Articles | Volume 24, issue 11
Hydrol. Earth Syst. Sci., 24, 5379–5406, 2020
https://doi.org/10.5194/hess-24-5379-2020
Hydrol. Earth Syst. Sci., 24, 5379–5406, 2020
https://doi.org/10.5194/hess-24-5379-2020
Research article
16 Nov 2020
Research article | 16 Nov 2020

Suitability of 17 gridded rainfall and temperature datasets for large-scale hydrological modelling in West Africa

Moctar Dembélé et al.

Related authors

Contrasting changes in hydrological processes of the Volta River basin under global warming
Moctar Dembélé, Mathieu Vrac, Natalie Ceperley, Sander J. Zwart, Josh Larsen, Simon J. Dadson, Grégoire Mariéthoz, and Bettina Schaefli
Hydrol. Earth Syst. Sci., 26, 1481–1506, https://doi.org/10.5194/hess-26-1481-2022,https://doi.org/10.5194/hess-26-1481-2022, 2022
Short summary

Related subject area

Subject: Hydrometeorology | Techniques and Approaches: Remote Sensing and GIS
Improved soil evaporation remote sensing retrieval algorithms and associated uncertainty analysis on the Tibetan Plateau
Jin Feng, Ke Zhang, Huijie Zhan, and Lijun Chao
Hydrol. Earth Syst. Sci., 27, 363–383, https://doi.org/10.5194/hess-27-363-2023,https://doi.org/10.5194/hess-27-363-2023, 2023
Short summary
SMPD: a soil moisture-based precipitation downscaling method for high-resolution daily satellite precipitation estimation
Kunlong He, Wei Zhao, Luca Brocca, and Pere Quintana-Seguí
Hydrol. Earth Syst. Sci., 27, 169–190, https://doi.org/10.5194/hess-27-169-2023,https://doi.org/10.5194/hess-27-169-2023, 2023
Short summary
Evaluating the accuracy of gridded water resources reanalysis and evapotranspiration products for assessing water security in poorly gauged basins
Elias Nkiaka, Robert G. Bryant, Joshua Ntajal, and Eliézer I. Biao
Hydrol. Earth Syst. Sci., 26, 5899–5916, https://doi.org/10.5194/hess-26-5899-2022,https://doi.org/10.5194/hess-26-5899-2022, 2022
Short summary
Attribution of global evapotranspiration trends based on the Budyko framework
Shijie Li, Guojie Wang, Chenxia Zhu, Jiao Lu, Waheed Ullah, Daniel Fiifi Tawia Hagan, Giri Kattel, and Jian Peng
Hydrol. Earth Syst. Sci., 26, 3691–3707, https://doi.org/10.5194/hess-26-3691-2022,https://doi.org/10.5194/hess-26-3691-2022, 2022
Short summary
The influence of vegetation water dynamics on the ASCAT backscatter–incidence angle relationship in the Amazon
Ashwini Petchiappan, Susan C. Steele-Dunne, Mariette Vreugdenhil, Sebastian Hahn, Wolfgang Wagner, and Rafael Oliveira
Hydrol. Earth Syst. Sci., 26, 2997–3019, https://doi.org/10.5194/hess-26-2997-2022,https://doi.org/10.5194/hess-26-2997-2022, 2022
Short summary

Cited articles

Acharya, S. C., Nathan, R., Wang, Q. J., Su, C.-H., and Eizenberg, N.: An evaluation of daily precipitation from a regional atmospheric reanalysis over Australia, Hydrol. Earth Syst. Sci., 23, 3387–3403, https://doi.org/10.5194/hess-23-3387-2019, 2019. 
Addor, N., and Melsen, L.: Legacy, rather than adequacy, drives the selection of hydrological models, Water Resour. Res., 55, 378–390, https://doi.org/10.1029/2018WR022958, 2019. 
Alazzy, A. A., Lü, H., Chen, R., Ali, A. B., Zhu, Y., and Su, J.: Evaluation of satellite precipitation products and their potential influence on hydrological modeling over the Ganzi River Basin of the Tibetan Plateau, Adv. Meteorol., 2017, 3695285, https://doi.org/10.1155/2017/3695285, 2017. 
Alemohammad, S. H., McColl, K. A., Konings, A. G., Entekhabi, D., and Stoffelen, A.: Characterization of precipitation product errors across the United States using multiplicative triple collocation, Hydrol. Earth Syst. Sci., 19, 3489–3503, https://doi.org/10.5194/hess-19-3489-2015, 2015. 
Allen, R. G., Pereira, L. S., Raes, D., and Smith, M.: Crop evapotranspiration-Guidelines for computing crop water requirements-FAO Irrigation and drainage paper 56, 326, available at: http://www.fao.org/docrep/X0490E/X0490E00.htm (last access: 14 November 2020), 1998. 
Download
Short summary
This study evaluates 102 combinations of rainfall and temperature datasets from satellite and reanalysis sources as input to a fully distributed hydrological model. The model is recalibrated for each input dataset, and the outputs are evaluated with streamflow, evaporation, soil moisture and terrestrial water storage data. Results show that no single rainfall or temperature dataset consistently ranks first in reproducing the spatio-temporal variability of all hydrological processes.