LOCAL POPULATION AS A CRITICAL PARTNER IN WATER-QUALITY MONITORING: THE BENIN EXPERIENCE

Well water quality in the Colline Department of Benin, West Africa, is recognized to be impacted by nitrate contamination. Due to resource limitations, time-series data with a frequency greater than once every 6 months is not possible using professional personnel from the University of Notre Dame, the Universite d'Abomey-Calavi (the national university in Benin) or the Direction de l'Hydraulique (the national water agency in Benin). Study of the source(s) and temporal trends in the nitrate concentrations was not possible in the absence of these data. Hence, a program was established whereby water quality monitoring teams within the local community were trained to perform basic water-quality measurements using test strips and colorimetry. Over the past three years, these teams have demonstrated that they can reliably measure water quality parameters on a weekly basis. Further, they have routinely measured unknown concentration of nitrate in samples provided by the University of Notre Dame and shown that they can reliably reproduce (with an identifiable bias) the concentrations in these samples. Difficulties in developing these measurement teams have included language barriers (both during training and in reference materials provided), provision and reliability of the test strip and colorimetry supplies, desire of the local population to be compensated for their efforts, and limitations imposed by Direction de l'Hydraulique concerning the level of disclosure to the local population regarding the quality of their water. Each of these difficulties has been overcome through open conversation with all parties involved (particularly the local population). The resulting time-series data sets have provided substantial insight into long-term changes in groundwater quality that would otherwise not be recorded by low-frequency sampling. It can be concluded that, in this case, the local population represents a critical partner in developing a long-term, high-frequency record of groundwater quality changes. Further, the model used in working with and training the measurement teams has been shown to be transferable to other villages in Benin.