Articles | Volume 27, issue 2
https://doi.org/10.5194/hess-27-501-2023
© Author(s) 2023. 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-27-501-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
26 Jan 2023
Research article |
| 26 Jan 2023
| 26 Jan 2023
The suitability of a seasonal ensemble hybrid framework including data-driven approaches for hydrological forecasting
Department of Physical Geography, Utrecht University, Princetonlaan 8a, Utrecht, the Netherlands
Marc F. P. Bierkens
Department of Physical Geography, Utrecht University, Princetonlaan 8a, Utrecht, the Netherlands
Deltares, Daltonlaan 600, 3584 BK Utrecht, the Netherlands
Vincent Beijk
Rijkswaterstaat, Water, Verkeer en Leefomgeving, Griffioenlaan 2, Utrecht, the Netherlands
Niko Wanders
Department of Physical Geography, Utrecht University, Princetonlaan 8a, Utrecht, the Netherlands
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Camelia-Eliza Telteu, Hannes Müller Schmied, Wim Thiery, Guoyong Leng, Peter Burek, Xingcai Liu, Julien Eric Stanislas Boulange, Lauren Seaby Andersen, Manolis Grillakis, Simon Newland Gosling, Yusuke Satoh, Oldrich Rakovec, Tobias Stacke, Jinfeng Chang, Niko Wanders, Harsh Lovekumar Shah, Tim Trautmann, Ganquan Mao, Naota Hanasaki, Aristeidis Koutroulis, Yadu Pokhrel, Luis Samaniego, Yoshihide Wada, Vimal Mishra, Junguo Liu, Petra Döll, Fang Zhao, Anne Gädeke, Sam S. Rabin, and Florian Herz
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We analyse water storage compartments, water flows, and human water use sectors included in 16 global water models that provide simulations for the Inter-Sectoral Impact Model Intercomparison Project phase 2b. We develop a standard writing style for the model equations. We conclude that even though hydrologic processes are often based on similar equations, in the end these equations have been adjusted, or the models have used different values for specific parameters or specific variables.
Noemi Vergopolan, Sitian Xiong, Lyndon Estes, Niko Wanders, Nathaniel W. Chaney, Eric F. Wood, Megan Konar, Kelly Caylor, Hylke E. Beck, Nicolas Gatti, Tom Evans, and Justin Sheffield
Hydrol. Earth Syst. Sci., 25, 1827–1847, https://doi.org/10.5194/hess-25-1827-2021, https://doi.org/10.5194/hess-25-1827-2021, 2021
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Drought monitoring and yield prediction often rely on coarse-scale hydroclimate data or (infrequent) vegetation indexes that do not always indicate the conditions farmers face in the field. Consequently, decision-making based on these indices can often be disconnected from the farmer reality. Our study focuses on smallholder farming systems in data-sparse developing countries, and it shows how field-scale soil moisture can leverage and improve crop yield prediction and drought impact assessment.
Edward R. Jones, Michelle T. H. van Vliet, Manzoor Qadir, and Marc F. P. Bierkens
Earth Syst. Sci. Data, 13, 237–254, https://doi.org/10.5194/essd-13-237-2021, https://doi.org/10.5194/essd-13-237-2021, 2021
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Continually improving and affordable wastewater management provides opportunities for both pollution reduction and clean water supply augmentation. This study provides a global outlook on the state of domestic and industrial wastewater production, collection, treatment and reuse. Our results can serve as a baseline in evaluating progress towards policy goals (e.g. Sustainable Development Goals) and as input data in large-scale water resource assessments (e.g. water quality modelling).
Sarah F. Kew, Sjoukje Y. Philip, Mathias Hauser, Mike Hobbins, Niko Wanders, Geert Jan van Oldenborgh, Karin van der Wiel, Ted I. E. Veldkamp, Joyce Kimutai, Chris Funk, and Friederike E. L. Otto
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Motivated by the possible influence of rising temperatures, this study synthesises results from observations and climate models to explore trends (1900–2018) in eastern African (EA) drought measures. However, no discernible trends are found in annual soil moisture or precipitation. Positive trends in potential evaporation indicate that for irrigated regions more water is now required to counteract increased evaporation. Precipitation deficit is, however, the most useful indicator of EA drought.
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Short summary
Forecasts on water availability are important for water managers. We test a hybrid framework based on machine learning models and global input data for generating seasonal forecasts. Our evaluation shows that our discharge and surface water level predictions are able to create reliable forecasts up to 2 months ahead. We show that a hybrid framework, developed for local purposes and combined and rerun with global data, can create valuable information similar to large-scale forecasting models.
Forecasts on water availability are important for water managers. We test a hybrid framework...
