Comparing and Evaluating Probabilistic and Deterministic Spatial Interpolation Methods for Groundwater Level of Haouz in Morocco

Abstract

Growing water scarcity is one of the major challenges of the 21st century, especially in arid and semi-arid climates such as our study area. The efficient, sustainable and integrated groundwater management plays a key role for conserving this vital resource. In order to overcome this issue, the study of aquifer system’s behavior seems necessary. For this purpose, the areal piezometric level map is an essential tool. As piezometric level data are spatially limited in sample points, the spatial interpolation and geostatistics are the best way to produce the needed map. Several methods exist allowing to approach real values with varying degrees of accuracy. This work aims to compare and evaluate spatial interpolation methods for groundwater level of Haouz using a dataset of 39 piezometers. The deterministic methods used in this study are Inverse Distance Weighted (IDW) and Radial Basis Functions (RBF) and the probabilistic ones are ordinary kriging (OK), simple kriging (SK) and universal kriging (UK). This study shows the difficulty of having a key role to choose the suitable method for given input dataset. The best model remains the one that, after comparing several methods, offers the best accuracy, which is assessed using Cross-validation and statistical indicators. The results reveals that ordinary kriging with trend removal technique is the optimal method in this case. It indicates the superiority of this technique with a decrease in Root Mean Square Error (RMSE) up to 61.67%. It underestimates groundwater level with an average of 2.8%, which is reliable. The areal piezometric level and associated prediction standard error maps give additional information and recommendations that characterize the studied aquifer system and will ultimately improve sustainable groundwater management.