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Accueil du site → Doctorat → États-Unis → 2011 → Assessing hydrologic impacts of climate change over semi-arid region using bias-adjusted dynamically downscaled meteorological forcing

University of California, Irvine (2011)

Assessing hydrologic impacts of climate change over semi-arid region using bias-adjusted dynamically downscaled meteorological forcing

Tsou Chun Jaw

Titre : Assessing hydrologic impacts of climate change over semi-arid region using bias-adjusted dynamically downscaled meteorological forcing

Auteur : Tsou Chun Jaw

Université de soutenance : University of California, Irvine

Grade : Doctor of Philosophy (Ph.D., Civil Engineering) 2011

Résumé
Twentieth century climate change induced by anthropogenic forcings has been recognized as one of the most serious issues affecting the development of mankind. Impacts of climate change on hydrologic processes are highly relevant to human activities and draw a great deal of scientific attention. In particular, semi-arid hydrology and water resources, which are encountering significant challenges in present climate, are projected to be more vulnerable to the future climate. While relevant studies emphasize large-scale impacts on hydrological processes due to climate changes, investigations of the impacts of climate changes on regional, even basin-scale hydrology are relatively limited. The main objective of this dissertation is to assess the potential hydrologic impacts of climate change over a semi-arid region by means of hydrologic modeling driven by high-resolution meteorological forcings. While GCMs are considered as powerful tools to simulate large-scale climate changes in the Earth system, climate information derived from GCMs needs to be further downscaled to meet the requirements of assessing the impact of regional climate and hydrology on global climate change. In this study, dynamical downscaling implementing a Regional Climate Model (RCM) to derive finerresolution climate data is conducted, and three GCMs (BCCR, CCSM3, and ECHAM5) are adopted as the forcing data sets of the dynamical downscaling to evaluate regional climate and its hydrologic impacts over the semi-arid Morocco under the present-day and future climate scenarios. Downscaled precipitation analyses indicate that, systematically, biases are present. Directly using biased RCM output for hydrologic assessments would lead to unrealistic results. Therefore, effective bias correction approaches for the meteorological forcings required in the hydrologic modeling are adopted. While dynamically-downscaled GCMs show varying biases, downscaled ECHAM5 runs are more realistic in reproducing the historical climate patterns. Furthermore, proposed bias corrections (QM, EDCDF, and MovingCDF) significantly reduce the biases both in the meteorological forcings and their hydrologic responses. Among the correction approaches, MovingCDF accounts for the nonstationarity within the projection period and displays the best performance in forcing correction. Hydrologic simulation runs forced by the corrected forcings are significantly improved in the historical period in comparison with the results directly forced by RCM output. For future hydrologic assessments, hydrologic simulations driven by bias-corrected climate forcings exhibit a more consistent agreement. A drier hydrologic condition in the study region is expected in the near future (2036-2065). However, the degrees of the hydrologic impact, are highly dependent on the behaviors of large-scale GCM forcings

Mots Clés : Dynamical downscaling, Hydrologic impacts, Semi-arid regions, Meteorological forcing

Présentation

Page publiée le 15 septembre 2012, mise à jour le 4 octobre 2017