Giorgio Roth

On the description of the basin effective drainage structure

Abstract The relationships between the local properties of the morphological elements of a drainage basin and its drainage structure are analysed. Two theoretical approaches are used for which hydro-dynamics and basin morphology are respectively assumed to represent the lowest and the highest starting scale level. The results show a convergence toward the idea of slope scaling with contributing area in river networks. This concept is then used as an indicator of channel initiation and maintenance for the identification of the effective drainage structure of the basin on the basis of existing digital elevation models (DEMs). Integral properties of the single DEM pixel are finally introduced to reduce the noise owing to a possible DEM low accuracy, e.g. in the estimation of the local slope value from the elevation data set. The resulting network is characterized by a non-uniform drainage density, as expected for natural river networks.

Terrain and Multiple-Scale Interactions as Factors in Generating Extreme Precipitation Events

Abstract The Mediterranean region is often affected by flooding and landslides due to heavy precipitation events. These events have been the subject of specific interest because they represent complex interaction of synoptic-scale upper-level steering flows and local topographic barriers. In the present work, data from a dense network of surface precipitation gauges over northern Italy and a global atmospheric analysis at a coarser scale are combined to develop a multiscale diagnostic model of the phenomenon. Composite maps are formed based on departures from climatology and standard deviation of sea level pressure, 500-hPa geopotential, wind, and water vapor flux. A diagnostic model is built based on the evidence that shows the spawning of secondary mesoscale features in the steering synoptic flow. The mesoscale features draw moisture and energy from local sources and cause extreme precipitation events over adjoining areas. The primary trough system steering the flow often originates in the North Sea and...

A semi-distributed rainfall-runoff model based on a geomorphologic approach

Abstract DRiFt (Discharge River Forecast), a semi-distributed event model based on a geomorphologic approach, is presented. This model is focused on the efficient description of the drainage system in its essential parts: hillslopes and channel networks are addressed with two kinematic scales, which determined the base of the geomorphologic response of the basin. The geomorphologic module is coupled with a simple distributed representation of soil infilration properties, while the rainfall event is schematized with its variability in time and space. The runoff volume is routed with a time variant TUH (T-hour Unit Hydrograph) technique, which takes into account the runoff production variability. Parameters calibration and validation have been carried out using different intense rainfall events in different size basins. This robust and parsimonious model is able to predict consistently the main features of the hydrograph; the observed parameter invariance allows the reliable utilization for flood forecasting, especially in regions where many small non-gauged basins are present.

Supervised and semi-supervised classifiers for the detection of flood-prone areas

Supervised and semi-supervised machine-learning techniques are applied and compared for the recognition of the flood hazard. The learning goal consists in distinguishing between flood-exposed and marginal-risk areas. Kernel-based binary classifiers using six quantitative morphological features, derived from data stored in digital elevation models, are trained to model the relationship between morphology and the flood hazard. According to the experimental outcomes, such classifiers are appropriate tools when one is interested in performing an initial low-cost detection of flood-exposed areas, to be possibly refined in successive steps by more time-consuming and costly investigations by experts. The use of these automatic classification techniques is valuable, e.g., in insurance applications, where one is interested in estimating the flood hazard of areas for which limited labeled information is available. The proposed machine-learning techniques are applied to the basin of the Italian Tanaro River. The experimental results show that for this case study, semi-supervised methods outperform supervised ones when—the number of labeled examples being the same for the two cases—only a few labeled examples are used, together with a much larger number of unsupervised ones.

Synoptic Preconditions for Extreme Flooding during the Summer Asian Monsoon in the Mumbai Area

ThesummermonsoonseasonisanimportanthydrometeorologicalfeatureoftheIndiansubcontinentandit has significant socioeconomic impacts. This study is aimed at understanding the processes associated with the occurrence of catastrophic flood events. The study has two novel features that add to the existing body of knowledge about the South Asian monsoon: 1) it combines traditional hydrometeorological observations (raingaugemeasurements)withunconventionaldata(mediaandstatehistoricalrecordsofreportedflooding) to produce value-added century-long time series of potential flood events and 2) it identifies the larger regional synoptic conditions leading to days with flood potential in the time series. The promise of mining unconventional data to extend hydrometeorological records is demonstrated in this study. The synoptic evolution of flooding events in the western-central coast of India and the densely populated Mumbai area are shown to correspond to active monsoon periods with embedded low pressure centers and have far-upstream influences from the western edge of the Indian Ocean basin. The coastal processes along the Arabian Peninsula where the currents interact with the continental shelf are found to be key features of extremes during the South Asian monsoon.

The Value of the Italian Civil Protection System in Integrated Water Management For The Mediterranean Environment

In the Mediterranean environment, specific aspects related to integrated water management are emphasized: water scarcity (droughts) or water excess (floods). Water-induced disasters are increasing in number and severity and international institutional frameworks to reduce disasters are being strengthened under the United Nations oversight. Italy, as well as many other Mediterranean countries, invested a large sum of money in water-related risk mitigation. In this paper, flood mitigation actions focusing on different aspects of the problem (urban planning and warning, floods management) and on different levels (scientific, technical, political, social) are presented. Their possible transfer into a broader integrated water management (IWM) scheme is discussed. Techniques for environmental data gathering from different sources (multi-sensor retrieved data), models for hydrologic cycle simulation and systems for social awareness improvement are described. These experiences where supported by different expertises that can be highly beneficial to other aspects of IWM levels from local to regional level.