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<rdf:RDF xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#" xmlns:dc="http://purl.org/dc/elements/1.1/"><rdf:Description rdf:about="https://repozitorij.uni-lj.si/IzpisGradiva.php?id=176041"><dc:title>Blue-green roof heat transfer modeling in drought conditions</dc:title><dc:creator>Žižak,	Tej	(Avtor)
	</dc:creator><dc:creator>Medved,	Sašo	(Avtor)
	</dc:creator><dc:creator>Arkar,	Ciril	(Avtor)
	</dc:creator><dc:subject>green roof</dc:subject><dc:subject>water storage</dc:subject><dc:subject>evapotranspiration</dc:subject><dc:subject>heat transfer</dc:subject><dc:subject>air gap</dc:subject><dc:description>This study presents a comprehensive numerical heat transfer model for a novel green roof system with water storage layer (blue-green roof). The experimental validation over a two-month period included 15 days of water stress conditions and validation of temperatures across layers, evapotranspiration (latent heat flux) and water balance based on water level measurements. A key focus is on the effect and modeling of the air gap within the water storage layer and the accurate prediction in water stress conditions. Different approaches to modeling are evaluated, and a detailed method with separate modeling of convective and radiative heat transfer within air gap is proposed, which improves the accuracy of surface temperature above air gap prediction with normalized mean error (NRMSE) of 6 %. Additionally, the role of convective heat flux in drought conditions is analysed. With incorporation of stabilization correction factor into the aerodynamic resistance model, normalized error of substrates surface temperatures was reduced to 6.1 %. To realistically simulate the water balance and distribution across layers, a water extraction coefficient was introduced, quantifying the portion of water for evapotranspiration taken directly from the water storage layer. For the studied blue-green roof with mineral, organic substrates and sedum under the site conditions of this experiment, the calibrated water extraction factor was K$_Z$ = 0.22. The proposed model provides a mean to predict the heat transfer of sustainable roof system adapted to increasingly frequent dry periods and extreme weather events.</dc:description><dc:date>2026</dc:date><dc:date>2025-11-19 10:09:38</dc:date><dc:type>Članek v reviji</dc:type><dc:identifier>176041</dc:identifier><dc:language>sl</dc:language></rdf:Description></rdf:RDF>
