ARTICLES

WP1: Water balance key variables from EO data

  • Ait Hssaine, B.; Chehbouni, A.; Er-Raki, S.; Khabba, S.; Ezzahar, J.; Ouaadi, N.; Ojha, N.; Rivalland, V.; Merlin, O. On the Utility of High-Resolution Soil Moisture Data for Better Constraining Thermal-Based Energy Balance over Three Semi-Arid Agricultural Areas. Remote Sens. 2021, 13, 727. https://doi.org/10.3390/rs13040727
  • Amazirh, A.; Bouras, E.H.; Olivera-Guerra, L.E.; Er-Raki, S.; Chehbouni, A. Retrieving Crop Albedo Based on Radar Sentinel-1 and Random Forest Approach. Remote Sens. 2021, 13, 3181. https://doi.org/10.3390/rs13163181
  • Ojha, N.; O. Merlin, C. Suere and M. J. Escorihuela. Extending the Spatio-Temporal Applicability of DISPATCH Soil Moisture Downscaling Algorithm: A Study Case Using SMAP, MODIS and Sentinel-3 Data. Frontiers in Environmental Science, 2021, 9,  555216. https://doi.org/10.3389/fenvs.2021.555216
  • Ojha, N., Merlin, O., Amazirh, A., Ouaadi, N., Rivalland, V., Jarlan, L., Er-Raki, S. & Escorihuela, M. J. (2021). A Calibration/Disaggregation Coupling Scheme for Retrieving Soil Moisture at High Spatio-Temporal Resolution: Synergy between SMAP Passive Microwave, MODIS/Landsat Optical/Thermal and Sentinel-1 Radar Data. Sensors21(21), 7406. https://doi.org/10.3390/s21217406
  • Paolini, G., Escorihuela, M. J., Bellvert, J., & Merlin, O. (2021). Disaggregation of SMAP Soil Moisture at 20 m Resolution: Validation and Sub-Field Scale Analysis. Remote Sensing14(1), 167. https://doi.org/10.3390/rs14010167

WP3: Multi-scale water accounting (irrigation and drainage) from EO data

  • Amazirh, A., Merlin, O., Er-Raki, S., Bouras, E., Chehbouni, A. Implementing a new texture-based soil evaporation reduction coefficient in the FAO dual crop coefficient method. Agricultural Water Management. 2021, 250, 106827. https://hal.archives-ouvertes.fr/hal-03438678
  • Amazirh, A., Er-Raki, S., Ojha, N., houssaine Bouras, E., Rivalland, V., Merlin, O., & Chehbouni, A. (2022). Assimilation of SMAP disaggregated soil moisture and Landsat land surface temperature to improve FAO-56 estimates of ET in semi-arid regions. Agricultural Water Management260, 107290.
  • Bouras, E.H.; Jarlan, L.; Er-Raki, S.; Balaghi, R.; Amazirh, A.; Richard, B.; Khabba, S. 2021. Cereal Yield Forecasting with Satellite Drought-Based Indices, Weather Data and Regional Climate Indices Using Machine Learning in Morocco. Remote Sens. 2021, 13, 3101. https://doi.org/10.3390/rs13163101.
  • Er-Raki, S., J. Ezzahar, O. Merlin, A. Amazirh, B. Ait Hssaine, M. H., Kharrou, S. Khabba, A. Chehbouni. 2021. Performance of the HYDRUS-1D model for water balance components assessment of irrigated winter wheat under different water managements in semi-arid region of Morocco. Agricultural Water Management. 244, 2021, 106546. https://hal.archives-ouvertes.fr/hal-03068188
  • Er-Raki, S., E. Bouras, J.C. Rodriguez, C.J. Watts, C. Lizarraga-Celaya, A. Chehbouni. 2021. Parameterization of the AquaCrop model for simulating table grapes growth and water productivity in an arid region of Mexico. Agricultural Water Management. 244, 2021, 106546.
  • Kharrou, M.H.; Simonneaux, V.; Er-Raki, S.; Le Page, M.; Khabba, S.; Chehbouni, A. Assessing Irrigation Water Use with Remote Sensing-Based Soil Water Balance at an Irrigation Scheme Level in a Semi-Arid Region of Morocco. Remote Sens. 2021, 13, 1133. https://doi.org/10.3390/rs13061133