Abstract
Hydrological impacts of climate change result from the combined effect of climate variables simulated by climate models. However, these variables are generally evaluated independently. We propose to evaluate climate model simulations in a process-oriented framework using hydrological modeling. We evaluate eleven GCM-RCMs climate variables (precipitation and temperature) issued from EURO-CORDEX, over a 30-year reference period (1970–2000) for Oued El Abid catchment situated in northern Tunisia, by using HBV-light rainfall-runoff model. Six discharge metrics were used to explore the representation of the hydrological processes. Due to the climate system complexity, there is no model that can reproduce this system perfectly. This implies applying bias correction before using their outputs in impact studies. In this study, we use Quantile Delta mapping to bias correct climate variables. Our results confirm the importance of bias correction. Additionally, we present a ranking of climate models according to their hydrological performance. GCM-RCM IPSL-IPSL-CM5A-MR-SMHI-RCA4 is the best in the reference period (metrics are met), whereas GCM-RCM IC-EC-EA- KNMI-RACMO22E is the worst for the study catchment area.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Bastola, S., Murphy, C., Sweeney, J.: The role of hydrological modelling uncertainties in climate change impact assessments of Irish river catchments. Adv. Water Res. 34, 562–576 (2011). https://doi.org/10.1016/j.advwatres.2011.01.008
Cannon, A., Sobie, S., Murdock, T.: Bias correction of GCM precipitation by quantile mapping: How well do methods preserve changes in quantiles and extremes? J. Climate. 28(17), 6938–6959 (2015). https://doi.org/10.1175/JCLI-D-14-00754.1
Dakhlaoui, H., Ruelland, D., Trambaly, Y., Bargaoui, Z.: Evaluating robustness of conceptual rainfall-runoff models under climate variability in Northern Tunisia. J. Hydrol. 550(2017), 201–217 (2017). https://doi.org/10.1016/j.jhydrol.2017.04.032
Dakhlaoui, H., Ruelland, D., Tramblay, Y.: A bootstrap-based differential split-sample test to assess the transferability of conceptual rainfall-runoff models under past and future climate variability. J. Hydrol. 575, 470–486 (2019). https://doi.org/10.1016/j.jhydrol.2019.05.056
Hakala, K., Addor, N., Seibert, J.: Hydrological modeling to evaluate climate model simulations and their bias correction. J. Hydrometeor. 19(8), 1321–1337 (2018). https://doi.org/10.1175/JHM-D-17-0189.1
Maraun, D., Wetterhall, F., Chandler, R.E., et al.: Precipitation downscaling under climate change: Recent developments to bridge the gap between dynamical models and the end userRev. Geophys. 48, 1–38 (2010). https://doi.org/10.1029/2009RG000314
Rummukainen, M.: Climate change impacts on runoff in Sweden assessments by global climate models, dynamical downscaling and hydrological modelling. Clim. Res. 16, 101–112 (2001). https://doi.org/10.3354/cr016101
Seibert, Vis, M.J.P.: Teaching hydrological modeling with a user-friendly catchment-runoff-model software package. Hydrol. Earth Syst. Sci. 16, 3315–3325 (2012). https://doi.org/10.5194/hess-16-3315-2012
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2022 The Author(s), under exclusive license to Springer Nature Switzerland AG
About this paper
Cite this paper
Djebbi, K., Dakhlaoui, H. (2022). Use of Hydrological Modeling as a Tool for Climate Model Evaluation at Oued el Abid Catchment [Tunisia]. In: Chenchouni, H., et al. New Prospects in Environmental Geosciences and Hydrogeosciences. CAJG 2019. Advances in Science, Technology & Innovation. Springer, Cham. https://doi.org/10.1007/978-3-030-72543-3_104
Download citation
DOI: https://doi.org/10.1007/978-3-030-72543-3_104
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-72542-6
Online ISBN: 978-3-030-72543-3
eBook Packages: Earth and Environmental ScienceEarth and Environmental Science (R0)