What Are The Key Soil Hydrological Processes To Control Soil Moisture Memory?
Presenter: Mohammad Farmani1
Co-Author(s): Aniket Gupta, Ahmad Tavakoly, Matthew Geheran
Advisor(s): Guo-Yue Niu and Ali Behrangi
1Department of Hydrology and Atmospheric Sciences, University of Arizona
Soil moisture memory (SMM), which measures how long a perturbation in soil moisture can last, is critical for understanding climatic, hydrologic, and ecosystem interactions. Most land surface models (LSMs) tend to overestimate surface soil moisture and its persistency, sustaining unexpectedly large soil surface evaporation. This study aims to use SMM) as a metric to 1) identify key soil hydrological/hydraulic processes that contribute to SMM and 2) improve the representations of soil hydrology using the widely-used Noah-MP LSM with optional physical representations of soil hydrology/hydraulics. We compare the computed SMM from various Noah-MP configurations against the benchmark data of the Soil Moisture Active Passive (SMAP) Level 3 and in-situ measurements of the International Soil Moisture Network (ISMN) from 2015 to 2019 over the contiguous United States (CONUS). The results suggest that 1) soil hydraulics plays a dominant role, and the Van-Genuchten hydraulic scheme reduces the overestimation of the long-term surface SMM produced by the Brooks-Corey scheme commonly used in LSMs; 2) Explicitly representing surface ponding prolongs SSM by allowing extended infiltration periods, improving SSM for both the surface layer and the root zone; and 3) Enhanced permeability through macropores enhances the overall representation of soil hydraulic dynamics. It has been instrumental in improving the SMM across both Stage-I and Stage-II evapotranspiration processes. In overall, the combination of the schemes introduced in this study could significantly improve the long-term memory overestimation and short-term memory underestimation issue observed in common LSMs.