Cuadernos de Investigación Geográfica

50 Years of Cuadernos de Investigación Geográfica

Tue, 29 Jul 2025 00:00:00 +0200

Snow Cover Variability in the Cantabrian Mountains (Spain): A Watershed-Level Study Using Satellite Records (2000–2024)

Adrián Melón-Nava, Amelia Gómez-Villar — Mon, 30 Jun 2025 00:00:00 +0200

This study presents an analysis of the main snow cover dynamics in the Cantabrian Mountains (northern Spain) using satellite imagery, examining the snow cover dates of appearance and melting, extent, duration and persistence. The study area comprises 36 hydrographic watersheds. Using Google Earth Engine (GEE), 14,082 satellite images (2000-2024) from MODIS-Terra, Landsat 5-8, and Sentinel-2 were analysed to create daily snow cover classifications. Seasonal series of Snow Cover Fraction (SCF) were extracted by 500-meter elevation intervals in each watershed and analyzed to extract indicators and trends.

Results reveal reductions in snow cover extent. In autumn, it is reduced at ~-2%/decade above 1,500 m. Notable and significant negative trends (~-10% and up to -16%/decade in some basins) were detected in winter, particularly on the southern slopes of the Cantabrian Mountains. In spring, most basins show negligible and homogeneous trends among watersheds, except above 2,000 m, where pronounced reductions in extent (2.5% per decade) are observed. A shortening snow season is detected, caused by earlier occurrences of the Last Ephemeral Snow Day (LESD), occurring 2.7 days by decade earlier vs 0.4 days by decade earlier in case of the First Ephemeral Snow Day (FESD). The duration of the first snow cover of the season decreased noticeably above 1,500 m (9 days/decade). Peak seasonal snow cover extent tends to occur slightly later, and above 2,000 m. These events are markedly shorter due to a delay in the Snow Onset Day (SOD) and earlier Snow Melt Out Day (SMOD). The maximum SCF occurs between January 22nd and February 5th, depending on altitude, and is shifting earlier, especially at lower elevations. The mean snow cover duration is 16.4 days, with notable altitudinal variability (6.6 days at 500–1000 m and 38.5 days above 2,000 m), decreasing by 1 day/decade, with reductions up to 5.8 days/decade above 2,000 m, where the duration of the longest snow cover has decreased 8 days/decade. Snow cover persistence has declined by 1.2%/decade, with sharper reductions (3.4%) above 1,500 m.

Despite biases from prolonged periods of cloud cover, dense canopy cover in some watersheds or the occurrence of rapid snow accumulation and melting events undetected by the satellites, findings ultimately reveal decreases in the duration, extent and persistence of snow cover since the early 21st century, although some of these are not statistically significant. These results highlight shifts in seasonal snow cycles, emphasizing the need for further research with longer time series and alternative observational datasets.

Effects of DEM Resolution and Area Thresholds on Automated Fluvial Morphometry, Arroyo del Oro (Argentina)

Ana Casado, Federico Javier Berón de la Puente, Verónica Gil — Tue, 22 Apr 2025 00:00:00 +0200

The resolution of Digital Elevation Models (DEM) as well as the area threshold to define streams and catchments are important sources of uncertainty in automated fluvial morphometry. This study examines the applicability of three global surface models, produced with resolutions of 12.5 (ALOS), 30 and 90 m (SRTM), along with five area thresholds ranging from 0.15 to 10%. It aims at evaluating the effects of varying resolution-threshold combinations on the extraction of morphometric parameters and indices (PIm) in the Arroyo del Oro, a mountain basin located in south-western Buenos Aires (Argentina). The analysis considers the accuracy of drainage definitions, the variability of resulting PIm, and its implications for flood and water erosion assessments. Results show that the higher thresholds affect the PIm that depend on the complexity of the drainage network. Coarser resolutions impact on relief, slope and length parameters, but yield small discrepancies for the remaining PIm. For the 0.15% threshold, SRTM30 provides good fit of drainage composition parameters, and it is therefore suitable to assess the efficiency and capacity of the basin to evacuate floods. However, the use of higher resolution (ALOS12) is most suitable to assess erosion potential, due to better fit of slope-dependent PIm. Applications based on the global characteristics of middle to large-sized basins rely on a more flexible choice, as geometry parameters are unaffected by resolution and threshold.

The Role of Green Roofs in Climate Change Mitigation and Adaptation

Fri, 13 Jun 2025 00:00:00 +0200

This study evaluated the water storage and runoff capacities of an extensive green roof simulator in Bahía Blanca, Argentina, during the region's most extreme precipitation event in 47 years. The analysis involved a time series of daily precipitation from 1961 to 2022. A Green Roof model was applied using daily precipitation data, potential evapotranspiration, and field-measured water storage capacity data from 2022. The model was based on a 1 m² green roof simulator, with 50 % of its surface covered by native species. The substrate depth was set at 15 cm, with a soil water storage capacity of 58.7 mm. Precipitation in Bahía Blanca showed considerable variability across temporal scales. The most frequent events (89 %) involved less than 20 mm of rainfall, followed by events between 20.1 mm and 40 mm (8 %). Eight events with precipitation between 80.1 mm and 100 mm were recorded, with March 24, 2022, marking the highest daily rainfall in 15 years (90.3 mm). However, when examining three-day accumulated rainfall, the period from March 23 to 25, 2022, accumulated 150.3 mm, making it the most extreme event in the last 47 years and the second highest in the 62 years analyzed. During this event, total runoff amounted to 83.4 mm, indicating a substantial water storage of 44.6 % by the green roof simulator. Given the projected increase in the frequency and intensity of extreme rainfall events, green roofs offer a sustainable and innovative solution for mitigating and adapting to climate change impacts. Additionally, they serve as crucial urban green infrastructures for managing runoff, particularly in regions prone to intense precipitation events like Bahía Blanca.

Assessing the Design and Management of Protected Areas

Marco Navarro, Melina Paredes, Miguel Pezo, Eduardo Oyague — Fri, 20 Jun 2025 00:00:00 +0200

Coastal desert ecosystems, such as the Lomas and Tillandsiales, are essential for the well-being of local populations, providing vital ecosystem goods and services, including climate regulation and water supply. These ecosystems are nationally recognized as important conservation targets. However, the Lomas and Tillandsiales in Tacna have been adversely affected and ecologically degraded due to uncontrolled population growth and inadequate regulation of human activities, such as agriculture, mining, and livestock grazing. Therefore, it is crucial to implement effective conservation strategies. Despite this need, when governmental entities delineate territories for potential protected areas, existing land use is often prioritized, leading to the exclusion of areas under current use rather than considering geographical criteria or ecological attributes of these vital ecosystems. This practice raises questions about the effectiveness of conservation efforts. To assess the proposed polygons for new protected areas by regional authorities, we compared these with natural ecosystem boundaries using various geographical tools. This comparison revealed substantial differences in geographical, ecological, and landscape metrics, indicating a decrease in ecological similarity and potentially lower effectiveness for conservation. We identified variations in geomorphological and morphometric diversity, with extreme cases showing coefficients of variability of 56% for the Gravelius index, 52% for the altitude index, and 43% for the morphometric protection index. These factors are critical as they strongly correlate with biodiversity, ecological processes, and the provision of ecosystem services, which are the main goals of conservation. Given these discrepancies, the newly proposed conservation area may inadequately fulfill its objectives. Once designated, the authorities should design and implement a management model that prioritizes expanding the protected areas to their natural limits, promoting restoration, and conducting ongoing monitoring of the metrics outlined in this research. Conservation should not merely involve declaring a spatial area as a reserve; it also requires defining these spaces based on tools and geographical knowledge to ensure the adequate protection and conservation of the Lomas and Tillandsiales ecosystems.

Analysis of Climate Change Impacts on Andean Forests Using Potential Distribution Models (2010-2069)

Virginia Alberdi Nieves — Tue, 29 Jul 2025 00:00:00 +0200

In the 21st century, climate change has become the greatest global threat that affects different countries in different ways, affecting different areas, from the increased risk of desertification due to rising temperatures to areas at risk of flooding caused by increased rainfall. Combating climate change has therefore become a priority for many forests in the Andes. In this research, a study was carried out on the possible changes in the forests, as this is one of the regions with the greatest variety of ecosystems and forest formations in the world, analysing the current and future distribution of eight forest formations throughout the study area, by means of potential distribution models, using Maxent software, under three emission scenarios RCP 4.5, RCP 6.0 and RCP 8.5; with projections for the current period 2010-2039 and the future 2040-2069. The results show significant changes in the potential area of distribution of several forests across the different scenarios. Most of the analysed forests will suffer modifications in their current distribution, as is the case of the Lowland Forests and Highland Shrublands of the Humid Puna, which will decrease by more than 60% of their current extent in Bolivia. In the future distribution all the forests analysed will reduce their potential range, such as the Submontane and Dry Montane Forest of the Northern Yungas by 81.6% and the Low Andean Forest of the Western Xerophytic Puna (Peru) by 89.5% in the most restrictive scenario RCP 8.5, which may cause shifts to higher latitudes, with the loss of habitats.

Spatial and Temporal Variability of Extraordinary Precipitations in Spain (1916-2022)

Mon, 30 Jun 2025 00:00:00 +0200

The use of AEMET's documentary archives and the Annual Summary Books has allowed us to create a catalog of extraordinary rainfall events in mainland Spain from 1916 to 2022. During this period, at least 19,184 daily observations of monthly maximum rainfall exceeding 100 mm were recorded, from 4,325 observatories, spread across 4,814 days. Records with more than 200 mm/day amounted to 1,130, spread over 530 days and 664 observatories. The spatial distribution shows that these events can occur anywhere, but there is a clear concentration of both records and dates along the coasts, particularly on the Mediterranean coast for rainfall over 200 mm. In general, extraordinary rainfalls are more frequent in autumn, while summer months have the fewest records and daily events. These events are strongly linked to specific weather patterns. Analyzing them by Hydrological Divisions allows us to differentiate areas influenced by Atlantic advections from those affected by Mediterranean advections. The Ebro Division, due to its size and location, experiences various influences. The region’s topography seems to play a role in determining the spatial extent of extraordinary rainfall events. Overall, the frequency of these events shows no clear trend over time.

Spatio-Temporal Spectral Analysis of High Mountains Wetlands and Their Relationship to Climate Variability

Carolina Calvi, Edoardo Melendi, Eleonora Carol — Wed, 14 May 2025 00:00:00 +0200

The high-altitude wetlands of the Andes in South America are unique ecosystems, characterized by their hyper-humidity and close connection with groundwater discharge or snowmelt. These environments exhibit relatively stagnant waters or low circulation, which favors the proliferation of vegetation that can be monitored through satellite imagery. The objective of this study is to analyze, through the use of remote sensors, the spatiotemporal variation associated with climate cycles in two high-Andean wetlands located in arid environments, where access and working conditions are limited. To achieve this, two case studies were taken: one involving wetlands associated with groundwater discharge, and another supported by river courses with contributions from rainfall and snowmelt.

The areal variation was linked to climate cycles, for which the spectral indices Normalized Difference Vegetation Index (NDVI) and Normalized Difference Water Index (NDWI) were calculated for representative years, selected according to the climate indices Standardized Precipitation-Evapotranspiration Index (SPEI) for dry and wet periods, Oceanic Niño Index (ONI), and data from available meteorological stations for the period 1980-2022. The results showed a variation in the extent of the wetlands between El Niño and La Niña periods. During wet periods (El Niño), the wetlands reached their largest extents, while in dry periods (La Niña), a reduction in wetland area of approximately 30% was quantified. This indicates a rapid hydrological response of the environment to climate changes, associated with contributions from shallow groundwater flow. Consequently, it is likely that in the future, the impact of atmospheric cycles, intensified by climate change, will lead to a critical decrease in the surface area of these wetlands. Monitoring the evolution of high-Andean wetlands in arid conditions is essential to characterize their response to climate cycles. Extrapolating these analyses to other wetlands in similar environments will enable future research on a broader regional scale, facilitating a comprehensive approach to their behavior in the face of climate variations. Understanding these fragile ecosystems is key to implementing effective conservation and management measures, especially in the face of growing pressure from global climate change.

Advancements in High-Resolution Land Use Mapping

Mon, 30 Jun 2025 00:00:00 +0200

Land use and land cover (LULC) mapping is essential for land-based climate change adaptation and mitigation strategies. This study presents the development of 10-meter high-resolution (HR) land use maps within the RethinkAction H2020 project, aimed at enhancing spatial planning for climate mitigation and adaptation. The methodology integrates multi-source remote sensing data, machine learning classification techniques, and auxiliary datasets to generate accurate and transferable land use classifications across six European bioclimatic regions. The study employs Sentinel-2 and Landsat-8 imagery, using supervised classification with Random Forest (RF) and Geographic Object-Based Image Analysis (GEOBIA) to enhance accuracy and minimize spectral confusion. This approach resulted in the creation of twelve HR land use maps at two classification levels, covering six case study (CS) areas. A key contribution of this research is the generation of suitability maps, which assess the potential for implementing land-based mitigation and adaptation solutions (LAMS) such as reforestation, water harvesting, and photovoltaic energy development. This study highlights the importance of integrating remote sensing, machine learning, and spatial analysis to support evidence-based decision-making in land use planning, offering a scalable and replicable methodology for detailed LULC classification.