環保專案成果報告查詢系統

專案計畫編號
經費年度	108
計畫經費	15,136 千元
預算科目	土壤及地下水污染整治策略規劃
專案開始日期	2019/09/09
專案結束日期	2021/03/08
專案主持人	夏安宙
主辦單位	土污基管會
承辦人	陳俞穎
執行單位	業興環境科技股份有限公司
專案分類	土壤及地下水
中文關鍵字	地下水三維井網聯合監測、農業區預警監測井網、水質自動監測
英文關鍵字	Joint Management of Three-dimensional Groundwater Monitoring Network, Agricultural Early-warning Monitoring Network, Automatic Real-time Water Quality Monitoring System
協同主持人	劉志忠
共同主持人
計畫聯絡人	王莀㥓
計畫聯絡電話	02-27691002#126
計畫聯絡信箱	wangci@setl.com.tw

中文摘要	本計畫主要辦理環保署地下水水質評析等工作，包含資料研析分析運用與監測井管理制度、檢討預警監測井網分布與監測方式、評析背景水質變化趨勢並建立關係模型、研擬地下水環境自動連續監測架構，及整合國內外地下水環境資料，強化地下水管理業務聯繫與交流。本計畫首先檢討區域性監測井採樣名單、監測項目及監測頻率等，並建議依據水文地質條件調整監測井監測頻率，另提出監測井生命週期相關作業原則及規範內容之主要修正方向。為掌握全國地下水不同含水層之水質特性，亦調查屏東平原之硝酸鹽氮高潛勢地區，研提地下水三維井網聯合監測篩選原則，建議提出定期關注之監(觀)測井名單。本計畫也於農業密集區建置農業區預警監測井網，已推估農業行為與地下水氨氮濃度有關，另為建立連續資料判讀及分析方法，本計畫評估以NB-IoT作為連續水質資料傳輸系統，提出未來自動連續監測架構應用之需求。此外，係針對氨氮及硝酸鹽氮濃度偏高地區進行類神經網路模型分析，顯示農牧行為與地下水水質變化有正相關，建議未來可透過自動水質監測設備應用提高數據量，精進模型分析準確度。另為研析地下水含氟鹽成因，研提地下水氟鹽來源判定流程，可透過判識地下水水質型態，歸納地下水氟鹽來源成因，並應持續加強流程之驗證。此外，本計畫為強化地下水管理業務聯繫與交流，亦協助辦理跨部會研商會、專家諮詢會及座談會等。
中文關鍵字	地下水三維井網聯合監測、農業區預警監測井網、水質自動監測

中文摘要

本計畫主要辦理環保署地下水水質評析等工作，包含資料研析分析運用與監測井管理制度、檢討預警監測井網分布與監測方式、評析背景水質變化趨勢並建立關係模型、研擬地下水環境自動連續監測架構，及整合國內外地下水環境資料，強化地下水管理業務聯繫與交流。本計畫首先檢討區域性監測井採樣名單、監測項目及監測頻率等，並建議依據水文地質條件調整監測井監測頻率，另提出監測井生命週期相關作業原則及規範內容之主要修正方向。為掌握全國地下水不同含水層之水質特性，亦調查屏東平原之硝酸鹽氮高潛勢地區，研提地下水三維井網聯合監測篩選原則，建議提出定期關注之監(觀)測井名單。本計畫也於農業密集區建置農業區預警監測井網，已推估農業行為與地下水氨氮濃度有關，另為建立連續資料判讀及分析方法，本計畫評估以NB-IoT作為連續水質資料傳輸系統，提出未來自動連續監測架構應用之需求。此外，係針對氨氮及硝酸鹽氮濃度偏高地區進行類神經網路模型分析，顯示農牧行為與地下水水質變化有正相關，建議未來可透過自動水質監測設備應用提高數據量，精進模型分析準確度。另為研析地下水含氟鹽成因，研提地下水氟鹽來源判定流程，可透過判識地下水水質型態，歸納地下水氟鹽來源成因，並應持續加強流程之驗證。此外，本計畫為強化地下水管理業務聯繫與交流，亦協助辦理跨部會研商會、專家諮詢會及座談會等。

中文關鍵字

地下水三維井網聯合監測、農業區預警監測井網、水質自動監測

類型	檔名	檔案大小	說明	最新版公開日期
期末報告	108年全國地下水水質管理策略推動計畫.pdf	33MB	期末報告	2021/6/30 上午 12:00:00

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.
英文關鍵字	Joint Management of Three-dimensional Groundwater Monitoring Network, Agricultural Early-warning Monitoring Network, Automatic Real-time Water Quality Monitoring System

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.

英文關鍵字

Joint Management of Three-dimensional Groundwater Monitoring Network, Agricultural Early-warning Monitoring Network, Automatic Real-time Water Quality Monitoring System