Fabio Di Nunno

Climate change is having an increasing effect on the water cycle, hindering the proper management of water resources for different purposes. Veneto, Northern Italy, is a region characterized by various climatic conditions, ranging from the coastal area to the inland, which exhibits significant agricultural productivity with high irrigation demand, up to the mountainous area to the north. This study assesses a key aspect of climate change in Veneto by focusing on a crucial hydrological parameter, the reference evapotranspiration (ETo), which is calculated using the Penman–Monteith equation. The K-means algorithm was employed to divide Veneto into nine homogeneous regions, each characterized by specific evapotranspiration and climatic features. Furthermore, the seasonal Mann–Kendall (MK) test and the innovative trends analysis (ITA) method were used to investigate the trends related to monthly precipitation, ETo, and climate variables. The seasonal MK test revealed negative trends in precipitation for all clusters. In contrast, ETo trends appear to be decreasing for some clusters, both on the coast and inland, and increasing for others. The ITA method indicated more pronounced trends for higher values of ETo and precipitation, highlighting significant variations that primarily impact extreme values. Overall, this study’s approach, which incorporates clustering and trends analysis methods, provides a detailed depiction of ETo in Veneto, enabling the identification of distinct homogeneous areas and the assessment of evolutionary trends concerning evapotranspiration and precipitation, from the coastal to the mountainous regions.

Forecasting upstream flow amount based on downstream flow values is a new way of managing flood risk. This kind of prediction of the flow, size, and intensity of rivers in the alluvial aquifers is, in most cases, a challenging task due to climate change, as well as anthropogenic impacts on river flows. The presented methodology allows for organizing and preparing measures for flood protection, the operational work of hydropower plants, and many other usages. The methodology consists of correlation, cross-correlation, and a rescaled adjusted partial sums (RAPS) method. Although all methods are known, they have not been used in a methodology like the one presented. Research is conducted on a real case study of the river Bednja, on five consecutive hydrological measurement stations in the northwestern part of Croatia, for an available time series of the average daily flows from 2007–2018. High correlations were observed between the five stations along the Bednja River, with values of the correlation coefficient between 0.85 and 0.97 for the average daily flows, and between 0.88 and 0.99 for the RAPS values. The presented analysis gives information about similarities and connections between all five hydrological stations, which is significant and can be used to predict flow intensity.