## 6 Conclusions  
The interpretation of SAR backscattering is not always straightforward, especially in regions where snowpack are shallow and not permanent throughout the snow season, like in Mediterranean mountain areas such as the Sierra Nevada. In this work, we analyzed snow dynamics and their relationship with streamflow response in such semi-arid mountains using S-1 SAR imagery. Sentinel-1 SAR imagery proved to be highly effective in capturing not only the final spring melting, but also all melting cycles throughout the year in such environments. This study successfully adapted the general change detection approach used in other regions to identify wet snow in semi-arid mountains by using the previous summer period of reference and establishing a wet-snow threshold of \(-3.00\) dB. Additionally, on a local scale, the analysis enabled the identification of four distinct types of melting runoff onsets, each one associated with specific snowpack characteristics such as depth, duration of the accumulation phase before melting, and timing within the year. At the catchment scale, a novel approach was introduced to delineate melting cycles throughout the year using Sentinel-1 SAR imagery exclusively. This method generated distributed melting runoff onset maps, thus enhancing our understanding of the spatiotemporal evolution of melting dynamics within the region. Furthermore, the study explored the connection between snowmelt dynamics and streamflow, through a piecewise function comprising three segments. This function was closely linked to the maximum snow water equivalent (SWE) achieved during the snow cycle, with a linear relationship for prolonged melting cycles. Finally, an average delay of approximately 21 days between the melting onset and the peak streamflow was also found in the selected catchment. This work constitutes a first approach to better understand S-1 SAR imagery backscattering and assess its capability to foresee changes in streamflow over Mediterranean mountains. As a next step, we intend to improve the interpretation on a local scale by using, in addition to terrestrial imagery, measured variables such as SWE or temperature at different heights of the snow cover as well as the morning acquisitions of S-1 data. These potential improvements will help to achieve better interpretations of the snowpack dynamics in this type of environment and therefore improve our predictive capacity of streamflow in the area. and C.N. ; Data curation, P.T. ; Writing--original draft, P.T. ; Writing--review & editing, R.P., M.J.P. and C.N. ; Visualization, P.T. and R.P. ; Supervision, R.P., M.J.P. and C.N. ; Funding acquisition, M.J.P. All authors have read and agreed to the published version of the manuscript. This research was funded by the Spanish Ministry of Science and Innovation through the research project PID2021-12323 SNB-I00, HYPOMED--\"Incorporating hydrological uncertainty and risk analysis to the operation of hydropower facilities in Mediterranean mountain watersheds\". The data presented in this study are available on request from the corresponding author. [PERSON] acknowledges fundings by the Ayudas para la formacion de profeso-rado universitario (FPU) (Convocatoria 2017) the Spanish Ministry of Education, Culture and Sports (FPU17/01003). [PERSON], [PERSON], and [PERSON] are members of DAUCO, Unit of Excellence ref. CEX2019-000968-M, with financial support from the Spanish Ministry of Science and Innovation, the Spanish State Research Agency, through the Severo Ochoa and Maria de Maeztu Program for Centers and Units of Excellence in R&D. The authors would like to thank Eurac Research, particularly to Institute for Earth Observation as it allowed [PERSON] for stay during the summer of 2021, which has been fundamental for this work. The authors declare no conflict of interest. The selected days have been the following scenes (i) 5 December 2016, (ii) 5 March 2017, (iii) 16 February 2018, (iv) 28 February 2018, (v) 12 April 2019 and (vi) 24 April 2019.