Volume 59, Issue 4 e2022WR032336
Research Article

The Benefits of Using State-Of-The-Art Digital Soil Properties Maps to Improve the Modeling of Soil Moisture in Land Surface Models

Chengcheng Xu

Corresponding Author

Chengcheng Xu

Department of Civil and Environmental Engineering, Duke University, Durham, NC, USA

Correspondence to:

C. Xu,

[email protected]

Search for more papers by this author
Laura Torres-Rojas

Laura Torres-Rojas

Department of Civil and Environmental Engineering, Duke University, Durham, NC, USA

Search for more papers by this author
Noemi Vergopolan

Noemi Vergopolan

Program in Atmospheric and Oceanic Sciences, Princeton University, Princeton, NJ, USA

NOAA Geophysical Fluid Dynamics Laboratory, Princeton, NJ, USA

Search for more papers by this author
Nathaniel W. Chaney

Nathaniel W. Chaney

Department of Civil and Environmental Engineering, Duke University, Durham, NC, USA

Search for more papers by this author
First published: 25 March 2023
Citations: 1

Abstract

This study assesses the added value of using emerging maps of soil properties to improve surface soil moisture simulations using the HydroBlocks land surface model with different soil hydraulic parameterization schemes. Simulations were run at an hourly 30-m resolution between 2012 and 2019 and evaluated against U.S. Climate Reference Network measurements. The results show that state-of-the-art soil properties maps (POLARIS and SoilGrids250m V2.0) improve the accuracy of simulated surface soil moisture when compared to the STATSGO-derived CONUS-SOIL map. Contemporary pedotransfer functions (multi-linear regression and Artificial Neural Networks-based) also improve model performance in comparison to the lookup table-derived soil parameterization schemes. The addition of vertical heterogeneity to the soil properties further improves the mean Kling-Gupta efficiency by 0.04 and lowers the mean Root mean square error by 0.003 over the CONUS. This study demonstrates that land surface modeling can be improved by using state-of-the-art maps of soil properties, accounting for the vertical heterogeneity of soils, and advancing the use of contemporary pedotransfer functions.

Key Points

  • State-of-the-art digital soil maps improve the agreement between soil moisture modeling and observations

  • Including vertical soil heterogeneity improves the accuracy of simulated soil moisture

  • Simulating soil moisture using soil hydraulic properties computed from contemporary pedotransfer functions generally outperforms classic lookup tables

Plain Language Summary

This work studied if advanced soil properties maps can improve soil moisture modeling using a Land Surface Model. The model was run over 7 years and was compared to site measurements. The results showed that using contemporary soil properties maps and pedotransfer functions to estimate soil properties improved model performance, especially for soils with different layers. This study demonstrated that improving hydraulic modeling is possible by using soil properties maps and contemporary pedotransfer functions in the setting of different vertical layers.

Data Availability Statement

POLARIS, SoilGrids250m V2.0, and CONUS-SOIL soil data used in this work can be found at the following site: http://hydrology.cee.duke.edu/POLARIS/ (Chaney et al., 2019; Chaney, Wood, et al., 2016); https://soilgrids.org/ (Poggio et al., 2021, p. 2); http://www.soilinfo.psu.edu/index.cgi?soil_data&conus (Miller & White, 1998). The HydroBlocks model (Chaney et al., 2021) code used in this study is preserved at https://zenodo.org/record/4071692. The USCRN soil moisture is available online at https://www.ncei.noaa.gov/access/crn/qcdatasets.html (Bell et al., 2013).