Articles | Volume 20, issue 2
https://doi.org/10.5194/nhess-20-471-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Special issue:
https://doi.org/10.5194/nhess-20-471-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
19 Feb 2020
Research article |
| 19 Feb 2020
| 19 Feb 2020
A joint probabilistic index for objective drought identification: the case study of Haiti
Beatrice Monteleone
CORRESPONDING AUTHOR
Scuola Universitaria Superiore IUSS Pavia, Pavia, 27100, Italy
Brunella Bonaccorso
Department of Engineering, University of Messina, St Agata, Messina, 98166, Italy
Mario Martina
Scuola Universitaria Superiore IUSS Pavia, Pavia, 27100, Italy
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Cited
17 citations as recorded by crossref.
- Quantitative analysis of input data uncertainty for SPI and SPEI in Peninsular Malaysia based on the bootstrap method Y. Tan et al. 10.1080/02626667.2023.2232348
- Spatial-Temporal Assessment of Drought in Hoa Vang district, Da Nang City, Vietnam Using Remote Sensing and Google Earth Engine L. Ngoc Hanh et al. 10.1088/1755-1315/1345/1/012013
- Quantifying agricultural drought in the Koshi River basin through soil moisture simulation P. Banjara et al. 10.1016/j.ejrh.2024.102132
- Quantification of interactions among agricultural drought indices within Köppen–Geiger climate zones in Bangladesh S. Osmani et al. 10.1016/j.agwat.2024.108952
- Evaluation Study of Ecological Resilience in Southern Red Soil Mining Areas Considering Rare Earth Mining Process J. Zhang et al. 10.3390/su15032258
- Vegetation drought risk assessment based on the multi-weight methods in Northwest China H. Chen et al. 10.1007/s10661-023-11747-z
- Input subsidies, credit constraints, and expectations of future transfers: Evidence from Haiti J. Gignoux et al. 10.1111/ajae.12337
- Innovative data clustering method improves drought prediction in heterogeneous landscapes using GEE-derived remote sensing indices H. Heydari et al. 10.1016/j.rsase.2023.101112
- Interactions between precipitation, evapotranspiration and soil-moisture-based indices to characterize drought with high-resolution remote sensing and land-surface model data J. Gaona et al. 10.5194/nhess-22-3461-2022
- Quantifying crop vulnerability to weather-related extreme events and climate change through vulnerability curves B. Monteleone et al. 10.1007/s11069-022-05791-0
- Space–time variability in soil moisture droughts in the Himalayan region S. Nepal et al. 10.5194/hess-25-1761-2021
- An improved global vegetation health index dataset in detecting vegetation drought J. Zeng et al. 10.1038/s41597-023-02255-3
- Improving the drought monitoring capability of VHI at the global scale via ensemble indices for various vegetation types from 2001 to 2018 J. Zeng et al. 10.1016/j.wace.2022.100412
- Developing stage-specific drought vulnerability curves for maize: The case study of the Po River basin B. Monteleone et al. 10.1016/j.agwat.2022.107713
- Drought frequency characteristics of China, 1981-2019, based on the vegetation health index J. Zeng et al. 10.3354/cr01616
- Preface: Recent advances in drought and water scarcity monitoring, modelling, and forecasting B. Bonaccorso et al. 10.5194/nhess-22-1857-2022
- Copula-based drought risk analysis on rainfed agriculture under stationary and non-stationary settings S. Das et al. 10.1080/02626667.2022.2079416
16 citations as recorded by crossref.
- Quantitative analysis of input data uncertainty for SPI and SPEI in Peninsular Malaysia based on the bootstrap method Y. Tan et al. 10.1080/02626667.2023.2232348
- Spatial-Temporal Assessment of Drought in Hoa Vang district, Da Nang City, Vietnam Using Remote Sensing and Google Earth Engine L. Ngoc Hanh et al. 10.1088/1755-1315/1345/1/012013
- Quantifying agricultural drought in the Koshi River basin through soil moisture simulation P. Banjara et al. 10.1016/j.ejrh.2024.102132
- Quantification of interactions among agricultural drought indices within Köppen–Geiger climate zones in Bangladesh S. Osmani et al. 10.1016/j.agwat.2024.108952
- Evaluation Study of Ecological Resilience in Southern Red Soil Mining Areas Considering Rare Earth Mining Process J. Zhang et al. 10.3390/su15032258
- Vegetation drought risk assessment based on the multi-weight methods in Northwest China H. Chen et al. 10.1007/s10661-023-11747-z
- Input subsidies, credit constraints, and expectations of future transfers: Evidence from Haiti J. Gignoux et al. 10.1111/ajae.12337
- Innovative data clustering method improves drought prediction in heterogeneous landscapes using GEE-derived remote sensing indices H. Heydari et al. 10.1016/j.rsase.2023.101112
- Interactions between precipitation, evapotranspiration and soil-moisture-based indices to characterize drought with high-resolution remote sensing and land-surface model data J. Gaona et al. 10.5194/nhess-22-3461-2022
- Quantifying crop vulnerability to weather-related extreme events and climate change through vulnerability curves B. Monteleone et al. 10.1007/s11069-022-05791-0
- Space–time variability in soil moisture droughts in the Himalayan region S. Nepal et al. 10.5194/hess-25-1761-2021
- An improved global vegetation health index dataset in detecting vegetation drought J. Zeng et al. 10.1038/s41597-023-02255-3
- Improving the drought monitoring capability of VHI at the global scale via ensemble indices for various vegetation types from 2001 to 2018 J. Zeng et al. 10.1016/j.wace.2022.100412
- Developing stage-specific drought vulnerability curves for maize: The case study of the Po River basin B. Monteleone et al. 10.1016/j.agwat.2022.107713
- Drought frequency characteristics of China, 1981-2019, based on the vegetation health index J. Zeng et al. 10.3354/cr01616
- Preface: Recent advances in drought and water scarcity monitoring, modelling, and forecasting B. Bonaccorso et al. 10.5194/nhess-22-1857-2022
1 citations as recorded by crossref.
Latest update: 08 Jan 2025
Short summary
This study proposes a new drought index that combines meteorological and agricultural drought aspects. The index is scalable, transferable all over the globe, can be updated in near real time and is a
remote-sensing product, since only satellite-based datasets were employed. A set of rules to objectively identify drought events is also implemented. We found that the set of rules, applied together with the new index, outperformed conventional drought indices in identifying droughts in Haiti.
This study proposes a new drought index that combines meteorological and agricultural drought...
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