How Critical Is the Assimilation Frequency of Water Content Measurements for Obtaining Soil Hydraulic Parameters with Data Assimilation?

Autor: Yakov Pachepsky, Concepción Pla, Gonzalo Martinez, Javier Valdes-Abellan
Přispěvatelé: Universidad de Alicante. Departamento de Ingeniería Civil, Ingeniería Hidráulica y Ambiental (IngHA), Petrología Aplicada
Rok vydání: 2019
Předmět:
Zdroj: Vadose Zone Journal, Vol 18, Iss 1 (2019)
RUA. Repositorio Institucional de la Universidad de Alicante
Universidad de Alicante (UA)
ISSN: 1539-1663
DOI: 10.2136/vzj2018.07.0142
Popis: Data assimilation (DA) is a promising alternative to infer soil hydraulic parameters from soil water dynamics data. Frequency of measurements and updates are important controls of DA efficiency; however, no strict guidance exists on determining the optimal frequency. In this study, DA was performed with the ensemble Kalman filter (EnKF) with a state augmentation approach to update both model states and parameters. We analyzed updates every 1, 2, 3, 5, 7, 9, 11, and 14 d. Two soil types (sandy loam and loam) and four climates (hot semiarid [Bwh], cold semiarid [Bsk], humid continental [Dfa], and humid subtropical [Cfa]) were considered. Results demonstrate that DA with high update frequencies does not provide better results than results obtained when using low frequencies. For sandy loam soil, assimilation of data every seven or more days yields better results for whatever climate considered. For loam soil, the same is true after 9 mo of assimilation. The chosen performance metric may affect the results, but the general trend of better results with low assimilation frequencies does not change. This study forms part of the projects GRE15-19 and GRE17-12 financed by the University of Alicante. A post-doctoral research fellowship (CAS 15/00244) funded by the Spanish Ministry of Science and Innovation was awarded to J. Valdes-Abellan for this project.
Databáze: OpenAIRE
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