State updating of root zone soil moisture estimates of an unsaturated zone metamodel for operational water resources management

Michiel Pezij*, Denie C.M. Augustijn, Dimmie M.D. Hendriks, Albrecht H. Weerts, Stef Hummel, Rogier van der Velde, Suzanne J.M.H. Hulscher

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

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Abstract

Combining metamodels with data assimilation schemes allows the incorporation of up-to-date information in metamodels, offering new opportunities for operational water resources management. We developed a data assimilation scheme for the unsaturated zone metamodel MetaSWAP using OpenDA, which is an open source data assimilation framework. A twin experiment showed the feasibility of applying an Ensemble Kalman filter as a data assimilation method for updating metamodels. Furthermore, we assessed the accuracy of root zone soil moisture model estimates when assimilating the regional SMAP L3 Enhanced surface soil moisture product. The model accuracy is assessed using in situ soil moisture measurements collected at 12 locations in the Twente region, the Netherlands. Although the accuracy of the model estimates does not improve in terms of correlation coefficient, the accuracy does improve in terms of Root Mean Square Error and bias. Therefore, the assimilation of surface soil moisture observations has value for updating root zone soil moisture model estimates. In addition, the accuracy of the model estimates improves on both regional and local spatial scales. The increasing availability of remotely sensed soil moisture data will lead to new possibilities for integrating metamodelling and data assimilation in operational water resources management. However, we expect that significant investments in computational capacities are necessary for effective implementation in decision-making.

Original languageEnglish
Article number100040
Number of pages13
JournalJournal of Hydrology X
Volume4
DOIs
Publication statusPublished - 1 Jul 2019

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vadose zone
rhizosphere
data assimilation
soil moisture
Kalman filter
water resources management
decision making
experiment

Keywords

  • Data assimilation
  • Ensemble Kalman filter
  • Hydrological modelling
  • Metamodelling
  • Remote sensing
  • SMAP
  • Soil moisture

Cite this

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title = "State updating of root zone soil moisture estimates of an unsaturated zone metamodel for operational water resources management",
abstract = "Combining metamodels with data assimilation schemes allows the incorporation of up-to-date information in metamodels, offering new opportunities for operational water resources management. We developed a data assimilation scheme for the unsaturated zone metamodel MetaSWAP using OpenDA, which is an open source data assimilation framework. A twin experiment showed the feasibility of applying an Ensemble Kalman filter as a data assimilation method for updating metamodels. Furthermore, we assessed the accuracy of root zone soil moisture model estimates when assimilating the regional SMAP L3 Enhanced surface soil moisture product. The model accuracy is assessed using in situ soil moisture measurements collected at 12 locations in the Twente region, the Netherlands. Although the accuracy of the model estimates does not improve in terms of correlation coefficient, the accuracy does improve in terms of Root Mean Square Error and bias. Therefore, the assimilation of surface soil moisture observations has value for updating root zone soil moisture model estimates. In addition, the accuracy of the model estimates improves on both regional and local spatial scales. The increasing availability of remotely sensed soil moisture data will lead to new possibilities for integrating metamodelling and data assimilation in operational water resources management. However, we expect that significant investments in computational capacities are necessary for effective implementation in decision-making.",
keywords = "Data assimilation, Ensemble Kalman filter, Hydrological modelling, Metamodelling, Remote sensing, SMAP, Soil moisture",
author = "Michiel Pezij and Augustijn, {Denie C.M.} and Hendriks, {Dimmie M.D.} and Weerts, {Albrecht H.} and Stef Hummel and {van der Velde}, Rogier and Hulscher, {Suzanne J.M.H.}",
year = "2019",
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State updating of root zone soil moisture estimates of an unsaturated zone metamodel for operational water resources management. / Pezij, Michiel; Augustijn, Denie C.M.; Hendriks, Dimmie M.D.; Weerts, Albrecht H.; Hummel, Stef; van der Velde, Rogier; Hulscher, Suzanne J.M.H.

In: Journal of Hydrology X, Vol. 4, 100040, 01.07.2019.

Research output: Contribution to journalArticleAcademicpeer-review

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AU - Augustijn, Denie C.M.

AU - Hendriks, Dimmie M.D.

AU - Weerts, Albrecht H.

AU - Hummel, Stef

AU - van der Velde, Rogier

AU - Hulscher, Suzanne J.M.H.

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