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Development of a Tool to Identify Groundwater Recharge Areas Vulnerable to Sodium Chloride Contamination in Well Head Protection Areas

Development of a Tool to Identify Groundwater Recharge Areas Vulnerable to Sodium Chloride Contamination in Well Head Protection Areas
开发工具来识别井口保护区易受氯化钠污染的地下水补给区
批准号:
543501-2019
负责人:
Daggupati, NagaPrasad
金额:
$1.82万
依托单位:
依托单位国家:
加拿大
项目类别:
Engage Grants Program
财政年份:
2019
资助国家:
加拿大
项目状态:
已结题
起止时间:
2019-01-01 至 2020-12-31

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中文摘要
翻译
在加拿大,经常使用岩盐来管理冬季驾驶条件,以及需要在城市环境中实施雨水管理(SWM)做法,导致地表水和地下水中含有大量氯化钠。高浓度的氯化钠正在影响水的饮用性和生态系统的可持续性。因此,圭尔夫大学和城市流域集团有限公司之间的一个合资企业将开发一个综合建模框架,其中包括开放建模接口(OpenMI)中广泛使用的地表水模型(SWAT)和地下水模型(MODFLOW),该模型可以模拟氯化钠通过土壤剖面进入地下水含水层以及通过陆地进入河流的传输机制。滑铁卢市内银上游的月桂溪子流域被选为试点研究区域之一。将利用地表水和地下水采样活动收集的监测数据对综合模型进行校准和验证。一旦经过校准和验证,将制定情景,以评估各种雨水管理(SWM)做法及其对地下水质量的影响以及对生态系统的影响。最后,遗传算法(GA)将与地表水-地下水模型,以优化选择最佳SWM的做法,并确定地下水补给区容易受到氯化钠污染的月桂溪子流域的井口保护区。
英文摘要
In Canada, frequent application of rock salt for managing winter driving conditions and the need to implement stormwater management (SWM) practices in urban environment result in large volumes of sodium chloride in surface and ground water. High concentrations of sodium chloride are affecting the potability of water and sustainability of ecosystems. Therefore, a joint venture between University of Guelph and Urban Watershed Group Ltd. will develop an integrated modelling framework involving a widely used surface water model (SWAT) and ground water model (MODFLOW) in Open Modelling Interface (OpenMI) which can simulate the transport mechanisms of sodium chloride through soil profile into ground water aquifer and also through overland into streams. The Laurel Creek sub-watershed upstream of Silver Lake within the City of Waterloo was selected as one of the pilot study areas. The integrated model will be calibrated and validated using monitoring data which will be collected in both surface and groundwater sampling campaigns. Once calibrated and validated, scenarios will be developed to evaluate various stormwater management (SWM) practices and their impact on groundwater quality as well as impacts on ecosystems. Finally, a genetic algorithm (GA) will be integrated with the surface water-groundwater model to optimize the selection of best SWM practices and to identify groundwater recharge areas vulnerable to sodium chloride contamination in well head protection areas of the Laurel Creek sub-watershed.
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