Neural network prediction of nitrate in groundwater of Harran Plain, Turkey

Monitoring groundwater quality by cost-effective techniques is important as the aquifers are vulnerable to contamination from the uncontrolled discharge of sewage, agricultural and industrial activities. Faulty planning and mismanagement of irrigation schemes are the principle reasons of groundwater quality deterioration. This study presents an artificial neural network (ANN) model predicting concentration of nitrate, the most common pollutant in shallow aquifers, in groundwater of Harran Plain. The samples from 24 observation wells were monthly analysed for 1 year. Nitrate was found in almost all groundwater samples to be significantly above the maximum allowable concentration of 50 mg/L, probably due to the excessive use of artificial fertilizers in intensive agricultural activities. Easily measurable parameters such as temperature, electrical conductivity, groundwater level and pH were used as input parameters in the ANN-based nitrate prediction. The best back-propagation (BP) algorithm and neuron numbers were determined for optimization of the model architecture. The Levenberg–Marquardt algorithm was selected as the best of 12 BP algorithms and optimal neuron number was determined as 25. The model tracked the experimental data very closely (R = 0.93). Hence, it is possible to manage groundwater resources in a more cost-effective and easier way with the proposed model application.     

乌鲁木齐河流域地下水水质监测网设计

文章运用地下水易污性编图及污染源分布图法进行了乌鲁木齐河流域地下水水质监测网设计。共设计了130监测孔,现有46个监测孔,另需要84个新的监测孔。按监测类型分为面源监测点22个,点源监测点87个,重点水源地与泉水监测点21个。按监测运行分长期监测点55个,流域普查监测点75个。普查监测点监测频率为1次/5年,长期监测点监测频率为1次/年。首期有针对性地在污染严重的柴窝堡新化厂排污区、乌鲁木齐河谷老排污区、米泉污灌区、米泉工业污染区、老龙河污染区取了25个污染水样测试分析,结果显示地下水已经受到严重污染。     

崎岖列岛附近海域环境质量现状与分析

根据 2 0 0 1年 2月和 7月对崎岖列岛附近海域的水质和底质表层沉积物调查结果 ,采用环境质量单项评价标准指数法 ,对该海域环境质量现状进行了评价与分析。结果表明 :(1 )该海域水质的 p H值、溶解氧和石油类等环境因子基本符合一类海水水质标准 ,化学需氧量、活性磷酸盐和无机氮浓度则超标严重 ,该海域水质已处于严重富营养化状态 (夏季比冬季富营养化程度略低 ) ;(2 )该海域底质表层沉积物中除部分站位的重金属 Cu、 Zn含量超标外 ,有机质、石油类和重金属 Pb、 Cd、 Hg的含量均未超标 ,底质环境状况尚好     

胶州湾海域水质预测

在已建潮流模型的基础上,用ADI法建立了胶州湾扩大域变动边界的平流—扩散输运模型,以COD为指示因子,预测了胶州湾海域1995年、2000年的水质、青岛环海公路海上段、沧口区北半部污水截流、北水南调、集中排放以及胶州湾西部经济开发对海域水质的影响等。为青岛市环保部门制定环保规划提供决策依据。     

海洋生态环境监测的指标体系研究

本文在总结国内外各种海洋生态监测方法的基础上,构建生物分布指数、生物暴露指数和生物反应指数,并由此确定生态质量总指教。生态质量总指数可以综合反映特定海洋环境的生物群落特征,典型污染物在生物体内的蓄积特征以及生物体对环境污染的生理生化反应特征,因此可以应用于近岸海洋环境质量的生态监测。     

A community-wide intercomparison exercise for the determination of dissolved iron in seawater

The first large-scale international intercomparison of analytical methods for the determination of dissolved iron in seawater was carried out between October 2000 and December 2002. The exercise was conducted as a rigorously “blind” comparison of 7 analytical techniques by 24 international laboratories. The comparison was based on a large volume (700 L), filtered surface seawater sample collected from the South Atlantic Ocean (the “IRONAGES” sample), which was acidified, mixed and bottled at sea. Two 1-L sample bottles were sent to each participant. Integrity and blindness were achieved by having the experiment designed and carried out by a small team, and overseen by an independent data manager. Storage, homogeneity and time-series stability experiments conducted over 2.5 years showed that inter-bottle variability of the IRONAGES sample was good (< 7%), although there was a decrease in iron concentration in the bottles over time (0.8–0.5 nM) before a stable value was observed. This raises questions over the suitability of sample acidification and storage.     

对虾养殖水质与饵料的关系研究

本文报道投喂不同厂家生产的对虾配合饵料致使水质因子变化的比较试验。结果表明：对虾养殖水体的ｐＨ、溶解氧及氨氮含量的变化和饵料的质量有直接关系，且影响到对虾的生存。而养殖水体的盐度、温度的变化和饵料的相关性不甚明显。文中还对配合饵料影响养殖水质因子变化的机理作了初步探讨。     

Kohonen网络与BP网络的集成应用研究

本文介绍了 Kohonen神经网络对输入数据进行聚类方法在卷烟配方中的应用 ,提出了从核心样本动态搜索 BP网络训练样本的新探索 ,摒弃了过去 BP算法中训练样本固定不变 ,互不相交的方法 ,实现了 BP网络和 Kohonen网络动态无缝集成。     

Sustainable shellfish aquaculture in Saldanha Bay,South Africa

The carrying capacity for bivalve shellfish culture in Saldanha Bay, South Africa, was analysed through the application of the well-tested EcoWin ecological model, in order to simulate key ecosystem variables. The model was set up using: (i) oceanographic and water-quality data collected from Saldanha Bay, and (ii) culture-practice information provided by local shellfish farmers. EcoWin successfully reproduced key ecological processes, simulating an annual mean phytoplankton biomass of 7.5 µg Chl a l^–1 and an annual harvested shellfish biomass of about 3 000 tonnes (t) y^–1, in good agreement with reported yield. The maximum annual carrying capacity of Small Bay was estimated as 20 000 t live weight (LW) of oysters Crassostrea gigas, or alternatively 5 100 t LW of mussels Mytilus galloprovincialis, and for Big Bay as 100 000 t LW of oysters. Two production scenarios were investigated for Small Bay: a production of 4 000 t LW y^–1 of mussels, and the most profitable scenario for oysters of 19 700 t LW y^–1. The main conclusions of this work are: (i) in 2015–2016, both Small Bay and Big Bay were below their maximum production capacity; (ii) the current production of shellfish potentially removes 85% of the human nitrogen inputs; (iii) a maximum-production scenario in both Big Bay and Small Bay would result in phytoplankton depletion in the farmed area; (iv) increasing the production intensity in Big Bay would probably impact the existing cultures in Small Bay; and (v) the production in Small Bay could be increased, resulting in higher income for farmers.     

连云港近岸海域物理自净能力研究及水质预测——Ⅲ.西大堤建成后对物质输运的影响

在连云港近岸海域计算潮流场基础上建立拉格朗日余流模型,并对连云港市两大堤建成前后的拉格朗日余流变化进行了分析,且选择有代表性的排污口进行了数值跟踪。