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LIBRIS Formathandbok  (Information om MARC21)

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• MARC

Fältnamn	Indikatorer	Metadata
000		03516naa a22004933a 4500
001		22199986
003		SE-LIBR
005		20180104201402.0
007		cr||||||||||||
008		180104s2016 sw |||| o |||| ||eng c
024	7	a http://urn.kb.se/resolve?urn=urn:nbn:se:ltu:diva-149382 uri
024	7	a urn:nbn:se:ltu:diva-149382 urn
024	7	a 10.4236/eng.2016.870432 doi
024	8	a e5fdd4ff-9020-46de-b926-4d4cf419ae37
040		a S
041	0	a eng
042		9 EPLK
100	1	a Abbas, Nahla4 aut
245	1 0	a Model-Based Assessment of Climate Change Impact on Isaac River Catchment, Queenslandh [Elektronisk resurs]
260		c 2016
500		a Validerad; 2016; Nivå 1; 20160729 (nadhir)
500		a Published
506	0	a gratis
520		a 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 12parameters 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 temperaturesand 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.
650	7	a Engineering and Technology2 hsv
650	7	a Civil Engineering2 hsv
650	7	a Geotechnical Engineering2 hsv
650	7	a Teknik och teknologier2 hsv
650	7	a Samhällsbyggnadsteknik2 hsv
650	7	a Geoteknik2 hsv
650	7	a Soil Mechanics2 ltu
650	7	a Geoteknik2 ltu
700	1	a Wasimi, Saleh A.4 aut
700	1	a Al-Ansari, Nadhir4 aut
710	1 2	a Luleå tekniska universitetb Institutionen för samhällsbyggnad och naturresurser4 pbl
772	1 8	i channel recordw 19941651
773	0 8	i Värdpublikationt Engineeringg 8:7, 460-470x 1947-3931
856	4 0	u http://urn.kb.se/resolve?urn=urn:nbn:se:ltu:diva-14938
856	4 0	u http://dx.doi.org/10.4236/eng.2016.87043
856	4 0	u http://ltu.diva-portal.org/smash/get/diva2:987911/FULLTEXT01
841		5 APISa x ab 180104||0000|||||001||||||000000e 1
024	7	5 APISa urn:nbn:se:ltu:diva-149382 urn
852		5 APISb APIS
856	4 0	5 APISu http://urn.kb.se/resolve?urn=urn:nbn:se:ltu:diva-14938

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