We introduce a new second-order central-upwind scheme for shallow water equations on the unstructured quadrilateral grids. We propose a new technique for bottom topography approximation over quadrilateral cells as well as an efficient water surface correction procedure which guarantee the positivity of the computed fluid depth. We also design a new quadrature for the discretization of the source term, using which the new scheme exactly preserves "lake at rest" steady states. We demonstrate these features of the new scheme as well as its high resolution and robustness and its potential advantages over the triangular central-upwind scheme in a number of numerical examples.

Climate change is expected to impact both the operational and structural performance of infrastructures such as roads, bridges, and buildings. However, most past life cycle assessment (LCA) studies do not consider how the operational/structural performance of infrastructure will be affected by a changing climate. The goal of this research was to develop a framework for integrating climate change impacts into LCA of infrastructure systems. To illustrate this framework, a flexible pavement case study was considered where life-cycle environmental impacts were compared across a climate change scenario and several time horizons. The Mechanistic-Empirical Pavement Design Guide (MEPDG) was utilized to capture the structural performance of each pavement performance scenario and performance distresses were used as inputs into a pavement LCA model that considered construction and maintenance/rehabilitation materials and activities, change in relative surface albedo, and impacts due to traffic. The results from the case study suggest that climate change will likely call for adaptive design requirements in the latter half of this century but in the near-to-mid term, the international roughness index (IRI) and total rutting degradation profile was very close to the historical climate run. While the inclusion of mechanistic performance models with climate change data as input introduces new uncertainties to infrastructure-based LCA, sensitivity analyses runs were performed to better understand a comprehensive range of result outcomes. Through further infrastructure cases the framework could be streamlined to better suit specific infrastructures where only the infrastructure components with the greatest sensitivity to climate change are explicitly modeled using mechanistic-empirical modeling routines.

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