Abstract

Headwaters in Alpine regions represent the large majority of streams in natural or nearly natural conditions, which provide essential ecosystem services. These catchments are particularly sensitive to temperature changes and may suer significant changes because of climate variations. Thus, identifying the main mechanisms controlling streamflow generation and understanding the nature and variability of streamflow in Alpine streams, represent a very important contribution towards a better understanding of these complex systems. Among the multiplicity of streamflow sources (e.g., rain, snow-melt, ice-melt and groundwater), in particular snow and ice-melt play a fundamental role on the hydrological cycle of Alpine catchments and strongly affect streamflow regime. Despite several research efforts over the past decades focused on understanding the complex dynamics of the hydrological processes that characterize these environments, there is still much to disclose. Hence, the interpretation of streamflow sources can become very difficult with water discharge as the sole observed variable. The previous calls for the use of alternative data sources and methods for data analysis and visualization. This doctoral thesis aimed to contribute with new insights into the multifaceted aspects of streamflow generation in Alpine river catchments, exploring the different roles played by hydrological and geochemical information and the use of several techniques, such us tracer-based analysis, continuous wavelet transform, wavelet coherence, cross-correlation and Hovmöller diagrams; in order to investigate the mechanisms controlling streamflow generation on real case studies at different temporal scales. Hence, the present thesis is based on four main elements. In the first part of this work we show how tracer data (i.e., electrical conductivity and stable isotopes of stream water) can be used to separate the contribution of pre-event and event waters applying a two-component mixing analysis on four single rainfall events identied in the Vermigliana catchment, North-Eastern Italian Alps. The separation of streamflow into two different components allowed us to improve the conceptual model of the catchment introducing constraints that are impossible to envision counting only on streamflow measurements. Moreover, we show that the relative contribution of event water with respect to pre-event water does not change only according to the magnitude of the precipitation event and on the variations in air temperature, but it also depends on the presence and thickness of the snowpack present during the event. Second, we explored the correlation between stream water electrical conductivity (EC) and water discharge (Q) using continuous records collected during two melting periods of the Vermigliana catchment. The analysis of the hysteresis relating EC and Q at the annual scale evidenced the limitations of the use of EC measurements as a proxy of Q in these type of catchments. In addition, the combined analysis of the correlation between both signals using wavelet coherence and cross-correlation, evidenced the nature of their relationship (i.e., out of phase) and the existence of relatively constant time lag between both signals. Wavelet coherence proved to be likewise useful to identify specic periods of significant changes in the dynamics controlling streamflow generation. Furthermore, the analysis of EC and Q diurnal cycles allowed us to obtain new insights related to snow-dynamics and were also used to estimate the daily contribution to streamflow from snow-melting processes. The previous contributions may support future research on the different transfer functions that characterize water and solute transport in snow and ice-melting dominated catchments. Third, the need to understand how short and long-term climate variations may influence streamflow variability in Alpine environments lead us to the use of alternative techniques to analyse traditional long-term hydrological time series, i.e., precipitation (P), temperature (T) and streamflow (Q). We compared streamflow variability and explored the relationship between atmospheric forcing and streamflow of two case studies: Vermigliana and Sarca di Genova catchments, both located in the same region and presenting similar features, like the presence of glaciers in their upper part. Hovmöller diagrams and continuous wavelet transform were used to investigate daily and seasonal climate influences on streamflow variability, while wavelet coherence analysis was used to explore the periods on which two time series experienced oscillations at a similar frequency. Moreover, the use of these alternative techniques for data analysis and visualization, provided further insights into the hydrological response and sensitivity of the systems under study to climate changes, leading to the improvement of current conceptual models and allowing us to define a suitable framework for modelling applications, as foreseen within the following research element. The fourth element of this thesis, includes the application of an existing stochastic analytical modelling framework to the two case studies mentioned above, with the aim of characterizing and predicting streamflow distribution in these glacierized catchments. Results evidence that the size of glacier coverage on these type of catchments represents a very important feature of the system that needs to be taken account for, in fact, glaciers store a large amount of water as snow and ice, which can be rapidly released affecting signicantly the magnitude and distribution of streamflow. Overall, the results obtained during this thesis provide new insights into the multi-faceted aspects of streamflow generation in snow and glacier dominated catchments, where geochemical data as an addition to hydrological information on real case studies played an essential role. Likewise, the application of different techniques for data analysis and visualization considering a variability of temporal scales provided valuable information about the sensitivity of Alpine systems to climate changes, which may serve as a support for water resources management in these important environments. Moreover, testing the applicability of an stochastic analytical approach to this complex context allowed us to understand the influence of the presence and size of glaciers on streamflow variability. Thus, the outcomes of this study may contribute to the improvement and development of new modelling structures.