Haojin Zhao, Carsten Montzka, Johannes Keller, Fang Li, Harry Vereecken, Harrie-Jan Hendricks Franssen
{"title":"How Does Assimilating SMAP Soil Moisture Improve Characterization of the Terrestrial Water Cycle in an Integrated Land Surface-Subsurface Model?","authors":"Haojin Zhao, Carsten Montzka, Johannes Keller, Fang Li, Harry Vereecken, Harrie-Jan Hendricks Franssen","doi":"10.1029/2024wr038647","DOIUrl":null,"url":null,"abstract":"Land surface modeling combined with data assimilation can yield highly accurate soil moisture estimates on regional and global scales. However, most land surface models often neglect lateral surface and subsurface flows, which are crucial for water redistribution and soil moisture. This study applies the Community Land Model (CLM) and the coupled CLM-ParFlow model over a 22,500 <span data-altimg=\"/cms/asset/53d005e1-8ce7-40d8-ba14-a2ac4e19099c/wrcr70140-math-0001.png\"></span><mjx-container ctxtmenu_counter=\"192\" ctxtmenu_oldtabindex=\"1\" jax=\"CHTML\" role=\"application\" sre-explorer- style=\"font-size: 103%; position: relative;\" tabindex=\"0\"><mjx-math aria-hidden=\"true\" location=\"graphic/wrcr70140-math-0001.png\"><mjx-semantics><mjx-mrow><mjx-msup data-semantic-children=\"0,1\" data-semantic- data-semantic-role=\"unknown\" data-semantic-speech=\"km Superscript 2\" data-semantic-type=\"superscript\"><mjx-mtext data-semantic-annotation=\"clearspeak:unit\" data-semantic-font=\"normal\" data-semantic- data-semantic-parent=\"2\" data-semantic-role=\"unknown\" data-semantic-type=\"text\"><mjx-c></mjx-c><mjx-c></mjx-c></mjx-mtext><mjx-script style=\"vertical-align: 0.421em;\"><mjx-mn data-semantic-annotation=\"clearspeak:simple\" data-semantic-font=\"normal\" data-semantic- data-semantic-parent=\"2\" data-semantic-role=\"integer\" data-semantic-type=\"number\" size=\"s\"><mjx-c></mjx-c></mjx-mn></mjx-script></mjx-msup></mjx-mrow></mjx-semantics></mjx-math><mjx-assistive-mml display=\"inline\" unselectable=\"on\"><math altimg=\"urn:x-wiley:00431397:media:wrcr70140:wrcr70140-math-0001\" display=\"inline\" location=\"graphic/wrcr70140-math-0001.png\" xmlns=\"http://www.w3.org/1998/Math/MathML\"><semantics><mrow><msup data-semantic-=\"\" data-semantic-children=\"0,1\" data-semantic-role=\"unknown\" data-semantic-speech=\"km Superscript 2\" data-semantic-type=\"superscript\"><mtext data-semantic-=\"\" data-semantic-annotation=\"clearspeak:unit\" data-semantic-font=\"normal\" data-semantic-parent=\"2\" data-semantic-role=\"unknown\" data-semantic-type=\"text\">km</mtext><mn data-semantic-=\"\" data-semantic-annotation=\"clearspeak:simple\" data-semantic-font=\"normal\" data-semantic-parent=\"2\" data-semantic-role=\"integer\" data-semantic-type=\"number\">2</mn></msup></mrow>${\\text{km}}^{2}$</annotation></semantics></math></mjx-assistive-mml></mjx-container> area in western Germany. Soil moisture retrievals from the Soil Moisture Active Passive mission are assimilated with the Localized Ensemble Kalman Filter (with and without parameter estimation). The simulated soil moisture, evapotranspiration (ET) and groundwater level are evaluated using in situ observations from a Cosmic-Ray Neutron Sensor network, Eddy Covariance (EC) stations and groundwater measurement wells. The assimilation improves the median correlation between simulated and measured soil moisture from 0.72 <span data-altimg=\"/cms/asset/3890f539-af30-4753-9a16-317e8da41c13/wrcr70140-math-0002.png\"></span><mjx-container ctxtmenu_counter=\"193\" ctxtmenu_oldtabindex=\"1\" jax=\"CHTML\" role=\"application\" sre-explorer- style=\"font-size: 103%; position: relative;\" tabindex=\"0\"><mjx-math aria-hidden=\"true\" location=\"graphic/wrcr70140-math-0002.png\"><mjx-semantics><mjx-mrow><mjx-mo data-semantic- data-semantic-role=\"equality\" data-semantic-speech=\"tilde\" data-semantic-type=\"relation\"><mjx-c></mjx-c></mjx-mo></mjx-mrow></mjx-semantics></mjx-math><mjx-assistive-mml display=\"inline\" unselectable=\"on\"><math altimg=\"urn:x-wiley:00431397:media:wrcr70140:wrcr70140-math-0002\" display=\"inline\" location=\"graphic/wrcr70140-math-0002.png\" xmlns=\"http://www.w3.org/1998/Math/MathML\"><semantics><mrow><mo data-semantic-=\"\" data-semantic-role=\"equality\" data-semantic-speech=\"tilde\" data-semantic-type=\"relation\">∼</mo></mrow>${\\sim} $</annotation></semantics></math></mjx-assistive-mml></mjx-container> 0.79 to 0.79 <span data-altimg=\"/cms/asset/b85688ce-3449-4a2b-b005-6a157d8640a6/wrcr70140-math-0003.png\"></span><mjx-container ctxtmenu_counter=\"194\" ctxtmenu_oldtabindex=\"1\" jax=\"CHTML\" role=\"application\" sre-explorer- style=\"font-size: 103%; position: relative;\" tabindex=\"0\"><mjx-math aria-hidden=\"true\" location=\"graphic/wrcr70140-math-0003.png\"><mjx-semantics><mjx-mrow><mjx-mo data-semantic- data-semantic-role=\"equality\" data-semantic-speech=\"tilde\" data-semantic-type=\"relation\"><mjx-c></mjx-c></mjx-mo></mjx-mrow></mjx-semantics></mjx-math><mjx-assistive-mml display=\"inline\" unselectable=\"on\"><math altimg=\"urn:x-wiley:00431397:media:wrcr70140:wrcr70140-math-0003\" display=\"inline\" location=\"graphic/wrcr70140-math-0003.png\" xmlns=\"http://www.w3.org/1998/Math/MathML\"><semantics><mrow><mo data-semantic-=\"\" data-semantic-role=\"equality\" data-semantic-speech=\"tilde\" data-semantic-type=\"relation\">∼</mo></mrow>${\\sim} $</annotation></semantics></math></mjx-assistive-mml></mjx-container> 0.83 and decreases the median unbiased Root Mean Square Error (ubRMSE) from 0.063 <span data-altimg=\"/cms/asset/49c277fd-c5c5-4458-bfa9-1acdc4aa438d/wrcr70140-math-0004.png\"></span><mjx-container ctxtmenu_counter=\"195\" ctxtmenu_oldtabindex=\"1\" jax=\"CHTML\" role=\"application\" sre-explorer- style=\"font-size: 103%; position: relative;\" tabindex=\"0\"><mjx-math aria-hidden=\"true\" location=\"graphic/wrcr70140-math-0004.png\"><mjx-semantics><mjx-mrow><mjx-mo data-semantic- data-semantic-role=\"equality\" data-semantic-speech=\"tilde\" data-semantic-type=\"relation\"><mjx-c></mjx-c></mjx-mo></mjx-mrow></mjx-semantics></mjx-math><mjx-assistive-mml display=\"inline\" unselectable=\"on\"><math altimg=\"urn:x-wiley:00431397:media:wrcr70140:wrcr70140-math-0004\" display=\"inline\" location=\"graphic/wrcr70140-math-0004.png\" xmlns=\"http://www.w3.org/1998/Math/MathML\"><semantics><mrow><mo data-semantic-=\"\" data-semantic-role=\"equality\" data-semantic-speech=\"tilde\" data-semantic-type=\"relation\">∼</mo></mrow>${\\sim} $</annotation></semantics></math></mjx-assistive-mml></mjx-container> 0.060 <span data-altimg=\"/cms/asset/eb1bdfac-9b49-427d-a169-b6c0b47b9085/wrcr70140-math-0005.png\"></span><mjx-container ctxtmenu_counter=\"196\" ctxtmenu_oldtabindex=\"1\" jax=\"CHTML\" role=\"application\" sre-explorer- style=\"font-size: 103%; position: relative;\" tabindex=\"0\"><mjx-math aria-hidden=\"true\" location=\"graphic/wrcr70140-math-0005.png\"><mjx-semantics><mjx-mrow><mjx-msup data-semantic-children=\"0,1\" data-semantic- data-semantic-role=\"unknown\" data-semantic-speech=\"cm Superscript 3\" data-semantic-type=\"superscript\"><mjx-mtext data-semantic-annotation=\"clearspeak:unit\" data-semantic-font=\"normal\" data-semantic- data-semantic-parent=\"2\" data-semantic-role=\"unknown\" data-semantic-type=\"text\"><mjx-c></mjx-c><mjx-c></mjx-c></mjx-mtext><mjx-script style=\"vertical-align: 0.363em;\"><mjx-mn data-semantic-annotation=\"clearspeak:simple\" data-semantic-font=\"normal\" data-semantic- data-semantic-parent=\"2\" data-semantic-role=\"integer\" data-semantic-type=\"number\" size=\"s\"><mjx-c></mjx-c></mjx-mn></mjx-script></mjx-msup></mjx-mrow></mjx-semantics></mjx-math><mjx-assistive-mml display=\"inline\" unselectable=\"on\"><math altimg=\"urn:x-wiley:00431397:media:wrcr70140:wrcr70140-math-0005\" display=\"inline\" location=\"graphic/wrcr70140-math-0005.png\" xmlns=\"http://www.w3.org/1998/Math/MathML\"><semantics><mrow><msup data-semantic-=\"\" data-semantic-children=\"0,1\" data-semantic-role=\"unknown\" data-semantic-speech=\"cm Superscript 3\" data-semantic-type=\"superscript\"><mtext data-semantic-=\"\" data-semantic-annotation=\"clearspeak:unit\" data-semantic-font=\"normal\" data-semantic-parent=\"2\" data-semantic-role=\"unknown\" data-semantic-type=\"text\">cm</mtext><mn data-semantic-=\"\" data-semantic-annotation=\"clearspeak:simple\" data-semantic-font=\"normal\" data-semantic-parent=\"2\" data-semantic-role=\"integer\" data-semantic-type=\"number\">3</mn></msup></mrow>${\\text{cm}}^{3}$</annotation></semantics></math></mjx-assistive-mml></mjx-container>/<span data-altimg=\"/cms/asset/b901e9c3-74e9-456e-80ba-d77cd71572b8/wrcr70140-math-0006.png\"></span><mjx-container ctxtmenu_counter=\"197\" ctxtmenu_oldtabindex=\"1\" jax=\"CHTML\" role=\"application\" sre-explorer- style=\"font-size: 103%; position: relative;\" tabindex=\"0\"><mjx-math aria-hidden=\"true\" location=\"graphic/wrcr70140-math-0006.png\"><mjx-semantics><mjx-mrow><mjx-msup data-semantic-children=\"3,4\" data-semantic- data-semantic-role=\"implicit\" data-semantic-speech=\"normal c normal m cubed\" data-semantic-type=\"superscript\"><mjx-mrow data-semantic-annotation=\"clearspeak:simple;clearspeak:unit\" data-semantic-children=\"0,1\" data-semantic-content=\"2\" data-semantic- data-semantic-parent=\"5\" data-semantic-role=\"implicit\" data-semantic-type=\"infixop\"><mjx-mi data-semantic-annotation=\"clearspeak:simple\" data-semantic-font=\"normal\" data-semantic- data-semantic-parent=\"3\" data-semantic-role=\"latinletter\" data-semantic-type=\"identifier\"><mjx-c></mjx-c></mjx-mi><mjx-mo data-semantic-added=\"true\" data-semantic- data-semantic-operator=\"infixop,\" data-semantic-parent=\"3\" data-semantic-role=\"multiplication\" data-semantic-type=\"operator\" style=\"margin-left: 0.056em; margin-right: 0.056em;\"><mjx-c></mjx-c></mjx-mo><mjx-mi data-semantic-annotation=\"clearspeak:simple\" data-semantic-font=\"normal\" data-semantic- data-semantic-parent=\"3\" data-semantic-role=\"latinletter\" data-semantic-type=\"identifier\"><mjx-c></mjx-c></mjx-mi></mjx-mrow><mjx-script style=\"vertical-align: 0.363em;\"><mjx-mn data-semantic-annotation=\"clearspeak:simple\" data-semantic-font=\"normal\" data-semantic- data-semantic-parent=\"5\" data-semantic-role=\"integer\" data-semantic-type=\"number\" size=\"s\"><mjx-c></mjx-c></mjx-mn></mjx-script></mjx-msup></mjx-mrow></mjx-semantics></mjx-math><mjx-assistive-mml display=\"inline\" unselectable=\"on\"><math altimg=\"urn:x-wiley:00431397:media:wrcr70140:wrcr70140-math-0006\" display=\"inline\" location=\"graphic/wrcr70140-math-0006.png\" xmlns=\"http://www.w3.org/1998/Math/MathML\"><semantics><mrow><msup data-semantic-=\"\" data-semantic-children=\"3,4\" data-semantic-role=\"implicit\" data-semantic-speech=\"normal c normal m cubed\" data-semantic-type=\"superscript\"><mrow data-semantic-=\"\" data-semantic-annotation=\"clearspeak:simple;clearspeak:unit\" data-semantic-children=\"0,1\" data-semantic-content=\"2\" data-semantic-parent=\"5\" data-semantic-role=\"implicit\" data-semantic-type=\"infixop\"><mi data-semantic-=\"\" data-semantic-annotation=\"clearspeak:simple\" data-semantic-font=\"normal\" data-semantic-parent=\"3\" data-semantic-role=\"latinletter\" data-semantic-type=\"identifier\" mathvariant=\"normal\">c</mi><mo data-semantic-=\"\" data-semantic-added=\"true\" data-semantic-operator=\"infixop,\" data-semantic-parent=\"3\" data-semantic-role=\"multiplication\" data-semantic-type=\"operator\"></mo><mi data-semantic-=\"\" data-semantic-annotation=\"clearspeak:simple\" data-semantic-font=\"normal\" data-semantic-parent=\"3\" data-semantic-role=\"latinletter\" data-semantic-type=\"identifier\" mathvariant=\"normal\">m</mi></mrow><mn data-semantic-=\"\" data-semantic-annotation=\"clearspeak:simple\" data-semantic-font=\"normal\" data-semantic-parent=\"5\" data-semantic-role=\"integer\" data-semantic-type=\"number\">3</mn></msup></mrow>${\\mathrm{c}\\mathrm{m}}^{3}$</annotation></semantics></math></mjx-assistive-mml></mjx-container> to 0.050 <span data-altimg=\"/cms/asset/642d06b2-6f05-4f64-bb66-27fbf230a7c7/wrcr70140-math-0007.png\"></span><mjx-container ctxtmenu_counter=\"198\" ctxtmenu_oldtabindex=\"1\" jax=\"CHTML\" role=\"application\" sre-explorer- style=\"font-size: 103%; position: relative;\" tabindex=\"0\"><mjx-math aria-hidden=\"true\" location=\"graphic/wrcr70140-math-0007.png\"><mjx-semantics><mjx-mrow><mjx-mo data-semantic- data-semantic-role=\"equality\" data-semantic-speech=\"tilde\" data-semantic-type=\"relation\"><mjx-c></mjx-c></mjx-mo></mjx-mrow></mjx-semantics></mjx-math><mjx-assistive-mml display=\"inline\" unselectable=\"on\"><math altimg=\"urn:x-wiley:00431397:media:wrcr70140:wrcr70140-math-0007\" display=\"inline\" location=\"graphic/wrcr70140-math-0007.png\" xmlns=\"http://www.w3.org/1998/Math/MathML\"><semantics><mrow><mo data-semantic-=\"\" data-semantic-role=\"equality\" data-semantic-speech=\"tilde\" data-semantic-type=\"relation\">∼</mo></mrow>${\\sim} $</annotation></semantics></math></mjx-assistive-mml></mjx-container> 0.045 <span data-altimg=\"/cms/asset/45604b63-f8ea-445e-9222-8e60f3542508/wrcr70140-math-0008.png\"></span><mjx-container ctxtmenu_counter=\"199\" ctxtmenu_oldtabindex=\"1\" jax=\"CHTML\" role=\"application\" sre-explorer- style=\"font-size: 103%; position: relative;\" tabindex=\"0\"><mjx-math aria-hidden=\"true\" location=\"graphic/wrcr70140-math-0008.png\"><mjx-semantics><mjx-mrow><mjx-msup data-semantic-children=\"0,1\" data-semantic- data-semantic-role=\"unknown\" data-semantic-speech=\"cm Superscript 3\" data-semantic-type=\"superscript\"><mjx-mtext data-semantic-annotation=\"clearspeak:unit\" data-semantic-font=\"normal\" data-semantic- data-semantic-parent=\"2\" data-semantic-role=\"unknown\" data-semantic-type=\"text\"><mjx-c></mjx-c><mjx-c></mjx-c></mjx-mtext><mjx-script style=\"vertical-align: 0.363em;\"><mjx-mn data-semantic-annotation=\"clearspeak:simple\" data-semantic-font=\"normal\" data-semantic- data-semantic-parent=\"2\" data-semantic-role=\"integer\" data-semantic-type=\"number\" size=\"s\"><mjx-c></mjx-c></mjx-mn></mjx-script></mjx-msup></mjx-mrow></mjx-semantics></mjx-math><mjx-assistive-mml display=\"inline\" unselectable=\"on\"><math altimg=\"urn:x-wiley:00431397:media:wrcr70140:wrcr70140-math-0008\" display=\"inline\" location=\"graphic/wrcr70140-math-0008.png\" xmlns=\"http://www.w3.org/1998/Math/MathML\"><semantics><mrow><msup data-semantic-=\"\" data-semantic-children=\"0,1\" data-semantic-role=\"unknown\" data-semantic-speech=\"cm Superscript 3\" data-semantic-type=\"superscript\"><mtext data-semantic-=\"\" data-semantic-annotation=\"clearspeak:unit\" data-semantic-font=\"normal\" data-semantic-parent=\"2\" data-semantic-role=\"unknown\" data-semantic-type=\"text\">cm</mtext><mn data-semantic-=\"\" data-semantic-annotation=\"clearspeak:simple\" data-semantic-font=\"normal\" data-semantic-parent=\"2\" data-semantic-role=\"integer\" data-semantic-type=\"number\">3</mn></msup></mrow>${\\text{cm}}^{3}$</annotation></semantics></math></mjx-assistive-mml></mjx-container>/<span data-altimg=\"/cms/asset/254722ca-17db-4feb-9821-843f679a8554/wrcr70140-math-0009.png\"></span><mjx-container ctxtmenu_counter=\"200\" ctxtmenu_oldtabindex=\"1\" jax=\"CHTML\" role=\"application\" sre-explorer- style=\"font-size: 103%; position: relative;\" tabindex=\"0\"><mjx-math aria-hidden=\"true\" location=\"graphic/wrcr70140-math-0009.png\"><mjx-semantics><mjx-mrow><mjx-msup data-semantic-children=\"3,4\" data-semantic- data-semantic-role=\"implicit\" data-semantic-speech=\"normal c normal m cubed\" data-semantic-type=\"superscript\"><mjx-mrow data-semantic-annotation=\"clearspeak:simple;clearspeak:unit\" data-semantic-children=\"0,1\" data-semantic-content=\"2\" data-semantic- data-semantic-parent=\"5\" data-semantic-role=\"implicit\" data-semantic-type=\"infixop\"><mjx-mi data-semantic-annotation=\"clearspeak:simple\" data-semantic-font=\"normal\" data-semantic- data-semantic-parent=\"3\" data-semantic-role=\"latinletter\" data-semantic-type=\"identifier\"><mjx-c></mjx-c></mjx-mi><mjx-mo data-semantic-added=\"true\" data-semantic- data-semantic-operator=\"infixop,\" data-semantic-parent=\"3\" data-semantic-role=\"multiplication\" data-semantic-type=\"operator\" style=\"margin-left: 0.056em; margin-right: 0.056em;\"><mjx-c></mjx-c></mjx-mo><mjx-mi data-semantic-annotation=\"clearspeak:simple\" data-semantic-font=\"normal\" data-semantic- data-semantic-parent=\"3\" data-semantic-role=\"latinletter\" data-semantic-type=\"identifier\"><mjx-c></mjx-c></mjx-mi></mjx-mrow><mjx-script style=\"vertical-align: 0.363em;\"><mjx-mn data-semantic-annotation=\"clearspeak:simple\" data-semantic-font=\"normal\" data-semantic- data-semantic-parent=\"5\" data-semantic-role=\"integer\" data-semantic-type=\"number\" size=\"s\"><mjx-c></mjx-c></mjx-mn></mjx-script></mjx-msup></mjx-mrow></mjx-semantics></mjx-math><mjx-assistive-mml display=\"inline\" unselectable=\"on\"><math altimg=\"urn:x-wiley:00431397:media:wrcr70140:wrcr70140-math-0009\" display=\"inline\" location=\"graphic/wrcr70140-math-0009.png\" xmlns=\"http://www.w3.org/1998/Math/MathML\"><semantics><mrow><msup data-semantic-=\"\" data-semantic-children=\"3,4\" data-semantic-role=\"implicit\" data-semantic-speech=\"normal c normal m cubed\" data-semantic-type=\"superscript\"><mrow data-semantic-=\"\" data-semantic-annotation=\"clearspeak:simple;clearspeak:unit\" data-semantic-children=\"0,1\" data-semantic-content=\"2\" data-semantic-parent=\"5\" data-semantic-role=\"implicit\" data-semantic-type=\"infixop\"><mi data-semantic-=\"\" data-semantic-annotation=\"clearspeak:simple\" data-semantic-font=\"normal\" data-semantic-parent=\"3\" data-semantic-role=\"latinletter\" data-semantic-type=\"identifier\" mathvariant=\"normal\">c</mi><mo data-semantic-=\"\" data-semantic-added=\"true\" data-semantic-operator=\"infixop,\" data-semantic-parent=\"3\" data-semantic-role=\"multiplication\" data-semantic-type=\"operator\"></mo><mi data-semantic-=\"\" data-semantic-annotation=\"clearspeak:simple\" data-semantic-font=\"normal\" data-semantic-parent=\"3\" data-semantic-role=\"latinletter\" data-semantic-type=\"identifier\" mathvariant=\"normal\">m</mi></mrow><mn data-semantic-=\"\" data-semantic-annotation=\"clearspeak:simple\" data-semantic-font=\"normal\" data-semantic-parent=\"5\" data-semantic-role=\"integer\" data-semantic-type=\"number\">3</mn></msup></mrow>${\\mathrm{c}\\mathrm{m}}^{3}$</annotation></semantics></math></mjx-assistive-mml></mjx-container>. ET characterization shows a limited improvement with a highest ubRMSE reduction of 15% at the Rollesbroich1 site with the CLM-ParFlow model. The assimilation does not improve the groundwater level characterization. Furthermore, the joint state-parameter update does not outperform state-only update. Overall, the simulation of full 3D subsurface hydrology with the ParFlow model component results in additional model outputs like groundwater levels and river stages, and a better soil moisture characterization (compared to CLM stand-alone), but it does not make soil moisture assimilation more efficient to correct model states.","PeriodicalId":23799,"journal":{"name":"Water Resources Research","volume":"237 1","pages":""},"PeriodicalIF":5.0000,"publicationDate":"2025-05-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Water Resources Research","FirstCategoryId":"89","ListUrlMain":"https://doi.org/10.1029/2024wr038647","RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ENVIRONMENTAL SCIENCES","Score":null,"Total":0}
引用次数: 0
Abstract
Land surface modeling combined with data assimilation can yield highly accurate soil moisture estimates on regional and global scales. However, most land surface models often neglect lateral surface and subsurface flows, which are crucial for water redistribution and soil moisture. This study applies the Community Land Model (CLM) and the coupled CLM-ParFlow model over a 22,500 area in western Germany. Soil moisture retrievals from the Soil Moisture Active Passive mission are assimilated with the Localized Ensemble Kalman Filter (with and without parameter estimation). The simulated soil moisture, evapotranspiration (ET) and groundwater level are evaluated using in situ observations from a Cosmic-Ray Neutron Sensor network, Eddy Covariance (EC) stations and groundwater measurement wells. The assimilation improves the median correlation between simulated and measured soil moisture from 0.72 0.79 to 0.79 0.83 and decreases the median unbiased Root Mean Square Error (ubRMSE) from 0.063 0.060 / to 0.050 0.045 /. ET characterization shows a limited improvement with a highest ubRMSE reduction of 15% at the Rollesbroich1 site with the CLM-ParFlow model. The assimilation does not improve the groundwater level characterization. Furthermore, the joint state-parameter update does not outperform state-only update. Overall, the simulation of full 3D subsurface hydrology with the ParFlow model component results in additional model outputs like groundwater levels and river stages, and a better soil moisture characterization (compared to CLM stand-alone), but it does not make soil moisture assimilation more efficient to correct model states.
期刊介绍:
Water Resources Research (WRR) is an interdisciplinary journal that focuses on hydrology and water resources. It publishes original research in the natural and social sciences of water. It emphasizes the role of water in the Earth system, including physical, chemical, biological, and ecological processes in water resources research and management, including social, policy, and public health implications. It encompasses observational, experimental, theoretical, analytical, numerical, and data-driven approaches that advance the science of water and its management. Submissions are evaluated for their novelty, accuracy, significance, and broader implications of the findings.