大提高了准确性。为了验证评价模型的准确性,将该理论应用到某高校图书馆火灾危险性评价中,快速、准确地得到了安全评价结果,取得了满意效果,为建筑物防火设计以及安全管理提供了可行的依据。     

A process integration approach to industrial water conservation: a case study for a Chinese steel plant

A systematic approach to optimizing water network has traditionally been utilized to exam and plan water conservation in industrial processes. In the present case study, water-pinch technology was used to analyze and optimize the water network of a steel plant near China's Zhangjiakou city. A system design was developed and a limiting constraint (Cl(-) concentration) was identified based on investigations of water quality then the minimum freshwater and wastewater targets were determined without considering water losses. The analysis was then extended by calculating the additional input of freshwater required to balance the actual water losses. A nearest-neighbor algorithm (NNA) was used to distribute the freshwater and recycled water among each of the plant's operations. The results showed that with some reconstruction of the water network, the flow rates of freshwater and wastewater could be decreased by 57.5% and 81.9%, respectively.     

环境监测信息网络建设思路的探讨

介绍了环境监测信息网络的组成、作用于流通范围,提出了环境监测信息的构架、环境数据库的设计原则、环境监测应用软件的开发思路,以及环境监测信息网络的管理与维护措施。     

Runoff of pesticides from rice fields in the Ile de Camargue (Rhône river delta, France): field study and modeling

A field study on the runoff of pesticides was conducted during the cultivation period in 2004 on a hydraulically isolated rice farm of 120 ha surface with one central water outlet. Four pesticides were studied: Alphamethrin, MCPA, Oxadiazon, and Pretilachlor. Alphamethrin concentrations in runoff never exceeded 0.001 microg L(-1). The three other pesticides were found in concentrations between 5.2 and 28.2 microg L(-1) in the runoff water shortly after the application and decreased thereafter. The data for MCPA compared reasonably well with predictions by an analytical runoff model, accounting for volatilization, degradation, leaching to groundwater, and sorption to soil. The runoff model estimated that runoff accounted for as much as 18-42% of mass loss for MCPA. Less runoff is observed and predicted for Oxadiazon and Pretilachlor. It was concluded that runoff from rice paddies carries important loads of dissolved pesticides to the wetlands in the Ile de Camargue, and that the model can be used to predict this runoff.     

Modeling the Effects of Potential Salinity Shifts on the Recovery of Striped Bass in the Savannah River Estuary,Georgia–South Carolina,United States

Increased salinity in spawning and nursery grounds in the Savannah River estuary was cited as the primary cause of a 97% decrease in adult striped bass (Morone saxatilis) and a concomitant 96% decrease in striped bass egg production. Restoration efforts focused on environmental remediation and stock enhancement have resulted in restored salinity patterns and increased egg and adult abundances. However, future water needs or harbor development may preclude further recovery by reducing freshwater inflow or increasing salinity intrusion. To assess the effect of potential changes in the salinity regime, we developed models relating discharge, tidal phase, and salinity to striped bass egg and early larval survival and re-cast these in a quantitative Bayesian belief network. The model indicated that a small upstream shift (≤1.67 km) in the salinity regime would have the least impact on striped bass early life history survival, whereas shifts >1.67 km would have progressively larger impacts, with a 8.33-km shift potentially reducing our estimated survival probability by >28%. Such an impact could have cumulative and long-term detrimental effects on the recovery of the Savannah River striped bass population. The available salinity data were collected during average and low flows, so our model represents some typical and some extreme conditions during a striped bass spawning season. Our model is a relatively simplistic, “first-order” attempt at evaluating potential effects of changes in the Savannah River estuarine salinity regime and points to areas of concern and potential future research.     

浅谈建筑施工噪声的网络化管理

通过《南宁市环境信息综合管理系统》中建筑施工噪声管理子系统的重点研究和建设,对建设施工项目审批、中午夜间施工许可登记及施工噪声投诉实时监控,加强监督,改善了管理环节,提高了管理效能,取得了良好的效果。     

基于BP神经网络的垃圾焚烧过程故障诊断

应用BP神经网络方法,建立了垃圾焚烧过程故障诊断的模型.该方法采用梯度下降法训练网络权值,利用最优停止法对网络进行了优化,避免了过拟合现象.提高了BP神经网络的训练速度和泛化能力.并以实际焚烧过程工况数据进行性能检验,检验结果表明了该BP网络具有较高的诊断精度.     

人工神经网络在预测深基坑周边地表沉降变形中的应用研究

深基坑开挖引起的周边地表变形预测是一个复杂非线性问题,引起地表沉降的影响因素很多,各因素之间呈高度的非线性关系。传统的基坑用边地表沉降变形预测方法存在着一定的局限性,其预测精度有待提高,而人工神经网络是一种多元非线性动力学系统,可以灵活方便地对多成因的复杂未知系统进行高度建模,实现全面考虑各种主要影响因素的深基坑周边地表沉降变形预测。本文介绍了误差反向传播(BP)网络模型的结构、学习过程及其算法的改进,径向基函数(RBF)网络模型的结构及其学习过程;分析了影响深基坑开挖周边土体沉降变形的主要影响因素;以25个基坑工程的地表沉降实测资料为训练样本,建立了11个输入影响因素的BP神经网络模型和RBF神经网络模型,通过对样本的学习训练过程及对5个检验样本的预测精度,说明了人工神经网络用于预测基坑周边地表沉降的可行性和准确性。