Articles | Volume 24, issue 1
https://doi.org/10.5194/hess-24-227-2020
© Author(s) 2020. 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-24-227-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
16 Jan 2020
Research article |
| 16 Jan 2020
| 16 Jan 2020
A framework for deriving drought indicators from the Gravity Recovery and Climate Experiment (GRACE)
Helena Gerdener
CORRESPONDING AUTHOR
Institute of Geodesy and Geoinformation, University of Bonn, Bonn, Germany
Olga Engels
Institute of Geodesy and Geoinformation, University of Bonn, Bonn, Germany
Jürgen Kusche
Institute of Geodesy and Geoinformation, University of Bonn, Bonn, Germany
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32 citations as recorded by crossref.
- Reconstructing a new terrestrial water storage deficit index to detect and quantify drought in the Yangtze River Basin N. Chao et al. 10.1016/j.jhydrol.2023.129972
- Developing a Long Short-Term Memory (LSTM)-Based Model for Reconstructing Terrestrial Water Storage Variations from 1982 to 2016 in the Tarim River Basin, Northwest China F. Wang et al. 10.3390/rs13050889
- Characterization of hydrological droughts in Brazil using a novel multiscale index from GNSS M. Tang et al. 10.1016/j.jhydrol.2022.128934
- An enhanced water storage deficit index (EWSDI) for drought detection using GRACE gravity estimates B. Khorrami & O. Gunduz 10.1016/j.jhydrol.2021.126812
- How realistic are multi-decadal reconstructions of GRACE-like total water storage anomalies? C. Hacker & J. Kusche 10.1016/j.jhydrol.2024.132180
- Quantifying the Central European Droughts in 2018 and 2019 With GRACE Follow‐On E. Boergens et al. 10.1029/2020GL087285
- Improving the resolution of GRACE-based water storage estimates based on machine learning downscaling schemes W. Yin et al. 10.1016/j.jhydrol.2022.128447
- Interannual variations of terrestrial water storage in the East African Rift region E. Boergens et al. 10.5194/hess-28-4733-2024
- Drought susceptibility modeling with geospatial techniques and AHP model: a case of Bilate River Watershed, Central Rift Valley of Ethiopia A. Burka et al. 10.1080/10106049.2024.2395319
- Detection of extreme hydrological droughts in the poyang lake basin during 2021–2022 using GNSS-derived daily terrestrial water storage anomalies Y. Peng et al. 10.1016/j.scitotenv.2024.170875
- Quantifying the 2022 extreme drought in the Yangtze River Basin using GRACE-FO A. Duan et al. 10.1016/j.jhydrol.2024.130680
- Monitoring annual meteorological drought in arid and semi-arid watersheds by SPI12 drought index and spatial autocorrelation pattern analysis: a case study of the Khuzestan province, Southwest Iran A. Adib et al. 10.1007/s40899-024-01142-y
- Reconstructing GRACE-type time-variable gravity from the Swarm satellites H. Richter et al. 10.1038/s41598-020-80752-w
- GRACE and land surface models reveal severe drought in eastern China in 2019 X. Yan et al. 10.1016/j.jhydrol.2021.126640
- Challenges in modeling and predicting floods and droughts: A review M. Brunner et al. 10.1002/wat2.1520
- Hydrological drought characterization based on GNSS imaging of vertical crustal deformation across the contiguous United States Z. Jiang et al. 10.1016/j.scitotenv.2022.153663
- Estimation of hydrological drought recovery based on precipitation and Gravity Recovery and Climate Experiment (GRACE) water storage deficit A. Singh et al. 10.5194/hess-25-511-2021
- Review of In-Situ and Remote Sensing-Based Indices and Their Applicability for Integrated Drought Monitoring in South Africa M. Mukhawana et al. 10.3390/w15020240
- RECOG RL01: correcting GRACE total water storage estimates for global lakes/reservoirs and earthquakes S. Deggim et al. 10.5194/essd-13-2227-2021
- Water cycle science enabled by the GRACE and GRACE-FO satellite missions M. Rodell & J. Reager 10.1038/s44221-022-00005-0
- Leveraging multi-variable observations to reduce and quantify the output uncertainty of a global hydrological model: evaluation of three ensemble-based approaches for the Mississippi River basin P. Döll et al. 10.5194/hess-28-2259-2024
- Changing intensity of hydroclimatic extreme events revealed by GRACE and GRACE-FO M. Rodell & B. Li 10.1038/s44221-023-00040-5
- Quantification and Assessment of Global Terrestrial Water Storage Deficit Caused by Drought Using GRACE Satellite Data J. Lu et al. 10.1109/JSTARS.2022.3180509
- Dynamics of meteorological and hydrological drought: The impact of groundwater and El Niño events on forest fires in the Amazon N. Toledo et al. 10.1016/j.scitotenv.2024.176612
- Forecasting terrestrial water storage for drought management in Ethiopia T. Kenea et al. 10.1080/02626667.2020.1790564
- Climatic teleconnection of the future trend of meteorological, GRACE-DSI, and vegetation-conditioned-based drought analysis in the Ganga Basin M. Hasan et al. 10.2166/ws.2024.173
- Drought assessment of China in 2002–2017 based on a comprehensive drought index Y. Xu et al. 10.1016/j.agrformet.2022.108922
- An optimized hydrological drought index integrating GNSS displacement and satellite gravimetry data C. Yao et al. 10.1016/j.jhydrol.2022.128647
- Hydrometeorological Extreme Events in West Africa: Droughts P. Dibi-Anoh et al. 10.1007/s10712-022-09748-7
- Insights into hydrological drought characteristics using GNSS-inferred large-scale terrestrial water storage deficits Z. Jiang et al. 10.1016/j.epsl.2021.117294
- GRACE Combined with WSD to Assess the Change in Drought Severity in Arid Asia J. Liu et al. 10.3390/rs14143454
- The global land water storage data set release 2 (GLWS2.0) derived via assimilating GRACE and GRACE-FO data into a global hydrological model H. Gerdener et al. 10.1007/s00190-023-01763-9
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Short summary
GRACE-derived drought indicators enable us to detect hydrological droughts based on changes observed in all storages. By performing synthetic experiments, we find that droughts identified by existing and modified indicators are biased by trends and GRACE-based spatial noise. A modified version of the Zhao et al. (2017) indicator is found to be particularly robust against spatial noise and is therefore applied to real GRACE data over South Africa.
GRACE-derived drought indicators enable us to detect hydrological droughts based on changes...
