地下水深度估算的最优插值法

IF 1.6 Q2 MULTIDISCIPLINARY SCIENCES MethodsX Pub Date : 2024-08-15 DOI:10.1016/j.mex.2024.102916
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引用次数: 0

摘要

在地表水资源匮乏的干旱和半干旱地区,地下水至关重要。准确绘制地下水深度图对于可持续管理至关重要。本研究评估了三种空间插值技术--反距离加权法(IDW)、普通克里金法(OK)和径向基函数法(RBF)--在预测埃塞俄比亚迪雷达瓦市地下水深度分布方面的性能。结果表明,与 IDW 和 OK 相比,RBF 方法的 RMSE(3.21 米)、MAE(0.16 米)最低,R2(0.99)最高,具有优势。其次是 IDW 方法(RMSE = 4.68 m,MAE = 0.16 m,R2= 0.97),然后是 OK 方法(RMSE = 5.32 m,MAE = 0.42 m,R2= 0.95)。RBF 的超高精度与其他半干旱地区的研究结果一致,突出表明它适用于像德雷达瓦这样的数据稀缺地区。这种比较评估为地下水深度绘图选择最佳插值方法提供了有价值的见解,为当地水资源管理的知情决策提供了支持。方法包括:-利用分散在整个研究区域的 56 个地点的地下水深度测量数据,实施三种插值技术,即反距离加权(IDW)、普通克里金(OK)和径向基函数(RBF)。-通过随机扣留 20% 的数据进行交叉验证。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

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Optimal interpolation approach for groundwater depth estimation

In arid and semi-arid regions where surface water resources are scarce, groundwater is crucial. Accurate mapping of groundwater depth is vital for sustainable management practices. This study evaluated the performance of three spatial interpolation techniques – inverse distance weighting (IDW), ordinary kriging (OK), and radial basis functions (RBF) – in predicting groundwater depth distribution across Dire Dawa City, Ethiopia. The results demonstrated the superiority of the RBF method, exhibiting the lowest RMSE (3.21 m), MAE (0.16 m), and the highest R2 (0.99) compared to IDW and OK. The IDW method emerged as the next best performer (RMSE = 4.68 m, MAE = 0.16 m, R2= 0.97), followed by OK (RMSE = 5.32 m, MAE = 0.42 m, R2= 0.95). The RBF's superior accuracy aligns with findings from other semi-arid regions, underscoring its suitability for data-scarce areas like Dire Dawa. This comparative evaluation provides valuable insights for selecting the optimal interpolation method for groundwater depth mapping, supporting informed decision-making in local water resource management.

The methodological approach comprised:

  • Implementation of three interpolation techniques, namely, inverse distance weighting (IDW), ordinary kriging (OK), and radial basis functions (RBF), utilizing 56 groundwater depth measurements from locations dispersed throughout the study area.

  • Cross-validation through randomly withholding 20 % of the data for validation purposes.

  • Comparison of the techniques based on statistical measures of accuracy, including root mean square error (RMSE), mean absolute error (MAE), and the coefficient of determination (R2).

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来源期刊
MethodsX
MethodsX Health Professions-Medical Laboratory Technology
CiteScore
3.60
自引率
5.30%
发文量
314
审稿时长
7 weeks
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