Department of Civil, Environmental and Geomatics Engineering, Florida Atlantic University, 777 Glades Road, Boca Raton, Florida, 33431, USA.
Department of Geosciences, Florida Atlantic University, 777 Glades Road, Boca Raton, Florida, 33431, USA.
Ground Water. 2021 Mar;59(2):190-198. doi: 10.1111/gwat.13041. Epub 2020 Sep 9.
Predicting and mapping high water table elevation in coastal landscapes is critical for both science application projects like inundation risk analysis and engineering projects like pond design and maintenance. Previous studies of water table mapping focused on the application of geostatistical methods, which cannot predict values beyond an observation spatial domain or generate an ideal pattern for regions with sparse measurements. In this study, we evaluated the multiple linear regression (MLR) and support vector machine (SVM) techniques for high water table prediction and mapping using fine spatial resolution lidar-derived Digital Elevation Model (DEM) data, and designed an application protocol of these two techniques for high water table mapping in a coastal landscape where groundwater, tide, and surface water are related. Testing results showed that SVM largely improved the high water table prediction with a mean absolute error (MAE) of 1.22 feet and root mean square error (RMSE) of 2.22 feet compared to the application of the ordinary Kriging method which could not generate a reasonable water table. MLR was also promising with a MAE of around 2 feet and RMSE of around 3 feet. The study suggests that both MLR and SVM are valuable alternatives to estimate high water table elevation in Florida. Fine resolution lidar DEMs are beneficial for high water table prediction and mapping.
预测和绘制沿海景观高地下水位图对于洪水风险分析等科学应用项目以及池塘设计和维护等工程项目都至关重要。先前的地下水位图绘制研究集中于应用地质统计学方法，这些方法无法预测观测空间域之外的值，也无法为测量稀疏的区域生成理想的模式。在这项研究中，我们评估了多元线性回归（MLR）和支持向量机（SVM）技术在使用精细空间分辨率激光雷达衍生数字高程模型（DEM）数据进行高地下水位预测和制图方面的应用，并为地下水、潮汐和地表水相关的沿海景观中的高地下水位制图设计了这两种技术的应用方案。测试结果表明，与无法生成合理地下水位的普通克里金法应用相比，SVM 极大地提高了高地下水位预测的准确性，平均绝对误差（MAE）为 1.22 英尺，均方根误差（RMSE）为 2.22 英尺。MLR 也很有前途，MAE 约为 2 英尺，RMSE 约为 3 英尺。该研究表明，MLR 和 SVM 都是在佛罗里达州估算高地下水位的有价值的替代方法。精细分辨率激光雷达 DEM 有利于高地下水位的预测和制图。
