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Diodato N.,Met European Research Observatory | Fiorillo F.,University of Sannio
Water and Environment Journal | Year: 2013

Climate variability induces considerable interannual fluctuations in spring discharge, especially in mountain areas, where groundwater is recharged mainly by rain and snow melt. This study presents the discharge climatological model (DISCLIM), which was developed to test a complexity-reduced approach to perform historical reconstruction in the lack of physical assumptions. The Mount Cervialto aquifer (Southern Italy) is the test site, where a powerful karst spring is monitored since the 1920s and is very sensitive to climatic conditions. DISCLIM incorporates seasonal precipitation and climate indicators only. Despite its simplicity, DISCLIM has been able to well estimate the yearly fluctuations of discharge hydrological, explaining about 90% of the interannual variability at the calibration stage, and more than 80% at validation stage. This means that DISCLIM can be easily used for estimating the discharge in historical times, when no all the hydrological balance data are available for the purpose. © 2012 CIWEM. Source


Borrelli P.,European Commission - Joint Research Center Ispra | Diodato N.,Met European Research Observatory | Panagos P.,European Commission - Joint Research Center Ispra
International Journal of Digital Earth | Year: 2016

Soil erosion by water is a serious threat for the Mediterranean region. Raindrop impacts and consequent runoff generation are the main driving forces of this geomorphic process of soil degradation. The potential ability for rainfall to cause soil loss is expressed as rainfall erosivity, a key parameter required by most soil loss prediction models. In Italy, rainfall erosivity measurements are limited to few locations, preventing researchers from effectively assessing the geography and magnitude of soil loss across the country. The objectives of this study were to investigate the spatio-temporal distribution of rainfall erosivity in Italy and to develop a national-scale grid-based map of rainfall erosivity. Thus, annual rainfall erosivity values were measured and subsequently interpolated using a geostatistical approach. Time series of pluviographic records (10-years) with high temporal resolution (mostly 30-min) for 386 meteorological stations were analysed. Regression-kriging was used to interpolate rainfall erosivity values of the meteorological stations to an Italian rainfall erosivity map (500-m). A set of 23 environmental covariates was tested, of which seven covariates were selected based on a stepwise approach (mostly significant at the 0.01 level). The interpolation method showed a good performance for both the cross-validation data set ((Formula presented.) = 0.777) and the fitting data set (R2 = 0.779). © 2016 The Author(s). Published by Taylor & Francis. Source


Grelle G.,University of Sannio | Soriano M.,University of Sannio | Revellino P.,University of Sannio | Guerriero L.,University of Sannio | And 7 more authors.
Bulletin of Engineering Geology and the Environment | Year: 2014

In landslide-prone areas the magnitude of events is related to recurring rainfall intensity. In a large sector of the Sannio Apennines (Southern Italy), predictive mapping of recurrent shallow landslides was undertaken by combining deterministic and probabilistic predictive approaches. This, with the aim to minimize the negative influence of the uniform distribution of the initial water table depth in steady condition that usually influence the theoretical instability resulting from the application of methods for large-scale estimation. The deterministic approach was performed by means of the Transient Rainfall Infiltration and Grid-based Regional Slope-stability model to obtain triggering maps in multi-temporal transient pore-water pressures. The optimized physical modeling was validated by back-analysis on large-magnitude landslide events which occurred in 2003 by means of the introduction of two cross-mapping correlation indexes. Subsequently, different predictive scenarios were proposed for different probabilistic return periods of the rainstorm events. The output data permitted the definition of a linear log regression curve to estimate the theoretical instability of the study area. This curve is defined as a function of cumulative precipitation, duration and return periods of the possible rainfall events. © 2013 Springer-Verlag Berlin Heidelberg. Source


Diodato N.,Met European Research Observatory | Diodato N.,University of Sannio | Guerriero L.,University of Sannio | Fiorillo F.,University of Sannio | And 4 more authors.
Water Resources Management | Year: 2014

Current precipitation and past climate variability induce considerable intermonthly fluctuations in spring discharges. This study presents the DISHMET model (Discharge Hydro-Climatological Model) developed to perform historical spring reconstructions in the lack of physical assumptions. We analyzed discharge data of the Caraventa spring, located on the southern side of Mount La Montagna in Southern Italy, which has been monitored since the 1996s. The La Montagna aquifer is tectonically and litologically complex and deformed bedding controls the groundwater flow. Due to this aspect a parsimonious model should be more suitable than a complex model in spring discharge estimation. Thus, the DISHMET model incorporates monthly and annual precipitation only. The model is able to estimate sufficiently well the monthly fluctuations of groundwater discharge. DISHMET can be easily used to assess historical discharge, even when hydrological data is discontinuously available. The magnitude of this discharge is linked to the frequency and type of weather patterns transiting over the central Mediterranean area during the autumn and winter seasons. It is mainly related to the local precipitation that recharges the Mt. La Montagna aquifer. An analysis of antecedent rainfall and spring discharge reveal moderate to strong relationships. © 2014 Springer Science+Business Media Dordrecht. Source


Diodato N.,Met European Research Observatory | Gericke A.,Leibniz Institute of Freshwater Ecology and Inland Fisheries | Bellocchi G.,Met European Research Observatory | Bellocchi G.,French National Institute for Agricultural Research
Catena | Year: 2012

Pulsing storms and prolonged rainfall events have been associated to floods, soil erosion and nutrient fluxes in many European river catchments. This motivated us to develop a parsimonious approach to model the climate forcing on sediment yields in a mountainous Austrian-German river catchment. The hydro-climatologic forcing was interpreted by the novel RAMSES (RAinfall Model for SEdiment yield Simulation) approach to estimate the annual sediment yields. We used annual data on suspended-solid yields at the gauge Füssen, monitored from 1924 to 2003, and monthly rainfall data. The dataset was split into the period 1924-1969 for calibration and the period 1970-2003 for validation. The quality of sediment yield data was critically examined, and a few outlying years were identified and removed from further analyses. These outliers revealed that our model underestimates exceptionally high sediment yields in years of severe flood events. For all other years, the RAMSES performed well against the calibration set, with a correlation coefficient (. r) equal to 0.83 and a Nash-Sutcliffe Index (. NSI) of 0.69. The lower performance in the validation period (. r=. 0.61, . NSI=. 0.36) has to be partly attributed to discontinuities in the monitoring strategy. For the calibration dataset, monthly precipitations proved nonetheless to be better predictors for annual sediment yields than annual values. These first results lay the foundation for reconstructing intra- to inter-decadal variability of sediment yields in river catchments where detailed precipitation records are not available as well as for the reconstruction of historical sediment yields. © 2012 Elsevier B.V. Source

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