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肯尼亚热带尼安多河流域的时空水化学和同位素数据集

Spatiotemporal hydro-chemical and isotopic dataset of the tropical Nyando river basin in Kenya.

作者信息

Nyilitya Benjamin, Mureithi Stephen, Boeckx Pascal

机构信息

Isotope Bioscience Laboratory - ISOFYS, Department of Green Chemistry and Technology, Faculty of Bioscience Engineering, Ghent University, Coupure Links 653, 9000 Gent, Belgium.

Department of Land Resource Management and Agricultural Technology, University of Nairobi, P. O. Box 29053-00625, Nairobi, Kenya.

出版信息

Data Brief. 2021 Jan 21;35:106787. doi: 10.1016/j.dib.2021.106787. eCollection 2021 Apr.

Abstract

This article presents hydro-chemical and isotopic (δN-, δO‒NO , δB data of water samples and potential nitrate sources from the Nyando river basin, a tributary of the Lake Victoria in Kenya. The data collection involved field sampling of water samples in 23 sampling stations spatially distributed in the basin during nine seasons from July/2016 to May/2018. The hydro-chemical data was generated from the Laboratory analysis of the water samples using the ion chromatogram. Samples for nitrate isotope (δN-, δO‒NO ) analysis were prepared via the bacterial denitrification method and analysed using Isotope Ratio Mass Spectrometer. The data, which is categorised in different land use zones and seasons, is important for understanding the spatiotemporal variation in nitrate and solute concentrations and the role of land use on the river water quality. In addition, the δN-, δO‒NO and δB values are key for elucidating nitrate pollution sources and potential biogeochemical processes for the management and control of nutrient pollution and eutrophication of the Lake Victoria. Furthermore, the dataset can be of great use in water quality models for understanding non-point pollution dynamics in tropical basins. This article is related to [1].

摘要

本文介绍了肯尼亚维多利亚湖支流尼安多河流域水样的水化学和同位素(δN、δO‒NO 、δB)数据以及潜在的硝酸盐来源。数据收集工作包括在2016年7月至2018年5月的九个季节里,对流域内23个空间分布的采样站的水样进行实地采样。水化学数据是通过对水样进行离子色谱实验室分析得出的。用于硝酸盐同位素(δN、δO‒NO )分析的样本通过细菌反硝化法制备,并使用同位素比率质谱仪进行分析。这些按不同土地利用区和季节分类的数据,对于理解硝酸盐和溶质浓度的时空变化以及土地利用对河流水质的作用至关重要。此外,δN、δO‒NO 和δB值对于阐明硝酸盐污染源以及维多利亚湖营养物污染和富营养化管理与控制的潜在生物地球化学过程至关重要。此外,该数据集在水质模型中对于理解热带流域的非点源污染动态可能非常有用。本文与[1]相关。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/af96/7856418/88d401df481f/gr1.jpg

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