A comparison of regional flood frequency analysis approaches in a simulation framework

Regional frequency analysis (RFA) is a well-established methodology to provide an estimate of the flood frequency curve at ungauged (or scarcely gauged) sites. Different RFA approaches exist, depending on the way the information is transferred to the site of interest, but it is not clear in the literature if a specific method systematically outperforms the others. The aim of this study is to provide a framework wherein carrying out the intercomparison by building up a virtual environment based on synthetically generated data. The considered regional approaches include: (i) a unique regional curve for the whole region; (ii) a multiple-region model where homogeneous subregions are determined through cluster analysis; (iii) a Region-of-Influence model which defines a homogeneous subregion for each site; (iv) a spatially smooth estimation procedure where the parameters of the regional model vary continuously along the space. Virtual environments are generated considering different patterns of heterogeneity, including step change and smooth variations. If the region is heterogeneous, with the parent distribution changing continuously within the region, the spatially smooth regional approach outperforms the others, with overall errors 10–50% lower than the other methods. In the case of a step-change, the spatially smooth and clustering procedures perform similarly if the heterogeneity is moderate, while clustering procedures work better when the stepchange is severe. To extend our findings, an extensive sensitivity analysis has been performed to investigate the effect of sample length, number of virtual stations, return period of the predicted quantile, variability of the scale parameter of the parent distribution, number of predictor variables and different parent distribution. Overall, the spatially smooth approach appears as the most robust approach as its performances are more stable across different patterns of heterogeneity, especially when short records are considered

Framework for Enhanced Stormwater Management by Optimization of Sewer Pumping Stations

: Control and reduction of pollution from stormwater overflow is a major concern to be addressed by municipalities in order to improve the quality of the receiving water bodies and the environment in general. In the European context, these actions are driven by the Water Directive 2000/60/CE. In this regard, assessment studies of the potential load from sewer networks recognize the need for adaptation and upgrade of existing networks with waterworks and management measures. In many cases this is done by building first-flush detention tanks that, however, present consistent practical and economical burdens. In this work, simple rules to manage existing pumping stations in combined sewer systems are proposed as a way to apply management rules that mitigate pollution load. Such rules can be easily implemented in real cases with minimal cost of activation and no need of additional infrastructures. The procedure is based on the previous knowledge of the precipitation forcing and of a quantity/quality model of the sewer network. The steps adopted are (1) use of a (long-term, high-resolution) sequence of rainfall events to compute a wide spectrum of flow conditions (hydrographs and pollutographs) to the pumping stations; (2) definitions of a pumping rule to apply to the whole sequence of events to filter the incoming flow toward the wastewater treatment plant, so to compute outflows; and (3) efficiency assessment of the pumping rule by cumulative frequency analysis of water volume, pollutant mass, and pollutant mean concentration. Rule optimization can be performed by iterating points (2) and (3). An example is proposed to show how two simple parameters (a discharge threshold on the inflow and a maximum pumping time) can control the management of water and pollutant fluxes. Numerical results show that a proper optimization allows one to reduce the pumped volumes (thus reducing energy requirements and increasing the treatment plant efficiency) without significant changes to the overall pollutant mass outflow. The new pumping rules can be implemented on real stations with minimal and economically sustainable intervention

Long-term spatial and temporal rainfall trends over Italy

In this work, we investigate the spatial and temporal trend of short-duration (1 to 24 h) annual maximum rainfall depths, derived from the Improved Italian—Rainfall Extreme Dataset (I2-RED). The investigation is conducted using time series of at least 30 years of data both at the national and regional level using the record-breaking analysis, the Mann-Kendall test, the Regional Kendall test and the Sen’s slope estimator. The results confirm that rainfall extremes of different durations are not increasing uniformly over Italy and that separate tendencies emerge in different sectors, even at close distances

Spatially-smooth regionalization of flow duration curves in non-pristine basins

The flow duration curve (FDC) is a fundamental signature of the hydrological cycle to support water management strategies. Despite many studies on this topic, its estimation in ungauged basins is still a relevant issue as the FDC is controlled by different types of processes at different time-space scales, thus resulting quite sensitive to the specific case study. In this work, a regional spatially-smooth procedure to evaluate the annual FDC in ungauged basins is proposed, based on the estimation of the L-moments (mean, L-CV and L-skewness) through regression models valid for the whole case study area. In this approach, homogeneous regions are no longer required and the L-moments are allowed to continuously vary along the river network, thus providing a final FDC smoothly evolving for different locations on the river. Regressions are based on a set of topographic, climatic, land use and vegetation descriptors at the basin scale. Moreover, the model ensures that the mean annual runoff is preserved at the river confluences, i.e. the sum of annual flows of the upstream reaches is equal to the predicted annual downstream flow. The proposed model is adapted to incorporate different “sub-models” to account for local information within the regional framework, where man-induced alterations are known, as common in non-pristine catchments. In particular, we propose a module to consider the impact of existing/designed water withdrawals on the L-moments of the FDC. The procedure has been applied to a dataset of daily observation of about 120 gauged basins on the upper Po river basin in North-Western Italy