An impediment in providing in situ, high-resolution observations for soil properties, which are of high spatial and temporal resolution, is the lack of automation or the availability of versatile techniques. Historically, monitoring at watershed scales has relied on in situ measurements that are time-consuming and therefore undersampled, thus providing results that incorrectly portray causal linkages and long-term trends and impede fundamental understanding of soil dynamics. Our approach introduces a new paradigm by combining automated DRI and EMI techniques to provide high spatial and temporal resolution information atop the soil surface and to account for soil heterogeneity in terms of aggregate attributes, landform, and management practices. This variability in terms of soil properties is found to be mostly represented by a log-normal distribution. While not every monitoring program in the country will need to assess the variability of soil properties, the probabilistic approach may be more appropriate than the deterministic one in treating the problem of soil heterogeneity.