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Land use change has been recognized throughout the Earth as one of the most important factors influencing the occurrence of rainfall-driven geomorphological processes. However, relating the occurrence of historical soil erosion rates is difficult because of the lack of long-term research projects in river basins. Also, complex models are not adequate to reconstruct erosion rate changes because they require significant input data not always available on long timescales. Given the problems with assessing sediment yield using complex erosion models, the objective of this study is to explore a parsimonious scale-adapted erosion model (ADT) from the original Thornes and Douglas algorithms, which aims at reconstruction of annual net erosion (ANE) upon multisecular timescales. As a test site, the Calore River basin (3015 km2 in southern Italy) provides a peculiar and unique opportunity for modelling erosion responses to climate and land cover changes, where input-data generation and interpretation results were also supported by documented hydrogeomorphological events that occurred before and after land deforestation. In this way, ANEADT-values were reconstructed for the period 1675–2004 by using precipitation indexes, complemented by recent instrumental records, and by using land cover statistics from documented agrarian sources. Pulses of natural sedimentation in the predeforestation period have been related to Vesuvius volcanic activity and changes in rainstorm frequency. After deforestation, the basin system became unstable with sudden fluctuations in the hydrogeomorphological regime contributing significantly to increased erosion and, in turn, sediment transport sequences via river drainage towards the Tyrrhenian coast. 相似文献
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Stefania Bonafoni Augusto Mazzoni Domenico Cimini Mario Montopoli Nazzareno Pierdicca Patrizia Basili Piero Ciotti Giovanni Carlesimo 《GPS Solutions》2013,17(4):475-484
We present an assessment of a GPS receiver operational network to produce accurate integrated precipitable water vapour (IPWV) during a two-week field experiment carried out in Central Italy around the city of Rome, where different instruments were operative. This experimental activity provided an excellent opportunity to compare the GPS products with independent measurements provided by ground-based and space-based sensors and to evaluate their quality in terms of absolute accuracy of IPWV, analyzing also the spatial scale of GPS estimates. For instance, the assimilation into Numerical Weather Prediction models of IPWV provided by a GPS network or its exploitation in space geodesy applications to correct tropospheric effects requires an accuracy in the order of 0.1 cm to be ascribed to IPWV observations. In this work, we assessed that the accuracy for GPS IPWV estimates is 0.07 cm. Moreover, this experiment has pointed out strengths and limitations of an operational network for the water vapor estimation, such as a proper receiver distribution to achieve the desired spatial resolution and a coverage of GPS stations in both flat and mountains regions. 相似文献
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Nazzareno Diodato Gianni Bellocchi Chiara Bertolin Dario Camuffo 《Theoretical and Applied Climatology》2013,113(1-2):187-196
This paper has exploited, for Central and Southern Italy (Mediterranean Sub-regional Area), an unprecedented historical dataset as an attempt to model seasonal (winter and summer) air temperatures in pre-instrumental time (back to 1500). Combining information derived from proxy–documentary data and large-scale simulation, a statistical downscaling approach in the form of mixed regression model was developed to adapt larger-scale estimations (regional component) to the sub-regional temperature pattern (local component). It interprets local temperature anomalies by means of monthly based Temperature Anomaly Scaled Index in the range ?5 (very cold conditions in June) to 2 (very warm conditions). The modelled response agrees well with the independent data from the validation sample (Nash–Sutcliffe efficiency coefficient, >0.60). The advantage of the approach is not merely increased accuracy in estimation. Rather, it relies on the ability to extract (and exploit) the right information to replicate coherent temperature series in historical times. 相似文献
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This study reveals the changes and evolution of rainstorm-driven intermediate floods occurring and driving multiple damaging hydrological events in the Rhone River Basin (RRB), since 1500 until 2010. A parsimonious approach was developed to simulate the major hydroclimatological flood-producing forcing, the Multiscale Rainstorm Climate Model (STORMCLIMM). We collected the frequency of intermediate floods—a type of particularly hazardous floods commonly taking place between June and beginning of November—from the RCB to be compared to STORMCLIMM estimates. The latter, smoothed by a moving window of 21 years, results in a high-pass filter in the time domain, which magnifies the signal of forcing variations causing intermediate floods. The RRB showed large temporal variations in both extreme rainstorms and associated multidecadal intermediate-floods (MUDIF) frequency at different climatic periods and land-use systems through historical times. An important peak was observed in the Maunder Minimum (1645–1715 AD). The model allowed detecting MUDIF occurred in the historical times. The situation becomes interesting with respect to recent times, because the Rhone landscape looks more vulnerable in the last decades as a consequence of land-use changes and climate shift towards more erratic and intensive storms. This evidence suggests that the interactions of land-use and climatic changes may turn into considerable vulnerability to fluvial flooding and agro-ecosystem connected to them for upcoming years. The Rhone, for example, provides basis for use of hydrological indicators (such as the one represented by STORMCLIMM) for one site or region and which, through minor modifications, can be made relevant to specific needs. 相似文献
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Nazzareno Diodato Massimo Fagnano Ines Alberico Giovanni Battista Chirico 《Natural Hazards》2011,58(1):445-457
Evaluation of soil erodibility is an important task for Mediterranean lands, in which fertility and crop yield are significantly
affected by soil erosion. The soil physicochemical parameters affecting soil erodibility are highly variable in space and,
as for many other environmental variables, sample measurements are generally not enough for assessing its spatial variability
with an acceptable level of uncertainty at the scales of practical interest. This study illustrates the procedure applied
for estimating the pattern of soil erodibility across the Sele Basin (Southern Italy), where soil properties have been measured
on a limited number of sparse samples. Sampled data were integrated with other sparse data estimated by local regression functions,
which relate soil erodibility to auxiliary variables, such as terrain attributes and land system class memberships. Sampled
and estimated data were merged in a composed data set to assess the spatial pattern of soil erodibility by ordinary kriging.
The proposed approach offers effective spatial predictions, and it is exportable to regions where financial costs for soil
sampling are not feasible. 相似文献
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The spatial variability of precipitation has often been a topic of research, since accurate modelling of precipitation is a crucial condition for obtaining reliable results in hydrology and geomorphology. In mountainous areas, the sparsity of the measurement networks makes an accurate and reliable spatialization of rainfall amounts at the local scale difficult. The purpose of this paper is to show how the use of a digital elevation model can improve interpolation processes at the subregional scale for mapping the mean annual and monthly precipitation from rainfall observations (40 years) recorded in a region of 1400 km2 in southern Italy. Besides linear regression of precipitation against elevation, two methods of interpolation are applied: inverse squared distance and ordinary cokriging. Cross‐validation indicates that the inverse distance interpolation, which ignores the information on elevation, yields the largest prediction errors. Smaller prediction errors are produced by linear regression and ordinary cokriging. However, the results seem to favour the multivariate geostatistical method including auxiliary information (related to elevation). We conclude that ordinary cokriging is a very flexible and robust interpolation method because it can take into account several properties of the landscape; it should therefore be applicable in other mountainous regions, especially where precipitation is an important geomorphological factor. Copyright © 2005 John Wiley & Sons, Ltd. 相似文献
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The advent of instrumental and digital weather observatories has not eliminated the substantial gaps within surface meteorological time series. In particular, the lack of long-term homogeneous snowfall records may be a major impediment for hydrologic studies. We tested the hypothesis that reliable estimates of snowy days per year (SDY) can be produced for peninsular Italy, based on weather and site measurements from a limited set of stations centrally located in the Central Mediterranean Area. The core weather data are those from three observatories: Naples (40° 51′ N, 14° 15′ E, 150 m a.s.l.), Rome (41° 53′ N, 12° 28′ E, 100 m a.s.l.) and Montevergine (40° 56′ N, 14° 43′ E, 1280 m a.s.l.). A linear multivariate regression model (LMRM) was developed with candidate predictors (elevation, snowfall days and winter temperatures) for SDY reconstructions in the Benevento Valley (calibration site), whose homogenised SDY time series covers the period 1869–2018 (the longest in Southern Italy, extending back to 1832 thanks to documentary proxies but with missing values from 1911 to 1949). Three validation sites across peninsular Italy were considered: Vesuvius (40° 49′ N, 14° 24′ E, 605 m a.s.l.), Perugia (43° 05′ N, 12° 30′ E, 205 m a.s.l.) and Padua (45° 23′ N, 11° 51′ E, 15 m a.s.l.). The percent relative mean absolute error (%RMAE) for Benevento Valley was 20.2%, and though higher model errors were encountered at validation sites, they were in an acceptable range (32.6, 39.3 and 39.5% at Vesuvius, Perugia and Padua, respectively). Our SDY reconstruction in the Benevento Valley parallels, the pattern of water discharge occurred in the region during the same period, whose fluctuations result in changes of the pattern of snowfall days (i.e. decreasing snowfall days in recent times was accompanied by decreasing groundwater levels). This corroborates that the approach used to reconstruct SDY data takes dominant climate controlling factors of hydrological changes. We conclude that the LMRM, a statistically developed model, is physically meaningful and may be reasonably used for estimating SDY in peninsular Italy roughly down from the sub-Alpine range. 相似文献
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Calibrating a rainfall erosivity assessment model at regional scale in Mediterranean area 总被引：3，自引：1，他引：2
Sergio Grauso Nazzareno Diodato Vladimiro Verrubbi 《Environmental Earth Sciences》2010,60(8):1597-1606
A simplified regression model is here calibrated on the basis of rainfall data records of Sicily (southern Italy), in order
to show the model reliability in assessing the R-factor of the Universal Soil Loss Equation and its revised version (RUSLE) and to provide an estimate of long-term rainfall
erosivity at medium-regional scale. The proposed model is a rearrangement of a former simplified model, formulated for the
Italian environment, grouping three easily available rainfall variables on various time scales, which has been shown to be
more successful than others in reproducing the rainfall erosive power over different locations of Italy. A geostatistical
interpolation procedure is then applied for generating the regional long-term erosivity map with associated standard error.
Areas with severe erosive rainfalls (from 2,000 up to more than 6,000 MJ mm ha−1 h−1) are pointed out which will correspond to areas suffering from severe soil erosion. Solving the problem of calculating the
R-factor value in the RUSLE equation by means of such a simplified model here formulated will allow to predict the related
soil loss. Moreover, given the availability of long time-series of concerned rainfall data, it will be possible to analyse
the variability of rainfall erosivity within the last 50 years, and to investigate the application of RUSLE or similar soil
erosion models with forecasting purposes of soil erosion risk. 相似文献