Articles | Volume 22, issue 11
https://doi.org/10.5194/hess-22-5697-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/hess-22-5697-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
05 Nov 2018
Research article |
| 05 Nov 2018
| 05 Nov 2018
Seasonal drought predictability and forecast skill in the semi-arid endorheic Heihe River basin in northwestern China
Feng Ma
State Key Laboratory of Earth Surface and Ecological Resources,
Faculty of Geographical Science, Beijing Normal University,
Beijing 100875, China
Department of Geography, Environment, and
Spatial Sciences, Michigan State University, East Lansing,
Michigan, USA
Lifeng Luo
Department of Geography, Environment, and
Spatial Sciences, Michigan State University, East Lansing,
Michigan, USA
State Key Laboratory of Earth Surface and Ecological Resources,
Faculty of Geographical Science, Beijing Normal University,
Beijing 100875, China
Qingyun Duan
State Key Laboratory of Earth Surface and Ecological Resources,
Faculty of Geographical Science, Beijing Normal University,
Beijing 100875, China
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Cited
17 citations as recorded by crossref.
- Comparison of parametric and nonparametric standardized precipitation index for detecting meteorological drought over the Indian region N. Mallenahalli 10.1007/s00704-020-03296-z
- The limitation of machine learning methods for water supply and demand forecasting: A case study for Greater Melbourne, Australia M. Mohammadi et al. 10.2166/ws.2024.225
- Comparison between canonical vine copulas and a meta-Gaussian model for forecasting agricultural drought over China H. Wu et al. 10.5194/hess-26-3847-2022
- Developing a hydrological monitoring and sub-seasonal to seasonal forecasting system for South and Southeast Asian river basins Y. Zhou et al. 10.5194/hess-25-41-2021
- Meteorological drought forecasting based on a statistical model with machine learning techniques in Shaanxi province, China R. Zhang et al. 10.1016/j.scitotenv.2019.01.431
- A framework of integrating heterogeneous data sources for monthly streamflow prediction using a state-of-the-art deep learning model W. Xu et al. 10.1016/j.jhydrol.2022.128599
- Meteorological drought predictability dynamics and possible driving mechanisms in a changing environment in the Loess Plateau, China Y. Wang et al. 10.1016/j.atmosres.2024.107842
- Ecosystem water use efficiency response to drought over southwest China A. Mokhtar et al. 10.1002/eco.2317
- Long-term monitoring and evaluation of drought and determining the accuracy of its indicators in western Iran A. Khasraei et al. 10.1007/s10668-024-04608-3
- Land-atmosphere and ocean–atmosphere couplings dominate the dynamics of agricultural drought predictability in the Loess Plateau, China J. Luo et al. 10.1016/j.jhydrol.2024.132225
- Hydrological drought class early warning using support vector machines and rough sets R. Kolachian & B. Saghafian 10.1007/s12665-021-09536-3
- Temporal Hydrological Drought Index Forecasting for New South Wales, Australia Using Machine Learning Approaches A. Dikshit et al. 10.3390/atmos11060585
- Characteristics of climate extremes in China during the recent global warming hiatus based upon machine learning P. Qin & C. Shi 10.1002/joc.7354
- Analysis of the atmospheric circulation pattern effects over SPEI drought index in Spain A. Manzano et al. 10.1016/j.atmosres.2019.104630
- Spatial association of anomaly correlation for GCM seasonal forecasts of global precipitation T. Zhao et al. 10.1007/s00382-020-05384-2
- Intensification of drought propagation over the Yangtze River basin under climate warming F. Ma et al. 10.1002/joc.8165
- Seasonal drought predictability and forecast skill in the semi-arid endorheic Heihe River basin in northwestern China F. Ma et al. 10.5194/hess-22-5697-2018
16 citations as recorded by crossref.
- Comparison of parametric and nonparametric standardized precipitation index for detecting meteorological drought over the Indian region N. Mallenahalli 10.1007/s00704-020-03296-z
- The limitation of machine learning methods for water supply and demand forecasting: A case study for Greater Melbourne, Australia M. Mohammadi et al. 10.2166/ws.2024.225
- Comparison between canonical vine copulas and a meta-Gaussian model for forecasting agricultural drought over China H. Wu et al. 10.5194/hess-26-3847-2022
- Developing a hydrological monitoring and sub-seasonal to seasonal forecasting system for South and Southeast Asian river basins Y. Zhou et al. 10.5194/hess-25-41-2021
- Meteorological drought forecasting based on a statistical model with machine learning techniques in Shaanxi province, China R. Zhang et al. 10.1016/j.scitotenv.2019.01.431
- A framework of integrating heterogeneous data sources for monthly streamflow prediction using a state-of-the-art deep learning model W. Xu et al. 10.1016/j.jhydrol.2022.128599
- Meteorological drought predictability dynamics and possible driving mechanisms in a changing environment in the Loess Plateau, China Y. Wang et al. 10.1016/j.atmosres.2024.107842
- Ecosystem water use efficiency response to drought over southwest China A. Mokhtar et al. 10.1002/eco.2317
- Long-term monitoring and evaluation of drought and determining the accuracy of its indicators in western Iran A. Khasraei et al. 10.1007/s10668-024-04608-3
- Land-atmosphere and ocean–atmosphere couplings dominate the dynamics of agricultural drought predictability in the Loess Plateau, China J. Luo et al. 10.1016/j.jhydrol.2024.132225
- Hydrological drought class early warning using support vector machines and rough sets R. Kolachian & B. Saghafian 10.1007/s12665-021-09536-3
- Temporal Hydrological Drought Index Forecasting for New South Wales, Australia Using Machine Learning Approaches A. Dikshit et al. 10.3390/atmos11060585
- Characteristics of climate extremes in China during the recent global warming hiatus based upon machine learning P. Qin & C. Shi 10.1002/joc.7354
- Analysis of the atmospheric circulation pattern effects over SPEI drought index in Spain A. Manzano et al. 10.1016/j.atmosres.2019.104630
- Spatial association of anomaly correlation for GCM seasonal forecasts of global precipitation T. Zhao et al. 10.1007/s00382-020-05384-2
- Intensification of drought propagation over the Yangtze River basin under climate warming F. Ma et al. 10.1002/joc.8165
Discussed (final revised paper)
Latest update: 21 Jan 2025
Short summary
Predicting meteorological droughts more than 2 months in advance became difficult due to low predictability, leading to weak skill for hydrological droughts in wet seasons. Hydrological drought forecasts showed skills up to 3–6 lead months due to the memory of initial hydrologic conditions in dry seasons. Human activities have increased hydrological predictability during wet seasons in the MHRB. This fills gaps in understanding drought and predictability predictions in endorheic and arid basins.
Predicting meteorological droughts more than 2 months in advance became difficult due to low...
