Assessing nitrate pollution in the Kinshasa groundwater system using a hybrid approach

This thesis studies the groundwater pollution by nitrate in the region of Kinshasa (DR Congo) using an integrated methodological approach combining physicochemical, isotopic and modeling analyses. The first main objective is to assess the groundwater quality and to identify the sources of nitrate. The groundwater is poorly mineralized and nitrate is one of the major ions contributing to the mineralization processes. The combined use of hydrochemical properties and multiple isotope tracers allows identifying and separating the sources of nitrate and elucidating complex mixing processes. The Bayesian mixing model of nitrogen and oxygen isotopes in nitrate provides general ordering of proportional source contributions. Two multivariate statistical approaches allow linking the measured groundwater nitrate to different land use attributes and demonstrate the overwhelming impact of poorly planned urbanization on groundwater nitrate contamination. The second main objective is to assess the regional groundwater contamination by mapping the groundwater body vulnerability and the nitrate concentrations which are measured on sparsely distributed sampling stations. The parametric vulnerability model is first modified and calibrated to predict the intrinsic vulnerability and the groundwater pollution risk to nitrate. A Bayesian data fusion approach is subsequently implemented to map the nitrate concentrations in areas located far away from monitoring stations. This approach reduces considerably uncertainty in regionally predicted concentration. Finally, a tracing experiment allows estimating vertical travel times through the vadose zone. The implemented hybrid approach is translated in state-of-the-art groundwater quality risk maps which are pivotal for designing future protection and management programs of the Kinshasa groundwater system.(AGRO - Sciences agronomiques et ingénierie biologique) -- UCL, 201

Assessing pollution pressures on the groundwater resource in Kinshasa (DR of Congo): an hybrid approach based on physico-chemical, isotopic and modelling analysis

The groundwater below the city of Kinshasa is an important freshwater resource and is a major resource for drinking water supply in the peri-urban area of the capital of D.R. of Congo. At some places, the groundwater body is confined, but in the overwhelming part of the aquifer, the water body is semi-confined or free. Hence the groundwater body is extremely vulnerable for pollution from anthropogenic origin. The overall objective of the project is to design, implement and test a novel integrated approach for quantifying the contribution of the different pollution sources (peri-urban agriculture vs. domestic) to the pollution of the groundwater body below the city of Kinshasa. The specific objectives are: (i) To elucidate the actual knowledge of the pollution pressure on the Kinshasa groundwater body. This should be done by re-analysing the historical groundwater quality data (physico-chemical and isotopic fingerprint) using recently developed geo-statistical, conceptual modelling and isotopic mixture modelling tools; (ii) To optimize the protocol for isotopic fingerprinting of the recharging water by means of vadose zone passive sampling systems; (iii) To optimize and monitor the chemical fingerprint (classical physico-chemical and isotopic) of a selected set of groundwater and recharging water sampling points. The approach integrates chemical and isotopic fingerprinting of groundwater and recharging water in the overlying unsaturated zone, with advanced mathematical modelling (space-time geostatistical modelling and process based vulnerability mapping) of pollution pressures on groundwater bodies. The novel approach will support the development of sustainable groundwater protection and exploitation programmes in urban and peri-urban environments in Africa, and in Kinshasa in particula

Explaining nitrate pollution pressure on the groundwater resource in Kinshasa using a multivariate statistical modelling approach

Drinking water in Kinshasa, the capital of the Democratic Republic of Congo, is provided by extracting groundwater from the local aquifer, particularly in peripheral areas. The exploited groundwater body is mainly unconfined and located within a continuous detrital aquifer, primarily composed of sedimentary formations. However, the aquifer is subjected to an increasing threat of anthropogenic pollution pressure. Understanding the detailed origin of this pollution pressure is important for sustainable drinking water management in Kinshasa. The present study aims to explain the observed nitrate pollution problem, nitrate being considered as a good tracer for other pollution threats. The analysis is made in terms of physical attributes that are readily available using a statistical modelling approach. For the nitrate data, use was made of a historical groundwater quality assessment study, for which the data were re-analysed. The physical attributes are related to the topography, land use, geology and hydrogeology of the region. Prior to the statistical modelling, intrinsic and specific vulnerability for nitrate pollution was assessed. This vulnerability assessment showed that the alluvium area in the northern part of the region is the most vulnerable area. This area consists of urban land use with poor sanitation. Re-analysis of the nitrate pollution data demonstrated that the spatial variability of nitrate concentrations in the groundwater body is high, and coherent with the fragmented land use of the region and the intrinsic and specific vulnerability maps. For the statistical modeling use was made of multiple regression and regression tree analysis. The results demonstrated the significant impact of land use variables on the Kinshasa groundwater nitrate pollution and the need for a detailed delineation of groundwater capture zones around the monitoring stations

L’union fait la force or how different approaches should be combined to assess groundwater vulnerability at the regional scale

The sustainable management of groundwater implies an in depth knowledge of the status of groundwater and the pressures that are exerted on it. Monitoring and modeling groundwater systems allows generating the required information for such an appropriate management. Yet, the classical monitoring techniques are confronted with small sampling support, and the current modelling techniques suffer from limited validation and accuracy. In this lecture, we show how advanced monitoring, including the monitoring of stable isotopes, in combination with spatially distributed modelling improves considerably the quality of the groundwater assessment. The techniques are illustrated for assessing groundwater contamination by nitrates

Modelling nitrate pollution pressure using a multivariate statistical approach: the case of Kinshasa groundwater body, Democratic Republic of Congo

A multivariate statistical modelling approach was applied to explain the anthropogenic pressure of nitrate pollution on the Kinshasa groundwater body (Democratic Republic of Congo). Multiple regression and regression tree models were compared and used to identify major environmental factors that control the groundwater nitrate concentration in this region. The analyses were made in terms of physical attributes related to the topography, land use, geology and hydrogeology in the capture zone of different groundwater sampling stations. For the nitrate data, groundwater datasets from two different surveys were used. The statistical models identified the topography, the residential area, the service land (cemetery), and the surface-water land-use classes as major factors explaining nitrate occurrence in the groundwater. Also, groundwater nitrate pollution depends not on one single factor but on the combined influence of factors representing nitrogen loading sources and aquifer susceptibility characteristics. The groundwater nitrate pressure was better predicted with the regression tree model than with the multiple regression model. Furthermore, the results elucidated the sensitivity of the model performance towards the method of delineation of the capture zones. For pollution modelling at the monitoring points, therefore, it is better to identify capture-zone shapes based on a conceptual hydrogeological model rather than to adopt arbitrary circular capture zones

Assessing groundwater vulnerability in the Kinshasa region, DR Congo, using a calibrated DRASTIC model

This study assessed the vulnerability of groundwater against pollution in the Kinshasa region, DR Congo, as a support of a groundwater protection program

Use of hydrochemical and isotopes for assessing nitrate pollution pressure in the Kinshasa groundwater body, DR Congo

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