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。     

中国辽宁-浙江沿海地区川蔓草分布现状、生态特征及其主要威胁

川蔓草(Ruppia)是一种广泛分布在咸水、半咸水生境中的广义海草, 其形成的川蔓草床具有重要的生态学价值。然而, 对于其在中国境内的分布情况尚缺乏大范围的调查。基于此, 本研究于2016—2019年对中国辽宁-浙江沿海区域的川蔓草分布情况进行了初步调查, 探究了调查区域内川蔓草的生境分布类型, 及生态特征, 分析了川蔓草床的主要威胁, 并提出了对川蔓草床科学管理的建议。结果表明: 川蔓草在中国浙江省、江苏省、山东省、天津市、河北省、辽宁省均有分布; 分布面积超过2 100 ha; 该区域内分布的川蔓草物种均为中国川蔓草, 主要分布生境包括咸水养殖池塘、咸水沟渠(池塘)、盐场、瀉湖(湖泊)、潮间带(围堰)5类; 人类活动影响(人工清捞、施药、河道工程等)与极端气候事件(极端干旱事件)都会导致川蔓草床退化, 但大部分川蔓草床可以依靠沉积物中的种子库在环境适宜时进行种群恢复; 不同生境中的川蔓草种群特征差异较大, 因此, 对不同生境中的川蔓草应制定差异性管理措施。     

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     

Spatial patterns and environmental risks of ringnet fishing along the Kenyan coast

Ringnet fishing began in the early 20th century and is practised worldwide, mainly to target nearshore pelagic species. The method was introduced to Kenya’s coastal waters by migrant fishers from Tanzania. However, the impacts of this fishing gear remain poorly assessed. We assessed the spatial distribution of ringnet fishing effort and its possible effects on ecosystem components, such as coral reefs, marine megafauna and marine protected areas, on the south coast of Kenya. We tracked 89 ringnet fishing trips made from December 2015 to January 2016 and used spatial multicriteria analysis to determine hotspots of possible environmental risks. The results showed that habitat type and bathymetric profile influenced the spatial distribution of ringnet fishing effort. Mixed seagrass and coral habitats had the highest concentration of the effort. Most of the habitats in the study area were moderately exposed to the impacts of the ringnet fishery. The study identifies high-risk areas that require spatial measures to minimise possible environmental risks of the gear both to habitats and to endangered sea turtles.     

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。     

A summary of the geology and oil habitat of the Eastern Flank Hydrocarbon Province of South Oman

The Eastern Flank Hydrocarbon Province borders the southeastern edge of the South Oman Salt Basin in the southern part of Oman. An intensive exploration programme by PDO over the past seven years has led to the discovery of almost 2 × 10⁹ m³ of oil with current production of some 15000 m³/d from six fields.In stark contrast to other oil habitats of the Arabian Peninsula, the main play involves rock units and geological events ranging in age from Late Precambrian to Quaternary Times, while trap development and charging are closely related to syn-tectonic salt dissolution.The principal reservoirs and seals are poorly consolidated, Palaeozoic clastics which drape, due to salt dissolution, over residual ‘cores’ principally composed of either Lower Palaeozoic sandstones (Haima Group), or Late Proterozoic carbonates (Huqf Group), or some combination of these. Oils have been geochemically correlated with algal source rocks of the Huqf Eastern Flank. Structures are considered to have been ‘charged’ from Late Mesozoic times onwards in conjunction with progressive subsurface salt removal and the onset of maturation of local source rocks. The effectiveness of ‘charging’ along the retreating salt edge is indicated by the small percentage of dry wells.Major oil zones are found in both anticlinal and truncation traps which are commonly developed around sandstone (Haima Group) cores. Oils show a wide range of characteristics but are typically heavy, early expulsion crudes, high sulphur with little associated gas. Bacterial transformation is not uncommon.Producing reservoirs mainly occur at relatively shallow depths (600–1200 m). Primary recovery factors of around 7% reflect the high density and viscosity of the Eastern Flank crudes and have initiated interest in Enhanced Oil Recovery (EOR) techniques. Two such pilot projects, involving steam and polymer flooding, are due to commence in 1984 and, if successful, will substantially increase the reserve base of these fields.     

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。     

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。     

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.