Articles | Volume 23, issue 6
Research article
19 Jun 2019
Research article |  | 19 Jun 2019

Sensitivity of hydrological models to temporal and spatial resolutions of rainfall data

Yingchun Huang, András Bárdossy, and Ke Zhang

Related authors

Simultaneous calibration of hydrological models in geographical space
András Bárdossy, Yingchun Huang, and Thorsten Wagener
Hydrol. Earth Syst. Sci., 20, 2913–2928,,, 2016
Short summary

Related subject area

Subject: Catchment hydrology | Techniques and Approaches: Modelling approaches
Technical note: Testing the connection between hillslope-scale runoff fluctuations and streamflow hydrographs at the outlet of large river basins
Ricardo Mantilla, Morgan Fonley, and Nicolás Velásquez
Hydrol. Earth Syst. Sci., 28, 1373–1382,,, 2024
Short summary
Empirical stream thermal sensitivity cluster on the landscape according to geology and climate
Lillian M. McGill, E. Ashley Steel, and Aimee H. Fullerton
Hydrol. Earth Syst. Sci., 28, 1351–1371,,, 2024
Short summary
Deep learning for monthly rainfall–runoff modelling: a large-sample comparison with conceptual models across Australia
Stephanie R. Clark, Julien Lerat, Jean-Michel Perraud, and Peter Fitch
Hydrol. Earth Syst. Sci., 28, 1191–1213,,, 2024
Short summary
On optimization of calibrations of a distributed hydrological model with spatially distributed information on snow
Dipti Tiwari, Mélanie Trudel, and Robert Leconte
Hydrol. Earth Syst. Sci., 28, 1127–1146,,, 2024
Short summary
Toward interpretable LSTM-based modeling of hydrological systems
Luis Andres De la Fuente, Mohammad Reza Ehsani, Hoshin Vijai Gupta, and Laura Elizabeth Condon
Hydrol. Earth Syst. Sci., 28, 945–971,,, 2024
Short summary

Cited articles

Ahmed, S. and De Marsily, G.: Comparison of geostatistical methods for estimating transmissivity using data on transmissivity and specific capacity, Water Resour. Res., 23, 1717–1737,, 1987. a
Bárdossy, A. and Das, T.: Influence of rainfall observation network on model calibration and application., Hydrol. Earth Syst. Sci., 12, 77–89,, 2008. a
Bárdossy, A. and Pegram, G.: Combination of radar and daily precipitation data to estimate meaningful sub-daily point precipitation extremes, J. Hydrol., 544, 397–406,, 2016a. a
Bárdossy, A. and Pegram, G.: Space-time conditional disaggregation of precipitation at high resolution via simulation, Water Resour. Res., 52, 920-937,, 2016b. a, b, c
Bárdossy, A. and Singh, S. K.: Robust estimation of hydrological model parameters., Hydrol. Earth Syst. Sci., 12, 1273–1283,, 2008. a
Short summary
This study investigates whether higher temporal and spatial resolution of rainfall can lead to improved model performance. Four rainfall datasets were used to drive lumped and distributed HBV models to simulate daily discharges. Results show that a higher temporal resolution of rainfall improves the model performance if the station density is high. A combination of observed high temporal resolution observations with disaggregated daily rainfall leads to further improvement of the tested models.