Data on spatial and temporal modelling of soil water storage in the Guinea savannah zone of Northern Ghana.

In this article, we present the space-time variability of soil moisture (SM) and soil water storage (SWS) from key agricultural benchmark soil types measured across the Guinea savannah zone of Ghana ( ≈ 2,000 measurements) in a single cropping season (Nketia et al., 2022). From 36 locations, SM measurements were obtained with a PR2/60 moisture probe calibrated for a 0-100 cm soil depth interval (at six depths).

A new method for selecting sites for soil sampling, coupling global weighted principal component analysis and a cost-constrained conditioned Latin hypercube algorithm.

Analysing spatial patterns of soil properties in a landscape requires a sampling strategy that adequately covers soil toposequences. In this context, we developed a hybrid methodology that couples global weighted principal component analysis (GWPCA) and cost-constrained conditioned Latin hypercube algorithm (cLHC). This methodology produce an optimized sampling stratification by analysing the local variability of the soil property, and the influence of environmental factors.