1,721,016 research outputs found
Regional assessment of daily reference evapotranspiration: Can ground observations be replaced by blending ERA5-Land meteorological reanalysis and CM-SAF satellite-based radiation data?
Full text linkThis study evaluates the accuracy of daily reference evapotranspiration (ETo), computed according to the FAO Penman-Monteith equation by using a set of input weather variables obtained by blending ERA5-Land (ERA5L) reanalysis data with surface incoming solar radiation (Rs) provided by the instruments on board the Meteosat geostationary satellites, operationally delivered by the Satellite Applications Facility on Climate Monitoring (CM-SAF). Performance assessment was carried out in Sicily (southern Italy) by using data from 38 automatic ground weather stations (AWSs) for years 2003–2020. ERA5L and CM-SAF data were first downscaled and bias-corrected with a calibration dataset; ERA5L air temperature data were also downscaled by lapse-rate correction. ETo estimates obtained with the blended ERA5L and CM-SAF validation dataset (ERA5L+CM-SAF) were compared with two other ETo estimates respectively obtained by using ERA5L and interpolated ground weather data (IGD). Performance indicators of the IGD dataset were evaluated by recursively applying universal kriging or ordinary kriging to the observed weather data, according to a cross-validation procedure. Rs provided by CM-SAF outperformed Rs obtained by ground interpolation, thus confirming the convenience of using bias-corrected CM-SAF data even when ground observations are available in the study area. ETo estimates with ERA5L+CM-SAF showed a normalized RMSE of 12%, outperforming ERA5L ETo estimates while performing comparably to ETo estimates obtained with the IGD dataset. The results suggested that the proposed blended dataset is a good proxy for interpolated ground weather observations in the assessment of ETo at regional scale when weather measurements cannot be easily gathered or in data-sparse regions
Rainfall Extraordinary Extreme Events (EEEs) Frequency and Magnitude Assessment: The EEE Occurred on 14th–15th October 2015 in Benevento Area (Southern Italy)
No full textThe identification of suitable statistical models of rainfall maxima at regional scale is a key element for the definition of reliable flood and landslide risk mitigation plans and for the design and security evaluation of high hazard strategic engineering structures. The ability to develop such models is highly dependent on a rain gauge monitoring network able to observe the extreme events that occurred in a region for several decades. In Italy, the density of the monitoring network and the time series lengths are often inadequate to capture some of the rainfall extreme events (referred to as extraordinary extreme events - EEEs), characterized by very low frequencies and spatial extent scales much smaller than those of rainfall ordinary maxima. In recent years, new operational statistical approaches were proposed to properly retrieve the EEEs frequency from the available database. However, the meteorological patterns of the EEEs are still poorly known, due to the limited number of documented cases studies available. The post-event rainfall analysis of observed EEEs and the evaluation of the efficiency of the monitoring network in detecting their magnitude and spatial properties may certainly help to improve the interpretation of the phenomena and their probabilistic modeling. In this study, new insights about the characteristics of EEEs are retrieved by analyzing data collected by different automatic rain gauge networks operating in Campania region (Southern Italy) from year 2001 to 2020. In this time frame, the extreme rainfall event occurred on 14th–15th October 2015 in Benevento area is the only daily EEE observed. The analyses show the capability of different monitoring networks to observe the phenomenon and the impact of different statistical regional models of rainfall maxima in assessing its frequency
Primary succession on slopes exposed to intense erosion: the case of Vesuvius Grand Cone
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Metrology for Agriculture and Forestry 2019
No full textThis Special Issue is focused on recent advances in integrated monitoring and modelling technologies for agriculture and forestry. The selected contributions cover a wide range of topics, including wireless field sensing systems, satellite and UAV remote sensing, ICT and IoT applications for smart farming
Assessing crop evapotranspiration by combining ERA5-Land meteorological reanalysis data and visible and near-infrared satellite imagery
No full textMeasuring irrigation water volumes at national and regional scales is one of the priorities that the Italian legislation has identified among the requirements to support environmental policies and land monitoring. Crop evapotranspiration estimates under standard conditions represent a key component for the indirect evaluation of irrigation water volumes at regional scale. In this study, we present a way to assess crop evapotranspiration by combining visible and near-infrared (VIS-NIR) satellite crop imagery and meteorological reanalysis data, in the hypothesis that reanalysis products represent a valid proxy of past weather data when ground-based meteorological observations are missing. The study was conducted in Campania region (Southern Italy) where VIS-NIR high-resolution multispectral satellite crop images have been validated with ground LAI measurements performed in two maize fields during the irrigation seasons of years 2014 and 2015. For the same seasons, full sets of weather data were recorded by 18 automatic weather stations distributed across the region. The results show that the use of reanalysis data as proxy of past weather data for crop evapotranspiration estimates introduces acceptable errors (with overall RMSE of about 0.65 mm day-1) in the assessment of the crop evapotranspiration and clearly support the idea that for regions with limited past weather data archives or served by sparse and irregular monitoring networks, reanalysis data can be successfully exploited as a source of gridded weather data in similar agricultural and hydrological applications
Rinaturazione del corso vallivo del fiume Alento: un programma di difesa idraulica compatibile con le esigenze di tutela ambientale
No full textRuolo della variabilità spaziale della precipitazione e morfologia del bacino nella risposta idrologica di piena
No full textComparing GEFS, ECMWF, and postprocessing methods for ensemble precipitation forecasts over Brazil
No full textRegional Assessment of Sub-Hourly Annual Rainfall Maxima
No full textThe assessment of rainfall extremes at sub-hourly scales is generally hindered by a lack of rainfall data at small timescale resolutions. This study proposes a methodology for assessing mean annual maximum rainfall at the sub-hourly scale by blending historical time series of annual maxima recorded by mechanical stations (operating at hourly scales) up to the end of the past century with newer time series of annual maxima at higher time resolutions recorded by automatic stations installed over the past twenty years. A linear correlation was found at the regional scale between the shape parameter controlling the dependency of rainfall maxima with a duration longer than one hour and the shape parameter of the dependency of rainfall maxima with the durations shorter than one hour. Thanks to this correlation, data recorded at the mechanical stations could be exploited to assess sub-hourly mean annual maxima. The proposed hybrid procedure was verified and was found to provide estimates with an accuracy close to those obtained with the high-resolution data, i.e., our best estimates. Moreover, the proposed procedure outperforms what could be achieved by spatially interpolating the best estimates at those locations where only hourly data are available
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