Marco Borga

HYMEX , a 10-year Multidisciplinary Program on the mediterranean water cycle.

The Mediterranean countries are experiencing important challenges related to the water cycle, including water shortages and floods, extreme winds, and ice/snow storms, that impact critically the socioeconomic vitality in the area (causing damage to property, threatening lives, affecting the energy and transportation sectors, etc.). There are gaps in our understanding of the Mediterranean water cycle and its dynamics that include the variability of the Mediterranean Sea water budget and its feedback on the variability of the continental precipitation through air–sea interactions, the impact of precipitation variability on aquifer recharge, river discharge, and soil water content and vegetation characteristics specific to the Mediterranean basin and the mechanisms that control the location and intensity of heavy precipitating systems that often produce floods. The Hydrological Cycle in Mediterranean Experiment (HyMeX) program is a 10-yr concerted experimental effort at the international level that aims to advance the scientific knowledge of the water cycle variability in all compartments (land, sea, and atmosphere) and at various time and spatial scales. It also aims to improve the processes-based models needed for forecasting hydrometeorological extremes and the models of the regional climate system for predicting regional climate variability and evolution. Finally, it aims to assess the social and economic vulnerability to hydrometeorological natural hazards in the Mediterranean and the adaptation capacity of the territories and populations therein to provide support to policy makers to cope with water-related problems under the influence of climate change, by linking scientific outcomes with related policy requirements.

HyMeX-SOP1: The Field Campaign Dedicated to Heavy Precipitation and Flash Flooding in the Northwestern Mediterranean

The Mediterranean region is frequently affected by heavy precipitation events associated with flash floods, landslides, and mudslides that cause hundreds of millions of euros in damages per year and often, casualties. A major field campaign was devoted to heavy precipitation and flash floods from 5 September to 6 November 2012 within the framework of the 10-year international HyMeX (Hydrological cycle in the Mediterranean Experiment) dedicated to the hydrological cycle and related high-impact events. The 2- month field campaign took place over the Northwestern Mediterranean Sea and its surrounding coastal regions in France, Italy, and Spain. The observation strategy of the field experiment was devised to improve our knowledge on the following key components leading to heavy precipitation and flash flooding in the region: i) the marine atmospheric flows that transport moist and conditionally unstable air towards the coasts; ii) the Mediterranean Sea acting as a moisture and energy source; iii) the dynamics and microphysics of the convective systems producing heavy precipitation; iv) the hydrological processes during flash floods. This article provides the rationale for developing this first HyMeX field experiment and an overview of its design and execution. Highlights of some Intense Observation Periods illustrate the potential of the unique datasets collected for process understanding, model improvement and data assimilation.

Hydrometeorological Analysis of the 29 August 2003 Flash Flood in the Eastern Italian Alps

The 29 August 2003 storm on the upper Tagliamento River basin in the eastern Italian Alps is examined as a prototype for organized convective systems that dominate the upper tail of the precipitation frequency distribution and are likely responsible for the majority of flash flood peaks in this area. The availability of high-resolution rainfall estimates from radar observations and rain gauge networks, together with flood response observations derived from stream gauge data and post-event surveys, provides the opportunity to study the hydrometeorological and hydrological mechanisms associated with this extreme storm and the associated flood. The flood occurred at the end of a climatic anomaly of prolonged drought and warm conditions over Europe and the Mediterranean region. A characteristic of the event is its organization in well-defined banded structures, some of which persisted in the same locations for the duration of the event. The steadiness of these rainbands led to highly variable precipitation accumulations and, associated with orographic enhancement, played a central role in the space–time organization of the storm. Two dominant controls on extreme flood response are recognized and analyzed: steadiness of convective bands and dry antecedent soil moisture conditions.

Accuracy of radar rainfall estimates for streamflow simulation

The aim of this work is to analyse the impact of errors in radar rainfall estimates on rainfall-runoff modelling. This issue is addressed through application of radar rainfall estimates for continuous, lumped rainfall-runoff modelling of the Brue catchment, a mid-sized basin in South-West England, over a two and a half-year period. The study is focused on radar rainfall errors associated with range-related bias due to the vertical profile of reflectivity and with mean-field bias due to systematic errors in the radar calibration and biased reflectivity-to-rainrate relationship. Streamflow is simulated through a conceptual hydrological model based on mean areal rainfall estimates obtained by using various radar rainfall processing scenarios. These simulations are evaluated and compared with corresponding streamflow simulations from a dense raingauge network. The comparisons show that radar errors may preclude the use of unadjusted radar estimates for runoff modelling. Radar rainfall adjustment significantly improves model results with simulation efficiency increasing up to 30% after adjustment. Comparison of radar-driven simulations with observed discharge data reveals a simulation efficiency of 0.75 for the lowest radar scan (adjusted), whereas simulation efficiencies are lower for higher radar scans. The results reveal the critical importance of using radar rainfall estimates as close as possible to the ground and the considerable impact that effects of vertical variability of reflectivity have on runoff simulation.

On the interpolation of hydrologic variables: formal equivalence of multiquadratic surface fitting and kriging

Abstract The paper focuses on the ties of kriging with a deterministic interpolation procedure, known as multiquadratic surface fitting. The two methods are compared, first from a theoretical point of view, then using a practical example. It is shown that kriging equations with a linear variogram model are identical in form to equations of multiquadratic surface fitting with cone surfaces. The issue of the accuracy of both estimators is discussed through a case study where hourly rainfall maps of real storm events collected by radar provided the reference rainfall. Random point sampling of the accumulation pattern simulated gauge returns. Eight sampling densities were used and for each density rainfall spatial distributions were estimated for a large number of realisations. It is shown that kriging performs better at lower gauge density, while at higher gauge density the accuracy of both estimators is similar.

On the use of real‐time radar rainfall estimates for flood prediction in mountainous basins

This paper investigates the effect of systematic mean-field and range-dependent radar rainfall errors on the accuracy of runoff simulation in mountainous basins. Statistical analysis of radar rainfall and runoff simulation error is performed on six flood events for two medium size watersheds in northern Italy, located at 38 and 60 km basin-to-radar distances, respectively. We show significant range-related rainfall biases, which are due to the high elevation radar scans used to minimize the interception of the radar beam with the topography. These biases are corrected by converting radar reflectivity measurements at a given altitude into their equivalent surface values, using real-time identification of the mean vertical reflectivity profile. The mean-field bias is adjusted using a multiplicative factor determined based on real-time radar-rain gauge comparisons. The impact of the above radar rainfall biases, and the improvements obtained from the proposed corrections, on areal-rainfall estimation and runoff simulation are evaluated. It is shown that radar rainfall biases magnify through the rainfall-runoff transformation and preclude the accurate simulation of runoff, particularly for the distant basin. The combined correction procedure results in significant reduction of the hydrologic prediction error, especially at the distant basin.

The missing link between flood risk awareness and preparedness: findings from case studies in an Alpine Region

The low risk awareness of the residents living in flood-prone areas is usually considered among the main causes of their low preparedness, which in turns generates inadequate response to natural disasters. In this paper, we challenge this assumption by reporting on the results of a sociological research in four communities exposed to flood risk in the Eastern Italian Alps. The research design included semi-structured interviews and focus groups with key local stakeholders and a standardized questionnaire submitted to 400 residents. Results revealed that residents felt both slightly worried about flood risk and slightly prepared to face an event. Considerable differences were found between the evaluations of individual subjects as opposed to overall communities. There was also a clear discrepancy between the actual adoption of household preparatory measures and the willingness to take self-protection actions. Overall, the risk awareness was significantly higher among those residents who had been personally affected by a flood in the past, were living in isolated (vs. urban) communities, in the most risky areas or had a lower level of trust in local authorities. The improvement of residents’ knowledge about their environment and the residual risk seemed to be crucial to increase risk awareness, and the same was true for the strengthening of local support networks to foster preparedness. The link between risk awareness and preparedness was not at all straightforward. Results revealed instead the complexity of residents’ perspectives, attitudes, behaviours and decisions about risk-related issues.

USE OF DIGITAL ELEVATION MODEL DATA FOR THE DERIVATION OF THE GEOMORPHOLOGICAL INSTANTANEOUS UNIT HYDROGRAPH

The use of digital elevation models (DEMs) allows the automatic derivation of channel networks and the quantitative description of the geomorphic characteristics of basins. A common method of channel network extraction from DEM data is based on the specification of a threshold area (At ) that is the minimum support area required to drain to a point for a channel to form. Usually, an arbitrary constant threshold area value is chosen for channel network extraction. In this study the effects of threshold area selection, both on the morphometric and scaling properties (such as drainage density, total channel length, Horton laws and fractal dimension) of a channel network and the associated hydrological response function are analysed. The response is obtained following the geomorphological instantaneous unit hydrograph theory. Two different probabilistic models are used. They both relate the characteristic response function of the basin to its DEM data derived networks: one is derived assuming a Strahler stream ordering system and the other is obtained by averaging a flow equation with respect to the network structure (described by the width function). Applications are shown for three mountainous basins in the Italian Alps. A sensitivity analysis is performed to study the influence of the variability of morphometric properties, with respect to At, on the hydrological response obtained. It is shown that the model based on the width function is able to reduce the effects of this variability on the simulated response.

Error Analysis of Satellite Precipitation Products in Mountainous Basins

Accuratequantitative precipitationestimationover mountainous basins is of great importancebecause of their susceptibility to hazards such as flash floods, shallow landslides, and debris flows, triggered by heavy precipitation events (HPEs). In situ observations over mountainous areas are limited, but currently available satellite precipitation products can potentially provide the precipitation estimation needed for hydrological applications. In this study, four widely used satellite-based precipitation products [Tropical Rainfall Measuring Mission (TRMM) Multisatellite Precipitation Analysis (TMPA) 3B42, version 7 (3B42V7), and in near‐real time (3B42-RT); Climate Prediction Center (CPC) morphing technique (CMORPH); and PrecipitationEstimationfromRemotelySensedImagery UsingArtificialNeural Networks(PERSIANN)] are evaluated with respect to their performance in capturing the properties of HPEs over different basin scales. Evaluation is carried out over the upper Adige River basin (eastern Italian Alps) for an 8-yr period (2003‐10). Basin-averaged rainfall derived from a dense rain gauge network in the region is used as a reference. Satellite precipitation error analysis is performed for warm (May‐August) and cold (September‐December) season months as well as for different quantile ranges of basin-averaged precipitation accumulations. Three error metrics and a score system are introduced to quantify the performances of the various satellite products. Overall, no single precipitation product can be considered ideal for detecting and quantifying HPE. Results show better consistency between gauges and the two 3B42 products, particularly during warm season months that are associated with high-intensity convective events. All satellite products are shown to have a magnitude-dependent error ranging from overestimation at low precipitation regimes to underestimation at high precipitation accumulations; this effect is more pronounced in the CMORPH and PERSIANN products.

Improving Radar-Based Estimation of Rainfall over Complex Terrain

Abstract This paper investigates a multicomponent radar-based rainfall estimation algorithm that includes optimum parameter estimation and error correction schemes associated with radar operation over mountainous terrain. Algorithm preprocessing steps include correction for terrain blocking, adjustment for rain attenuation, and interpolation of reflectivity data from polar radar coordinates to a three-level (1, 2, and 3 km) vertically integrated Cartesian grid. The error correction schemes investigated herein include a simple but efficient approach to correct for the vertical variation of reflectivity and a stochastic filtering approach for mean-field radar-rainfall bias adjustment. The primary algorithm parameters are estimated through a global optimization scheme. Eight major flood-inducing storm events observed coincidentally by a C-band weather radar and 39 rain gauge stations over an alpine region of northeast Italy are used. We describe sensitivity analysis of the parameter values obtained from glob...