19 Aug 2025

Do Land Models Miss Key Soil Hydrological Processes Controlling Soil Moisture Memory?

Abstract: Soil moisture memory is critical for understanding climatic, hydrological, and ecosystem interactions. Most land surface models overestimate surface soil moisture and its persistency, sustaining spuriously large soil surface evaporation during dry-down periods. Do LSMs miss or misrepresent key hydrological processes controlling SMM? We used Noah-MP with advanced hydrology that represents preferential flow and surface ponding and provides optional schemes of soil hydraulics. Effects were tested, which are generally missed by LSMs in SMM. We compare SMMs computed from various Noah-MP configurations against that derived from the Soil Moisture Active Passive L3 soil moisture and in situ measurements from the International Soil Moisture Network between 2015 to 2019 over the contiguous US. Results suggest soil hydraulics plays a dominant role and the Van Genuchten hydraulic scheme reduces overestimation of the long-term surface SMM produced by the Brooks–Corey scheme; explicitly representing surface ponding enhances SMM for the surface layer and the root zone; and representing preferential flow improves overall representation of soil moisture dynamics. The combination of these missing schemes can significantly improve the long-term memory overestimation and short-term memory underestimation issues in LSMs. LSMs for use in seasonal-to-subseasonal climate prediction should, at least, adopt the Van Genuchten hydraulic scheme.