Additional value of using satellite-based soil moisture and two sources of groundwater data for hydrological model calibration

Mehmet Cüneyd Demirel; Alparslan Özen; Selen Orta; Emir Toker; Hatice Kübra Demir; Ömer Ekmekcioğlu; Hüsamettin Tayşi; Sinan Eruçar; Ahmet Bilal Sağ; Ömer Sari; Ecem Tuncer; Hayrettin Hanci; Türkan Irem Özcan; Hilal Erdem; Mehmet Melih Koşucu; Eyyup Ensar Başakin; Kamal Ahmed; Awat Anwar; Muhammet Bahattin Avcuoğlu; Ömer Vanli; Simon Stisen; Martijn J. Booij

doi:10.3390/w11102083

Additional value of using satellite-based soil moisture and two sources of groundwater data for hydrological model calibration

Mehmet Cüneyd Demirel^*, Alparslan Özen, Selen Orta, Emir Toker, Hatice Kübra Demir, Ömer Ekmekcioğlu, Hüsamettin Tayşi, Sinan Eruçar, Ahmet Bilal Sağ, Ömer Sari, Ecem Tuncer, Hayrettin Hanci, Türkan Irem Özcan, Hilal Erdem, Mehmet Melih Koşucu, Eyyup Ensar Başakin, Kamal Ahmed, Awat Anwar, Muhammet Bahattin Avcuoğlu, Ömer VanliSimon Stisen, Martijn J. Booij

^*Corresponding author for this work

Research output: Contribution to journal › Article › peer-review

28 Citations (Scopus)

Abstract

Although the complexity of physically-based models continues to increase, they still need to be calibrated. In recent years, there has been an increasing interest in using new satellite technologies and products with high resolution in model evaluations and decision-making. The aim of this study is to investigate the value of different remote sensing products and groundwater level measurements in the temporal calibration of a well-known hydrologic model i.e., Hydrologiska Bryåns Vattenbalansavdelning (HBV). This has rarely been done for conceptual models, as satellite data are often used in the spatial calibration of the distributed models. Three different soil moisture products from the European Space Agency Climate Change Initiative Soil Measure (ESA CCI SM v04.4), The Advanced Microwave Scanning Radiometer on the Earth Observing System (EOS) Aqua satellite (AMSR-E), soil moisture active passive (SMAP), and total water storage anomalies from Gravity Recovery and Climate Experiment (GRACE) are collected and spatially averaged over the Moselle River Basin in Germany and France. Different combinations of objective functions and search algorithms, all targeting a good fit between observed and simulated streamflow, groundwater and soil moisture, are used to analyze the contribution of each individual source of information. Firstly, the most important parameters are selected using sensitivity analysis, and then these parameters are included in a subsequent model calibration. The results of our multi-objective calibration reveal a substantial contribution of remote sensing products to the lumped model calibration, even if their spatially-distributed information is lost during the spatial aggregation. Inclusion of new observations, such as groundwater levels from wells and remotely sensed soil moisture to the calibration improves the model's physical behavior, while it keeps a reasonable water balance that is the key objective of every hydrologic model.

Original language	English
Article number	2083
Journal	Water (Switzerland)
Volume	11
Issue number	10
DOIs	https://doi.org/10.3390/w11102083
Publication status	Published - 1 Oct 2019

Bibliographical note

Publisher Copyright:
© 2019 by the authors.

Funding

This research received funding from the TüBITAK grant 118C020. The first author (M.C.D.) is supported by the Turkish Scientific and Technical Research Council (TüBITAK grant 118C020). The co-author K.A. is supported by the Professional Development Research University (PDRU) grant no. Q.J130000.21A2.04E10 of Universiti Teknologi Malaysia. Authors S.S. and M.C.D. acknowledge the financial support for the SPACE project by the Villum Foundation (http://villumfonden.dk/) through their Young Investigator Program (grant VKR023443). We also acknowledge the financial support of the Cornelis Lely Stichting (C.L.S.), Project No. 20957310. We thank Bart van Osnabrugge, Albrecht Weerts and Eric Sprokkereef for providing the meteorological data from the IMPREX project. Groundwater data for the French part of the Moselle sub-basin were obtained from Portail national d'Accès aux Données sur les Eaux Souterraines (http://www.ades.eaufrance.fr/), and for the Saar sub-basin from the Wasser-und Schifffahrtsamt Saarbrücken. We thank Dennis Meissner from Referat M2-Mitarbeiter/innen group in BfG, Koblenz for the valuable discussions about Saar groundwater data during C.L.S. project meetings Acknowledgments: The first author (M.C.D.) is supported by the Turkish Scientific and Technical Research Council (TÜBİTAK grant 118C020). The co-author K.A. is supported by the Professional Development Research University (PDRU) grant no. Q.J130000.21A2.04E10 of Universiti Teknologi Malaysia. Authors S.S. and M.C.D. acknowledge the financial support for the SPACE project by the Villum Foundation (http://villumfonden.dk/) through their Young Investigator Program (grant VKR023443). We also acknowledge the financial support of the Cornelis Lely Stichting (C.L.S.), Project No. 20957310. We thank Bart van Osnabrugge, Albrecht Weerts and Eric Sprokkereef for providing the meteorological data from the IMPREX project. Groundwater data for the French part of the Moselle sub-basin were obtained from Portail national d’Accès aux Données sur les Eaux Souterraines (http://www.ades.eaufrance.fr/), and for the Saar sub-basin from the Wasser-und Schifffahrtsamt Saarbrücken. We thank Dennis Meissner from Referat M2–Mitarbeiter/innen group in BfG, Koblenz for the valuable discussions about Saar groundwater data during C.L.S. project meetings. Funding: This research received funding from the TÜBİTAK grant 118C020.

Funders	Funder number
Portail national d'Accès aux Données sur les Eaux Souterraines
Professional Development Research University	Q.J130000.21A2.04E10
Turkish Scientific and Technical Research Council
Villum Fonden	VKR023443, 20957310
Türkiye Bilimsel ve Teknolojik Araştirma Kurumu	118C020
Universiti Teknologi Malaysia

Keywords

AMSR-E
ESA CCI SM v04.4
GRACE
HBV
Moselle River
SMAP

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Access to Document

10.3390/w11102083

Cite this

Demirel, M. C., Özen, A., Orta, S., Toker, E., Demir, H. K., Ekmekcioğlu, Ö., Tayşi, H., Eruçar, S., Sağ, A. B., Sari, Ö., Tuncer, E., Hanci, H., Özcan, T. I., Erdem, H., Koşucu, M. M., Başakin, E. E., Ahmed, K., Anwar, A., Avcuoğlu, M. B., ... Booij, M. J. (2019). Additional value of using satellite-based soil moisture and two sources of groundwater data for hydrological model calibration. Water (Switzerland), 11(10), Article 2083. https://doi.org/10.3390/w11102083

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title = "Additional value of using satellite-based soil moisture and two sources of groundwater data for hydrological model calibration",

abstract = "Although the complexity of physically-based models continues to increase, they still need to be calibrated. In recent years, there has been an increasing interest in using new satellite technologies and products with high resolution in model evaluations and decision-making. The aim of this study is to investigate the value of different remote sensing products and groundwater level measurements in the temporal calibration of a well-known hydrologic model i.e., Hydrologiska Bry{\aa}ns Vattenbalansavdelning (HBV). This has rarely been done for conceptual models, as satellite data are often used in the spatial calibration of the distributed models. Three different soil moisture products from the European Space Agency Climate Change Initiative Soil Measure (ESA CCI SM v04.4), The Advanced Microwave Scanning Radiometer on the Earth Observing System (EOS) Aqua satellite (AMSR-E), soil moisture active passive (SMAP), and total water storage anomalies from Gravity Recovery and Climate Experiment (GRACE) are collected and spatially averaged over the Moselle River Basin in Germany and France. Different combinations of objective functions and search algorithms, all targeting a good fit between observed and simulated streamflow, groundwater and soil moisture, are used to analyze the contribution of each individual source of information. Firstly, the most important parameters are selected using sensitivity analysis, and then these parameters are included in a subsequent model calibration. The results of our multi-objective calibration reveal a substantial contribution of remote sensing products to the lumped model calibration, even if their spatially-distributed information is lost during the spatial aggregation. Inclusion of new observations, such as groundwater levels from wells and remotely sensed soil moisture to the calibration improves the model's physical behavior, while it keeps a reasonable water balance that is the key objective of every hydrologic model.",

keywords = "AMSR-E, ESA CCI SM v04.4, GRACE, HBV, Moselle River, SMAP",

author = "Demirel, {Mehmet C{\"u}neyd} and Alparslan {\"O}zen and Selen Orta and Emir Toker and Demir, {Hatice K{\"u}bra} and {\"O}mer Ekmekcioğlu and H{\"u}samettin Tay{\c s}i and Sinan Eru{\c c}ar and Sağ, {Ahmet Bilal} and {\"O}mer Sari and Ecem Tuncer and Hayrettin Hanci and {\"O}zcan, {T{\"u}rkan Irem} and Hilal Erdem and Ko{\c s}ucu, {Mehmet Melih} and Ba{\c s}akin, {Eyyup Ensar} and Kamal Ahmed and Awat Anwar and Avcuoğlu, {Muhammet Bahattin} and {\"O}mer Vanli and Simon Stisen and Booij, {Martijn J.}",

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year = "2019",

month = oct,

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doi = "10.3390/w11102083",

language = "English",

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Demirel, MC, Özen, A, Orta, S, Toker, E, Demir, HK, Ekmekcioğlu, Ö, Tayşi, H, Eruçar, S, Sağ, AB, Sari, Ö, Tuncer, E, Hanci, H, Özcan, TI, Erdem, H, Koşucu, MM , Başakin, EE, Ahmed, K, Anwar, A, Avcuoğlu, MB, Vanli, Ö, Stisen, S & Booij, MJ 2019, 'Additional value of using satellite-based soil moisture and two sources of groundwater data for hydrological model calibration', Water (Switzerland), vol. 11, no. 10, 2083. https://doi.org/10.3390/w11102083

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T1 - Additional value of using satellite-based soil moisture and two sources of groundwater data for hydrological model calibration

AU - Demirel, Mehmet Cüneyd

AU - Özen, Alparslan

AU - Orta, Selen

AU - Toker, Emir

AU - Demir, Hatice Kübra

AU - Ekmekcioğlu, Ömer

AU - Tayşi, Hüsamettin

AU - Eruçar, Sinan

AU - Sağ, Ahmet Bilal

AU - Sari, Ömer

AU - Tuncer, Ecem

AU - Hanci, Hayrettin

AU - Özcan, Türkan Irem

AU - Erdem, Hilal

AU - Koşucu, Mehmet Melih

AU - Başakin, Eyyup Ensar

AU - Ahmed, Kamal

AU - Anwar, Awat

AU - Avcuoğlu, Muhammet Bahattin

AU - Vanli, Ömer

AU - Stisen, Simon

AU - Booij, Martijn J.

PY - 2019/10/1

Y1 - 2019/10/1

N2 - Although the complexity of physically-based models continues to increase, they still need to be calibrated. In recent years, there has been an increasing interest in using new satellite technologies and products with high resolution in model evaluations and decision-making. The aim of this study is to investigate the value of different remote sensing products and groundwater level measurements in the temporal calibration of a well-known hydrologic model i.e., Hydrologiska Bryåns Vattenbalansavdelning (HBV). This has rarely been done for conceptual models, as satellite data are often used in the spatial calibration of the distributed models. Three different soil moisture products from the European Space Agency Climate Change Initiative Soil Measure (ESA CCI SM v04.4), The Advanced Microwave Scanning Radiometer on the Earth Observing System (EOS) Aqua satellite (AMSR-E), soil moisture active passive (SMAP), and total water storage anomalies from Gravity Recovery and Climate Experiment (GRACE) are collected and spatially averaged over the Moselle River Basin in Germany and France. Different combinations of objective functions and search algorithms, all targeting a good fit between observed and simulated streamflow, groundwater and soil moisture, are used to analyze the contribution of each individual source of information. Firstly, the most important parameters are selected using sensitivity analysis, and then these parameters are included in a subsequent model calibration. The results of our multi-objective calibration reveal a substantial contribution of remote sensing products to the lumped model calibration, even if their spatially-distributed information is lost during the spatial aggregation. Inclusion of new observations, such as groundwater levels from wells and remotely sensed soil moisture to the calibration improves the model's physical behavior, while it keeps a reasonable water balance that is the key objective of every hydrologic model.

AB - Although the complexity of physically-based models continues to increase, they still need to be calibrated. In recent years, there has been an increasing interest in using new satellite technologies and products with high resolution in model evaluations and decision-making. The aim of this study is to investigate the value of different remote sensing products and groundwater level measurements in the temporal calibration of a well-known hydrologic model i.e., Hydrologiska Bryåns Vattenbalansavdelning (HBV). This has rarely been done for conceptual models, as satellite data are often used in the spatial calibration of the distributed models. Three different soil moisture products from the European Space Agency Climate Change Initiative Soil Measure (ESA CCI SM v04.4), The Advanced Microwave Scanning Radiometer on the Earth Observing System (EOS) Aqua satellite (AMSR-E), soil moisture active passive (SMAP), and total water storage anomalies from Gravity Recovery and Climate Experiment (GRACE) are collected and spatially averaged over the Moselle River Basin in Germany and France. Different combinations of objective functions and search algorithms, all targeting a good fit between observed and simulated streamflow, groundwater and soil moisture, are used to analyze the contribution of each individual source of information. Firstly, the most important parameters are selected using sensitivity analysis, and then these parameters are included in a subsequent model calibration. The results of our multi-objective calibration reveal a substantial contribution of remote sensing products to the lumped model calibration, even if their spatially-distributed information is lost during the spatial aggregation. Inclusion of new observations, such as groundwater levels from wells and remotely sensed soil moisture to the calibration improves the model's physical behavior, while it keeps a reasonable water balance that is the key objective of every hydrologic model.

KW - AMSR-E

KW - ESA CCI SM v04.4

KW - GRACE

KW - HBV

KW - Moselle River

KW - SMAP

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U2 - 10.3390/w11102083

DO - 10.3390/w11102083

M3 - Article

AN - SCOPUS:85073186893

SN - 2073-4441

VL - 11

JO - Water (Switzerland)

JF - Water (Switzerland)

IS - 10

M1 - 2083

ER -

Additional value of using satellite-based soil moisture and two sources of groundwater data for hydrological model calibration

Abstract

Bibliographical note

Funding

Keywords

UN SDGs

Access to Document

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