Quality assessment of groundwater from the south-eastern Arabian Peninsula

Assessment of groundwater quality plays a significant role in the utilization of the scarce water resources globally and especially in arid regions. The increasing abstraction together with man-made contamination and seawater intrusion have strongly affected groundwater quality in the Arabia Peninsula, exemplified by the investigation given here from the United Arab Emirates, where the groundwater is seldom reviewed and assessed. In the aim of assessing current groundwater quality, we here present a comparison of chemical data linked to aquifers types. The results reveal that most of the investigated groundwater is not suitable for drinking, household, and agricultural purposes following the WHO permissible limits. Aquifer composition and climate have vital control on the water quality, with the carbonate aquifers contain the least potable water compared to the ophiolites and Quaternary clastics. Seawater intrusion along coastal regions has deteriorated the water quality and the phenomenon may become more intensive with future warming climate and rising sea level.     

高原机场飞机噪声监测与计算结果比较分析

高原机场飞机架次较少,机型单一,飞行周期稳定,以及高原特殊的环境特征,有时会导致现场实际噪声监测数据无效。应用综合噪声模型(INM)软件对青海玉树机场飞机噪声进行计算,其结果与监测结果比较显示,计算值和监测值误差在±6 d B的范围以内。探讨提出采用飞机噪声计算模式,可以为高原机场飞机噪声管理提供可靠技术支撑。     

An Approach to Reaeration Coefficient Modeling in Local Surface Water Quality Monitoring

Reaeration coefficient (k ₂) for River Atuwara, Ogun State, Nigeria was calculated from dissolved oxygen and biochemical oxygen demand data collected over period of 3 months covering the two prevailing climatic seasons in the country. Both the Akaike and Bayesian information criteria were used in the selection and analysis of ten models to identify the most suitable reaeration coefficient (k ₂) model for Atuwara River. Models that passed the confidence limit were subjected to model evaluation using measures of agreement between observed and predicted data such as percent bias, Nash–Sutcliffe efficiency, and root mean square observation standard deviation ratio. The used approach yield better results than empirical models developed for local conditions while it is also useful in conserving scarce resources.