6533b7d3fe1ef96bd1261657

RESEARCH PRODUCT

A BMA Analysis to Assess the Urbanization and Climate Change Impact on Urban Watershed Runoff

Vincenza NotaroGabriele FreniLorena Liuzzo

subject

WatershedBMA analysis010504 meteorology & atmospheric sciencesMeteorologyWatershed area0208 environmental biotechnologyClimate changeurbanizationProbability density function02 engineering and technologyGeneral MedicineBayesian inference01 natural sciences020801 environmental engineeringurban drainage system design.climate changeImpervious surfaceEconometricsEnvironmental scienceSurface runoffEngineering(all)Uncertainty analysis0105 earth and related environmental sciences

description

Abstract A reliable planning of urban drainage systems aimed at the mitigation of flooding, should take into account the possible change over time of impervious cover in the urban watershed and of the climate features. The present study proposes a methodology to analyze the changing in runoff response for a urban watershed accounting several plausible future states of new urbanization and climate. To this aim, several models simulating the evolution scenario of impervious watershed area and of climate change were adopted. However, it is known that an evolution scenario represents only one of all possible occurrence and it is not necessary the true future state, therefore it is needed to find the plausible forecast of the future state by taking into account and combining several possible evolution models. According to this aim, in the present study the Bayesian Model Averaging (BMA) approach was applied to several evolution models for climate variables. The Bayesian Model Averaging is a statistic multi-model method that computes a weighted average of the series of available competing models forecast overcoming the problem of arbitrary selecting of single best model and, consequently, the relative requirements of uncertainty analysis. The weighted average is the probability density function (pdf) of the quantity to be forecasted, while the weights correspond to the comparative performance of the models over training period of observation. After the application of BMA, for a given probability, the impervious area extension and the design rainfall event were identified and used as input data for a numerical model based on the SWMM software which was adopted to simulate the behavior of the urban drainage-system adopted as case study. Particularly, the proposed procedure was applied with reference to the Sicilian climate regions (southern Italy).

https://doi.org/10.1016/j.proeng.2016.07.461