Alexandru Onaca

Rock glaciers are critical indicators of periglacial environments and the spatial distribution of mountain permafrost. Given their complex deformation patterns and temporal variability, which may indicate progressive destabilization, a quantitative evaluation of their kinematic activity is critical from both climatological and geohazard perspectives. This study applies Persistent Scatterer Interferometric Synthetic Aperture Radar (PSInSAR) to Sentinel-1 radar imagery on both ascending and descending orbits, in order to detect and map moving areas (MA) within the Pirin Mountains (Bulgaria). The primary objective of this study is to update the existing rock glacier inventory (RoGI) by integrating high-resolution Line-of-Sight (LOS) velocity data in accordance with the latest international standards established by the Rock Glacier Inventories and Kinematics (RGIK) standing committee. A secondary objective is to investigate the spatial relationships between the identified moving areas (MAs) and other surrounding geomorphological features (e.g., talus slopes), hence providing a wider context for slope dynamics and landform evolution. The results identified MAs with PSInSAR-derived Line-of-Sight (LOS) velocities reaching up to 10 cm yr⁻¹, which were subsequently classified according to RGIK kinematic categories. A substantial proportion of the detected moving areas occur outside mapped rock glacier boundaries and may reflect a range of geomorphological processes, including permafrost-related creep, talus creep, or other forms of slope deformation. The LOS velocity data were used to assess the activity status of 74 rock glacier units within the regional inventory, classifying 8 as transitional (velocity exceeding 1 cm yr⁻¹) and 66 as relict. Furthermore, we analyse the spatial distribution of these moving areas in relation to primary topographic variables, such as elevation, aspect, and slope. The results highlight the influence of topographic control factors and rock glacier dynamics and provide new insights into the distribution of active periglacial landforms and terrain potentially affected by permafrost in the Balkan Peninsula under changing climatic conditions.

Snow depth and persistence strongly influence ground–atmosphere energy exchange, meltwater input, and the thermal regime of rock glacier systems, yet high-resolution snow monitoring remains scarce in the Southern Carpathians. This study uses multi-temporal Unmanned Aerial Vehicle (UAV) Structure-from-Motion (SfM) photogrammetry to map snow-depth variability and microtopographic controls on the Galeșu Rock Glacier, Retezat Mountains. Eight UAV surveys were conducted between 2023 and 2025, including seven snow-covered acquisitions and one snow-free reference survey in August 2025. Snow depth was derived by DEM differencing and analyzed against morphometric indices, mainly profile curvature and relative topographic position. Results reveal strong spatial heterogeneity, with recurrent snow accumulation in furrowed, concave, and depressional sectors and reduced snow depth on local topographic highs. The 2024 surveys showed substantially deeper snow than 2025, with mean snow depths of 1.82 m in February and 1.62 m in March 2024, compared with 0.72 m and 0.83 m in February and March 2025. April 2023 displayed the deepest snowpack, with a mean snow depth of 2.27 m. Class-based analysis showed median contrasts of 2.30 m in 2024 and 1.20 m in 2025 between strong negative and strong positive curvature classes. These findings demonstrate that rock glacier microtopography exerts a first-order control on snow accumulation and persistence, providing a basis for future studies linking snow redistribution to ground thermal regimes, meltwater pathways, and ground-ice preservation in marginal periglacial environments.

Artificial levees along major rivers are critical for flood-risk mitigation, yet many aging structures have poorly constrained internal composition and material heterogeneity, limiting the reliability of conventional safety assessments. This study develops a quantitative, non-destructive framework for characterizing levee internal structure by integrating electrical resistivity tomography (ERT) with borehole (BH) observations. ERT profiles were combined with borehole measurements of grain size (D50) and water content to investigate subsurface compositional variability and to evaluate relationships between sedimentological and geophysical parameters. Grain-size data from borehole samples were modeled using four predictive approaches—random forest regression (RFR), artificial neural networks (ANN), linear regression (LR), and support vector regression (SVR)—based on ERT-derived resistivity and moisture information. The results reveal pronounced internal heterogeneity within the investigated levees and demonstrate consistent relationships between sediment composition, water content, and electrical resistivity. Among the tested models, the ensemble-based RFR provided the highest predictive performance (R² = 0.81). These findings indicate that D50 characteristics of levee materials can be reliably inferred from ERT data using machine learning, reducing the need for destructive sampling. The proposed approach offers a transferable methodology for levee assessment and supports future applications in non-destructive monitoring, spatially explicit flood-risk analysis, and climate-resilient flood-protection management.

Understanding long-term snow cover dynamics is essential in mountain regions with limited meteorological or in situ observations. This study examines seasonal snow cover evolution across the Romanian Carpathians (2000–2025) using daily MODIS/Terra MOD10A1 Cloud-Gap-Filled data at 500 m resolution. Snow-covered pixels were identified using an NDSI ≥ 40 threshold, and snow cover duration (SCD), snow onset date (SOD), and snow end date (SED) were analyzed in relation to elevation and aspect from the FABDEM, complemented by snow-covered area (SCA) and snowline elevation (SLE) metrics. Across the entire range, the snow season shortens mainly due to later onset (+0.28 days/year) and earlier melt (−0.78 days/year), resulting in an SCD decrease of −1.14 days/year. High-elevation (>2000 m) areas show only small changes (SCD: −0.13 days/year; SOD: +0.46 days/year; SED: +0.32 days/year), while the strongest reductions occur at low and mid elevations, where snow persistence is most sensitive to warming; consistent declines in seasonal SCA and a pronounced monthly SLE cycle further document the spatial expression of this variability. Uncertainty was assessed by comparison with station-based snow cover duration (n = 230 station-years), indicating strong agreement (r = 0.95) with a modest negative bias (median: −8 days) and a mean absolute error (MAE) of 16.7 days. Climate correlations highlight air temperature as the dominant covariate of interannual snow-phenology variability, whereas precipitation associations are weaker. Overall, these shifts in snow phenology highlight increasing instability of the Carpathian snow regime and emphasize the value of long-term MODIS observations for tracking cryospheric change in a warming southeastern European mountain system.

This study examines ground surface and air temperatures and their implications for periglacial activity in the Țarcu Massif, Southern Carpathians, where data on current dynamics and climate responses remain scarce despite widespread periglacial landforms. To address this, we deployed seven temperature loggers between 2018 and 2024 across a range of periglacial landforms, including non-sorted patterned ground, a periglacial hummock, protalus rampart, block stream, periglacial tor, ploughing boulder, and nival niche. We analyzed key thermal indicators such as freeze–thaw cycles, freezing and thawing degree days, frost weathering intervals, frost days, and winter equilibrium temperatures—in relation to long-term air temperature records (1961–2023), snow cover dynamics, and local topographic and substrate conditions. Results reveal a marked warming trend at the Țarcu meteorological station, particularly after 1995, along with a shift in net thermal balance beginning in the late 1990s. Since then, climatic conditions at this site have no longer been favorable for the persistence of sporadic permafrost. Ground thermal conditions varied spatially, with coarse debris sites and rock wall maintaining the lowest MAGST values—typically with 1 to 2.5 °C cooler than fine-grained sediments—and the highest potential for frost-related weathering. Despite low and variable freeze–thaw cycle frequency, the high number of frost days (around 200 per year) and sustained frost weathering potential—exceeding 50 days annually at key sites—indicate that periglacial conditions remain active for nearly half the year around 2000 m in the Southern Carpathians. Snow cover dynamics proved to be a major control on ground thermal behavior, with earlier melting and delayed onset shortening its duration but amplifying early winter cooling. These findings indicate that the Țarcu Massif is a transitional periglacial environment, where active and relict features coexist under growing climatic pressure. The ongoing decline in frost-driven processes highlights the vulnerability of mid-latitude mountain periglacial systems to climate warming and underscores the need for continued monitoring to better understand future landscape evolution in the Southern Carpathians.

Mountain watersheds play a crucial role in sustaining freshwater resources, yet they are highly vulnerable to climate change. In this study, we investigated the summer water temperature of 35 alpine springs in the highest part of the Retezat Mountains, Southern Carpathians, between 2020 and 2023. During the four-year monitoring period, water temperatures across all springs ranged from 1.2 °C to 10.5 °C. Springs emerging from rock glaciers had the lowest average temperature (2.37 °C), while those on cirque and valley floors were the warmest (6.20 °C), followed closely by springs from meadow-covered slopes (6.20 °C) and those from scree and talus slopes (4.70 °C). However, only four springs recorded summer temperatures below 2 °C, suggesting a direct interaction with ground ice. The majority of springs exhibited temperatures between 2 and 4 °C, exceeding conventional thresholds for permafrost presence. This challenges the applicability of traditional thermal indicators in marginal periglacial environments, where reduced ground ice content within rock glaciers and talus slopes can lead to spring water temperatures ranging from 2 °C to 4 °C during summer. Additionally, cold springs emerging from rock glaciers displayed minimal daily and seasonal temperature fluctuations, highlighting their thermal stability and decoupling from atmospheric conditions. These findings underscore the critical role of rock glaciers in maintaining alpine spring temperatures and acting as refugia for cold-adapted organisms. As climate change accelerates permafrost degradation, these ecosystems face increasing threats, with potential consequences for biodiversity and hydrological stability. This study emphasizes the need for long-term monitoring and expanded investigations into water chemistry and discharge dynamics to improve our understanding of high-altitude hydrological systems. Furthermore, it provides valuable insights for the sustainable management of water resources in Retezat National Park, advocating for conservation strategies to mitigate the impacts of climate change on mountain hydrology and biodiversity.

The hydrology of rock glaciers is a complex and poorly understood field, marked by uncertainties in water flow dynamics and the uneven distribution of the frozen substrate. One effective method for identifying permafrost - particularly in marginal permafrost regions like the Southern Carpathians - is measuring the temperature of mountain springs at the end of summer. Once seasonal snow has melted, permafrost becomes the primary factor influencing the low temperatures of the springs.This study examines the spatial and temporal variability of spring water temperatures in the Retezat Mountains to assess the distribution of permafrost and its impact on spring water temperatures. In mid-August 2024, water temperatures were recorded at 62 springs using a Testo 110 instrument with a resolution of 0.10 C resolution. The springs, situated at elevations between 1770 and 2230 meters and were categorized into four groups: (1) springs emerging from rock glaciers, (2) springs from scree slopes and talus slopes, (3) springs from areas with slopes covered with meadows and (4) springs from cirque or valley floors.Additionally, continuous temperature monitoring was implemented for six springs originating from rock glaciers, using dataloggers, with data collection starting in the summer of 2021. Due to their greater resilience to climate change compared to glaciers, rock glaciers are expected to play an increasingly significant hydrological role in the face of ongoing climate change, acting as vital long-term water reservoirs thanks to their thick insulating debris cover.

Advective heat fluxes (chimney effect) in porous debris facilitate ground cooling on scree slopes, even at low altitudes, and promote the occurrence of sporadic permafrost. The spatial distribution of ground surface temperature on an overcooled, low-altitude scree slope in the Romanian Carpathians was analyzed using UAV-based infrared thermography in different seasons. The analysis revealed significant temperature gradients within the scree slope, with colder, forest-insulated lower sections contrasting with warmer, solar-exposed upper regions. Across all surveyed seasons, this pattern remained evident, with the strongest temperature contrasts in December and April. February exhibited the most stable temperatures, with thermal readings primarily corresponding to snow surfaces rather than exposed rock. Rock surfaces displayed greater temperature variation than vent holes. Vent holes were generally cooler than rock surfaces, particularly in warmer periods. The persistent presence of ice and low temperatures at the end of the warm season suggested the potential existence of isolated permafrost. The results confirm the chimney effect, where cold air infiltrates the lower talus, gradually warms as it ascends, and outflows at higher elevations. UAV-based thermal imagery proved effective in detecting microclimatic variability and elucidating thermal processes governing talus slopes. This study provides valuable insights into extrazonal permafrost behavior, particularly in the context of global climate change.

Permafrost is defined as the ground (including soil or rock) that remains at or below 0°C for a minimum of two consecutive years (Harris et al., 1988). Due to permafrost`s sensitivity to climate change, it is essential to study the hydrology of rock glaciers to predict and mitigate the impacts of climate-induced changes, including permafrost thaw.Physico-chemical analyses along with temperature monitoring of springs seeping from the base of the rock glacier fronts were conducted over two consecutive years (2022 and 2023) in various glacial valleys in the central part of the Retezat Mountains.The measurement of spring water temperature during late summer (SWTS) is employed to discern permafrost distribution in alpine regions. According to previous studies (Frauenfelder et al., 1998; Scapozza, 2009), a water temperature above 2°C indicates the absence of permafrost, while a temperature between 1 and 2°C indicates the possible presence of permafrost, and a temperature below 1°C indicates that permafrost is likely.In this study physico-chemical and isotopic analyses along with temperature measurements were conducted on springs not originating from rock glaciers, serving as a comparative approach.The springs associated to rock glaciers draw water from four sources: groundwater, rain, snow and permafrost (Krainer et al., 2007). Among these, snow and permafrost are the primary sources that regulate the low spring temperatures. The cooling effect of a persistent snow layer in mountainous regions such as the Retezat Mountains can have significant influence on spring water temperatures even in the summer months. After snow melts, the presence of permafrost mainly governs the low temperatures of the springs. Only four springs exhibited temperatures below 2°C during the warm season, while many others showed temperatures close to 2-3°C. Given the patchy occurrence of permafrost in the Southern Carpathians and the fact that the frozen materials are located a few hundred meters away from the rock glacier front we hypothesize that permafrost may also be present in rock glaciers characterized by spring temperatures above 2°C. Based solely on the results of physico-chemical analysis, it is impossible to differentiate whether the spring water originates from ice or snow.KEYWORDS: permafrost, spring water, rock glaciers, SWTSREFERENCESFrauenfelder, R., Allgöwer, B., Haeberli, W. & Hoelzle, M. (1998). Permafrost investigations with GIS – a case study in the Fletschhorn area, Wallis, Swiss Alps. In Permafrost, Proceedings of the Seventh International Conference, 23–27June 1998, Yellowknife, Canada, Lewkowicz AG, Allard M (eds) eds, Collection Nordicana 57. Centre d’études Nordiques, Université Laval: Québec; 291–295.Harris, S.A., French, H.M., Heginbottom, J.A., Johnston, G.H., Ladanyi, B., Sego, D.C., van Everdingen, R.O., 1988, Glossary of Permafrost and Related Ground-Ice Terms, National Research Council of Canada, Ottawa, 156 p.Krainer, K., Mostler, W. & Spötl, C. (2007). Discharge from active rock glaciers, Austrian Alps: a stable isotope approach. Austrian Journal of Earth Sciences 100: 102–112.Scapozza, C. (2009). Contributo dei metodi termici alla prospezione del permafrost montano: esempi dal massiccio della Cima di Gana Bianca (Val Blenio, Svizzera). Bollettino della Società Ticinese di Scienze Naturali 97: 55–66.

Computer modeling of sporadic and isolated patches of mountain permafrost distribution is difficult to implement without overestimating it. The main challenge is to determine the very areas where the criteria for permafrost maintenance are met. This paper aims to modeling the permafrost distribution in the Southern Carpathians (SC), a typical marginal periglacial mountain range. For this purpose, a collection of 883 bottom temperature of late winter snow cover (BTS) points was used as a proxy for permafrost presence or absence in order to train several machine learning models. The performances of each model were evaluated with AUC with varying between 0.99 for Maxent and 0.74 for K‐nearest neighbors and most models (five) exhibiting values between 0.82 and 0.86. Other tests such as confusion matrices, sensitivity analyses, data shuffling, and data size reduction tests indicated that Maxent, AdaBoost, and support vector machine offered the best results while logistic regression, neural network, and gradient boosting exhibited rather poor permafrost distributions. The final ensemble median model indicated a total permafrost area of 19.2 km ² occupying 1%–9% of the alpine area of the studied massifs. NDVI proved crucial for permafrost prediction because it allows delimiting the debris surfaces where permafrost is probable.