Departamento de Ingeniería Hidráulica y Ambiental, Pontificia Universidad Católica de Chile, Avda, Vicuña Mackenna, 4860, Macul, Santiago, Chile.
Departamento de Ingeniería Hidráulica y Ambiental, Pontificia Universidad Católica de Chile, Avda, Vicuña Mackenna, 4860, Macul, Santiago, Chile; Universidad Alas Peruanas Filial Tumbes, Avda. Tumbes Norte 1662, Tumbes, Peru.
J Environ Manage. 2020 May 1;261:110232. doi: 10.1016/j.jenvman.2020.110232. Epub 2020 Mar 2.
To protect fragile groundwater-dependent environments of arid zones, it is important to monitor soil moisture and groundwater evaporation. Hence, it is important to assess new methods to quantify these environmental variables. In this work, we propose a new method to determine groundwater evaporation rates by combining the actively heated fiber-optic (AHFO) method with vadose zone modeling, assuming that the evaporation front remains at the soil surface. In our study, the AHFO method yielded estimates of the soil moisture (θ) profile with a spatial resolution of ~6.5 mm and with an error of 0.026 m m. The numerical model resulted in a slightly different θ profile than that measured, where the largest differences occurred at the soil surface. Sensitivity and uncertainty analyses highlighted that a better precision is required when determining the soil hydraulic parameters. To improve the proposed method, the soil heat-vapor-water dynamics should be included and the assumption that the evaporation front remains at the soil surface must be relaxed. Additionally, if the AHFO calibration curve is enhanced, the errors of the estimated θ profile can be reduced and thus, successful estimation of the evaporation rates for a wider range of soil textures can be achieved. The spatial scales measured are an important advantage of the proposed method that should be further explored to improve the analysis presented here.
为了保护干旱地区脆弱的地下水依赖型环境，监测土壤湿度和地下水蒸发至关重要。因此，评估量化这些环境变量的新方法非常重要。在这项工作中，我们提出了一种新的方法，通过将主动加热光纤（AHFO）方法与土壤水分剖面模型相结合来确定地下水蒸发率，假设蒸发前沿保持在土壤表面。在我们的研究中，AHFO 方法产生的土壤湿度（θ）剖面空间分辨率约为 6.5mm，误差为 0.026m m。数值模型得出的θ剖面与实测值略有不同，最大差异出现在土壤表面。敏感性和不确定性分析强调，在确定土壤水力参数时需要更高的精度。为了改进所提出的方法，应包括土壤热-水汽动力学，并放宽蒸发前沿保持在土壤表面的假设。此外，如果增强 AHFO 校准曲线，则可以减少估计的θ剖面的误差，从而可以实现更广泛的土壤质地范围的蒸发率的成功估计。所提出方法的测量空间尺度是一个重要优势，应进一步探索以改进这里提出的分析。
