E valuation of s urface soil moisture is necessary to understand spatiotemporal soil moisture trends and their implications on water resources management. This research evaluated a real - time instantiation of NASA’s Land Information System (LIS) for water resources manageme nt applications at a higher spatial and temporal resolution than is currently available with remotely - sensed satellite estimates or in situ measurements of the same product. Ma naged by NASA’s Short - term Prediction Research and Transition (SPoRT) Center, th e “SPoRT - LIS” is an observation - driven , real - time simulation of the Noah land surface model at a 3 - km resolution over the full continental United States . Surface soil moisture estimates from SPoRT - LIS (0 - 10 cm layer ) w ere validated against in situ soil moisture from the International Soil Moisture Network in the M issouri and Arkansas - Red - White R iv er B asins. Validation was conducted at in situ measurement depths of 5 - cm and 10 - cm , and performance was evaluated across varying soil types, land cover, 2 depth, slope, aspect, and pixel heterogeneity to determine conditions under which SPoRT - LIS surface soil moisture had excellent estimation capability. Results demonstrate that 53% of data at a depth of 5 - cm and 51% of the data at a depth of 10 - cm w ere significan tly correlated with a Spearman’s ρ greater than 0.5 on a daily basis . Based upon validation results, it is evident that t he SPoRT - LIS surface soil moisture estimate is satisfactory for research and operational water resources management applications .
