Optimal interpolation methods for predicting groundwater levels in Abu Dhabi Emirate using ArcGIS
Year: 2025
Type: article
Abstract: This research aimed to determine the optimal interpolation methods for predicting unsampled groundwater levels in Abu Dhabi Emirate. Geostatistical and deterministic interpolation techniques including Inverse Distance Weighting (IDW), Ordinary Kriging (OK), Radial Basis Function (RBF), Global Polynomial Interpolation (GPI) and Local Polynomial Interpolation (LPI) were applied using ArcGIS software. A dataset of 261 wells spanning the period from 2002 to 2013 was utilized using two data selection approaches (random and non-random). Statistical calculations were conducted using SPSS statistics and Excel, while prediction maps were generated using ArcMap 10.8.1. The (LPI) and (EXP-OK) models demonstrated the highest efficiencies and lowest error rates across both selected methods. In contrary, despite of high cross-validation performance, (GPI) could be suitable for broader overviews. Comparisons between random and non-random selection approach revealed the superiority of models with random data selection approach, provides extensive coverage within the critical zones. The EXP-OK interpolation method exhibits the most balanced model between capturing local anomalies and creating smooth gradients within critical zone of 70m to 114m covering 4797.41 for random selection and 2213.49 for non-random selection. This study highlighted the relevance of choosing appropriate models based on the targeted objectives, evaluating interpolation methods under two selection approaches, while examining the effectiveness of both selection methods offering valuable insights for robust groundwater management.
Source: Scientific Reports
Authors: Tala Maksoud, Abdalmonem Alkhawaga, Mohamed Mohamed
Language: English
Subfield: Environmental Engineering
Field: Environmental Science
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $2,690
Award: G3555158368
OpenAlex ID: W4417138683