Centuries of cultivation in the Highland Aynoka of Puno, Peru, have endowed indigenous crops such as potato and quinoa with rich cultural and nutritional value deeply ingrained in local traditions. This study meticulously evaluates their economic viability, environmental implications, and cultural importance by employing a mixed-methods research approach involving surveys, interviews, and observations. The outcome reveals that while the Economic Sustainability Index (EKI) moderately supports potato and quinoa production sustainability, with a value of 2.98, it falls short of significant impact. Conversely, the Environmental Sustainability Index (ESI) and the Social Sustainability Index (SSI) exhibit moderate levels of sustainability, recording values of 4.04 and 3.38 for ESI and SSI, respectively. These crops demonstrate acceptable economic feasibility, marked by consistent sales, income generation, and manageable production expenses. The findings underscore the urgency of endorsing sustainable farming methods to safeguard cultural heritage, boost market prospects, and fortify regional ecological robustness. Rooted in ancestral sustainability, potato and quinoa cultivation is a cornerstone in local food systems. Recognizing the cultural, economic, and environmental significance inherent to these crops, efforts can be channeled towards nurturing sustainable agricultural systems that uphold community well-being, conserve biodiversity, and facilitate cultural resilience in Puno’s Highland Aynoka.

Effects of climate change have led to a reduction in precipitation and an increase in temperature across several areas of the world. This has resulted in a sharp decline of glaciers and an increase in surface runoff in watersheds due to snowmelt. This situation requires a better understanding to improve the management of water resources in settled areas downstream of glaciers. In this study, the snowmelt runoff model (SRM) was applied in combination with snow-covered area information (SCA), precipitation, and temperature climatic data to model snowmelt runoff in the Santa River sub-basin (Peru). The procedure consisted of calibrating and validating the SRM model for 2005–2009 using the SRTM digital elevation model (DEM), observed temperature, precipitation and SAC data. Then, the SRM was applied to project future runoff in the sub-basin under the climate change scenarios RCP 4.5 and RCP 8.5. SRM patterns show consistent results; runoff decreases in the summer months and increases the rest of the year. The runoff projection under climate change scenarios shows a substantial increase from January to May, reporting the highest increases in March and April, and the lowest records from June to August. The SRM demonstrated consistent projections for the simulation of historical flows in tropical Andean glaciers.

Soil organic carbon (SOC) is a crucial component of the planet and is essential for agriculture development. Our region is known for its livestock and agricultural activities. Hence, understanding the spatial distribution of SOC is crucial for sustainable land management of soils in the mountain ecosystems in the Andes. The methodology consisted of obtaining 53 soil samples from depths of 0 to 105 cm, which were analyzed to obtain SOC (Kg/m²) and organic matter (OM) (%). Ordinary kriging, a geostatistical method, was used to determine SOC. Pearson’s statistical method was applied to determine the association between SOC and precipitation, temperature, altitude, and organic matter and gave acceptable correlations of 0.38, −0.32, 0.40, and 0.59. These results were used to apply weighting criteria for climatological and environmental variables. The weighted overlay tool was used for modeling and mapping the spatial variability of SOC. The estimated spatial distribution of SOC in the micro-watershed reveals an increasing trend from south to north, specifically within the 0–20 cm depth profile. The study confirmed through the spatial analysis that regions with intensive agriculture have low reserves (<3 Kg/m²) of SOC, and areas without agricultural activity but with grazing have average resources of 3 Kg/m² to 5 Kg/m² of SOC. Finally, in the upper micro-watersheds where there is no agricultural activity, the reserves are high (5 Kg/m² to 6.8 Kg/m²). Accordingly, we can promote sustainable and responsible land use practices that support long-term productivity, environmental protection, and societal well-being by prioritizing efficient land utilization, soil conservation, biodiversity conservation, land restoration, and informed land use planning in the high Andean ecosystem of Puno–Peru.

The retreats of the planet’s tropical glaciers are natural indicators of the variation of precipitation, temperature, and other variables. The glaciers of the Alto Santa sub-basin are sources of freshwater storage for consumptive and non-consumptive use for different sectors. As a result of climatic variations, it is essential to analyze the dynamics of the snow cover area (SCA). The methodology consisted of processing 6578 MODIS Snow Cover MOD10A1 product images and generating 18-year time series using the Platform Google Earth Engine (GEE). Normalized Difference Snow Index (NDSI) was used to estimate the extent of snow cover, and to validate the MODIS snow cover product, we used the same overlapping date of Landsat 5 and 8 Surface Reflectance Tier 1, to examine the relationships between daily precipitation and temperature. The standardized correlation results gave good results with stations over 4500 m.a.s.l., such as Artesonraju AP2 (4828 m.a.s.l.) of −0.84 and −0.74, precipitation, and temperature. These results show coherent behaviors of the retreat due to the variation of the climatological variables. In some years, there were anomalies in the conduct of the three variables, but these originated from events of natural weather phenomena. Regarding the dynamics of the SCA in 18 years, it decreased from 649 km² to 311.6. km² between 2000 and 2017, representing a retreat of 41%; we can conclude and confirm that the glacier retreat is imminent due to the consequences of climate change, which would affect the security of freshwater from the tropical glaciers of the Peruvian Andes.

Ensuring global food security and adapting to the challenges posed by climate change, particularly in rainfed agriculture, are paramount concerns. This research investigates the impacts of climate change on the yield of the potato crop variety Imilla Negra (Solanum tuberosum spp.) under the extreme climatic conditions of the Peruvian Altiplano. From the experimentation in six crop plots under a rainfed agricultural system, periodic crop growth parameter measurements were obtained from 2017 to 2018. The results showed a good performance of the AquaCrop model in the calibration and validation, successfully simulating crop growth and yield parameters. Climate projections showed precipitation decreases and temperature and evapotranspiration increases for the representative concentration pathway (RCP), RCP 4.5, and RCP 8.5 scenarios in 2023–2050. A comparison of crop yields between the base period (2006–2021) and the period 2023–2037 showed no significant changes, whereas a more considerable decrease was observed for the period 2038–2050. It is concluded that climate change generates moderate impacts on potato crop yields under the rainfed agricultural system in the Peruvian Altiplano due to the average reduction in precipitation.