Abstract A test using Rhodamine WT and heat as tracers, conducted over a 78 day period in a strongly heterogeneous alluvial aquifer, was used to evaluate the utility of the combined observation dataset for aquifer characterization. A highly parameterized model was inverted, with concentration and temperature time-series as calibration targets. Groundwater heads recorded during the experiment were boundary dependent and were ignored during the inversion process. The inverted model produced a high resolution depiction of the hydraulic conductivity and porosity fields. Statistical properties of these fields are in very good agreement with estimates from previous studies at the site. Spatially distributed sensitivity analysis suggests that both solute and heat transport were most sensitive to the hydraulic conductivity and porosity fields and less sensitive to dispersivity and thermal distribution factor, with sensitivity to porosity greatly reducing outside the monitored area. The issues of model over-parameterization and non-uniqueness are addressed through identifiability analysis. Longitudinal dispersivity and thermal distribution factor are highly identifiable, however spatially distributed parameters are only identifiable near the injection point. Temperature related density effects became observable for both heat and solute, as the temperature anomaly increased above 12 degrees centigrade, and affected down gradient propagation. Finally we demonstrate that high frequency and spatially dense temperature data cannot inform a dual porosity model in the absence of frequent solute concentration measurements.

中文翻译：

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在强非均质冲积含水层中使用溶质和热示踪剂进行含水层表征

摘要 使用罗丹明 WT 和热量作为示踪剂的测试，在强烈异质冲积含水层中进行了 78 天，用于评估组合观测数据集对含水层表征的效用。一个高度参数化的模型被反转，浓度和温度时间序列作为校准目标。实验期间记录的地下水水头是边界相关的，在反演过程中被忽略。反演模型产生了水力传导率和孔隙度场的高分辨率描述。这些字段的统计特性与现场先前研究的估计值非常吻合。空间分布敏感性分析表明，溶质和热传输对水力传导率和孔隙度场最敏感，对弥散度和热分布因子不太敏感，在监测区域外对孔隙度的敏感性大大降低。通过可识别性分析解决了模型过度参数化和非唯一性的问题。纵向色散率和热分布因子是高度可识别的，但是空间分布参数只能在注入点附近识别。热和溶质都可以观察到与温度相关的密度效应，因为温度异常增加到 12 摄氏度以上，并影响梯度向下传播。