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Model-based assessment of climate change impact on Isaac River Catchment, Queensland

journal contribution
posted on 2018-06-14, 00:00 authored by Nahlah Abbas, Saleh Wasimi, N Al-Ansari
Isaac River catchment, which is located within Fitzroy basin in Central Queensland, Australia is mostly a semi-arid region, sparsely populated, but rife with economic activities such as mining, grazing, cropping and production forestry. Hydro-meteorological data over the past several decades reveal that the catchment is experiencing increasing variability in precipitation and streamflow contributing to more severe droughts and floods supposedly due to climate change. The exposure of the economic activities in the catchment to the vagaries of nature and the possible impacts of climate change on the stream flow regime are to be analyzed. For the purpose, SWAT model was adopted to capture the dynamics of the catchment. During calibration of the model 12 parameters were found to be significant which yielded a R2 value of 0.73 for calibration and 0.66 for validation. In the next stage, six GCMs from CMIP3 namely, CGCM3.1/T47, CNRM-CM3, GFDLCM2.1, IPSLCM4, MIROC3.2 (medres) and MRI CGCM2.3.2 were selected for climate change projections in the Fitzroy basin under a very high emissions scenario (A2), a medium emissions scenario (A1B) and a low emissions scenario (B1) for two future periods (2046-2064) and (2080-2100). All GCMs showed consistent increases in temperature, and as expected, highest rate for A2 and lowest rate for B1. Precipitation predictions were mixed-reductions in A2 and increases in A1B and B1, and more variations in distant future compared to near future. When the projected temperatures and precipitation were inputted into the SWAT model, and the model outputs were compared with the baseline period (1980-2010), the picture that emerged depicted worsening water resources variability.

History

Volume

8

Issue

7

Start Page

460

End Page

470

Number of Pages

11

eISSN

1947-394X

ISSN

1947-3931

Additional Rights

Published under the Creative Commons Attribution International License (CC BY 4.0)

Peer Reviewed

  • Yes

Open Access

  • Yes

External Author Affiliations

Lulea University of Technology, Lulea, Sweden

Author Research Institute

  • Centre for Intelligent Systems

Era Eligible

  • Yes

Journal

Engineering