Core Ideas Land surface models (LSMs) show a large variety in describing and upscaling infiltration. Soil structural effects on infiltration in LSMs are mostly neglected. New soil databases may help to parameterize infiltration processes in LSMs. Infiltration in soils is a key process that partitions precipitation at the land surface into surface runoff and water that enters the soil profile. We reviewed the basic principles of water infiltration in soils and we analyzed approaches commonly used in land surface models (LSMs) to quantify infiltration as well as its numerical implementation and sensitivity to model parameters. We reviewed methods to upscale infiltration from the point to the field, hillslope, and grid cell scales of LSMs. Despite the progress that has been made, upscaling of local‐scale infiltration processes to the grid scale used in LSMs is still far from being treated rigorously. We still lack a consistent theoretical framework to predict effective fluxes and parameters that control infiltration in LSMs. Our analysis shows that there is a large variety of approaches used to estimate soil hydraulic properties. Novel, highly resolved soil information at higher resolutions than the grid scale of LSMs may help in better quantifying subgrid variability of key infiltration parameters. Currently, only a few LSMs consider the impact of soil structure on soil hydraulic properties. Finally, we identified several processes not yet considered in LSMs that are known to strongly influence infiltration. Especially, the impact of soil structure on infiltration requires further research. To tackle these challenges and integrate current knowledge on soil processes affecting infiltration processes into LSMs, we advocate a stronger exchange and scientific interaction between the soil and the land surface modeling communities.

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Objectives The majority of infants in the US do not receive exclusive breastfeeding in the first six months of age, highlighting the necessity of infant formula. The artificially reared piglet is a common model utilized to support substantiation of novel bioactive components in milk or infant formula. However, it is currently unclear to what extent maternal and environmental rearing confounders affect growth outcomes in early life nutrition piglet studies. The objective of the present work is to use historical data to begin to chart typical development of the pig and to develop healthy reference value ranges for the purpose of assessing the safety of bioactive components in infant formula.  Methods 8 piglet studies conducted at the University of Illinois Urbana-Champaign over the past ten years were compiled to create and model reference values for body and organ weights in artificially-reared and sow reared pigs. Metadata were organized to include milk replacer sources, bioactive components, sex, breed, source of herd, feeding rates, rearing styles, and health status. A combination of statistical models including simple linear regression, polynomial regression, and generalized additive models were used to analyze how such parameters influence typical growth. The diet of the 18 studies were blinded during data modeling phase. Results Over 13,000 data points from over 500 animals were identified to be suitable for data mining. Minimal differences in the growth of artificially or sow reared pigs were observed in the first 30 days of life (P  > 0.05). Similarly,  male and female bodyweight growth were nearly identical (P  > 0.05).  Development outcomes such as brain, liver, and intestinal organ weights were classified as typical for developing pigs. A subset of the data containing subjects with poor growth was identified to model growth under deficient or sub-optimal conditions. Conclusions The use of artificial rearing had no impact on body weight, nor did sex contribute to differences in growth during early life. Ultimately, these data can be used to create preliminary weight-for-age charts in the pig model to better interpret whether bioactive ingredients tested in the pig model affect animal growth within typical reference values. Funding Sources Funding was provided by Mead Johnson Nutrition, LLC, a Reckitt Benckiser LLC company.