Expanding the Application of Soil Moisture Monitoring Systems through Regression-Based Transformation
Name
hydr-JHM-D-21-0061.1.pdf
Description
Published version
Size
2.16 MB
Format
Adobe PDF
Checksum (MD5)
64aa6aaefccc6db2c213abafc9809130
Author(s)
Crow, Wade T
Reichle, Rolf H
Dong, Jianzhi
Date Issued
September 29, 2021
Journal
Journal of Hydrometeorology
Publisher
American Meteorological Society
Citation
Crow, W. T., R. H. Reichle, and J. Dong, 2021: Expanding the Application of Soil Moisture Monitoring Systems through Regression-Based Transformation. J. Hydrometeor., 22, 2601–2615.
Version
Final published version
Abstract
Relative to other geophysical variables, soil moisture (SM) estimates derived from land surface models (LSMs) and land data assimilation systems (LDAS) are difficult to transfer between platforms and applications. This difficulty stems from the highly model-dependent nature of LSM SM estimates and differences in the vertical support of discretized SM values. As a result, operational SM estimates generated by one LSM (or LDAS) cannot generally be directly applied to a hydrologic monitoring or forecast system designed around a second LSM. This lack of transferability is particularly problematic for LDAS applications, where the time, expertise, and computational resources required to generate an operational LDAS analysis cannot be practically duplicated for every LSM-specific application. Here, we develop a set of simple regression tools for translating SM estimates between LSMs and multiple LDAS analyses. Results demonstrate that simple multivariate linear regression—utilizing independent variables based on multilayer and temporally lagged SM estimates—can significantly improve upon baseline transformation approaches using direct percentile matching. The proposed regression approaches are effective for both the LSM-to-LSM and LDAS-to-LDAS transformation of multilayer SM percentiles. Application of this approach will expand the utility of existing, high-quality (but LSM-specific) operational sources of SM information like the NASA Soil Moisture Active Passive Level-4 Soil Moisture product.
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DOI of Published Version
https://doi.org/10.1175/JHM-D-21-0061.1
