4 papers
Pure and Physics-Guided Deep Learning Solutions for Spatio-Temporal Groundwater Level Prediction at Arbitrary Locations
Matteo Salis, Gabriele Sartor, Rosa Meo +2
Groundwater represents a key element of the water cycle, yet it exhibits intricate and context-dependent relationships that make its modeling a challenging task. Theory-based model…
Time Distributed Deep Learning Models for Purely Exogenous Forecasting: Application to Water Table Depth Prediction using Weather Image Time Series
Matteo Salis, Abdourrahmane M. Atto, Stefano Ferraris +1
Groundwater resources are one of the most relevant elements in the water cycle, therefore developing models to accurately predict them is a pivotal task in the sustainable resource…
Analysis of Diurnal Air Temperature Trends and Pattern Similarities in Highland and Lowland Stations of Italy and UK
Chalachew Muluken Liyew. Rosa Meo, Stefano Ferraris, Elvira Di Nardo
In this paper, an analysis of hourly air temperatures in four groups of 32 stations of the UK highland (five stations), UK lowland (four stations), Italian highland (eleven station…
Identifying Time Patterns of Highland and Lowland Air Temperature Trends in Italy and UK across monthly and annual scales
Chalachew Muluken Liyew, Elvira Di Nardo, Rosa Meo +1
This paper presents a statistical analysis of air temperature data from 32 stations in Italy and the UK up to 2000 m above sea level, from 2002 to 2021. The data came from both hig…