Contribution of infiltration process uncertainty on the simulation of terrestrial water and energy budgets

Land surface models (LSMs) have been widely used in agriculture management, flood prevention, and drought simulation. Infiltration is the top boundary condition for the solution of water redistribution below ground surface in the LSMs. Infiltration schemes partition throughfall, which is the part of precipitation penetrating through canopy and reaches soil surface, into surface runoff and infiltration water. The infiltration water then redistributes into soil layers and eventually leaves the soil column as transpiration, subsurface runoff, and deep drainage. The modeling of infiltration process has profound impacts on the output and state variables of LSMs, such as evapotranspiration, soil moisture, and runoffs.

It is difficult to directly assess the infiltration schemes at the operational scales of numerical weather forecasts and hydrometeorological applications, as no direct measurements of infiltration are typically available. Observational datasets of evapotranspiration, soil moisture contents, and streamflow are relevant but not only related to infiltration. To reveal the sources of uncertainty possibly brought by the infiltration schemes, we present an intercomparison study of LSMs from the perspective of infiltration. The study is based on the software framework of the NASA Land Information System (LIS), which has an array of LSMs integrated, for example, JULES, Noah-MP, Noah, and VIC. These models use different physical or conceptual schemes to describe the infiltration process.

In this study, we compare the throughfall and infiltration outputs from the four LSMs. All analyses are conducted with the NLDAS Science Testbed, in which LIS runs over the NLDAS domain with the same forcing data. The results of this study provide important insights into understanding the infiltration behavior of these models. Such insights will be helpful for evaluating uncertainties in streamflow, evapotranspiration, and estimates of hydrologic extremes simulated with various LSMs and modeling systems.