The Importance of Subsurface Processes in Land Surface Modeling over a Temperate Region: An Analysis with SMAP, Cosmic Ray Neutron Sensing and Triple Collocation Analysis

Abstract

Land surface models (LSMs) simulate water and energy cycles at the atmosphere–soil interface, however, the physical processes in the subsurface are typically oversimplified and lateral water movement is neglected. Here, a cross-evaluation of land surface model results (with and without lateral flow processes), the National Aeronautics and Space Administration (NASA) Soil Moisture Active/Passive (SMAP) mission soil moisture product, and cosmic-ray neutron sensor (CRNS) measurements is carried out over a temperate climate region with cropland and forests over western Germany. Besides a traditional land surface model (the Community Land Model (CLM) version 3.5), a coupled land surface-subsurface model (CLM-ParFlow) is applied. Compared to CLM stand-alone simulations, the coupled CLM-ParFlow model considered both vertical and lateral water movement. In addition to standard validation metrics, a triple collocation (TC) analysis has been performed to help understanding the random error variances of different soil moisture datasets. In this study, it is found that the three soil moisture datasets are consistent. The coupled and uncoupled model simulations were evaluated at CRNS sites and the coupled model simulations showed less bias than the CLM-standalone model (−0.02 cm3 cm−3 vs. 0.07 cm3 cm−3), similar random errors, but a slightly smaller correlation with the measurements (0.67 vs. 0.71). The TC-analysis showed that CLM-ParFlow reproduced better soil moisture dynamics than CLM stand alone and with a higher signal-to-noise ratio. This suggests that the representation of subsurface physics is of major importance in land surface modeling and that coupled land surface-subsurface modeling is of high interest.

Can a Sparse Network of Cosmic Ray Neutron Sensors Improve Soil Moisture and Evapotranspiration Estimation at the Larger Catchment Scale?

“…The CRNS footprint covers up to 18 ha with a measurement depth of up to 80 cm (Bogena et al., 2015; Köhli et al., 2015; Zreda et al., 2008). The continuous development of CRNS technology has enabled SM monitoring under a variety of climatic conditions, which has promoted its application in hydrological modeling (R. Baatz et al., 2017), satellite product validation (Zhao et al., 2021), extreme weather event (drought and flood risk) assessment (Bogena et al., 2022), ecohydrological (e.g., snow, precipitation, and vegetation) monitoring (Bogena et al., 2020), and agricultural management (Li et al., 2019). The advantages of CRNS have made it increasingly attractive, and large‐scale CRNS networks have been established in Europe, the USA, Australia, and India for large‐scale soil moisture monitoring with high temporal resolution, which can also benefit the multifaceted hydrological applications mentioned above.…”

“…Zhao et al. (2021) compared the CRNS data with simulated soil moisture using both the land surface model Community Land Model (CLM, version 3.5) and a coupled land surface‐subsurface model (CLM‐ParFlow). They found that the coupled model simulations showed less bias and reproduced better soil moisture dynamics than the CLM stand‐alone, demonstrating the importance of considering lateral subsurface flow in subsurface hydrological simulations.…”

“…To date, however, such assimilation experiments with CRNS data have been conducted only with land surface models that do not adequately describe lateral water movement and groundwater-land surface interactions (Kollet & Maxwell, 2008). Zhao et al (2021) compared the CRNS data with simulated soil moisture using both the land surface model Community Land Model (CLM, version 3.5) and a coupled land surface-subsurface model (CLM-ParFlow). They found that the coupled model simulations showed less bias and reproduced better soil moisture dynamics than the CLM stand-alone, demonstrating the importance of considering lateral subsurface flow in subsurface hydrological simulations.…”