Accurate soil moisture and streamflow data are an aspirational need of many hydrologically relevant fields. Model simulated soil moisture and streamflow hold promise but models require validation prior to application. Calibration methods are commonly used to improve model fidelity but misrepresentation of the true dynamics remains a challenge. In this study, we leverage soil parameter estimates from the Soil Survey Geographic (SSURGO) database and the probability mapping of SSURGO (POLARIS) to improve the representation of hydrologic processes in the Weather Research and Forecasting Hydrological modeling system (WRF‐Hydro) over a central California domain. Our results show WRF‐Hydro soil moisture exhibits increased correlation coefficients (
This content will become publicly available on May 29, 2025
- Award ID(s):
- 2012893
- PAR ID:
- 10514649
- Publisher / Repository:
- Wiley
- Date Published:
- Journal Name:
- Water Resources Management
- ISSN:
- 0920-4741
- Subject(s) / Keyword(s):
- critical zone observatory
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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