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Dataset on the spatial distribution of groundwater quality for pH, Electrical Conductivity (EC), Total Hardness (TH), Ca 2+ , Mg 2+ , HCO 3 -, F - , and NO 3 - in Dodoma, Singida, and Tabora regions located in central Tanzania
Groundwater is an important source of water for drinking and irrigation purposes in semi-arid regions like central Tanzania. Groundwater quality is degraded by anthropogenic and geogenic pollution. Anthropogenic pollution depends on the disposal of contaminants from human activities into the environ...
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Published in: | Data in brief 2023-06, Vol.48, p.109239 |
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Main Authors: | , |
Format: | Article |
Language: | English |
Online Access: | Get full text |
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Summary: | Groundwater is an important source of water for drinking and irrigation purposes in semi-arid regions like central Tanzania. Groundwater quality is degraded by anthropogenic and geogenic pollution. Anthropogenic pollution depends on the disposal of contaminants from human activities into the environment, which can leach and pollute groundwater. Geogenic pollution depends on the presence and dissolution of mineral rocks. High geogenic pollution is observed in aquifers that are rich in carbonates, feldspars, and mineral rocks. Consumption of polluted groundwater has negative health effects. Therefore, protection of public health necessitates the evaluation of groundwater in order to identify a general pattern and spatial distribution of groundwater pollution. A literature search uncovered no publications that describe the spatial distribution of hydrochemical parameters across central Tanzania. Central Tanzania is located within East Africa Rift Valley, Tanzania craton and is made up of Dodoma, Singida and Tabora regions. To fill the gap, this article contains a data set for pH, Electrical Conductivity (EC), Total Hardness (TH), Ca
, Mg
, HCO
, F
, and NO
from 64 groundwater samples collected from Dodoma region (22 samples), Singida region (22 samples) and Tabora region (20 samples). Data collection covered a total distance of 1344 km, which was divided into east-west along B129, B6, and B143 roads and north-south along A104, B141, and B6 roads. The present dataset can be used to model the geochemistry and spatial variation of physiochemical parameters across these three regions. |
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ISSN: | 2352-3409 |