Many parameters in environmental, scientific and human sciences investigations need to be interpolated. Geostatistics, with its structural analysis step, is widely used for this purpose. This precious step that evaluates data correlation and dependency is performed thanks to semivariogram. However, an incorrect choice of a semivariogram model can skew all the prediction results. The main objectives of this paper are (1) to simply illustrate the influence of the choice of an inappropriate semivariogram model and (2) to show how a best-fitted model can be selected. This may lessen the adverse effect of the semivariogram model selection on an interpolation survey using kriging technique. The influence of the semivariogram model selection is highlighted and illustrated by thematic maps drawn using four different models (Gaussian, magnetic, spherical and exponential). Then, a guideline to select the most suitable model, using mean error (ME), mean square error (MSE), root mean square error (RMSE), average standard error (ASE), and root mean square standardized error (RMSSE), is proposed. The choice of a semivariogram model seriously influences the results of a kriging survey at both endpoints and amplitude of the range of the estimated values. However, the direction of variation of the interpolated values is independent of the semivariogram model: different semivariogram models (with the same characteristics) produce different thematic maps but, the areas of minimum and maximum values remain unchanged. Yet, the suitable model can be selected by means of ME, MSE, RMSE, ASE and RMSSE. The present article illustrates how the use of an inappropriate semivariogram model can seriously distort the results of an evaluation, assessment or prediction survey. To avoid such an inconveniency, a methodical approach based on the computation and analysis of ME, RMSE, ASE, RMSSE and MSE is proposed.

Water stress is an everyday issue in developing countries and especially in Foumban, a municipality located in the West Region of Cameroon between longitudes 10^°40’-11^°10’E and latitudes 05^°30’-05^°55’N. The failure of the water distribution system in the Municipality of Foumban (MoF) led the citizens as well as the municipal authorities to exploit groundwater. Unfortunately, an extensive hydrogeophysical field campaign, with incidental cost, is required because the groundwater potential is not priorly assessed. The main objective of this article is to demarcate groundwater potential zones of MoF. For this, six thematic layers contributing to groundwater occurrences are combined using analytical hierarchy process (AHP) on a GIS environment to produce a sound groundwater potential map. This map is classified into three zones: low potential for 39.06%, acceptable potential for 27.27% and high potential for 33.68% of the study area. This may help to increase the rate of productive wells (by focusing hydrogeophysical investigation on areas with high groundwater potential) using little financial resources.