Articles | Volume 22, issue 9
https://doi.org/10.5194/hess-22-4685-2018
https://doi.org/10.5194/hess-22-4685-2018
Research article
 | 
07 Sep 2018
Research article |  | 07 Sep 2018

Global re-analysis datasets to improve hydrological assessment and snow water equivalent estimation in a sub-Arctic watershed

David R. Casson, Micha Werner, Albrecht Weerts, and Dimitri Solomatine

Related authors

Forecasting estuarine salt intrusion in the Rhine-Meuse delta using an LSTM model
Bas Johan Marinus Wullems, Claudia Catharina Brauer, Fedor Baart, and Albrecht Henricus Weerts
EGUsphere, https://doi.org/10.5194/egusphere-2023-217,https://doi.org/10.5194/egusphere-2023-217, 2023
Short summary
Machine Learning and Committee Models for Improving ECMWF Subseasonal to Seasonal (S2S) Precipitation Forecast
Mohamed Elneel Elshaikh Eltayeb Elbasheer, Gerald Augusto Corzo, Dimitri Solomatine, and Emmanouil Varouchakis
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2022-348,https://doi.org/10.5194/hess-2022-348, 2022
Manuscript not accepted for further review
Short summary
Large-sample assessment of varying spatial resolution on the streamflow estimates of the wflow_sbm hydrological model
Jerom P. M. Aerts, Rolf W. Hut, Nick C. van de Giesen, Niels Drost, Willem J. van Verseveld, Albrecht H. Weerts, and Pieter Hazenberg
Hydrol. Earth Syst. Sci., 26, 4407–4430, https://doi.org/10.5194/hess-26-4407-2022,https://doi.org/10.5194/hess-26-4407-2022, 2022
Short summary
Spatiotemporal changes of drought area as input for a machine-learning approach for crop yield prediction
Vitali Diaz, Ahmed A. A. Osman, Gerald A. Corzo Perez, Henny A. J. Van Lanen, Shreedhar Maskey, and Dimitri Solomatine
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2022-252,https://doi.org/10.5194/hess-2022-252, 2022
Preprint under review for HESS
Short summary
Wflow_sbm v0.6.1, a spatially distributed hydrologic model: from global data to local applications
Willem J. van Verseveld, Albrecht H. Weerts, Martijn Visser, Joost Buitink, Ruben O. Imhoff, Hélène Boisgontier, Laurène Bouaziz, Dirk Eilander, Mark Hegnauer, Corine ten Velden, and Bobby Russell
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2022-182,https://doi.org/10.5194/gmd-2022-182, 2022
Preprint under review for GMD
Short summary

Related subject area

Subject: Global hydrology | Techniques and Approaches: Modelling approaches
Poor correlation between large-scale environmental flow violations and freshwater biodiversity: implications for water resource management and the freshwater planetary boundary
Chinchu Mohan, Tom Gleeson, James S. Famiglietti, Vili Virkki, Matti Kummu, Miina Porkka, Lan Wang-Erlandsson, Xander Huggins, Dieter Gerten, and Sonja C. Jähnig
Hydrol. Earth Syst. Sci., 26, 6247–6262, https://doi.org/10.5194/hess-26-6247-2022,https://doi.org/10.5194/hess-26-6247-2022, 2022
Short summary
Accuracy of five ground heat flux empirical simulation methods in the surface-energy-balance-based remote-sensing evapotranspiration models
Zhaofei Liu
Hydrol. Earth Syst. Sci., 26, 6207–6226, https://doi.org/10.5194/hess-26-6207-2022,https://doi.org/10.5194/hess-26-6207-2022, 2022
Short summary
Coupling a global glacier model to a global hydrological model prevents underestimation of glacier runoff
Pau Wiersma, Jerom Aerts, Harry Zekollari, Markus Hrachowitz, Niels Drost, Matthias Huss, Edwin H. Sutanudjaja, and Rolf Hut
Hydrol. Earth Syst. Sci., 26, 5971–5986, https://doi.org/10.5194/hess-26-5971-2022,https://doi.org/10.5194/hess-26-5971-2022, 2022
Short summary
Revisiting large-scale interception patterns constrained by a synthesis of global experimental data
Feng Zhong, Shanhu Jiang, Albert I. J. M. van Dijk, Liliang Ren, Jaap Schellekens, and Diego G. Miralles
Hydrol. Earth Syst. Sci., 26, 5647–5667, https://doi.org/10.5194/hess-26-5647-2022,https://doi.org/10.5194/hess-26-5647-2022, 2022
Short summary
Investigating coastal backwater effects and flooding in the coastal zone using a global river transport model on an unstructured mesh
Dongyu Feng, Zeli Tan, Darren Engwirda, Chang Liao, Donghui Xu, Gautam Bisht, Tian Zhou, Hong-Yi Li, and L. Ruby Leung
Hydrol. Earth Syst. Sci., 26, 5473–5491, https://doi.org/10.5194/hess-26-5473-2022,https://doi.org/10.5194/hess-26-5473-2022, 2022
Short summary

Cited articles

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, 6541, 1998. 
AMAP: Arctic Climate Issues 2011: Changes in Arctic Snow, Water, Ice and Permafrost, SWIPA 2011, Gaustadalléen 21, 0349 Oslo, Norway, 2012. 
Beck, H., van Dijk, A., Leviizzani, V., Schellekens, J., Miralles, G., Martrens, B., de Roo, A., Pappenberger, F., Huffman, G., and Wood, E.: MSWEP: 3-hourly 0.1? fully global precipitation (1979–present) by merging gauge, satellite, and weather model data [Abstract], Geophysical Research Abstracts, 19, 2017. 
Beck, H. E., van Dijk, A. I. J. M., Levizzani, V., Schellekens, J., Miralles, D. G., Martens, B., and de Roo, A.: MSWEP: 3-hourly 0.25 global gridded precipitation (1979–2015) by merging gauge, satellite, and reanalysis data, Hydrol. Earth Syst. Sci., 21, 589–615, https://doi.org/10.5194/hess-21-589-2017, 2017. 
Bergström, S.: The HBV Model – its structure and applications, NORRKÖPING, Sweden, 1992. 
Download
Short summary
In high-latitude (> 60° N) watersheds, measuring the snowpack and predicting of snowmelt runoff are uncertain due to the lack of data and complex physical processes. This provides challenges for hydrological assessment and operational water management. Global re-analysis datasets have great potential to aid in snowpack representation and snowmelt prediction when combined with a distributed hydrological model, though they still have clear limitations in remote boreal forest and tundra environments.