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Human impact parameterizations in global hydrological models improves estimates of monthly discharges and hydrological extremes: a multi-model validation study

Veldkamp, Ted Isis Elize; Zhao, Fang; Ward, Philip J.; Moel, Hans de; Aerts, Jeroen C.J.H.; Müller Schmied, Hannes; Portmann, Felix T.; Masaki, Yoshimitsu; Pokhrel, Yadu; Liu, Xingcai; Satoh, Yusuke; Gerten, Dieter; Gosling, Simon N.; Zaherpour, Jamal; Wada, Y.

Authors

Ted Isis Elize Veldkamp

Fang Zhao

Philip J. Ward

Hans de Moel

Jeroen C.J.H. Aerts

Hannes Müller Schmied

Felix T. Portmann

Yoshimitsu Masaki

Yadu Pokhrel

Xingcai Liu

Yusuke Satoh

Dieter Gerten

Simon N. Gosling

Jamal Zaherpour lgxjz1@nottingham.ac.uk

Y. Wada



Abstract

Human activities have a profound influence on river discharge, hydrological extremes, and water-related hazards. In this study, we compare the results of five state-of-the-art global hydrological models (GHMs) with observations to examine the role of human impact parameterizations (HIP) in the simulation of the mean, high, and low flows. The analysis is performed for 471 gauging stations across the globe and for the period 1971-2010. We find that the inclusion of HIP improves the performance of GHMs, both in managed and near-natural catchments. For near-natural catchments, the improvement in performance results from improvements in incoming discharges from upstream managed catchments. This finding is robust across GHMs, although the level of improvement and reasons for improvement vary greatly by GHM. The inclusion of HIP leads to a significant decrease in the bias of long-term mean monthly discharge in 36-73% of the studied catchments, and an improvement in modelled hydrological variability in 31-74% of the studied catchments. Including HIP in the GHMs also leads to an improvement in the simulation of hydrological extremes, compared to when HIP is excluded. Whilst the inclusion of HIP leads to decreases in simulated high-flows, it can lead to either increases or decreases in low-flows. This is due to the relative importance of the timing of return flows and reservoir operations and their associated uncertainties. Even with the inclusion of HIP, we find that model performance still not optimal. This highlights the need for further research linking the human management and hydrological domains, especially in those areas with a dominant human impact. The large variation in performance between GHMs, regions, and performance indicators, calls for a careful selection of GHMs, model components, and evaluation metrics in future model applications.

Journal Article Type Article
Journal Environmental Research Letters
Electronic ISSN 1748-9326
Publisher IOP Publishing
Peer Reviewed Peer Reviewed
Volume 13
Issue 5
Article Number 055008
APA6 Citation Veldkamp, T. I. E., Zhao, F., Ward, P. J., Moel, H. D., Aerts, J. C., Müller Schmied, H., …Wada, Y. (in press). Human impact parameterizations in global hydrological models improves estimates of monthly discharges and hydrological extremes: a multi-model validation study. Environmental Research Letters, 13(5), doi:10.1088/1748-9326/aab96f
DOI https://doi.org/10.1088/1748-9326/aab96f
Publisher URL https://doi.org/10.1088/1748-9326/aab96f
Copyright Statement Copyright information regarding this work can be found at the following address: http://creativecommons.org/licenses/by/4.0

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Copyright Statement
Copyright information regarding this work can be found at the following address: http://creativecommons.org/licenses/by/4.0


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PDF

Copyright Statement
Copyright information regarding this work can be found at the following address: http://creativecommons.org/licenses/by/4.0





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