Human impact parameterizations in global hydrological models improve estimates of monthly discharges and hydrological extremes: a multi-model validation study
By T. Veldkamp, Fang Zhao, Philip J. Ward, H. de Moel, Jeroen C. J. H. Aerts, Hannes Müller Schmied, F. Portmann, Yoshimitsu Masaki, Y. Pokhrel, Xingcai Liu and 5 more. 2018
208 citations recorded by the source corpus.
Human activity has a profound influence on river discharges, 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 mean, high- and low-flows. The analysis is performed for 471 gauging stations across the globe for the period 1971–2010. We find that the inclusion of HIP improves the performance of the 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 the GHMs, although the level of improvement and the reasons for it vary greatly. The inclusion of HIP leads to a significant decrease in the bias of the long-term mean monthly discharge in 36%–73% of the studied catchments, and an improvement in the modeled 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 the simulated high-flows, it can lead to either increases or decreases in the low-flows. This is due to the relative importance of the timing of return flows and reservoir operations as well as their associated uncertainties. Even with the inclusion of HIP, we find that the model performance is still not optimal. This highlights the need for further research linking human management and hydrological domains, especially in those areas in which human impacts are dominant. 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.
Subfields: Global and Planetary Change, Water Science and Technology
View Paper: https://www.semanticscholar.org/paper/45c5e59f4f1b9dd6f67ccd65c30c5656618a418d
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In Global and Planetary Change
In Water Science and Technology
Citations in the corpus
- Dependence between high sea-level and high river discharge increases flood hazard in global deltas and estuaries (2018, background): “Recent advances in large-scale flood modelling enable the simulation of continuous time-series at daily to sub-daily time scales (e.g. Ward et al 2013, 2017, Muis et al 2016, Yamazaki et al 2011, Vousdoukas et al 2016, Veldkamp et al 2018).”