Due to inadequate data support, existing algorithms used to estimate soil hydraulic conductivity, K, in (eco)hydrological models ignore the effects of key site factors such as land use and climate and underplay the significant effects of soil structure on water flow at and near saturation. These limitations may introduce serious bias and error into predictions of terrestrial water balances and soil moisture status, and thus plant growth and rates of biogeochemical processes. To resolve these issues, we collated a new global database of hydraulic conductivity measured by tension infiltrometer under field conditions. The results of our analyses on this data set contrast markedly with those of existing algorithms used to estimate K. For example, saturated hydraulic conductivity, Ks, in the topsoil (Ks depends more strongly on bulk density, organic carbon content and land use. In this respect, organic carbon was negatively correlated with Ks, presumably due to water repellency, while Ks at arable sites was, on average, ca. 2–3 times smaller than under natural vegetation, forests and perennial agriculture. The data also clearly demonstrates that clay soils have smaller K in the soil matrix and thus a larger contribution of soil macropores to K at and near saturation.
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