1,721,059 research outputs found
Large-scale atmospheric patterns associated with mesoscale features leading to extreme precipitation events in Northwestern Italy
No full textThe synoptic and large‐scale atmospheric conditions for heavy rainfall events in Northwestern Italy are diagnosed through the joint analysis of surface precipitation gauges and reanalysis atmospheric fields. Quantiles of local surface gauge precipitation observations are used to estimate the much larger‐scale composite maps (conditional mean fields) of vertically integrated moisture flux, low‐level winds, sea‐level pressure, and 500 hPa height across the Atlantic and European domains. Remarkably, coarse‐resolution reanalysis data show distinct synoptic conditions for heavy precipitation in localized regions that are below the resolution of the reanalysis. In this paper the key attributes of the new approach that is based on the joint analysis of gridded reanalysis and station data are presented. Applications of the methodology are used to establish supporting evidence for hydrometeorological processes that lead to extreme precipitation across Northwest Italy. The results confirm the role of large-scale flow features that interact with regional topography in producing localized extreme precipitation. Whereas previous studies were based on a few case studies (modeled or observational), in this study the approach to producing a large ensemble of cases and composite statistics are introduced
A procedure for drainage network identification from geomorphology and its application to the prediction of the hydrologic response
No full textIdentifying channel initiation points is central to geomorphology and hydrology as they relate morphology, climate, and soil properties at the boundary between different surface runoff paths. Since catchment response is strongly influenced by the dynamics of water movement on the hillslope and in the channel, rainfall‐runoff modeling is one of the fields in which improving the identification of channel initiation can lead to benefits. Among the various filtering criteria that can be found in the literature for channel recognition from digital elevation models, the one using contributing area and topographic slope shows interesting features in this context. Nevertheless, the area‐slope criterion has been poorly applied. This is mainly due to the difficulties in objectively defining appropriate threshold values. This study proposes a new procedure to assess the area‐slope threshold value. The resulting channel network is then used as input to a semi‐distributed, event‐based rainfall‐runoff model able to describe severe rainfall events in small, steep basins. This model accounts for network and hillslope contributions to the total dispersion in the routing process, a key factor in determining the main features of the hydrologic response. In a geomorphologically homogeneous region, the set of model parameters shows interesting invariance properties with respect to storm and basin characteristics
Multivariate skew-t approach to the design of accumulation risk scenarios for the flooding hazard
No full textThe multivariate version of the skew‐t distribution provides a powerful analytical description of the joint behavior of multivariate processes. It enjoys valuable properties: from the aptitude to model skewed as well as leptokurtic datasets to the availability of moments and likelihood analytical expressions. Moreover, it offers a wide range of extremal dependence strength, allowing for upper and lower tail dependence. The idea underneath this work is to employ the multivariate skew‐t distribution to provide an estimation of the joint probability of flood events in a multi‐site multi‐basin approach. This constitutes the basis for the design and evaluation of flood hazard scenarios for large areas in terms of their intensity, extension and frequency, i.e. those information required by civil protection agencies to put in action mitigation strategies and by insurance companies to price the flooding risk and to evaluate portfolios. Performances of the skew‐t distribution and the corresponding t copula function, introduced to represent the state of the art for multivariate simulations, are discussed with reference to the Tanaro Basin, North‐western Italy. To enhance the characteristics of the correlation structure, three nested and non‐nested gauging stations are selected with contributing areas from 1500 to 8000 km2. A dataset of 76 trivariate flood events is extracted from a mean daily discharges database available for the time period from January 1995 to December 2003. Applications include the generation of multivariate skew‐t and t copula samples and models' comparison through the principle of minimum cross‐entropy, here revised for the application to multivariate samples. Copula and skew‐t based scenario return period estimations are provided for the November 1994 flood event, i.e. the worst on record in the 1801–2001 period. Results are encouraging: the skew‐t distribution seems able to describe the joint behavior, being close to the observations. Marginal distributions derived from the skew‐t multivariate fit are comparable to the observed ones, and the model is also able to describe the tail behavior
The importance of drainage network definition in the determination of the basin response
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