Articles | Volume 25, issue 1
https://doi.org/10.5194/hess-25-147-2021
https://doi.org/10.5194/hess-25-147-2021
Research article
 | 
07 Jan 2021
Research article |  | 07 Jan 2021

The role and value of distributed precipitation data in hydrological models

Ralf Loritz, Markus Hrachowitz, Malte Neuper, and Erwin Zehe

Related authors

Unveiling the Limits of Deep Learning Models in Hydrological Extrapolation Tasks
Sanika Baste, Daniel Klotz, Eduardo Acuña Espinoza, Andras Bardossy, and Ralf Loritz
EGUsphere, https://doi.org/10.5194/egusphere-2025-425,https://doi.org/10.5194/egusphere-2025-425, 2025
This preprint is open for discussion and under review for Hydrology and Earth System Sciences (HESS).
Short summary
Can discharge be used to inversely correct precipitation?
Ashish Manoj J, Ralf Loritz, Hoshin Gupta, and Erwin Zehe
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2024-375,https://doi.org/10.5194/hess-2024-375, 2024
Preprint under review for HESS
Short summary
Technical note: An approach for handling multiple temporal frequencies with different input dimensions using a single LSTM cell
Eduardo Acuña Espinoza, Frederik Kratzert, Daniel Klotz, Martin Gauch, Manuel Álvarez Chaves, Ralf Loritz, and Uwe Ehret
EGUsphere, https://doi.org/10.5194/egusphere-2024-3355,https://doi.org/10.5194/egusphere-2024-3355, 2024
Short summary
CAMELS-DE: hydro-meteorological time series and attributes for 1582 catchments in Germany
Ralf Loritz, Alexander Dolich, Eduardo Acuña Espinoza, Pia Ebeling, Björn Guse, Jonas Götte, Sibylle K. Hassler, Corina Hauffe, Ingo Heidbüchel, Jens Kiesel, Mirko Mälicke, Hannes Müller-Thomy, Michael Stölzle, and Larisa Tarasova
Earth Syst. Sci. Data, 16, 5625–5642, https://doi.org/10.5194/essd-16-5625-2024,https://doi.org/10.5194/essd-16-5625-2024, 2024
Short summary
Analyzing the generalization capabilities of hybrid hydrological models for extrapolation to extreme events
Eduardo Acuna Espinoza, Ralf Loritz, Frederik Kratzert, Daniel Klotz, Martin Gauch, Manuel Álvarez Chaves, Nicole Bäuerle, and Uwe Ehret
EGUsphere, https://doi.org/10.5194/egusphere-2024-2147,https://doi.org/10.5194/egusphere-2024-2147, 2024
Short summary

Related subject area

Subject: Catchment hydrology | Techniques and Approaches: Modelling approaches
Exploring the potential processes controlling changes in precipitation–runoff relationships in non-stationary environments
Tian Lan, Tongfang Li, Hongbo Zhang, Jiefeng Wu, Yongqin David Chen, and Chong-Yu Xu
Hydrol. Earth Syst. Sci., 29, 903–924, https://doi.org/10.5194/hess-29-903-2025,https://doi.org/10.5194/hess-29-903-2025, 2025
Short summary
A diversity-centric strategy for the selection of spatio-temporal training data for LSTM-based streamflow forecasting
Everett Snieder and Usman T. Khan
Hydrol. Earth Syst. Sci., 29, 785–798, https://doi.org/10.5194/hess-29-785-2025,https://doi.org/10.5194/hess-29-785-2025, 2025
Short summary
Simulating the Tone River eastward diversion project in Japan carried out 4 centuries ago
Joško Trošelj and Naota Hanasaki
Hydrol. Earth Syst. Sci., 29, 753–766, https://doi.org/10.5194/hess-29-753-2025,https://doi.org/10.5194/hess-29-753-2025, 2025
Short summary
Lack of robustness of hydrological models: a large-sample diagnosis and an attempt to identify hydrological and climatic drivers
Léonard Santos, Vazken Andréassian, Torben O. Sonnenborg, Göran Lindström, Alban de Lavenne, Charles Perrin, Lila Collet, and Guillaume Thirel
Hydrol. Earth Syst. Sci., 29, 683–700, https://doi.org/10.5194/hess-29-683-2025,https://doi.org/10.5194/hess-29-683-2025, 2025
Short summary
Achieving water budget closure through physical hydrological process modelling: insights from a large-sample study
Xudong Zheng, Dengfeng Liu, Shengzhi Huang, Hao Wang, and Xianmeng Meng
Hydrol. Earth Syst. Sci., 29, 627–653, https://doi.org/10.5194/hess-29-627-2025,https://doi.org/10.5194/hess-29-627-2025, 2025
Short summary

Cited articles

Berger, M. J. and Oliger, J.: Adaptive mesh refinement for hyperbolic partial differential equations, J. Comput. Phys., 53, 484–512, https://doi.org/10.1016/0021-9991(84)90073-1, 1984. 
Berkowitz, B. and Zehe, E.: Surface water and groundwater: Unifying conceptualization and quantification of the two “water worlds”, Hydrol. Earth Syst. Sci., 24, 1831–1858, https://doi.org/10.5194/hess-24-1831-2020, 2020. 
Beven, K.: Changing ideas in hydrology – The case of physically-based models, J. Hydrol., 105, 157–172, https://doi.org/10.1016/0022-1694(89)90101-7, 1989. 
Beven, K.: Prophecy, reality and uncertainty in distributed hydrological modelling, Adv. Water Resour., 16, 41–51, https://doi.org/10.1016/0309-1708(93)90028-E, 1993. 
Beven, K.: Dalton Lecture: How Far Can We Go In Distributed Hydrological Modelling?, Lancaster University, Long Beach, California, 1–12, available at: http://eprints.lancs.ac.uk/4420/ (last access: 15 June 2020), 2001. 
Download
Short summary
This study investigates the role and value of distributed rainfall in the runoff generation of a mesoscale catchment. We compare the performance of different hydrological models at different periods and show that a distributed model driven by distributed rainfall yields improved performances only during certain periods. We then step beyond this finding and develop a spatially adaptive model that is capable of dynamically adjusting its spatial model structure in time.
Share