Co-evolution of hydrological components under climate change scenarios in the Mediterranean area.

The Mediterranean area is historically characterized by high human pressure on water resources. Today, while climate is projected to be modified in the future, through precipitation decrease and temperature increase, that jointly and non-linearly may affect runoff, concerns about water availability are increasing. For these reasons, quantitative assessment of future modifications in the mean annual water availability are important; likewise, the description of the future interannual variability of some hydrological components such as runoff and evapotranspiration are highly wished for water management and ecosystems dynamics analyses. This study investigates at basin spatial scale future runoff and evapotranspiration, exploring their probability density functions and their interdependence as functions of climatic changes. In order to do that, a parsimonious conceptual lumped model is here used. The model is forced by different future climate scenarios, generated through a weather generator based on a stochastic downscaling of an ensemble of General Circulation Models (GCMs) realizations. The use of the adopted hydrological model, under reliable stochastic future climate scenarios, allows to project future values of evapotranspiration and runoff in a probabilistic framework and, at the same time, the evaluation of their bivariate frequency distributions for changes through the Multivariate Kernel Density Estimation method. As a case study, a benchmark Mediterranean watershed has been proposed (Imera Meridionale, Italy). Results suggest a radical shift and shape modification of the annual runoff and evapotranspiration probability density functions. Possible implications and impacts on water resources management are here addressed and discussed.

Uncertainty evaluation of design rainfall for urban flood risk analysis.

A reliable and long dataset describing urban flood locations, volumes and depths would be an ideal prerequisite for assessing flood frequency distributions. However, data are often piecemeal and long-term hydraulic modelling is often adopted to estimate floods from historical rainfall series. Long-term modelling approaches are time- and resource-consuming, and synthetically designed rainfalls are often used to estimate flood frequencies. The present paper aims to assess the uncertainty of such an approach and for suggesting improvements in the definition of synthetic rainfall data for flooding frequency analysis. According to this aim, a multivariate statistical analysis based on a copula method was applied to rainfall features (total depth, duration and maximum intensity) to generate synthetic rainfalls that are more consistent with historical events. The procedure was applied to a real case study, and the results were compared with those obtained by simulating other typical synthetic rainfall events linked to intensity-duration-frequency (IDF) curves. The copula-based multi-variate analysis is more robust and adapts well to experimental flood locations even if it is more complex and time-consuming. This study demonstrates that statistical correlations amongst rainfall frequency, duration, volume and peak intensity can partially explain the weak reliability of flood-frequency analyses based on synthetic rainfall events.

Uncertainty in urban flood damage assessment due to urban drainage modelling and depth-damage curve estimation.

Due to the increased occurrence of flooding events in urban areas, many procedures for flood damage quantification have been defined in recent decades. The lack of large databases in most cases is overcome by combining the output of urban drainage models and damage curves linking flooding to expected damage. The application of advanced hydraulic models as diagnostic, design and decision-making support tools has become a standard practice in hydraulic research and application. Flooding damage functions are usually evaluated by a priori estimation of potential damage (based on the value of exposed goods) or by interpolating real damage data (recorded during historical flooding events). Hydraulic models have undergone continuous advancements, pushed forward by increasing computer capacity. The details of the flooding propagation process on the surface and the details of the interconnections between underground and surface drainage systems have been studied extensively in recent years, resulting in progressively more reliable models. The same level of was advancement has not been reached with regard to damage curves, for which improvements are highly connected to data availability; this remains the main bottleneck in the expected flooding damage estimation. Such functions are usually affected by significant uncertainty intrinsically related to the collected data and to the simplified structure of the adopted functional relationships. The present paper aimed to evaluate this uncertainty by comparing the intrinsic uncertainty connected to the construction of the damage-depth function to the hydraulic model uncertainty. In this way, the paper sought to evaluate the role of hydraulic model detail level in the wider context of flood damage estimation. This paper demonstrated that the use of detailed hydraulic models might not be justified because of the higher computational cost and the significant uncertainty in damage estimation curves. This uncertainty occurs mainly because a large part of the total uncertainty is dependent on depth-damage curves. Improving the estimation of these curves may provide better results in term of uncertainty reduction than the adoption of detailed hydraulic models.