| 英文摘要 |
The focus of this project is to provide insights on groundwater quality assessment and management. Primary tasks include the management of groundwater monitoring wells via data analysis, the establishment of early-warning groundwater monitoring network, assessment of water quality changes, the development of automatic real-time groundwater monitoring platform, and supporting governmental administration activities. Sampling frequency of groundwater monitoring wells was reviewed and the concept of including hydrogeological parameter was proposed. The guideline of monitoring wells life cycle management were also reviewed and revision notes were provided. Besides, results from the investigation on high nitrate-nitrogen pollution potential area at Pingtung Plain indicated that candidate list for wells of concern for joint management is required. An agricultural early-warning monitoring network was also established. It was found that agricultural activities were related to ammonia nitrogen concentration in groundwater. This study could be enhanced through developing continuous monitoring system with NB-IoT as data transmission system. The artificial neural network (ANN) model was also applied to predict the impacts of human activities on groundwater quality. Results showed that changes of ammonia-nitrogen concentration had positive correlation with farming activities, however the model accuracy would only be improved with more data collected from automatic monitoring system. Also, a work flow to identify the source of fluoride in groundwater was proposed and potential fluoride-rich regions were determined. Finally, inter-ministerial meetings and expert advisory meetings were held to pave the way of government’s future direction.
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