Rainy Day Prediction Model with Climate Covariates Using Artificial Neural Network MLP, Pilot Area: Central Italy

The reconstruction of daily precipitation data is a much-debated topic of great practical use, especially when weather stations have missing data. Missing data are particularly numerous if rain gauges are poorly maintained by their owner institutions and if they are located in inaccessible areas.In this context, an attempt was made to assess the possibility of reconstructing daily rainfall data from other climatic variables other than the rainfall itself, namely atmospheric pressure, relative humidity and prevailing wind direction.The pilot area for the study was identified in Central Italy, especially on the Adriatic side, and 119 weather stations were considered.The parameters of atmospheric pressure, humidity and prevailing wind direction were reconstructed at all weather stations on a daily basis by means of various models, in order to obtain almost continuous values rain gauge by rain gauge. The results obtained using neural networks to reconstruct daily precipitation revealed a lack of correlation for the prevailing wind direction, while correlation is significant for humidity and atmospheric pressure, although they explain only 10–20% of the total precipitation variance. At the same time, it was verified by binary logistic regression that it is certainly easier to understand when it will or will not rain without determining the amount. In this case, in fact, the model achieves an accuracy of about 80 percent in identifying rainy and non-rainy days from the aforementioned climatic parameters. In addition, the modelling was also verified on all rain gauges at the same time and this showed reliability comparable to an arithmetic average of the individual models, thus showing that the neural network model fails to prepare a model that performs better from learning even in the case of many thousands of data (over 400,000). This shows that the relationships between precipitation, relative humidity and atmospheric pressure are predominantly local in nature without being able to give rise to broader generalisations

Natural and anthropic changes on landscapes: signs and designs in a river system. The study-case of the Potenza River final sector (Porto Recanati, Italy)

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MAN OR NATURE? THE ROLE OF NATURAL EVENTS IN THE ABANDONING OF THE ROMAN TOWN OF CARSULAE (TIBER BASIN ITALY)

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Landslide Susceptibility Using Climatic–Environmental Factors Using the Weight-of-Evidence Method—A Study Area in Central Italy

The Italian territory is subject to a high level of hydrogeological instability that periodically results in the loss of lives, buildings and productive activities. Therefore, the recognition of areas susceptible to hydrogeological instability is the basis for preparing countermeasures. In this context, landslide susceptibility in the mid-Adriatic slope was analyzed using a statistical method, the weight of evidence (WoE), which uses information from several independent sources to provide sufficient evidence to predict possible system developments. Only flows, slides, debris flows and mud flows were considered, with a total of 14,927 landslides obtained from the IFFI (Inventory of Franous Phenomena in Italy) database. Seven climatic–environmental factors were used for mapping landslide susceptibility in the study area: slope, aspect, extreme precipitation, normalized difference vegetation index (NDVI), CORINE land cover (CLC), and topographic wetness index (TWI). The introduction of these factors into the model resulted in rasters that allowed calculation by GIS-type software of a susceptibility map. The result was validated by the ROC curve method, using a group of landslides, equal to 20% of the total, not used in the modeling. The performance of the model, i.e., the ability to predict the presence or absence of a landslide movement correctly, was 0.75, indicating a moderately accurate model, which nevertheless appears innovative for two reasons: the first is that it analyzes an inhomogeneous area of more than 9000 km2 , which is very large compared to similar analyses, and the second reason is the causal factors used, which have high weights for some classes despite the heterogeneity of the area. This research has enabled the simultaneous introduction of unconventional factors for landslide susceptibility analysis, which, however, could be successfully used at larger scales in the future

A Multi-Model Approach Using Statistical Index and Information Criteria to Evaluate the Adequacy of the Model Geometry in a Fissured Carbonate Aquifer (Italy)

A conceptual model related to a mountain aquifer that is characterized by a lack of data of hydrogeological parameters and boundary conditions, which were based on a single available observational dataset used for calibration, was studied using numerical models. For the first time, a preliminary spatial-temporal analysis has been applied to the study area in order to evaluate the real extension of the aquifer studied. The analysis was based on four models that were characterized by an increasing degree of complexity using a minimum of two zones and a maximum of five zones, which consequently increased the number of adjustable parameters from a minimum of 10 to a maximum of 22, calibrated using the parameter estimation code PEST. Statistical index and information criteria were calculated for each model, which showed comparable results; the information criteria indicated that the model with the low number of adjustable parameters was the optimal model. A comparison of the simulated and observed spring hydrographs showed a good shape correspondence but a general overestimation of the discharge, which indicated a good fit with the rainfall time series and a probably incorrect extension of the aquifer structure: the recharge contributes more than half of the total outflow at the springs but is not able to completely feed the springs

DSGSDs induced by post glacial decompression in central Apennine (Italy)

During the last 30 years of studies in the field of mass movements located in the calcareous-marly and marly-sandy Apennines (Umbria-Marches and Latium-Abruzzi regions), over to a large number of landslides with different dimensions, even a lot of deep-seated gravitational slope deformations (DSGSDs) have been recognized and analysed. These phenomena are also located in that sector of central Italy affected by a cold climate during the past and actually temperate (central Apennine chain)

The significance of recent and short pluviometric time series for the assessment of flood hazard in the context of climate change: examples from some sample basins of the Adriatic Central Italy

Numerical hydrological models are increasingly a fundamental tool for the analysis of floods in a river basin. If used for predictive purposes, the choice of the “design storm” to be applied, once set other variables (as basin geometry, land use, etc.), becomes fundamental. All the statistical methods currently adopted to calculate the design storm, suggest the use of long rainfall series (at least 40–50 years). On the other hand, the increasingly high frequency of intense events (rainfalls and floods) in the last twenty years, also as a result of the ongoing climate change, testify to the need for a critical analysis of the statistical significance of these methods. The present work, by applying the Gumbel distribution (Generalized Extreme Value Type-I distribution) on two rainfall series (1951–2018 and 1998–2018) coming from the same rain gauges and the “Chicago Method” for the calculation of the design storm, highlights how the choice of the series may influence the formation of flood events. More in particular, the comparison of different hydrological models, generated using HEC-HMS software on three sample basins of the Adriatic side of central Italy, shows that the use of shorter and recent rainfall series results in a generally higher runoff, mostly in case of events with a return time equal or higher than 100 year

Geo-environmental changes and historical events in the area of the Greek archaeological site of Selinunte (Western Sicily, Italy)

Detailed geomorphological and geo-archaeological surveys were carried out in this study at the Greek archaeological site of Selinunte to reconstruct the landscape evolution that occurred before and during the anthropization of the site and to verify the possible correlations between geo-environmental changes and human events that characterized almost four centuries of the history of the city. By using a multidisciplinary approach and different survey techniques, this study testified the role played by climate, geomorphological setting and georesources in conditioning the development of the city and the close relationship sometimes observed between the historical events and natural processes. This included the controversial and never discovered hydraulic work of Empedocles who, according to textual sources, in 444 BC, resolved a public health problem linked to the presence of marshy areas