1.
2.
Bertini, Claudia, et al.
(författare)
An entropy-based approach for the optimization of rain gauge network using satellite and ground-based data
2021
Ingår i: Hydrology Research. - : IWA Publishing. - 1998-9563 .- 2224-7955 .- 0029-1277. ; 52:3, s. 620-635
Tidskriftsartikel (refereegranskat) abstract
Accurate and precise rainfall records are crucial for hydrological applications and water resources management. The accuracy and continuity of ground-based time series rely on the density and distribution of rain gauges over territories. In the context of a decline of rain gauge distribution, how to optimize and design optimal networks is still an unsolved issue. In this work, we present a method to optimize a ground-based rainfall network using satellite-based observations, maximizing the information content of the network. We combine Climate Prediction Center MORPhing technique (CMORPH) observations at ungauged locations with an existing rain gauge network in the Rio das Velhas catchment, in Brazil. We use a greedy ranking algorithm to rank the potential locations to place new sensors, based on their contribution to the joint entropy of the network. Results show that the most informative locations in the catchment correspond to those areas with the highest rainfall variability and that satellite observations can be successfully employed to optimize rainfall monitoring networks.
3.
Bertini, Claudia, et al.
(författare)
On the Use of Satellite Rainfall Data to Design a Dam in an Ungauged Site
2020
Ingår i: Water. - : MDPI AG. - 2073-4441. ; 12:11
Tidskriftsartikel (refereegranskat) abstract
The estimation of the design peak discharge is crucial for the hydrological design of hydraulic structures. A commonly used approach is to estimate the design storm through the intensity-duration-area-frequency (IDAF) curves and then use it to generate the design discharge through a hydrological model. In ungauged areas, IDAF curves and design discharges are derived throughout regionalization studies, if any exist for the area of interest, or from using the hydrological information of the closest and most similar gauged place. However, many regions around the globe remain ungauged or are very poorly gauged. In this regard, a unique opportunity is provided by satellite precipitation products developed and improved in the last decades. In this paper, we show weaknesses and potentials of satellite data and, for the first time, we evaluate their applicability for design purposes. We employ CMORPH-Climate Prediction Center MORPHing technique satellite precipitation estimates to build IDAF curves and derive the design peak discharges for the Pietrarossa dam catchment in southern Italy. Results are compared with the corresponding one provided by a regionalization study, i.e., VAPI-VAlutazione delle Piene in Italia project, usually used in Italy in ungauged areas. Results show that CMORPH performed well for the estimation of low duration and small return periods storm events, while for high return period storms, further research is still needed.
4.
Bertini, Claudia, et al.
(författare)
Optima Rain Gauge Network Design Based On Multi-Objective Optimization Approach
2020
Ingår i: International conference on numerical analysis and applied mathematics ICNAAM 2019. - : AIP Publishing. - 9780735440258
Konferensbidrag (refereegranskat) abstract
Precipitation is a main input to many hydrological applications, such as water management, flood forecasting and hydrological modelling. The goodness of the rainfall field estimation can thus affect their performances. Despite radar-based and satellite-based measurements have nowadays become very common and accurate, rain gauges monitoring stations are still needed. The gauge density and its spatial distribution are two of the key factors influencing the accuracy in precipitation estimation. Even if in the last decades many studies proposed several methodologies for the design of optimal monitoring networks, only few studies use hydrological model performance as a design criterion. The purpose of this study is to define the optimal rain gauge network for the Mignone River catchment (Italy). The optimal network is defined through a multi-objective optimization approach, where the interpolation error of precipitation is minimised and the performance of a hydrological model based on the Width Function Instantaneous Unit Hydrograph theory is maximised. The optimization is run both without and with constraints, which are based on rainfall patterns. A score to choose the best set of points in the Pareto front is presented. The results suggest that there are preferential areas where sensors locations achieve optimal interpolation error and model performance.
5.
Mineo, Claudio, et al.
(författare)
Assessment of Rainfall Kinetic-Energy-Intensity Relationships
2019
Ingår i: Water. - : MDPI. - 2073-4441. ; 11:10
Tidskriftsartikel (refereegranskat) abstract
Raindrop-impact-induced erosion starts when detachment of soil particles from the surface results from an expenditure of raindrop energy. Hence, rain kinetic energy is a widely used indicator of the potential ability of rain to detach soil. Although it is widely recognized that knowledge of rain kinetic energy plays a fundamental role in soil erosion studies, its direct evaluation is not straightforward. Commonly, this issue is overcome through indirect estimation using another widely measured hydrological variable, namely, rainfall intensity. However, it has been challenging to establish the best expression to relate kinetic energy to rainfall intensity. In this study, first, kinetic energy values were determined from measurements of an optical disdrometer. Measured kinetic energy values were then used to assess the applicability of the rainfall intensity relationship proposed for central Italy and those used in the major equations employed to estimate the mean annual soil loss, that is, the Universal Soil Loss Equation (USLE) and its two revised versions (RUSLE and RUSLE2). Then, a new theoretical relationship was developed and its performance was compared with equations found in the literature.
6.
Mineo, Claudio, et al.
(författare)
The areal reduction factor : A new analytical expression for the Lazio Region in central Italy
2018
Ingår i: Journal of Hydrology. - Amsterdam : Elsevier. - 0022-1694 .- 1879-2707. ; 560, s. 471-479
Tidskriftsartikel (refereegranskat) abstract
For the study and modeling of hydrological phenomena, both in urban and rural areas, a proper estimation of the areal reduction factor (ARF) is crucial. In this paper, we estimated the ARF from observed rainfall data as the ratio between the average rainfall occurring in a specific area and the point rainfall. Then, we compared the obtained ARF values with some of the most widespread empirical approaches in literature which are used when rainfall observations are not available. Results highlight that the literature formulations can lead to a substantial over- or underestimation of the ARF estimated from observed data. These findings can have severe consequences, especially in the design of hydraulic structures where empirical formulations are extensively applied. The aim of this paper is to present a new analytical relationship with an explicit dependence on the rainfall duration and area that can better represent the ARF-area trend over the area case of study. The analytical curve presented here can find an important application to estimate the ARF values for design purposes. The test study area is the Lazio Region (central Italy).
7.
Moccia, Benedetta, et al.
(författare)
Probability distributions of daily rainfall extremes in Lazio and Sicily, Italy, and design rainfall inferences
2021
Ingår i: Journal of Hydrology. - : Elsevier. - 2214-5818. ; 33
Tidskriftsartikel (refereegranskat) abstract
Study region: We investigate samples from two Italian regions, i.e. Lazio and Sicily, located in central and south Italy, respectively, and characterized by two diverse climates. Study focus: In engineering practice, the study of maxima daily rainfall values is commonly dealt with light-tailed probability distribution functions, such as the Gumbel. The choice of a distribution rather than another may cause estimation errors of rainfall values associated to specific return periods. Recently, several studies demonstrate that heavy-tailed distributions are preferable for extreme events modelling. Here, we opt for six theoretical probability distribution functions and evaluate their performance in fitting extreme precipitation samples. We select the samples with two common methods, i.e. the Peak-Over-Threshold and the Annual Maxima. We assess the best fitting distribution to the empirical samples of extreme values through the Ratio Mean Square Error Method and the Kolmogorov-Smirnov test. New hydrological insights for the region: The assessment of the best fitting distribution to daily rainfall of the two different areas investigated here leads to interesting remarks. Despite the diversity of their climate, results suggest that heavy-tailed distributions describe more accurately empirical data rather than light-tailed ones. Therefore, extreme events may have been largely underestimated in the past in both areas. The proposed investigation can prompt the choice of the best fitting probability distribution to evaluate the design hydrological quantities supporting common engineering practice.
8.
Montesarchio, Valeria, et al.
(författare)
A comparison of two rainfall disaggregation models
2012
Ingår i: AIP Conference Proceedings. - : American Institute of Physics (AIP). - 0094-243X.
Konferensbidrag (refereegranskat) abstract
Whitin the context of flood management, and generally for performing environmental, climate, hydrological, and water resources analysis, it is useful and reliable to provide scenarios by rainfall simulation, in order to overcome data limitations in terms of time and spatial resolution. Generally, it is required that the stochastic model preservesimportant properties of the rainfall process, such as intermittency, seasonality and scaling behavior in space and time, so that there will be no substantial differences between historical rainfall data and synthetic records. In this work, two rainfall disaggregation models are evaluated in terms of their ability to reproduce rainfall hourly statistics in four sites in Central Italy. The considered models are an entropy based disaggregation model and Hyetos-R (Bartlett-Lewis rectangular pulses rainfall)
9.
Montesarchio, Valeria, et al.
(författare)
Comparison of methodologies for flood rainfall thresholds estimation
2015
Ingår i: Natural Hazards. - : Springer Netherlands. - 0921-030X .- 1573-0840. ; 75:1, s. 909-934
Tidskriftsartikel (refereegranskat) abstract
A flood warning system based on rainfall thresholds makes it possible to issue alarms via an off-line approach. This technique is useful for mitigating the effects of flooding in small-to-medium-sized basins characterized by an extremely rapid response to rainfall. Rainfall threshold values specify the amount of precipitation that occurs over a given period of time and are dependent on both the amount of soil moisture and the spatiotemporal distribution of the rainfall. The precipitation generates a critical discharge in a particular river cross section. Exceeding these values can produce a critical situation in river sites that make them susceptible to flooding. In this work, we present a comparison of methodologies for estimating rainfall thresholds. Critical precipitation amounts are evaluated using empirical data, hydrological simulations and probabilistic methods. The study focuses on three small-to-medium-sized basins located in central Italy. For each catchment, historical data are first used to theoretically evaluate the empirical rainfall thresholds. Next, we calibrate a semi-distributed hydrological model that is validated using rain gauge and weather radar data. Critical rainfall depths over 30 min and 1, 3, 6, 12 and 24 h durations are then evaluated using the hydrological simulation. In the probabilistic approach, rainfall threshold values result from a minimization of two different functions, one following the Bayesian decision theory and the other following the informative entropy concept. In order to implement both functions, it is necessary to evaluate the joint probability function. The joint probability function is built up as a bivariate distribution of rainfall depth for a given duration with the corresponding flow peak value. Finally, in order to assess the performance of each methodology, we construct contingency tables to highlight the system performance.
10.
Montesarchio, Valeria, et al.
(författare)
Rainfall threshold definition using an entropy decision approach and radar data
2012
Ingår i: Natural hazards and earth system sciences. - : Copernicus GmbH. - 1561-8633 .- 1684-9981. ; 7, s. 2061-2074
Tidskriftsartikel (refereegranskat) abstract
Flash flood events are floods characterised by a very rapid response of basins to storms, often resulting in loss of life and property damage. Due to the specific space-time scale of this type of flood, the lead time available for triggering civil protection measures is typically short. Rainfall threshold values specify the amount of precipitation for a given duration that generates a critical discharge in a given river cross section. If the threshold values are exceeded, it can produce a critical situation in river sites exposed to alluvial risk. It is therefore possible to directly compare the observed or forecasted precipitation with critical reference values, without running online real-time forecasting systems. The focus of this study is the Mignone River basin, located in Central Italy. The critical rainfall threshold values are evaluated by minimising a utility function based on the informative entropy concept and by using a simulation approach based on radar data. The study concludes with a system performance analysis, in terms of correctly issued warnings, false alarms and missed alarms.
