Research Article
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Mapping the structural vulnerability to drought in Morocco

Year 2024, , 264 - 280, 28.07.2024
https://doi.org/10.26833/ijeg.1404507

Abstract

Because of its recurrence and the durability of its effects, drought in Morocco has become a structural component of the Moroccan climate. It is a real threat to the agricultural sector, which represents nearly 20% of the Moroccan economy. The spatiotemporal variability of this phenomenon makes drought risk management more complex. The current study seeks to map the structural vulnerability to drought in Morocco by using remote sensing techniques to characterize its sensitivity to drought. In this premise, we utilized a weighted combination of soil classes, land cover and socio-economic data with seasonal drought monitoring through a composite index generated monthly over the past twenty years. The generated map shows dominance of areas with high and very high vulnerability risk to drought over respectively 38.5% and 14.4% of the country and this concerns both agricultural and non-agricultural zones. The map also indicates that 36.5% of Morocco presents a medium vulnerability to drought and only 10.6% of the national territory is considered non-vulnerable to drought. This map can be used as a planning tool to support natural resources management and mitigate drought impacts.

References

  • Khorrami, B., & Gündüz, O. (2022). Detection and analysis of drought over Turkey with remote sensing and model-based drought indices. Geocarto International, 37(26), 12171-12193. https://doi.org/10.1080/10106049.2022.2066197
  • Observatoire du Sahara et du Sahel. (2013). Vers un système d'alerte précoce à la sécheresse au Maghreb. OSS. Collection Synthèse, 4. OSS: Tunis.
  • World Bank. (2022). Country Climate and Development Report: Morocco. Washington, DC: World Bank
  • Fritzsche, K., Schneiderbauer, S., Bubeck, P., Kienberger, S., Buth, M., Zebisch, M., & Kahlenborn, W. (2014). The Vulnerability Sourcebook: Concept and guidelines for standardised vulnerability assessments.
  • Hoque, M., Pradhan, B., Ahmed, N., & Alamri, A. (2021). Drought vulnerability assessment using geospatial techniques in southern Queensland, Australia. Sensors, 21(20), 6896. https://doi.org/10.3390/s21206896
  • West, H., Quinn, N., & Horswell, M. (2019). Remote sensing for drought monitoring & impact assessment: Progress, past challenges and future opportunities. Remote Sensing of Environment, 232, 111291. https://doi.org/10.1016/j.rse.2019.111291
  • Wilhite, D. A. (2000). Drought as a natural hazard: Concepts and Definitions. Drought: A Global Assessment.
  • Svoboda, M., & Fuchs, B. (2016). Handbook of Drought Indicators and Indices. Integrated Drought Management Programme (IDMP)
  • Iglesias, A., Cancelliere, S., Gabiña, D., López-Francos, A., Moneo, A., & Rossi, G. (2007). Medroplan Drought Management Guidelines and Examples of Application; European Commission. MEDA-Water Programme: Zaragoza, Spain.
  • RICCAR (2017). Training manual on the integrated vulnerability assessment methodology.
  • Szaboova, L. (2023). Climate change, migration and rural adaptation in the Near East and North Africa region. Food and Agriculture Organization of the United Nations.
  • Fritzsche, K., Schneiderbauer, S., Bubeck, P., Kienberger, S., Buth, M., Zebisch, M. & Kahlenborn, W. (2017). The vulnerability sourcebook. Concept and guidelines for standardized vulnerability assessments. Risk Supplement: How to apply the approach with the IPCC AR5 risk concept.
  • Bijaber, N., El Hadani, D., Saidi, M., Svoboda, M. D., Wardlow, B. D., Hain, C. R., ... & Rochdi, A. (2018). Developing a remotely sensed drought monitoring indicator for Morocco. Geosciences, 8(2), 55. https://doi.org/10.3390/geosciences8020055
  • Fragaszy, S. R., Jedd, T., Wall, N., Knutson, C., Fraj, M. B., Bergaoui, K., ... & McDonnell, R. (2020). Drought monitoring in the Middle East and North Africa (MENA) region: participatory engagement to inform early warning systems. Bulletin of the American Meteorological Society, 101(7), E1148-E1173. https://doi.org/10.1175/BAMS-D-18-0084.1
  • Svoboda, M. D., Fuchs, B. A., Poulsen, C. C., & Nothwehr, J. R. (2015). The drought risk atlas: enhancing decision support for drought risk management in the United States. Journal of Hydrology, 526, 274-286. https://doi.org/10.1016/j.jhydrol.2015.01.006
  • Funk, C. C., Peterson, P. J., Landsfeld, M. F., Pedreros, D. H., Verdin, J. P., Rowland, J. D., ... & Verdin, A. P. (2014). A quasi-global precipitation time series for drought monitoring. US Geological Survey, 832. https://dx.doi.org/10.3133/ds832
  • McKee, T. B., Doesken, N. J., & Kleist, J. (1995). Drought monitoring with multiple time scales. Proceedings of the Conference on Applied Climatology.
  • McKee, T. B., Doesken, N. J., & Kleist, J. (1993). The relationship of drought frequency and duration to time scales. Proceedings of the 8th Conference on Applied Climatology.
  • Senay, G. B., Velpuri, N. M., Bohms, S., Budde, M., Young, C., Rowland, J., & Verdin, J. P. (2015). Drought monitoring and assessment: remote sensing and modeling approaches for the famine early warning systems network. Hydro-meteorological Hazards, Risks and Disasters, 233-262. https://doi.org/10.1016/B978-0-12-394846-5.00009-6
  • Hain, C. R., Crow, W. T., Mecikalski, J. R., Anderson, M. C., & Holmes, T. (2011). An intercomparison of available soil moisture estimates from thermal infrared and passive microwave remote sensing and land surface modeling. Journal of Geophysical Research: Atmospheres, 116, D15107. https://doi.org/10.1029/2011JD015633
  • Wan, Z. (2006). MODIS land surface temperature products users’ guide. Institute for Computational Earth System Science, University of California: Santa Barbara, CA, USA, 805, 26.
  • Wan, Z., Zhang, Y., Zhang, Q., & Li, Z. L. (2002). Validation of the land-surface temperature products retrieved from Terra Moderate Resolution Imaging Spectroradiometer data. Remote Sensing of Environment, 83(1-2), 163-180. https://doi.org/10.1016/S0034-4257(02)00093-7
  • Senay, G. B., Bohms, S., Singh, R. K., Gowda, P. H., Velpuri, N. M., Alemu, H., & Verdin, J. P. (2013). Operational evapotranspiration mapping using remote sensing and weather datasets: A new parameterization for the SSEB approach. JAWRA Journal of the American Water Resources Association, 49(3), 577-591. https://doi.org/10.1111/jawr.12057
  • Bijaber N., El Hadani, D., Saidi, M., Svoboda, M. D., Poulsen, C. C., Hain, C. R., Wardlow, B. D., & Yessef, M. (2017). Suivi mensuel de la sécheresse au Maroc par techniques basées sur l'indice composite. GéoObservateur n°23, Rabat, Marocco, 25-37
  • Jia, H., Chen, F., Zhang, J., & Du, E. (2020). Vulnerability analysis to drought based on remote sensing indexes. International Journal of Environmental Research and Public Health, 17(20), 7660. https://doi.org/10.3390/ijerph17207660
  • Tran, H. T., Campbell, J. B., Tran, T. D., & Tran, H. T. (2017). Monitoring drought vulnerability using multispectral indices observed from sequential remote sensing (Case Study: Tuy Phong, Binh Thuan, Vietnam). GIScience & Remote Sensing, 54(2), 167-184. https://doi.org/10.1080/15481603.2017.1287838
  • Hanadé Houmma, I., Gadal, S., El Mansouri, L., Garba, M., Gbetkom, P. G., Mamane Barkawi, M. B., & Hadria, R. (2023). A new multivariate agricultural drought composite index based on random forest algorithm and remote sensing data developed for Sahelian agrosystems. Geomatics, Natural Hazards and Risk, 14(1), 2223384. https://doi.org/10.1080/19475705.2023.2223384
  • Badraoui, M. (2006). Connaissance et utilisation des ressources en sol au Maroc. Rapport thématique, 50.
  • Hengl, T., Mendes de Jesus, J., Heuvelink, G. B., Ruiperez Gonzalez, M., Kilibarda, M., Blagotić, A., ... & Kempen, B. (2017). SoilGrids250m: Global gridded soil information based on machine learning. PLoS One, 12(2), e0169748. https://doi.org/10.1371/journal.pone.0169748
  • Reichhuber, A., Gerber, N., Mirzabaev, A., Svoboda, M., López Santos, A., Graw, V., ... & Jia, X. (2019). The land-drought nexus enhancing the role of land-based interventions in drought mitigation and risk management. In United Nations Convention to Combat Desertification, Bonn.
  • Inglada, J., Vincent, A., Arias, M., Tardy, B., Morin, D., & Rodes, I. (2017). Operational high resolution land cover map production at the country scale using satellite image time series. Remote Sensing, 9(1), 95. https://doi.org/10.3390/rs9010095
  • Van Thinh, T., Duong, P. C., Nasahara, K. N., & Tadono, T. (2019). How does land use/land cover map's accuracy depend on number of classification classes?. Sola, 15, 28-31. https://doi.org/10.2151/sola.2019-006
  • Winsemius, H. C., Jongman, B., Veldkamp, T. I., Hallegatte, S., Bangalore, M., & Ward, P. J. (2018). Disaster risk, climate change, and poverty: assessing the global exposure of poor people to floods and droughts. Environment and Development Economics, 23(3), 328-348. https://doi.org/10.1017/S1355770X17000444
  • UNDRR (2021). Global Assessment Report on Disaster Risk Reduction GAR, Special Report on Drought.
  • Haut-Commissariat au Plan. (2017). Principaux résultats de la cartographie de la pauvreté multidimensionnelle 2014. Paysage territorial et dynamique, Rapport.
  • Murthy, C. S., Laxman, B., & Sai, M. S. (2015). Geospatial analysis of agricultural drought vulnerability using a composite index based on exposure, sensitivity and adaptive capacity. International Journal of Disaster Risk Reduction, 12, 163-171. https://doi.org/10.1016/j.ijdrr.2015.01.004
  • Balaghi, R., Jlibene, M., Tychon, B., & Eerens, H. (2012). La prédiction agrométéorologique des rendements céréaliers au Maroc. Institut National de La Recherche Agronomique, Maroc.
  • Bijaber, N., & Rochdi, A. (2019, November). Development of a comprehensive remote sensing technique for drought monitoring in Morocco. In Conference of the Arabian Journal of Geosciences, 311-313. https://doi.org/10.1007/978-3-030-72896-0_70
  • de Forges, A. R., Feller, C., Jamagne, M., & Arrouays, D. (2008). Perdus dans le triangle des textures. Etudes et gestion des Sols, 15(2), 97-111.
  • Motib, I., Batchi, M., & Fatah, F. (2020). Conservation Des Ressources Naturelles Pour Une Sécurité Alimentaire Durable Au Maroc. European Scientific Journal, 16, 240-260.
  • Alkire, S., Conconi, A., & Seth, S. (2014). Multidimensional Poverty Index 2014: Brief methodological note and results. OPHI briefing, 19.
Year 2024, , 264 - 280, 28.07.2024
https://doi.org/10.26833/ijeg.1404507

Abstract

References

  • Khorrami, B., & Gündüz, O. (2022). Detection and analysis of drought over Turkey with remote sensing and model-based drought indices. Geocarto International, 37(26), 12171-12193. https://doi.org/10.1080/10106049.2022.2066197
  • Observatoire du Sahara et du Sahel. (2013). Vers un système d'alerte précoce à la sécheresse au Maghreb. OSS. Collection Synthèse, 4. OSS: Tunis.
  • World Bank. (2022). Country Climate and Development Report: Morocco. Washington, DC: World Bank
  • Fritzsche, K., Schneiderbauer, S., Bubeck, P., Kienberger, S., Buth, M., Zebisch, M., & Kahlenborn, W. (2014). The Vulnerability Sourcebook: Concept and guidelines for standardised vulnerability assessments.
  • Hoque, M., Pradhan, B., Ahmed, N., & Alamri, A. (2021). Drought vulnerability assessment using geospatial techniques in southern Queensland, Australia. Sensors, 21(20), 6896. https://doi.org/10.3390/s21206896
  • West, H., Quinn, N., & Horswell, M. (2019). Remote sensing for drought monitoring & impact assessment: Progress, past challenges and future opportunities. Remote Sensing of Environment, 232, 111291. https://doi.org/10.1016/j.rse.2019.111291
  • Wilhite, D. A. (2000). Drought as a natural hazard: Concepts and Definitions. Drought: A Global Assessment.
  • Svoboda, M., & Fuchs, B. (2016). Handbook of Drought Indicators and Indices. Integrated Drought Management Programme (IDMP)
  • Iglesias, A., Cancelliere, S., Gabiña, D., López-Francos, A., Moneo, A., & Rossi, G. (2007). Medroplan Drought Management Guidelines and Examples of Application; European Commission. MEDA-Water Programme: Zaragoza, Spain.
  • RICCAR (2017). Training manual on the integrated vulnerability assessment methodology.
  • Szaboova, L. (2023). Climate change, migration and rural adaptation in the Near East and North Africa region. Food and Agriculture Organization of the United Nations.
  • Fritzsche, K., Schneiderbauer, S., Bubeck, P., Kienberger, S., Buth, M., Zebisch, M. & Kahlenborn, W. (2017). The vulnerability sourcebook. Concept and guidelines for standardized vulnerability assessments. Risk Supplement: How to apply the approach with the IPCC AR5 risk concept.
  • Bijaber, N., El Hadani, D., Saidi, M., Svoboda, M. D., Wardlow, B. D., Hain, C. R., ... & Rochdi, A. (2018). Developing a remotely sensed drought monitoring indicator for Morocco. Geosciences, 8(2), 55. https://doi.org/10.3390/geosciences8020055
  • Fragaszy, S. R., Jedd, T., Wall, N., Knutson, C., Fraj, M. B., Bergaoui, K., ... & McDonnell, R. (2020). Drought monitoring in the Middle East and North Africa (MENA) region: participatory engagement to inform early warning systems. Bulletin of the American Meteorological Society, 101(7), E1148-E1173. https://doi.org/10.1175/BAMS-D-18-0084.1
  • Svoboda, M. D., Fuchs, B. A., Poulsen, C. C., & Nothwehr, J. R. (2015). The drought risk atlas: enhancing decision support for drought risk management in the United States. Journal of Hydrology, 526, 274-286. https://doi.org/10.1016/j.jhydrol.2015.01.006
  • Funk, C. C., Peterson, P. J., Landsfeld, M. F., Pedreros, D. H., Verdin, J. P., Rowland, J. D., ... & Verdin, A. P. (2014). A quasi-global precipitation time series for drought monitoring. US Geological Survey, 832. https://dx.doi.org/10.3133/ds832
  • McKee, T. B., Doesken, N. J., & Kleist, J. (1995). Drought monitoring with multiple time scales. Proceedings of the Conference on Applied Climatology.
  • McKee, T. B., Doesken, N. J., & Kleist, J. (1993). The relationship of drought frequency and duration to time scales. Proceedings of the 8th Conference on Applied Climatology.
  • Senay, G. B., Velpuri, N. M., Bohms, S., Budde, M., Young, C., Rowland, J., & Verdin, J. P. (2015). Drought monitoring and assessment: remote sensing and modeling approaches for the famine early warning systems network. Hydro-meteorological Hazards, Risks and Disasters, 233-262. https://doi.org/10.1016/B978-0-12-394846-5.00009-6
  • Hain, C. R., Crow, W. T., Mecikalski, J. R., Anderson, M. C., & Holmes, T. (2011). An intercomparison of available soil moisture estimates from thermal infrared and passive microwave remote sensing and land surface modeling. Journal of Geophysical Research: Atmospheres, 116, D15107. https://doi.org/10.1029/2011JD015633
  • Wan, Z. (2006). MODIS land surface temperature products users’ guide. Institute for Computational Earth System Science, University of California: Santa Barbara, CA, USA, 805, 26.
  • Wan, Z., Zhang, Y., Zhang, Q., & Li, Z. L. (2002). Validation of the land-surface temperature products retrieved from Terra Moderate Resolution Imaging Spectroradiometer data. Remote Sensing of Environment, 83(1-2), 163-180. https://doi.org/10.1016/S0034-4257(02)00093-7
  • Senay, G. B., Bohms, S., Singh, R. K., Gowda, P. H., Velpuri, N. M., Alemu, H., & Verdin, J. P. (2013). Operational evapotranspiration mapping using remote sensing and weather datasets: A new parameterization for the SSEB approach. JAWRA Journal of the American Water Resources Association, 49(3), 577-591. https://doi.org/10.1111/jawr.12057
  • Bijaber N., El Hadani, D., Saidi, M., Svoboda, M. D., Poulsen, C. C., Hain, C. R., Wardlow, B. D., & Yessef, M. (2017). Suivi mensuel de la sécheresse au Maroc par techniques basées sur l'indice composite. GéoObservateur n°23, Rabat, Marocco, 25-37
  • Jia, H., Chen, F., Zhang, J., & Du, E. (2020). Vulnerability analysis to drought based on remote sensing indexes. International Journal of Environmental Research and Public Health, 17(20), 7660. https://doi.org/10.3390/ijerph17207660
  • Tran, H. T., Campbell, J. B., Tran, T. D., & Tran, H. T. (2017). Monitoring drought vulnerability using multispectral indices observed from sequential remote sensing (Case Study: Tuy Phong, Binh Thuan, Vietnam). GIScience & Remote Sensing, 54(2), 167-184. https://doi.org/10.1080/15481603.2017.1287838
  • Hanadé Houmma, I., Gadal, S., El Mansouri, L., Garba, M., Gbetkom, P. G., Mamane Barkawi, M. B., & Hadria, R. (2023). A new multivariate agricultural drought composite index based on random forest algorithm and remote sensing data developed for Sahelian agrosystems. Geomatics, Natural Hazards and Risk, 14(1), 2223384. https://doi.org/10.1080/19475705.2023.2223384
  • Badraoui, M. (2006). Connaissance et utilisation des ressources en sol au Maroc. Rapport thématique, 50.
  • Hengl, T., Mendes de Jesus, J., Heuvelink, G. B., Ruiperez Gonzalez, M., Kilibarda, M., Blagotić, A., ... & Kempen, B. (2017). SoilGrids250m: Global gridded soil information based on machine learning. PLoS One, 12(2), e0169748. https://doi.org/10.1371/journal.pone.0169748
  • Reichhuber, A., Gerber, N., Mirzabaev, A., Svoboda, M., López Santos, A., Graw, V., ... & Jia, X. (2019). The land-drought nexus enhancing the role of land-based interventions in drought mitigation and risk management. In United Nations Convention to Combat Desertification, Bonn.
  • Inglada, J., Vincent, A., Arias, M., Tardy, B., Morin, D., & Rodes, I. (2017). Operational high resolution land cover map production at the country scale using satellite image time series. Remote Sensing, 9(1), 95. https://doi.org/10.3390/rs9010095
  • Van Thinh, T., Duong, P. C., Nasahara, K. N., & Tadono, T. (2019). How does land use/land cover map's accuracy depend on number of classification classes?. Sola, 15, 28-31. https://doi.org/10.2151/sola.2019-006
  • Winsemius, H. C., Jongman, B., Veldkamp, T. I., Hallegatte, S., Bangalore, M., & Ward, P. J. (2018). Disaster risk, climate change, and poverty: assessing the global exposure of poor people to floods and droughts. Environment and Development Economics, 23(3), 328-348. https://doi.org/10.1017/S1355770X17000444
  • UNDRR (2021). Global Assessment Report on Disaster Risk Reduction GAR, Special Report on Drought.
  • Haut-Commissariat au Plan. (2017). Principaux résultats de la cartographie de la pauvreté multidimensionnelle 2014. Paysage territorial et dynamique, Rapport.
  • Murthy, C. S., Laxman, B., & Sai, M. S. (2015). Geospatial analysis of agricultural drought vulnerability using a composite index based on exposure, sensitivity and adaptive capacity. International Journal of Disaster Risk Reduction, 12, 163-171. https://doi.org/10.1016/j.ijdrr.2015.01.004
  • Balaghi, R., Jlibene, M., Tychon, B., & Eerens, H. (2012). La prédiction agrométéorologique des rendements céréaliers au Maroc. Institut National de La Recherche Agronomique, Maroc.
  • Bijaber, N., & Rochdi, A. (2019, November). Development of a comprehensive remote sensing technique for drought monitoring in Morocco. In Conference of the Arabian Journal of Geosciences, 311-313. https://doi.org/10.1007/978-3-030-72896-0_70
  • de Forges, A. R., Feller, C., Jamagne, M., & Arrouays, D. (2008). Perdus dans le triangle des textures. Etudes et gestion des Sols, 15(2), 97-111.
  • Motib, I., Batchi, M., & Fatah, F. (2020). Conservation Des Ressources Naturelles Pour Une Sécurité Alimentaire Durable Au Maroc. European Scientific Journal, 16, 240-260.
  • Alkire, S., Conconi, A., & Seth, S. (2014). Multidimensional Poverty Index 2014: Brief methodological note and results. OPHI briefing, 19.
There are 41 citations in total.

Details

Primary Language English
Subjects Land Management, Geospatial Information Systems and Geospatial Data Modelling, Cartography and Digital Mapping
Journal Section Articles
Authors

Noureddine Bijaber 0009-0004-0202-2788

Atmane Rochdi 0000-0002-8185-9866

Mohammed Yessef 0009-0000-6723-6390

Houda El Yacoubi 0000-0001-8017-6732

Early Pub Date July 25, 2024
Publication Date July 28, 2024
Submission Date December 13, 2023
Acceptance Date March 24, 2024
Published in Issue Year 2024

Cite

APA Bijaber, N., Rochdi, A., Yessef, M., El Yacoubi, H. (2024). Mapping the structural vulnerability to drought in Morocco. International Journal of Engineering and Geosciences, 9(2), 264-280. https://doi.org/10.26833/ijeg.1404507
AMA Bijaber N, Rochdi A, Yessef M, El Yacoubi H. Mapping the structural vulnerability to drought in Morocco. IJEG. July 2024;9(2):264-280. doi:10.26833/ijeg.1404507
Chicago Bijaber, Noureddine, Atmane Rochdi, Mohammed Yessef, and Houda El Yacoubi. “Mapping the Structural Vulnerability to Drought in Morocco”. International Journal of Engineering and Geosciences 9, no. 2 (July 2024): 264-80. https://doi.org/10.26833/ijeg.1404507.
EndNote Bijaber N, Rochdi A, Yessef M, El Yacoubi H (July 1, 2024) Mapping the structural vulnerability to drought in Morocco. International Journal of Engineering and Geosciences 9 2 264–280.
IEEE N. Bijaber, A. Rochdi, M. Yessef, and H. El Yacoubi, “Mapping the structural vulnerability to drought in Morocco”, IJEG, vol. 9, no. 2, pp. 264–280, 2024, doi: 10.26833/ijeg.1404507.
ISNAD Bijaber, Noureddine et al. “Mapping the Structural Vulnerability to Drought in Morocco”. International Journal of Engineering and Geosciences 9/2 (July 2024), 264-280. https://doi.org/10.26833/ijeg.1404507.
JAMA Bijaber N, Rochdi A, Yessef M, El Yacoubi H. Mapping the structural vulnerability to drought in Morocco. IJEG. 2024;9:264–280.
MLA Bijaber, Noureddine et al. “Mapping the Structural Vulnerability to Drought in Morocco”. International Journal of Engineering and Geosciences, vol. 9, no. 2, 2024, pp. 264-80, doi:10.26833/ijeg.1404507.
Vancouver Bijaber N, Rochdi A, Yessef M, El Yacoubi H. Mapping the structural vulnerability to drought in Morocco. IJEG. 2024;9(2):264-80.