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1. Evaluation of Statistical and Deep Learning Methods for Short-Term Weather Forecasting in Semi-arid Regions

Author

El Hachimi, Chouaib, Belaqziz, Salwa, Khabba, Saïd, Chehbouni, Abdelghani, Pisello, Anna Laura, Editorial Board Member, Hawkes, Dean, Editorial Board Member, Bougdah, Hocine, Editorial Board Member, Rosso, Federica, Editorial Board Member, Abdalla, Hassan, Editorial Board Member, Boemi, Sofia-Natalia, Editorial Board Member, Mohareb, Nabil, Editorial Board Member, Mesbah Elkaffas, Saleh, Editorial Board Member, Bozonnet, Emmanuel, Editorial Board Member, Pignatta, Gloria, Editorial Board Member, Mahgoub, Yasser, Editorial Board Member, De Bonis, Luciano, Editorial Board Member, Kostopoulou, Stella, Editorial Board Member, Pradhan, Biswajeet, Editorial Board Member, Abdul Mannan, Md., Editorial Board Member, Alalouch, Chaham, Editorial Board Member, Gawad, Iman O., Editorial Board Member, Nayyar, Anand, Editorial Board Member, Amer, Mourad, Series Editor, Chenchouni, Haroun, editor, Zhang, Zhihua, editor, Bisht, Deepak Singh, editor, Gentilucci, Matteo, editor, Chen, Mingjie, editor, Chaminé, Helder I., editor, Barbieri, Maurizio, editor, Jat, Mahesh Kumar, editor, Rodrigo-Comino, Jesús, editor, Panagoulia, Dionysia, editor, Kallel, Amjad, editor, Biswas, Arkoprovo, editor, Turan, Veysel, editor, Knight, Jasper, editor, Çiner, Attila, editor, Candeias, Carla, editor, and Ergüler, Zeynal Abiddin, editor

Published
2024
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2. Topography-Based Estimation of Evapotranspiration at High Altitudes in Semi-arid Regions

Author

Sebbar, Badreddine, Merlin, Olivier, Khabba, Saïd, Simonneaux, Vincent, Bouchet, Marine, Chehbouni, Abdelghani, Pisello, Anna Laura, Editorial Board Member, Hawkes, Dean, Editorial Board Member, Bougdah, Hocine, Editorial Board Member, Rosso, Federica, Editorial Board Member, Abdalla, Hassan, Editorial Board Member, Boemi, Sofia-Natalia, Editorial Board Member, Mohareb, Nabil, Editorial Board Member, Mesbah Elkaffas, Saleh, Editorial Board Member, Bozonnet, Emmanuel, Editorial Board Member, Pignatta, Gloria, Editorial Board Member, Mahgoub, Yasser, Editorial Board Member, De Bonis, Luciano, Editorial Board Member, Kostopoulou, Stella, Editorial Board Member, Pradhan, Biswajeet, Editorial Board Member, Abdul Mannan, Md., Editorial Board Member, Alalouch, Chaham, Editorial Board Member, Gawad, Iman O., Editorial Board Member, Nayyar, Anand, Editorial Board Member, Amer, Mourad, Series Editor, Bezzeghoud, Mourad, editor, Ergüler, Zeynal Abiddin, editor, Rodrigo-Comino, Jesús, editor, Jat, Mahesh Kumar, editor, Kalatehjari, Roohollah, editor, Bisht, Deepak Singh, editor, Biswas, Arkoprovo, editor, Chaminé, Helder I., editor, Shah, Afroz Ahmad, editor, Radwan, Ahmed E., editor, Knight, Jasper, editor, Panagoulia, Dionysia, editor, Kallel, Amjad, editor, Turan, Veysel, editor, Chenchouni, Haroun, editor, Ciner, Attila, editor, and Gentilucci, Matteo, editor

Published
2024
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5. Analysis of C-Band Radar Temporal Coherence Over an Irrigated Olive Orchard in a Semi-Arid Region

Author

Adnane Chakir, Pierre-Louis Frison, Ludovic Villard, Nadia Ouaadi, Pascal Fanise, Khabba Said, Valerie Le Dantec, Rafi Zoubair, Jamal Ezzahar, Benedicte Fruneau, Jean-Paul Rudant, and Jarlan Lionel

Subjects
$C$ -band, olive orchard, radar, temporal coherence, water status, Ocean engineering, TC1501-1800, Geophysics. Cosmic physics, QC801-809
Abstract

This article aimed to monitor vegetation using C-band radar data at a subdaily time step. To this end, radar measurements using tower-mounted antennas with a 15-min time step, along with physiology-related information (sapflow and micrometric dendrometry), were acquired quasi-continuously from March 2020 to December 2021 in an olive orchard located near Marrakech, Morocco. The article focused on temporal coherence, whose clear diurnal cycle (highest at night and lowest at the end of the afternoon) had been highlighted over tropical and boreal forests in previous studies. The results showed that coherence was highly sensitive to: wind-induced movement of scatterers, since coherence was lowest when wind speed was highest in late afternoon, and vegetation activity, especially its water dynamics, since the morning coherence drop coincided with the onset of sapflow and the daily evapotranspiration cycle, as well as the good agreement between the temporal drop rate of coherence and the daily residual variation in trunk circumference (i.e., deviation from long-term trend). Finally, coherence remained high for temporal baselines of several days, showing that sentinel-1 data (when both satellites are operational) may be well suited for such studies, especially with acquisitions made during morning passes, when wind speed is low. These results open perspectives for monitoring tree crop physiology using high-revisit-time radar observations.

Published
2024
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6. Sentinel-1 Backscatter and Interferometric Coherence for Soil Moisture Retrieval in Winter Wheat Fields Within a Semiarid South-Mediterranean Climate: Machine Learning Versus Semiempirical Models

Author

Jamal Ezzahar, Abdelghani Chehbouni, Nadia Ouaadi, Mohammed Madiafi, Khabba Said, Salah Er-Raki, Ahmed Laamrani, Adnane Chakir, Zohra Lili Chabaane, and Mehrez Zribi

Subjects
Backscattering models, irrigated and rainfed winter wheat, machine learning (ML), semiarid regions, Sentinel-1 backscatter and interferometric coherence, surface soil moisture (SSM), Ocean engineering, TC1501-1800, Geophysics. Cosmic physics, QC801-809
Abstract

This work aims to assess the effectiveness of machine learning (ML) algorithms and semiempirical models for surface soil moisture (SSM) retrieval by exploring the Sentinel-1 backscatter and interferometric coherence data. First, three commonly used categories of ML algorithms are evaluated using data gathered from diverse rainfed and irrigated wheat fields located in Morocco and Tunisia. Specifically, these algorithms include artificial neural network (ANN), deep neural network, three support vector regression (SVR) models [radial basis function (SVR_rbf), linear (SVR_linear), and polynomial (SVR_quad) kernels], and two tree-based methods [random forest and eXtreme Gradient Boosting (XGBoost)]. The comparison between predicted and measured SSM showed that the best retrieval results were obtained using Sentinel-1 data at VV polarization with R ranging between $ 0.68$ and $ 0.76$ and root-mean-square error (RMSE) of $ \text{0.05}\,\text{m}^{3}/\text{m}^{3}$ and $ \text{0.06}\,\text{m}^{3}/\text{m}^{3}$. Second, to further assess their transferability, the ANN, SVR_rbf, and XGBoost, which demonstrated the most favorable results from each category, were evaluated and compared against the coupled Water Cloud and Oh models (WCM), using a second dataset collected over a drip-irrigated wheat field in Morocco. Overall, the best retrieval results were achieved by ANN and SVR_rbf with R and RMSE of $ 0.81$ and $ \text{0.034}\,\text{m}^{3}/\text{m}^{3}$, respectively. In addition, their performances were consistent with that of WCM, which yielded R and RMSE values of $ 0.81$ and $ \text{0.04}\,\text{m}^{3}/\text{m}^{3}$, respectively. Finally, due to its good compromise between retrieval accuracy of SSM, processing time, and simplicity, SVR_rbf was chosen to generate high-resolution SSM maps from Sentinel-1 data over irrigated wheat fields.

Published
2024
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7. Mapping Soil Clay Content and Hydraulic Properties over an Agricultural Semiarid Plain Using Remote Sensing and Interpolation Techniques

Author

Houda Nassah, Fakir Younes, Erraki Salah, Khabba Said, and Bernard Mougenot

Subjects
topsoil clay content, mid-infrared index, landsat-8 images, ordinary cokriging, soil hydraulic properties, Ecology, QH540-549.5
Abstract

Clay content is an important parameter governing hydrodynamics property of soils and consequently crucial to environmental management and agricultural development. The present study aims to use the textural middle infrared index (MID index) product of Landsat-8 Operational Land Images to map clay content over the Haouz plain (Central Morocco). The clay content was mapped at 30 m grid spatial resolution based on the relationship between the MID index and a large set of soil samples. Over the areas covered by green vegetation, the clay content was predicted using the ordinary cokriging technique. Then, this information was used to derive soil hydraulic properties such as the field capacity (θfc), the wilting point (θwp) and the saturated hydraulic conductivity (Ksat) by using different pedotransfer functions. The validation of the maps was performed by using independent soil samples and measurements. The results showed that the clay content is significantly correlated to MID index. The ordinary cokriging improved mapping of clay content over the Haouz plain (R2 = 0.70, RMSE = 3.5%). The obtained maps of θfc, θwp and Ksat revealed a good correlation between the simulated values and the measured values.

Published
2024
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10. Synergy of Sentinel-1 and Sentinel-2 Satellites for Surface Soil Moisture Retrieval Over Wheat Crops in Semi-arid Areas

Author

Ouaadi, Nadia, Ezzahar, Jamal, Jarlan, Lionel, Khabba, Saïd, Frison, Pierre Luis, Angrisani, Leopoldo, Series Editor, Arteaga, Marco, Series Editor, Panigrahi, Bijaya Ketan, Series Editor, Chakraborty, Samarjit, Series Editor, Chen, Jiming, Series Editor, Chen, Shanben, Series Editor, Chen, Tan Kay, Series Editor, Dillmann, Rüdiger, Series Editor, Duan, Haibin, Series Editor, Ferrari, Gianluigi, Series Editor, Ferre, Manuel, Series Editor, Hirche, Sandra, Series Editor, Jabbari, Faryar, Series Editor, Jia, Limin, Series Editor, Kacprzyk, Janusz, Series Editor, Khamis, Alaa, Series Editor, Kroeger, Torsten, Series Editor, Li, Yong, Series Editor, Liang, Qilian, Series Editor, Martín, Ferran, Series Editor, Ming, Tan Cher, Series Editor, Minker, Wolfgang, Series Editor, Misra, Pradeep, Series Editor, Möller, Sebastian, Series Editor, Mukhopadhyay, Subhas, Series Editor, Ning, Cun-Zheng, Series Editor, Nishida, Toyoaki, Series Editor, Oneto, Luca, Series Editor, Pascucci, Federica, Series Editor, Qin, Yong, Series Editor, Seng, Gan Woon, Series Editor, Speidel, Joachim, Series Editor, Veiga, Germano, Series Editor, Wu, Haitao, Series Editor, Zamboni, Walter, Series Editor, Zhang, Junjie James, Series Editor, Bekkay, Hajji, editor, Mellit, Adel, editor, Gagliano, Antonio, editor, Rabhi, Abdelhamid, editor, and Amine Koulali, Mohammed, editor

Published
2023
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12. Are raw satellite bands and machine learning all you need to retrieve actual evapotranspiration?

Author

El Hachimi Chouaib, Khabba Said, Belaqziz Salwa, Ayi Hssaine Bouchra, Kharrou Mohamed Hakim, and Chehbouni Abdelghani

Subjects
Environmental sciences, GE1-350
Abstract

Accurately estimating latent heat flux (LE) is crucial for achieving efficiency in irrigation. It is a fundamental component in determining the actual evapotranspiration (ETa), which in turn, quantifies the amount of water lost that needs to be adequately compensated through irrigation. Empirical and physics-based models have extensive input data and site-specific limitations when estimating the LE. In contrast, the emergence of data-driven techniques combined with remote sensing has shown promising results for LE estimation with minimal and easy-to-obtain input data. This paper evaluates two machine learning-based approaches for estimating the LE. The first uses climate data, the Normalized Difference Vegetation Index (NDVI), and Land Surface Temperature (LST), while the second uses climate data combined with raw satellite bands. In-situ data were sourced from a flux station installed in our study area. The data include air temperatures (Ta), global solar radiation (Rg), and measured LE for the period 2015-2018. The study uses Landsat 8 as a remote sensing data source. At first, 12 raw available bands were downloaded. The LST is then derived from thermal bands using the Split Window algorithm (SW) and the NDVI from optical bands. During machine learning modeling, the CatBoost model is fed, trained, and evaluated using the two data combination approaches. Cross-validation of 3-folds gave an average RMSE of 27.54 W.nr2 using the first approach and 27.05 W.nr2 using the second approach. Results raise the question: Do we need additional computational layers when working with remote sensing products combined with machine learning? Future work is to generalize the approach and test it for other applications such as soil moisture retrieval, and yield prediction.

Published
2024
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13. Snow hydrology in the Moroccan Atlas Mountains

Author

Hanich, Lahoucine, Chehbouni, Abdelghani, Gascoin, Simon, Boudhar, Abdelghani, Jarlan, Lionel, Tramblay, Yves, Boulet, Gilles, Marchane, Ahmed, Baba, Mohamed Wassim, Kinnard, Christophe, Simonneaux, Vincent, Fakir, Younes, Bouchaou, Lhoussaine, Leblanc, Marc, Le Page, Michel, Bouamri, Hafsa, Er-Raki, Salah, and Khabba, Saïd

Published
2022
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14. Estimation of the Evapotranspiration over Heterogeneous Region Using Shuttleworth-Wallace Model

Author

Elfarkh, Jamal, Er-Raki, Salah, Ezzahar, Jamal, Jarlan, Lionel, Khabba, Said, Chehbouni, Abdelghani, Angrisani, Leopoldo, Series Editor, Arteaga, Marco, Series Editor, Panigrahi, Bijaya Ketan, Series Editor, Chakraborty, Samarjit, Series Editor, Chen, Jiming, Series Editor, Chen, Shanben, Series Editor, Chen, Tan Kay, Series Editor, Dillmann, Rüdiger, Series Editor, Duan, Haibin, Series Editor, Ferrari, Gianluigi, Series Editor, Ferre, Manuel, Series Editor, Hirche, Sandra, Series Editor, Jabbari, Faryar, Series Editor, Jia, Limin, Series Editor, Kacprzyk, Janusz, Series Editor, Khamis, Alaa, Series Editor, Kroeger, Torsten, Series Editor, Liang, Qilian, Series Editor, Martín, Ferran, Series Editor, Ming, Tan Cher, Series Editor, Minker, Wolfgang, Series Editor, Misra, Pradeep, Series Editor, Möller, Sebastian, Series Editor, Mukhopadhyay, Subhas, Series Editor, Ning, Cun-Zheng, Series Editor, Nishida, Toyoaki, Series Editor, Pascucci, Federica, Series Editor, Qin, Yong, Series Editor, Seng, Gan Woon, Series Editor, Speidel, Joachim, Series Editor, Veiga, Germano, Series Editor, Wu, Haitao, Series Editor, Zhang, Junjie James, Series Editor, El Moussati, Ali, editor, Kpalma, Kidiyo, editor, Ghaouth Belkasmi, Mohammed, editor, Saber, Mohammed, editor, and Guégan, Sylvain, editor

Published
2020
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15. Inter-comparison Between Different Techniques for Evapotranspiration Partitioning: Eddy Covariance-, Sap Flow-, Lysimeter- and FAO-Based Methods

Author

Rafi, Zoubair, Merlin, Olivier, Le Dantec, Valérie, Khabba, Saïd, Er-Raki, Salah, Mordelet, Patrick, Angrisani, Leopoldo, Series Editor, Arteaga, Marco, Series Editor, Panigrahi, Bijaya Ketan, Series Editor, Chakraborty, Samarjit, Series Editor, Chen, Jiming, Series Editor, Chen, Shanben, Series Editor, Chen, Tan Kay, Series Editor, Dillmann, Rüdiger, Series Editor, Duan, Haibin, Series Editor, Ferrari, Gianluigi, Series Editor, Ferre, Manuel, Series Editor, Hirche, Sandra, Series Editor, Jabbari, Faryar, Series Editor, Jia, Limin, Series Editor, Kacprzyk, Janusz, Series Editor, Khamis, Alaa, Series Editor, Kroeger, Torsten, Series Editor, Liang, Qilian, Series Editor, Martín, Ferran, Series Editor, Ming, Tan Cher, Series Editor, Minker, Wolfgang, Series Editor, Misra, Pradeep, Series Editor, Möller, Sebastian, Series Editor, Mukhopadhyay, Subhas, Series Editor, Ning, Cun-Zheng, Series Editor, Nishida, Toyoaki, Series Editor, Pascucci, Federica, Series Editor, Qin, Yong, Series Editor, Seng, Gan Woon, Series Editor, Speidel, Joachim, Series Editor, Veiga, Germano, Series Editor, Wu, Haitao, Series Editor, Zhang, Junjie James, Series Editor, El Moussati, Ali, editor, Kpalma, Kidiyo, editor, Ghaouth Belkasmi, Mohammed, editor, Saber, Mohammed, editor, and Guégan, Sylvain, editor

Published
2020
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30. A Systematic National Stocktake of Crop Models in Morocco

Author

Epule, Terence Epule, primary, Chehbouni, Abdelghani, additional, Chfadi, Tarik, additional, Ongoma, Victor, additional, Er-Raki, Salah, additional, Khabba, Said, additional, Etongo, Daniel, additional, Martínez-Cruz, Adán L., additional, Molua, Ernest L., additional, Achli, Soumia, additional, Salih, Wiam, additional, Chuwah, Clifford, additional, Jemo, Martin, additional, and Chairi, Ikram, additional

Published
2022
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39. Linkages between Rainfed Cereal Production and Agricultural Drought through Remote Sensing Indices and a Land Data Assimilation System: A Case Study in Morocco

Author

Bouras, Elhoussaine, Jarlan, Lionel, Er-Raki, Salah, Albergel, Clément, Richard, Bastien, Balaghi, Riad, Khabba, Said, Université Cadi Ayyad [Marrakech] (UCA), Centre d'études spatiales de la biosphère (CESBIO), Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire Midi-Pyrénées (OMP), Météo France-Centre National d'Études Spatiales [Toulouse] (CNES)-Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Météo France-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS), Faculté des Sciences et Techniques Marrakech, Centre national de recherches météorologiques (CNRM), Institut national des sciences de l'Univers (INSU - CNRS)-Météo France-Centre National de la Recherche Scientifique (CNRS), Gestion de l'Eau, Acteurs, Usages (UMR G-EAU), Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Institut de Recherche pour le Développement (IRD)-AgroParisTech-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Institut national de la recherche agronomique [Maroc] (INRA Maroc), European Commission - 645642, European Commission Joint Research Centre - 823965, SAGESSE 'Systeme d'Aide à la décision pour la GEstion des reSSources en Eau' - PPR/2015/48, PHC Toubkal - 39064WG/2018, ARTS program from IRD, France, H2020 PRIMA ALTOS project, MISTRALS/SICMED2, European Project: 645642,H2020,H2020-MSCA-RISE-2014,REC(2015), Institut de Recherche pour le Développement (IRD)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire Midi-Pyrénées (OMP), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Faculté des Sciences et Techniques Marrakech (FSTG), Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire Midi-Pyrénées (OMP), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Institut de Recherche pour le Développement (IRD)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Centre National de la Recherche Scientifique (CNRS), Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Institut de Recherche pour le Développement (IRD)-AgroParisTech-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Institut Agro - Montpellier SupAgro, and Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)

Subjects
remote sensing, Science, [SDE]Environmental Sciences, assimilation systems, cereal yield, semiarid region, land data, agricultural drought, land data assimilation systems
Abstract

International audience; In Morocco, cereal production shows high interannual variability due to uncertain rainfall and recurrent drought periods. Considering the socioeconomic importance of cereal for the country, there is a serious need to characterize the impact of drought on cereal yields. In this study, drought is assessed through (1) indices derived from remote sensing data (the vegetation condition index (VCI), temperature condition index (TCI), vegetation health ind ex (VHI), soil moisture condition index (SMCI) and soil water index for different soil layers (SWI)) and (2) key land surface variables (Land Area Index (LAI), soil moisture (SM) at different depths, soil evaporation and plant transpiration) from a Land Data Assimilation System (LDAS) over 2000–2017. A lagged correlation analysis was conducted to assess the relationships between the drought indices and cereal yield at monthly time scales. The VCI and LAI around the heading stage (March-April) are highly linked to yield for all provinces (R = 0.94 for the Khemisset province), while a high link for TCI occurs during the development stage in January-February (R = 0.83 for the Beni Mellal province). Interestingly, indices related to soil moisture in the superficial soil layer are correlated with yield earlier in the season around the emergence stage (December). The results demonstrate the clear added value of using an LDAS compared with using a remote sensing product alone, particularly concerning the soil moisture in the root-zone, considered a key variable for yield production, that is not directly observable from space. The time scale of integration is also discussed. By integrating the indices on the main phenological stages of wheat using a dynamic threshold approach instead of the monthly time scale, the correlation between indices and yield increased by up to 14%. In addition, the contributions of VCI and TCI to VHI were optimized by using yield anomalies as proxies for drought. This study opens perspectives for the development of drought early warning systems in Morocco and over North Africa, as well as for seasonal crop yield forecasting.

Published
2020
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42. An evapotranspiration model self-calibrated from remotely sensed surface soil moisture, land surface temperature and vegetation cover fraction: application to disaggregated SMOS and MODIS data

Author

Ait Hssaine, Bouchra, Merlin, Olivier, Ezzahar, Jamal, Ojha, Nitu, Er-Raki, Salah, Khabba, Said, Centre d'études spatiales de la biosphère (CESBIO), Institut de Recherche pour le Développement (IRD)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire Midi-Pyrénées (OMP), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), and LMFE, Département de physique, Faculté des sciences Semlalia, Université Cadi Ayyad, Marrakech, Morocco

Subjects
2. Zero hunger, 010504 meteorology & atmospheric sciences, [SDU]Sciences of the Universe [physics], 0211 other engineering and technologies, 02 engineering and technology, [SDU.STU.HY]Sciences of the Universe [physics]/Earth Sciences/Hydrology, 15. Life on land, [SDU.ENVI]Sciences of the Universe [physics]/Continental interfaces, environment, 01 natural sciences, 021101 geological & geomatics engineering, 0105 earth and related environmental sciences
Abstract

Thermal-based two-source energy balance modeling is essential to estimate the land evapotranspiration (ET) in a wide range of spatial and temporal scales. However, the use of thermal-derived land surface temperature (LST) is not sufficient to simultaneously constrain both soil and vegetation flux components. Therefore, assumptions (about either soil or vegetation fluxes) are commonly required. To avoid such assumptions, an energy balance model, TSEB-SM, was recently developed by Ait Hssaine et al. (2018b) in order to consider the microwave-derived near-surface soil moisture (SM), in addition to the thermal-derived LST and vegetation cover fraction (fc) normally used. While TSEB-SM has been successfully tested using in situ measurements, this paper represents its first evaluation in real life using 1 km resolution satellite data, comprised of MODIS (MODerate resolution Imaging Spectroradiometer) for LST and fc data and 1 km resolution SM data disaggregated from SMOS (Soil Moisture and Ocean Salinity) observations. The approach is applied during a 4-year period (2014–2018) over a rainfed wheat field in the Tensift basin, central Morocco. The field used was seeded for the 2014–2015 (S1), 2016–2017 (S2) and 2017–2018 (S3) agricultural seasons, while it remained unploughed (as bare soil) during the 2015–2016 (B1) agricultural season. The classical TSEB model, which is driven only by LST and fc data, significantly overestimates latent heat fluxes (LE) and underestimates sensible heat fluxes (H) for the four seasons. The overall mean bias values are 119, 94, 128 and 181 W m−2 for LE and −104, −71, −128 and −181 W m−2 for H, for S1, S2, S3 and B1, respectively. Meanwhile, when using TSEB-SM (SM and LST combined data), these errors are significantly reduced, resulting in mean bias values estimated as 39, 4, 7 and 62 W m−2 for LE and −10, 24, 7, and −59 W m−2 for H, for S1, S2, S3 and B1, respectively. Consequently, this finding confirms again the robustness of the TSEB-SM in estimating latent/sensible heat fluxes at a large scale by using readily available satellite data. In addition, the TSEB-SM approach has the original feature to allow for calibration of its main parameters (soil resistance and Priestley–Taylor coefficient) from satellite data uniquely, without relying either on in situ measurements or on a priori parameter values.

Published
2020

43. Agriculture in Southern Mediterranean areas under climate change: Impacts on irrigated wheat grain yield and irrigation requirements

Author

Sghir Fathallah, Khabba Said, Bouras El houssaine, Yves Tramblay, Er-Raki Salah, Jarlan Lionel, and Dezetter Alain

Subjects
Mediterranean climate, Wheat grain, Irrigation, Agronomy, Agriculture, business.industry, Yield (finance), Climate change, Environmental science, business
Abstract

The southern Mediterranean regions are likely to face drastic climate changes (CC). Agricultural yields, particularly of cereals, could be severely affected, especially if significant changes occur at the key phenological stages. In addition, while agriculture is expected to meet around 83% of North African food demand by 2050, the increase in agricultural water requirements due to the intensification of practices, the extension of arable land and the expected warming could jeopardize the water supply of other key economic sectors. In this context, the present work aims to quantify the impact of CC on the grain yields of irrigated cereals and their water requirements in the Tensift-Haouz region of Morocco. The Med-CORDEX ensemble runs under scenarios RCP4.5 and RCP8.5 are first evaluated and disaggregated using the quantile-quantile approach. The impact of CC on the duration of the main wheat phenological stages based on the degree-day approach is then analysed by considering three typical sowing dates (early, around November 15th; intermediate, around December 15th; and late, around January, 15th). The results show that the rise in air temperature causes a shortening of the development cycle of up to 50 days (around 30%). The impacts of rising temperature, increasing atmospheric CO2 concentration and changes in precipitation on wheat yields are next evaluated, based on the AquaCrop model (previously calibrated on several plots of winter wheat in the region of study), both with and without taking into account the fertilizing effect of CO2. As expected, optimal wheat yields for all climate scenarios and time horizons will decrease on the order of 7 to 30% depending on the sowing date, if CO2 concentration rise is not considered. The results also show that the fertilizing effect of CO2 can counterbalance yield losses, since optimal yields could increase by 7% and 13% respectively at mid-century for the RCP4.5 and RCP8.5 scenarios. Finally, water requirements are expected to decrease by 13 to 42% depending on sowing date, scenario and horizon, mainly in response to the shortening of the cycle. This decrease is associated with a change in temporal patterns, with the requirement peak coming two months earlier than under current conditions. This study provides some quantitative elements for agricultural practices adaptation, in particular concerning the sowing date and also for water management in the south mediterranean region related to the temporal patterns of the crop water needs

Published
2020

44. Evapotranspiration partition using the multiple energy balance version of the ISBA-A-gs land surface model over two irrigated crops in a semi-arid Mediterranean region (Marrakech, Morocco)

Author

Aouade, Ghizlane, Jarlan, Lionel, Ezzahar, Jamal, Er-Raki, Salah, Napoly, Adrien, Benkaddour, Abdelfattah, Khabba, Said, Boulet, Gilles, Garrigues, Sebastien, Chehbouni, Abdelghani, Boone, Aaron, Aouade, Ghizlane, Jarlan, Lionel, Ezzahar, Jamal, Er-Raki, Salah, Napoly, Adrien, Benkaddour, Abdelfattah, Khabba, Said, Boulet, Gilles, Garrigues, Sebastien, Chehbouni, Abdelghani, and Boone, Aaron

Abstract

The main objective of this work is to question the representation of the energy budget in soil–vegetation–atmosphere transfer (SVAT) models for the prediction of the turbulent fluxes in the case of irrigated crops with a complex structure (row) and under strong transient hydric regimes due to irrigation. To this end, the Interaction between Soil, Biosphere, and Atmosphere (ISBA-A-gs) is evaluated at a complex open olive orchard and, for the purposes of comparison, on a winter wheat field taken as an example of a homogeneous canopy. The initial version of ISBA-A-gs, based on a composite energy budget (hereafter ISBA-1P for one patch), is compared to the new multiple energy balance (MEB) version of ISBA that represents a double source arising from the vegetation located above the soil layer. In addition, a patch representation corresponding to two adjacent, uncoupled source schemes (hereafter ISBA-2P for two patches) is also considered for the olive orchard. Continuous observations of evapotranspiration (ET), with an eddy covariance system and plant transpiration (Tr) with sap flow and isotopic methods were used to evaluate the three representations. A preliminary sensitivity analyses showed a strong sensitivity to the parameters related to turbulence in the canopy introduced in the new ISBA–MEB version. For wheat, the ability of the single- and dual-source configuration to reproduce the composite soil–vegetation heat fluxes was very similar; the root mean square error (RMSE) differences between ISBA-1P, ISBA-2P and ISBA–MEB did not exceed 10 W m−2 for the latent heat flux. These results showed that a composite energy balance in homogeneous covers is sufficient to reproduce the total convective fluxes. The two configurations are also fairly close to the isotopic observations of transpiration in spite of a light underestimation (overestimation) of ISBA-1P (ISBA–MEB). At the olive orchard, contrasting results are obtained. The dual-source configurations, including both

Published
2020

46. List of contributors

Author

Albuquerque, Marcia Fajardo Cavalcanti de, Anubhuti, Aruna, K., Baitha, R., Biswas, Pradyut, Blumenstein, Benjamin, Borah, S., Chehbouni, Abdelghani, Chfadi, Tarik, Choudhary, B.K., Choudhary, Mamta, Correia, Helena E., Costa, Cristina A., Costa, Daniela V.T.A., Das, B.K., Das, Suryatapa, Debbarma, Reshmi, Dhiba, Driss, Epule, Terence Epule, Er-Raki, Salah, Etongo, Daniel, Guiné, Raquel P.F., Gupta, Chinmay, Hassan, M.A., Jemo, Martin, Khabba, Said, Kumar, Rakesh, Kumar, Satendra, Kundlas, Kanchan, Lal, Jham, Martinez Cruz, Adan L., Meena, D.K., Meena, Kanti, Meena, N.D., Meena, Ram Narayan, Meena, Shashi, Mehta, Naresh Kumar, Meitei, Maibam Malemngamba, Merfield, Charles N., Mohanta, K.N., Möller, Detlev, Molua, Ernest L., Naseri, Bita, Nave, Anabela, Nayak, A.P., Ongoma, Victor, Patel, Arun B., Pawar, Lokesh, Pillai, B.R., Rakshit, Amitava, Rathore, Shalika, Rattan, Shiv, Sahoo, A.K., Sahoo, S.N., Satvik, K., Sethi, S.N., Sharma, Sanjeev, Siegmeier, Torsten, Singh, Jayesh, Singh, Soibam Khogen, Suman, Jarupula, Swain, S.K., Tiwari, P.K., Triphati, Hemant Hari, Waikhom, Gusheinzed, Warghat, Ashish R., Yadav, Mahendra K., and Yadav, Nitesh K.

Published
2023
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47. Evapotranspiration partition using the multiple energy balance version of the ISBA-A-g<sub>s</sub> land surface model over two irrigated crops in a semi-arid Mediterranean region (Marrakech, Morocco)

Author

Aouade, Ghizlane, primary, Jarlan, Lionel, additional, Ezzahar, Jamal, additional, Er-Raki, Salah, additional, Napoly, Adrien, additional, Benkaddour, Abdelfattah, additional, Khabba, Said, additional, Boulet, Gilles, additional, Garrigues, Sébastien, additional, Chehbouni, Abdelghani, additional, and Boone, Aaron, additional

Published
2020
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