ASSIMILATION OF SMAP BASED DISAGGREGATED SOIL MOISTURE FOR IMPROVING SOIL EVAPORATION ESTIMATES BY FAO-2Kc MODEL

Abdelhakim Amazirh; Abdelghani Chehbouni; Olivier Merlin; Elhoussaine Bouras; Salah Er-Raki

doi:10.1109/IGARSS47720.2021.9554432

ASSIMILATION OF SMAP BASED DISAGGREGATED SOIL MOISTURE FOR IMPROVING SOIL EVAPORATION ESTIMATES BY FAO-2Kc MODEL

Abdelhakim Amazirh, Abdelghani Chehbouni, Olivier Merlin, Elhoussaine Bouras, Salah Er-Raki

Research output: Contribution to conference › Paper, not in proceeding › peer-review

Abstract

Food and Agriculture Organization (FAO) dual crop coefficient (FAO-2Kc) is one of the widely used formulation to estimate soil evaporation (E) due to its operationality and simplicity. The FAO-2Kc method could explicitly distinguish the contribution of E and plant transpiration, separately. However, systematic and random uncertainty in E observations still exist. In this vein, this paper attempts to improve FAO-2Kc evapotranspiration estimates through assimilating SMAP-based disaggregated soil moisture (SM) into FAO-2Kc E component via the soil evaporation coefficient. Sequential data assimilation methods (Kalman filter) was used for this purpose, where E is strongly linked to SM especially under arid atmospheric conditions where energy is not the limited factor. The proposed approach is applied over a semi-arid site in central Morocco. Results revealed that the assimilation approach provides better results in term of evapotranspiration by decreasing the root mean square error from 0.98 mm/day to 0.75 mm/day compared to the standard FAO-2Kc.

Original language	English
Pages	6568-6571
Number of pages	4
DOIs	https://doi.org/10.1109/IGARSS47720.2021.9554432
Publication status	Published - 2021
Externally published	Yes
Event	2021 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2021 - Brussels, Belgium Duration: 2021 Jul 12 → 2021 Jul 16

Conference

Conference	2021 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2021
Country/Territory	Belgium
City	Brussels
Period	2021/07/12 → 2021/07/16

Bibliographical note

Funding Information:
This study was conducted within the Center of remote sensing application, at the Mohammed VI university-Morocco and funded by OCP (AS No 71). The in situ data set was provided by the Joint International Laboratory TREMA (https://www.lmi-trema.ma/). The MIT-OCP-CRSA “African data portal geospatial frameworks for science, capacity-building and decision-making purposes” project. RISE-H2020-ACCWA. PRIMA-IDEWA, and PRIMA-ALTOS is also acknowledged.

Publisher Copyright:
© 2021 IEEE

Subject classification (UKÄ)

Soil Science

Free keywords

Data assimilation
FAO-2Kc
SMAP
Soil evaporation
Soil moisture

Access to Document

10.1109/IGARSS47720.2021.9554432

Cite this

@conference{1d2f8404b9944abb88370b11231b2d0d,

title = "ASSIMILATION OF SMAP BASED DISAGGREGATED SOIL MOISTURE FOR IMPROVING SOIL EVAPORATION ESTIMATES BY FAO-2Kc MODEL",

abstract = "Food and Agriculture Organization (FAO) dual crop coefficient (FAO-2Kc) is one of the widely used formulation to estimate soil evaporation (E) due to its operationality and simplicity. The FAO-2Kc method could explicitly distinguish the contribution of E and plant transpiration, separately. However, systematic and random uncertainty in E observations still exist. In this vein, this paper attempts to improve FAO-2Kc evapotranspiration estimates through assimilating SMAP-based disaggregated soil moisture (SM) into FAO-2Kc E component via the soil evaporation coefficient. Sequential data assimilation methods (Kalman filter) was used for this purpose, where E is strongly linked to SM especially under arid atmospheric conditions where energy is not the limited factor. The proposed approach is applied over a semi-arid site in central Morocco. Results revealed that the assimilation approach provides better results in term of evapotranspiration by decreasing the root mean square error from 0.98 mm/day to 0.75 mm/day compared to the standard FAO-2Kc.",

keywords = "Data assimilation, FAO-2Kc, SMAP, Soil evaporation, Soil moisture",

author = "Abdelhakim Amazirh and Abdelghani Chehbouni and Olivier Merlin and Elhoussaine Bouras and Salah Er-Raki",

note = "Funding Information: This study was conducted within the Center of remote sensing application, at the Mohammed VI university-Morocco and funded by OCP (AS No 71). The in situ data set was provided by the Joint International Laboratory TREMA (https://www.lmi-trema.ma/). The MIT-OCP-CRSA “African data portal geospatial frameworks for science, capacity-building and decision-making purposes” project. RISE-H2020-ACCWA. PRIMA-IDEWA, and PRIMA-ALTOS is also acknowledged. Publisher Copyright: {\textcopyright} 2021 IEEE; 2021 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2021 ; Conference date: 12-07-2021 Through 16-07-2021",

year = "2021",

doi = "10.1109/IGARSS47720.2021.9554432",

language = "English",

pages = "6568--6571",

}

Amazirh, A, Chehbouni, A, Merlin, O, Bouras, E & Er-Raki, S 2021, 'ASSIMILATION OF SMAP BASED DISAGGREGATED SOIL MOISTURE FOR IMPROVING SOIL EVAPORATION ESTIMATES BY FAO-2Kc MODEL', Paper presented at 2021 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2021, Brussels, Belgium, 2021/07/12 - 2021/07/16 pp. 6568-6571. https://doi.org/10.1109/IGARSS47720.2021.9554432

ASSIMILATION OF SMAP BASED DISAGGREGATED SOIL MOISTURE FOR IMPROVING SOIL EVAPORATION ESTIMATES BY FAO-2Kc MODEL. / Amazirh, Abdelhakim; Chehbouni, Abdelghani; Merlin, Olivier et al.
2021. 6568-6571 Paper presented at 2021 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2021, Brussels, Belgium.

Research output: Contribution to conference › Paper, not in proceeding › peer-review

TY - CONF

T1 - ASSIMILATION OF SMAP BASED DISAGGREGATED SOIL MOISTURE FOR IMPROVING SOIL EVAPORATION ESTIMATES BY FAO-2Kc MODEL

AU - Amazirh, Abdelhakim

AU - Chehbouni, Abdelghani

AU - Merlin, Olivier

AU - Bouras, Elhoussaine

AU - Er-Raki, Salah

N1 - Funding Information: This study was conducted within the Center of remote sensing application, at the Mohammed VI university-Morocco and funded by OCP (AS No 71). The in situ data set was provided by the Joint International Laboratory TREMA (https://www.lmi-trema.ma/). The MIT-OCP-CRSA “African data portal geospatial frameworks for science, capacity-building and decision-making purposes” project. RISE-H2020-ACCWA. PRIMA-IDEWA, and PRIMA-ALTOS is also acknowledged. Publisher Copyright: © 2021 IEEE

PY - 2021

Y1 - 2021

N2 - Food and Agriculture Organization (FAO) dual crop coefficient (FAO-2Kc) is one of the widely used formulation to estimate soil evaporation (E) due to its operationality and simplicity. The FAO-2Kc method could explicitly distinguish the contribution of E and plant transpiration, separately. However, systematic and random uncertainty in E observations still exist. In this vein, this paper attempts to improve FAO-2Kc evapotranspiration estimates through assimilating SMAP-based disaggregated soil moisture (SM) into FAO-2Kc E component via the soil evaporation coefficient. Sequential data assimilation methods (Kalman filter) was used for this purpose, where E is strongly linked to SM especially under arid atmospheric conditions where energy is not the limited factor. The proposed approach is applied over a semi-arid site in central Morocco. Results revealed that the assimilation approach provides better results in term of evapotranspiration by decreasing the root mean square error from 0.98 mm/day to 0.75 mm/day compared to the standard FAO-2Kc.

AB - Food and Agriculture Organization (FAO) dual crop coefficient (FAO-2Kc) is one of the widely used formulation to estimate soil evaporation (E) due to its operationality and simplicity. The FAO-2Kc method could explicitly distinguish the contribution of E and plant transpiration, separately. However, systematic and random uncertainty in E observations still exist. In this vein, this paper attempts to improve FAO-2Kc evapotranspiration estimates through assimilating SMAP-based disaggregated soil moisture (SM) into FAO-2Kc E component via the soil evaporation coefficient. Sequential data assimilation methods (Kalman filter) was used for this purpose, where E is strongly linked to SM especially under arid atmospheric conditions where energy is not the limited factor. The proposed approach is applied over a semi-arid site in central Morocco. Results revealed that the assimilation approach provides better results in term of evapotranspiration by decreasing the root mean square error from 0.98 mm/day to 0.75 mm/day compared to the standard FAO-2Kc.

KW - Data assimilation

KW - FAO-2Kc

KW - SMAP

KW - Soil evaporation

KW - Soil moisture

U2 - 10.1109/IGARSS47720.2021.9554432

DO - 10.1109/IGARSS47720.2021.9554432

M3 - Paper, not in proceeding

AN - SCOPUS:85130061260

SP - 6568

EP - 6571

T2 - 2021 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2021

Y2 - 12 July 2021 through 16 July 2021

ER -

ASSIMILATION OF SMAP BASED DISAGGREGATED SOIL MOISTURE FOR IMPROVING SOIL EVAPORATION ESTIMATES BY FAO-2Kc MODEL

Abstract

Conference

Bibliographical note

Subject classification (UKÄ)

Free keywords

Access to Document

Fingerprint

Cite this