Articles | Volume 29, issue 5
https://doi.org/10.5194/hess-29-1379-2025
https://doi.org/10.5194/hess-29-1379-2025
Review article
 | 
13 Mar 2025
Review article |  | 13 Mar 2025

Drought research priorities, trends, and geographic patterns

Roland Baatz, Gohar Ghazaryan, Michael Hagenlocher, Claas Nendel, Andrea Toreti, and Ehsan Eyshi Rezaei

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Cited articles

Al Mamun, M. A., Sarker, M. R., Sarkar, M. A. R., Roy, S. K., Nihad, S. A. I., McKenzie, A. M., Hossain, M. I., and Kabir, M. S.: Identification of influential weather parameters and seasonal drought prediction in Bangladesh using machine learning algorithm, Scientific Reports, 14, 566, https://doi.org/10.1038/s41598-023-51111-2, 2024. 
Anders, S., Cowling, W., Pareek, A., Gupta, K. J., Singla-Pareek, S. L., and Foyer, C. H.: Gaining Acceptance of Novel Plant Breeding Technologies, Trends Plant Sci., 26, 575–587, https://doi.org/10.1016/j.tplants.2021.03.004, 2021. 
Bailey-Serres, J., Parker, J. E., Ainsworth, E. A., Oldroyd, G. E. D., and Schroeder, J. I.: Genetic strategies for improving crop yields, Nature, 575, 109–118, https://doi.org/10.1038/s41586-019-1679-0, 2019. 
Belesova, K., Agabiirwe, C. N., Zou, M., Phalkey, R., and Wilkinson, P.: Drought exposure as a risk factor for child undernutrition in low- and middle-income countries: A systematic review and assessment of empirical evidence, Environ. Int., 131, 104973, https://doi.org/10.1016/j.envint.2019.104973, 2019. 
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Our global review of 130 000 peer-reviewed articles reveals that drought forecasting and plant genetics dominate drought research priorities. Using topic modelling, we traced evolving themes from 1901 to 2022, highlighting a shift from ecology to cutting-edge technologies. By applying unsupervised machine learning, we offer insights into how integrated approaches matter, guiding future priorities to strengthen drought resilience and to safeguard water resources.
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