Groundwater constitutes a vital resource for public water supply, and thus, it is imperative to recognize the areas of highest potential for increasing availability. The present study employs the MaxEnt model to discern the most favorable areas for locating high -yield wells in Caxias do Sul, Rio Grande do Sul, southern Brazil, where the Serra Geral Aquifer System, a fractured volcanic aquifer, emerges. This aquifer system is characterized by its heterogeneous, discontinuous, and highly anisotropic nature. A dataset comprising 83 wells with high flow rates (>= 10 m3/h) was selected from the municipal registry of deep tubular wells, along with 14 factors that influence groundwater occurrence (specific capacity, transmissivity, altitude, slope, horizontal curvature, vertical curvature, relief dis index, drainage density, distance to drainage, topographic wetness index, distance to lineament, lineament density, precipitation, and soil hydrological group). The model output was a Groundwater Potential Map, which stochastically expresses the probability of obtaining flow rates >= 10 m3/h. The map was validated through cross -validation, resulting in an average accuracy of 65.14%, and by the Receiver Operating Characteristic analysis, resulting in an Area Under the Curve value of 0.911, indicating satisfactory validation. While the MaxEnt model is widely used in ecology to model species distribution, its application in groundwater prediction remains limited, particularly in fractured aquifers associated with volcanic rocks. Apart from optimizing the use of groundwater resources, this study also enhances the understanding of natural phenomena in this type of aquifer.

High-resolution permafrost mapping is an important direction in permafrost research. Arxan is a typical area with permafrost degradation and is situated on the southern boundary of the permafrost region in Northeast China. With the help of Google Earth Engine (GEE), the maximum entropy classifier (MaxEnt) is used for permafrost mapping using the land surface temperature (LST) of different seasons, deviation from mean elevation (DEV), solar radiation (SR), normalized difference vegetation index (NDVI), and normalized difference water index (NDWI) as the characteristic variables. The prior data of permafrost distribution were primarily based on 201 borehole data and field investigation data. A permafrost probability (PP) distribution map with a resolution of 30 m was obtained. The receiver operating characteristic (ROC) curve was used to test the distribution results, with an area under the curve (AUC) value of 0.986. The results characterize the distribution of permafrost at a high resolution. Permafrost is mainly distributed in the Greater Khingan Mountains (GKM) in the research area, which run from the northeast to the southwest, followed by low-altitude area in the northwest. According to topographic distribution, permafrost is primarily found on slope surfaces, with minor amounts present in peaks, ridges, and valleys. The employed PP distribution mapping method offers a suggestion for high-resolution permafrost mapping in permafrost degradation areas.