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Research Article

Drought vulnerability of central Sahel agrosystems: a modelling-approach based on magnitudes of changes and machine learning techniques

, , , , , , , & show all
Pages 4262-4300 | Received 27 Mar 2023, Accepted 26 Jun 2023, Published online: 24 Jul 2023

References

  • Alamdarloo, E. H., M. B. Manesh, and H. Khosravi. 2018. “Probability Assessment of Vegetation Vulnerability to Drought Based on Remote Sensing Data.” Environmental Monitoring and Assessment 190 (12): 1–11. https://doi.org/10.1007/s10661-018-7089-1.
  • Arabameri, A., S. Chandra Pal, M. Santosh, R. Chakrabortty, P. Roy, and H. Moayedi. 2021. “Drought Risk Assessment: Integrating Meteorological, Hydrological, Agricultural, and Socioeconomic Factors Using Ensemble Models and Geospatial Techniques.” Geocarto International 37 (21): 1–29. https://doi.org/10.1080/10106049.2021.1926558.
  • Arshad, S., S. Morid, M. R. Mobasheri, and M. A. Alikhani. 2008. “Development of Agricultural Drought Risk Assessment Model for Kermanshah Province (Iran), Using Satellite Data and Intelligent Methods.” In Proceeding: The first international conference on Drought Management, Zaragoza, Spain (Vol. 12, pp. 303–310).
  • Adamou, Rabani and Ibrahim, Boubacar and Bonkaney, Abdou Latif and Seyni, Abdoul Aziz and Idrissa, Mamoudou, Niger - Land, Climate, Energy, Agriculture and Development: A Study in the Sudano-Sahel Initiative for Regional Development, Jobs, and Food Security (January 19, 2021). ZEF Working Paper Series, ISSN 1864-6638, Center for Development Research, University of Bonn, January 2021, Available at SSRN: https://ssrn.com/abstract=3769119
  • Ayantunde, A. A., M. D. Turner, and A. Kalilou. 2015. “Participatory Analysis of Vulnerability to Drought in Three Agro-Pastoral Communities in the West African Sahel.” Pastoralism 5 (13). https://doi.org/10.1186/s13570-015-0033-x.
  • Bachmair, S., K. Stahl, K. Collins, J. Hannaford, M. Acreman, M. Svoboda, and I. C. Overton. 2016. “Drought Indicators Revisited: The Need for a Wider Consideration of Environment and Society.” Wiley Interdisciplinary Reviews: Water 3 (4): 516–536.
  • Bahta, Y. T. 2022. “Social Vulnerability to Agricultural Drought: Insights from Northern Cape, South Africa.” Scientific African 17:e01324. https://doi.org/10.1016/j.sciaf.2022.e01324.
  • Banerjee, S., and A. C. Pandey. 2021. “Catchment-Level Agricultural Drought Hazard Vulnerability Analysis of Ganga Basin (India) Using Spectral Indices.” Arabian Journal of Geosciences 14 (17): 1–22. https://doi.org/10.1007/s12517-021-07825-6.
  • Bhavani, P., P. S. Roy, V. Chakravarthi, and V. P. Kanawade. 2017. “Satellite Remote Sensing for Monitoring Agriculture Growth and Agricultural Drought Vulnerability Using Long-Term (1982–2015) Climate Variability and Socioeconomic Dataset.” Proceedings of the National Academy of Sciences, India Section A: Physical Sciences 87 (4): 733–750. https://doi.org/10.1007/s40010-017-0445-7.
  • Chen, T., S. Zhou, C. Liang, D. F. T. Hagan, N. Zeng, J. Wang, T. Shi, X. Chen, and A. J. Dolman. 2020. “The Greening and Wetting of the Sahel Have Leveled off Since 999 in Relation to SST.” Remote Sensing 12 (17): 2723. https://doi.org/10.3390/rs12172723.
  • Choubin, B., F. Soleimani, A. Pirnia, F. Sajedi-Hosseini, H. Alilou, O. Rahmati, A. M. Melesse, V. P. Singh, and H. Shahabi. 2019. “Effects of Drought on Vegetative Cover Changes: Investigating Spatiotemporal Patterns.” In Extreme Hydrology and Climate Variability, 213–222. Elsevier.
  • Costa, L., A. A. Sant’anna, and C. E. F. Young. 2021. “Barren Lives: Drought Shocks and Agricultural Vulnerability in the Brazilian Semi-Arid.” Environment and Development Economics 1–21. https://doi.org/10.1017/S1355770X21000176.
  • Cruz, M. G., E. A. Hernandez, and V. Uddameri. 2021. “Vulnerability Assessment of Agricultural Production Systems to Drought Stresses Using Robustness Measures.” Scientific Reports 11 (1): 1–21. https://doi.org/10.1038/s41598-021-98829-5.
  • Cui, Y., J. Jin, X. Bai, S. Ning, L. Zhang, C. Wu, and Y. Zhang. 2022. “Quantitative Evaluation and Obstacle Factor Diagnosis of Agricultural Drought Disaster Risk Using Connection Number and Information Entropy.” Entropy 24 (7): 872. https://doi.org/10.3390/e24070872.
  • Dalezios, N. R., A. Blanta, N. V. Spyropoulos, and A. M. Tarquis. 2014. “Risk Identification of Agricultural Drought for Sustainable Agroecosystems.” Natural Hazards and Earth System Sciences 14 (9): 2435–2448. https://doi.org/10.5194/nhess-14-2435-2014.
  • Dardel, C., L. Kergoat, P. Hiernaux, E. Mougin, M. Grippa, and C. J. Tucker. 2014. “Regreening Sahel: 30 Years of Remote Sensing Data and Field Observations (Mali, Niger).” Remote Sensing of Environment 140:350–364. https://doi.org/10.1016/j.rse.2013.09.011.
  • Daryanto, S., L. Wang, and P. A. Jacinthe. 2017. “Global Synthesis of Drought Effects on Cereal, Legume, Tuber and Root Crops Production: A Review.” Agricultural Water Management 179: 18–33.
  • Desquith, L. E., and O. Renault. 2021. “Gestion du risque climatique : Les déterminants des stratégies d’adaptation des agriculteurs en Afrique subsaharienne.” In EconomiX Working Papers (No 202117; EconomiX Working Papers). University of Paris Nanterre, EconomiX. https://ideas.repec.org/p/drm/wpaper/2021-17.html.
  • Dilawar, A., B. Chen, A. Ashraf, K. Alphonse, Y. Hussain, S. Ali, J. Jinghong, et al. 2022. “Development of a GIS Based Hazard, Exposure, and Vulnerability Analysing Method for Monitoring Drought Risk at Karachi, Pakistan.” Geomatics, Natural Hazards and Risk 13 (1): 1700–1720. https://doi.org/10.1080/19475705.2022.2090863.
  • Dunne, A., and Y. Kuleshov. 2022. Drought Risk Assessment and Mapping for the Murray–Darling Basin, Australia. Natural Hazards.1–25.
  • Durowoju, O. S., T. E. Ologunorisa, and A. Akinbobola. 2022. “Assessing Agricultural and Hydrological Drought Vulnerability in a Savanna Ecological Zone of Sub-Saharan Africa.” Natural Hazards 111 (3): 2431–2458. https://doi.org/10.1007/s11069-021-05143-4.
  • Elusma, M., C. P. Tung, and C. C. Lee. 2022. “Agricultural Drought Risk Assessment in the Caribbean Region: The Case of Haiti.” International Journal of Disaster Risk Reduction 83:103414. https://doi.org/10.1016/j.ijdrr.2022.103414.
  • Elbeltagi, A., Kumari, N., Dharpure, J.K., Mokhtar, A., Alsafadi, K., Kumar, M., Mehdinejadiani, B., Ramezani Etedali, H., Brouziyne, Y., Towfiqul Islam, A.R.M., Kuriqi, A. 2021. Prediction of Combined Terrestrial Evapotranspiration Index (CTEI) over Large River Basin Based on Machine Learning Approaches. Water. 13: 547.
  • Emeterio, J. L. S., F. Alexandre, J. Andrieu, A. Génin, and C. Mering. 2013. “Changements socio-environnementaux et dynamiques des paysages ruraux le long du gradient bioclimatique nord-sud dans le sud-ouest du Niger (régions de Tillabery et de Dosso).” VertigO - la revue électronique en sciences de l’environnement 13 (Volume 13 Numéro 3): 3. https://doi.org/10.4000/vertigo.14456.
  • Epule, T. E., D. Dhiba, and A. Chehbouni. 2021. “Recent Climate Shocks in the Sahel: A Systematic Review.” The Nature, Causes, Effects and Mitigation of Climate Change on the Environment. https://doi.org/10.5772/intechopen.98882.
  • Faridatul, M. I., and B. Ahmed. 2020. “Assessing Agricultural Vulnerability to Drought in a Heterogeneous Environment: A Remote Sensing-Based Approach.” Remote Sensing 12 (20): 3363. https://doi.org/10.3390/rs12203363.
  • Faye, C. 2018. “Climatic Variability and Hydrological Impacts in West Africa: Case of the Gambia Watershed (Senegal).” Environmental and Water Sciences, Public Health and Territorial Intelligence Journal 2 (1): 54 66.
  • Fall, C. M. N., Lavaysse, C., Kerdiles, H., Dramé, M. S., Roudier, P., & Gaye, A. T. 2021. Performance of dry and wet spells combined with remote sensing indicators for crop yield prediction in Senegal. Climate Risk Management. 33: 100331.
  • Feller U. 2016. “Drought Stress and Carbon Assimilation in a Warming Climate: Reversible and Irreversible Impacts.” Journal of Plant Physiology 203: 84–94.
  • Feller, U., and Vaseva II. 2014. “Extreme Climatic Events: Impacts of Drought and High Temperature on Physiological Processes in Agronomically Important Plants.” Frontiers in Environmental Science 2: 39.
  • Frischen, J., I. Meza, D. Rupp, K. Wietler, and M. Hagenlocher. 2020. “Drought Risk to Agricultural Systems in Zimbabwe: A Spatial Analysis of Hazard, Exposure, and Vulnerability.” Sustainability 12 (3): 752. https://doi.org/10.3390/su12030752.
  • Guo, H., J. Chen, and C. Pan. 2021. “Assessment on Agricultural Drought Vulnerability and Spatial Heterogeneity Study in China.” International Journal of Environmental Research and Public Health 18 (9): 4449. https://doi.org/10.3390/ijerph18094449.
  • Guo, H., L. Feng, Y. Wu, J. Wang, and Q. Liang. 2022. “Assessment of smallholders’ Vulnerability to Drought Based on Household-Scale Planting Strategies and Adaptability: A Survey Study of Xinghe County.” International Journal of Disaster Risk Reduction 72:102820. https://doi.org/10.1016/j.ijdrr.2022.102820.
  • Hao, H., H. Zhu, and F. Wang. 2022. “Regional Agricultural Drought Risk Assessment Based on Attribute Interval Identification: A Study from Zhengzhou, China.” Water Supply 22 (5): 5309–5330. https://doi.org/10.2166/ws.2022.177.
  • Habibie MI, Ahamed T, Noguchi R, Matsushita S. (2020, December). Deep learning algorithms to determine drought prone areas using remote sensing and GIS. In 2020 IEEE Asia-Pacific Conference on Geoscience, Electronics and Remote Sensing Technology (AGERS) (pp. 69-73). IEEE.
  • Heidari, H., M. Arabi, M. Ghanbari, and T. Warziniack. 2020. “A Probabilistic Approach for Characterization of Sub-Annual Socioeconomic Drought Intensity-Duration-Frequency (IDF) Relationships in a Changing Environment.” Water 12 (6): 1522. https://doi.org/10.3390/w12061522.
  • Hina, S., F. Saleem, A. Arshad, A. Hina, and I. Ullah. 2021. “Drought Over Pakistan: Possible Cycle, Precursors and Associated Mechanisms.” Geomatic and Naturel Hazard Risks 12 (1): 1638–1668.
  • Hoque, M. A. A., B. Pradhan, and N. Ahmed. 2020. “Assessing Drought Vulnerability Using Geospatial Techniques in Northwestern Part of Bangladesh.” Science of the Total Environment 705:135957. https://doi.org/10.1016/j.scitotenv.2019.135957.
  • Hoque, M. A. A., B. Pradhan, N. Ahmed, and M. S. I. Sohel. 2021. “Agricultural Drought Risk Assessment of Northern New South Wales, Australia Using Geospatial Techniques.” Science of the Total Environment 756:143600. https://doi.org/10.1016/j.scitotenv.2020.143600.
  • Ilbahar, E. 2022. “Drought Vulnerability Assessment Based on IVIF AHP and IVIF WASPAS: A Case Study in Turkey.” In Multi-Criteria Decision Analysis, 107–121. CRC Press.
  • Ippolito, T. A., J. E. Herrick, E. L. Dossa, M. Garba, M. Ouattara, U. Singh, Z. P. Stewart, P. V. V. Prasad, I. A. Oumarou, and J. C. Neff. 2021. “A Comparison of Approaches to Regional Land-Use Capability Analysis for Agricultural Land-Planning.” Land 10 (5): 458. Land 2021. https://doi.org/10.3390/land10050458.
  • Imani, Y., Lahlou, O., Bennasser Alaoui, S., Naumann, G., Barbosa, P., & Vogt, J. (2014, May). Drought vulnerability assesssment and mapping in Morocco. In EGU General Assembly Conference Abstracts (p. 276).
  • Kafy, A. A., A. Bakshi, M. Saha, A. Al Faisal, A. I. Almulhim, Z. A. Rahaman, and P. Mohammad. 2023. “Assessment and Prediction of Index Based Agricultural Drought Vulnerability Using Machine Learning Algorithms.” Science of the Total Environment 867:161394. https://doi.org/10.1016/j.scitotenv.2023.161394.
  • Latha, S. 2021. “Assessment of Agricultural Drought Vulnerability in Tamil Nadu Using MODIS NDVI, NDWI and VSDI.” In Sustainable Climate Action and Water Management, 211–228. Singapore: Springer Singapore. https://doi.org/10.1007/978-981-15-8237-0_18.
  • Le Page, M., and M. Zribi. 2019. “Analysis and Predictability of Drought in Northwest Africa Using Optical and Microwave Satellite Remote Sensing Products.” Scientific Reports 9 (1): 1466.
  • Leroux, L., Castets, M., Baron, C., Escorihuela, M. J., Bégué, A., Seen, D. L. 2019. Maize yield estimation in West Africa from crop process-induced combinations of multi-domain remote sensing indices. European Journal of Agronomy. 108: 11-26.
  • Liang, L., F. Zhang, and K. Qin. 2021. “Assessing the Vulnerability of Agricultural Systems to Drought in Kyrgyzstan.” Water 13 (21): 3117. https://doi.org/10.3390/w13213117.
  • Li, L. L., Zhao, X., Tseng, M. L., Tan, R. R. 2020. Short-term wind power forecasting based on support vector machine with improved dragonfly algorithm. Journal of Cleaner Production. 242: 118447.
  • Li, Z., Z. Zhang, and L. Zhang. 2021. “Improving Regional Wheat Drought Risk Assessment for Insurance Application by Integrating Scenario-Driven Crop Model, Machine Learning, and Satellite Data.” Agricultural Systems 191:103141. https://doi.org/10.1016/j.agsy.2021.103141.
  • Ma, Y., S. Guga, J. Xu, X. Liu, Z. Tong, and J. Zhang. 2022. “Evaluation of Drought Vulnerability of Maize and Influencing Factors in Songliao Plain Based on the SE-DEA-Tobit Model.” Remote Sensing 14 (15): 3711. https://doi.org/10.3390/rs14153711.
  • Masroor, M., S. V. Razavi-Termeh, M. H. Rahaman, P. Choudhari, L. C. Kulimushi, and H. Sajjad. 2023. “Adaptive Neuro Fuzzy Inference System (ANFIS) Machine Learning Algorithm for Assessing Environmental and Socio-Economic Vulnerability to Drought: A Study in Godavari Middle Sub-Basin, India.” Stochastic Environmental Research and Risk Assessment: Research Journal 37 (1): 233–259. https://doi.org/10.1007/s00477-022-02292-1.
  • Mohammadi, H., N. Iizadi, and E. Ghasemi Garkani. 2022. “Investigation of Vulnerability and Spatial Analysis of Drought Risk in the Agricultural Sector in Iran.” Journal of Natural Environmental Hazards 12 (36): 79–98.
  • Mohan, N. P. 2022. “Rapid Diagnosis and Evaluation of Agricultural Drought Based on Machine Learning Language.” Journal of Innovation and Social Science Research 9 (2). https://doi.org/10.53469/jissr.2022.09(02).04.
  • Monteleone, B., I. Borzí, B. Bonaccorso, and M. Martina. 2022. “Developing Stage-Specific Drought Vulnerability Curves for Maize: The Case Study of the Po River Basin.” Agricultural Water Management 269:107713. https://doi.org/10.1016/j.agwat.2022.107713.
  • Murthy, C. S., M. V. R. Sesha Sai, K. Chandrasekar, and P. S. Roy. 2009. “Spatial and Temporal Responses of Different Crop‐Growing Environments to Agricultural Drought: A Study in Haryana State, India Using NOAA AVHRR Data.” International Journal of Remote Sensing 30 (11): 2897–2914. https://doi.org/10.1080/01431160802558626.
  • Nooni IK, Hagan DFT, Wang G, Ullah W, Li S, Lu J, Bhatti AS, Shi X, Lou D, Prempeh NA, Lim Kam Sian KTC, Dzakpasu M, Amankwah SOY, Zhu C. 2021. Spatiotemporal Characteristics and Trend Analysis of Two Evapotranspiration-Based Drought Products and Their Mechanisms in Sub-Saharan Africa. Remote Sensing. 13(3):533.
  • Nsch, R. H., Wiesner, P., Wendler, S., Hellwich, O. (2019, January). Colorful trees: Visualizing random forests for analysis and interpretation. In 2019 IEEE Winter Conference on Applications of Computer Vision (WACV) (pp. 294-302). IEEE.
  • Murthy, C. S., M. Yadav, J. Mohammed Ahamed, B. Laxman, R. Prawasi, M. R. Sesha Sai, and R. S. Hooda. 2015. “A Study on Agricultural Drought Vulnerability at Disaggregated Level in a Highly Irrigated and Intensely Cropped State of India.” Environmental Monitoring and Assessment 187 (3): 1–14. https://doi.org/10.1007/s10661-015-4296-x.
  • Noureldeen, N., K. Mao, A. Mohmmed, Z. Yuan, and Y. Yang. 2020. “Spatiotemporal Drought Assessment Over Sahelian Countries from 1985 to 2015.” Journal of Meteorological Research 34 (4): 760–774. https://doi.org/10.1007/s13351-020-9178-7.
  • Ortega-Gaucin, D., J. A. Ceballos-Tavares, A. Ordoñez Sánchez, and H. V. Castellano-Bahena. 2021. “Agricultural Drought Risk Assessment: A Spatial Analysis of Hazard, Exposure, and Vulnerability in Zacatecas, Mexico.” Water 13 (10): 1431. https://doi.org/10.3390/w13101431.
  • Ortega-Gaucin, D., D. la Cruz Bartolón J, and H. V. Castellano Bahena. 2018. “Drought Vulnerability Indices in Mexico.” Water 10 (11): 1671. https://doi.org/10.3390/w10111671.
  • Rahmati, O., F. Falah, K. S. Dayal, R. C. Deo, F. Mohammadi, T. Biggs, D. D. Moghaddam, S. A. Naghibi, and D. T. Bui. 2020. “Machine Learning Approaches for Spatial Modeling of Agricultural Droughts in the South-East Region of Queensland Australia.” Science of the Total Environment 699:134230. https://doi.org/10.1016/j.scitotenv.2019.134230.
  • Roodposhti, M. S., T. Safarrad, and H. Shahabi. 2017. “Drought Sensitivity Mapping Using Two One-Class Support Vector Machine Algorithms.” Atmospheric Research 193:73–82. https://doi.org/10.1016/j.atmosres.2017.04.017.
  • Saha, S., P. Gogoi, A. Gayen, and G. C. Paul. 2021a. “Constructing the Machine Learning Techniques Based Spatial Drought Vulnerability Index in Karnataka State of India.” Journal of Cleaner Production 314:128073. https://doi.org/10.1016/j.jclepro.2021.128073.
  • Saha, S., B. Kundu, G. C. Paul, and B. Pradhan. 2023a. “Proposing an Ensemble Machine Learning Based Drought Vulnerability Index Using M5P, Dagging, Random Sub-Space and Rotation Forest Models.” Stochastic Environmental Research and Risk Assessment 37 (7): 1–28. https://doi.org/10.1007/s00477-023-02403-6.
  • Saha, S., B. Kundu, G. C. Pau, K. Mukherje, B. Pradhan, A. Dikshit, K. N. Abdul Maulud, and A. M. Alamri. 2021b. “Spatial Assessment of Drought Vulnerability Using Fuzzy-Analytical Hierarchical Process: A Case Study at the Indian State of Odisha.” Geomatics, Natural Hazards and Risk 12 (1): 123–153. https://doi.org/10.1080/19475705.2020.1861114.
  • Saha, S., B. Kundu, A. Saha, K. Mukherjee, and B. Pradhan. 2023b. “Manifesting Deep Learning Algorithms for Developing Drought Vulnerability Index in Monsoon Climate Dominant Region of West Bengal, India.” Theoretical and Applied Climatology 15 (1–2): 891–913. https://doi.org/10.1007/s00704-022-04300-4.
  • Sarkar, H., S. Soni, I. Ahmad, and M. K. Verma. 2020. “Assessment of Agricultural Drought in Upper Seonath Sub-Basin of Chhattisgarh (India) Using Remote Sensing and GIS-Based Indices.” Journal of the Indian Society of Remote Sensing 48 (6): 921–933. https://doi.org/10.1007/s12524-020-01124-5.
  • Sehgal, V. K., and R. Dhakar. 2016. “Geospatial Approach for Assessment of Biophysical Vulnerability to Agricultural Drought and Its Intraseasonal Variations.” Environmental Monitoring and Assessment 188 (3): 1–18. https://doi.org/10.1007/s10661-016-5187-5.
  • Serdeczny, O., S. Adams, F. Baarsch, D. Coumou, A. Robinson, W. Hare, M. Schaeffer, M. Perrette, and J. Reinhardt. 2017. “Climate Change Impacts in Sub-Saharan Africa: From Physical Changes to Their Social Repercussions.” Regional Environmental Change 17 (6): 1585 1600. https://doi.org/10.1007/s10113-015-0910-2.
  • Shiferaw, B., K. Tesfaye, M. Kassie, T. Abate, B. M. Prasanna, and A. Menkir. 2014. “Managing Vulnerability to Drought and Enhancing Livelihood Resilience in Sub-Saharan Africa: Technological, Institutional and Policy Options.” Weather and Climate Extremes 3:67–79. https://doi.org/10.1016/j.wace.2014.04.004.
  • Singh, P., A. K. Kannaujiya, A. Deep, S. Singh, T. Mohanty, and K. Prakash. 2023. “Spatio‐Temporal Drought Susceptibility Assessment of Ken River Basin, Central India, and Its Evaluation Through River’s Morphometry.” Geological Journal 58 (2): 755–779. https://doi.org/10.1002/gj.4622.
  • Stevens, F. R., A. E. Gaughan, C. Linard, and A. J. Tatem. 2015. “Disaggregating Census Data for Population Mapping Using Random Forests with Remotely Sensed and Ancillary Data.” PLoS ONE 10 (2): e0107042. https://doi.org/10.1371/journal.pone.0107042.
  • Su, Y., Q. Li, and Y. Niu 2022, April. Study into the Evolution of Temporal and Spatial Pattern of the Agricultural Drought Vulnerability and the Agricultural Insurance Development. In Proceedings of the 4th International Conference on Management Science and Industrial Engineering, Chiang Mai Thailand April 28-30 (pp. 260–269).
  • Sultana, M. S., M. Y. Gazi, and M. B. Mia. 2021. “Multiple Indices Based Agricultural Drought Assessment in the Northwestern Part of Bangladesh Using Geospatial Techniques.” Environmental Challenges 4:100120. https://doi.org/10.1016/j.envc.2021.100120.
  • Sun, H., L. Fang, Y. Dang, and W. Mao. 2020. “Identifying Influence Patterns of Regional Agricultural Drought Vulnerability Using a Two-Phased Grey Rough Combined Model.” Grey Systems: Theory and Application 12 (1): 230–25. https://doi.org/10.1108/GS-07-2020-0090.
  • Tallar, R. Y., and B. A. Dhian. 2021. “A Viable Drought Vulnerability Index for Outermost Small Islands in Indonesia.” Groundwater for Sustainable Development 15:100698. https://doi.org/10.1016/j.gsd.2021.100698.
  • Traore, S. M. A., D. H. Oumarou, B. Issoufou, and A. Balla. 2020. “Offre et demande en cereales au Sahel et in Afrqiue de l’Ouest.” Agronomie Africaine 32 (3): 251264.
  • Tschakert, P. 2007. “Views from the Vulnerable: Understanding Climatic and Other Stressors in the Sahel.” Global Environmental Change 17 (3–4): 381–396. https://doi.org/10.1016/j.gloenvcha.2006.11.008.
  • Upadhyay, M., and S. M. Avarachen. 2023. “Multivariate Framework for Integrated Drought Vulnerability Assessment–An Application to India.” International Journal of Disaster 85:103515. Risk Reduction.85:103515. https://doi.org/10.1016/j.ijdrr.2022.103515.
  • Vicente-Serrano, S. M., D. Cabello, M. Tomás-Burguera, N. Martín-Hernández, S. Beguería, C. Azorin-Molina, and A. E. Kenawy. 2015. “Drought Variability and Land Degradation in Semiarid Regions: Assessment Using Remote Sensing Data and Drought Indices (1982–2011).” Remote Sensing 7 (4): 4391–4423. https://doi.org/10.3390/rs70404391.
  • Wilhelmi, O. V., and D. A. Wilhite. 2002. “Assessing Vulnerability to Agricultural Drought: A Nebraska Case Study.” Natural Hazards 25 (1): 37–58. https://doi.org/10.1023/A:1013388814894.
  • Wu, J., X. Lin, M. Wang, J. Peng, and Y. Tu. 2017. “Assessing Agricultural Drought Vulnerability by a VSD Model: A Case Study in Yunnan Province, China.” Sustainability 9 (6): 918. https://doi.org/10.3390/su9060918.
  • Xu, L., and W. Zhang. 2018. “Assessment of Regional Agricultural Drought Vulnerability and Main Influencing Factors.” Advances in Science and Technology of Water Resources 38 (2): 14–19.
  • Zeng, Z., W. Wu, Z. Li, Y. Zhou, Y. Guo, and H. Huang. 2019. “Agricultural Drought Risk Assessment in Southwest China.” Water 11 (5): 1064. https://doi.org/10.3390/w11051064.
  • Zhang, D., W. Cao, B. Qi, and Z. Wang. 2021. “Identifying Influencing Factors of Regional Agricultural Drought Vulnerability Based on PSR-TGRC Method.” Mathematical Problems in Engineering 2021:1–13. https://doi.org/10.1155/2021/9933152.
  • Zhou, R., J. Jin, Y. Cui, S. Ning, X. Bai, L. Zhang, Y. Zhou, C. Wu, and F. Tong. 2022. “Agricultural Drought Vulnerability Assessment and Diagnosis Based on Entropy Fuzzy Pattern Recognition and Subtraction Set Pair Potential.” Alexandria Engineering Journal 61 (1): 51–63. https://doi.org/10.1016/j.aej.2021.04.090.
  • Zhu, X., K. Xu, Y. Liu, R. Guo, and L. Chen. 2021. “Assessing the Vulnerability and Risk of Maize to Drought in China Based on the AquaCrop Model.” Agricultural Systems 189:103040. https://doi.org/10.1016/j.agsy.2020.103040.

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