Groundwater modelling is a commonly used technique to determine the influence of surficial processes on subsurface aquifers. In this study, a groundwater monitoring study was conducted on an agricultural field adjacent to a large drainage canal to determine the effects of the canal's operation as it relates to soil salinity during periods around flood events. The groundwater monitoring program consisted of twenty standpipes instrumented with groundwater pressure transducers that took four daily measurements. A finite element model was generated using data collected from the 2017 flood year to determine the effect of the flood on the local groundwater regime within one area consisting of four standpipes. The analysis of the model calibration yielded good to excellent results using the Nash–Sutcliffe Model Efficiency technique, with three of the four standpipes. The salt content within the model area was primarily gypsum initially derived from the underlying till and bedrock units. Model analysis indicated that various processes might impact soil salinity, including canal seepage, evapotranspiration and excessive snowmelt/recharge. The largest flood event on record for the canal was used in the calibrated model to determine the maximum extent of influence the canal has on the adjacent lands. The maximum extent of impact was found to be 112 m in the alluvial sediments and 240 m in the surficial sand structure.

地下水建模是确定表层过程对地下含水层影响的常用技术。在这项研究中，在毗邻大排水渠的农田上进行了地下水监测研究，以确定在洪水事件发生期间，运河的运营与土壤盐分相关的影响。地下水监测程序由二十根竖管组成，这些竖管上装有地下水压力传感器，每天进行四次测量。使用从2017洪水年度收集的数据生成了一个有限元模型，以确定洪水对由四个竖管组成的一个区域内的局部地下水状况的影响。使用Nash–Sutcliffe模型效率技术对模型校准进行的分析得出了很好的结果，与四个竖管中的三个。模型区域内的盐含量主要是石膏，最初来自下层耕层和基岩单元。模型分析表明，各种过程都可能影响土壤盐分，包括渠道渗水，蒸散和过多的融雪/补给。经校准的模型使用了有记录以来最大的运河洪水事件，以确定运河对邻近土地的最大影响程度。发现冲积沉积物的最大影响范围为112 m，表层砂构造的最大影响范围为240 m。蒸散和过多的融雪/补给。经校准的模型使用了有记录以来最大的运河洪水事件，以确定运河对邻近土地的最大影响程度。发现冲积沉积物的最大影响范围为112 m，表层砂构造的最大影响范围为240 m。蒸散和过多的融雪/补给。经校准的模型使用了有记录以来最大的运河洪水事件，以确定运河对邻近土地的最大影响程度。发现冲积沉积物的最大影响范围为112 m，表层砂构造的最大影响范围为240 m。