Wildfire is a major concern worldwide and particularly in Australia. The 2019–2020 wildfires in Australia became historically significant as they were widespread and extremely severe. Linking climate and vegetation settings to wildfires can provide insightful information for wildfire prediction, and help better understand wildfires behavior in the future. The goal of this research was to examine the relationship between the recent wildfires, various hydroclimatological variables, and satellite-retrieved vegetation indices. The analyses performed here show the uniqueness of the 2019–2020 wildfires. The near-surface air temperature from December 2019 to February 2020 was about 1 °C higher than the 20-year mean, which increased the evaporative demand. The lack of precipitation before the wildfires, due to an enhanced high-pressure system over southeast Australia, prevented the soil from having enough moisture to supply the demand, and set the stage for a large amount of dry fuel that highly favored the spread of the fires.

Several studies have focused on why the Aculeo Lagoon in central Chile disappeared, with a recent one concluding that a lack of precipitation was the main cause, bringing tremendous political consequences as it supported the argument that the government is not responsible for this environmental, economic, and social disaster. In this study, we evaluated in detail the socio-economic history of the watershed, the past climate and its effects on the lagoon’s water levels (including precipitation recycling effects), anthropogenic modifications to the lagoon’s water balance, the evolution of water rights and demands, and inaccurate estimates of sustainable groundwater extraction volumes from regional aquifers. This analysis has revealed novel and undisputable evidence that this natural body of water disappeared primarily because of anthropogenic factors (mostly river deviations and aquifer pumping) that, combined with the effects of less than a decade with below-normal precipitation, had a severe impact on this natural lagoon–aquifer system.

Access to accurate spatio-temporal groundwater level data is crucial for sustainable water management in Chile. Despite this importance, a lack of unified, quality-controlled datasets have hindered large-scale groundwater studies. Our objective was to establish a comprehensive, reliable nationwide groundwater dataset. We curated over 120,000 records from 640 wells, spanning 1970-2021, provided by the General Water Resources Directorate. One notable enhancement to our dataset is the incorporation of elevation data. This addition allows for a more comprehensive estimation of groundwater elevation. Rigorous data quality analysis was executed through a classification scheme applied to raw groundwater level records. This resource is invaluable for researchers, decision-makers, and stakeholders, offering insights into groundwater trends to support informed, sustainable water management. Our study bridges a crucial gap by providing a dependable dataset for expansive studies, aiding water management strategies in Chile.

This study leverages a Random Forest model to predict flood hazard in Arizona, New Mexico, Colorado, and Utah, focusing on enhancing sustainability in flood management. Utilizing the National Flood Hazard Layer (NFHL), an intricate flood map of Arizona was generated, with the Random Forest Classification algorithm assessing flood hazard for each grid cell. Weather variable predictions from TerraClimate were integrated with NFHL classifications and Digital Elevation Model (DEM) analyses, providing a comprehensive understanding of flood dynamics. The research highlights the model’s capability to predict flood hazard in areas lacking NFHL classifications, thereby supporting sustainable flood management by elucidating weather’s influence on flood hazard. This approach aligns with sustainable development goals by aiding in resilient infrastructure design and informed urban planning, reducing the impact of floods on communities. Despite recognizing constraints such as input data precision and the model’s potential limitations in capturing complex variable interactions, the methodology offers a robust framework for flood hazard evaluation in other regions. Integrating diverse data sources, this study presents a valuable tool for decision-makers, supporting sustainable practices, and enhancing the resilience of vulnerable regions against flood hazards. This integrated approach underscores the potential of advanced modeling techniques in promoting sustainability in environmental hazard management.

The Aculeo lagoon basin is facing a severe drought, resulting in a restriction of water usage solely for domestic purposes, and legal sanctions for those who use water for grass irrigation. To identify illegal use of water resources, this project evaluates the health of lawns during a dry season, using multi-spectral and multitemporal satellite data. Soil indices, including NDVI, EVI, GNDVI, SAVI, NDMI, MSI, and BSI, were derived between October 2021 and April 2022. Cluster analysis was performed to evaluate the statistical distribution of healthy vegetation cover, with results available on an ArcGIS web map. The study estimates the areas and corresponding water consumption of lawns in the basin, identifying properties that have used water illegally. The cluster analysis also indicates an unusual pattern of healthy vegetation cover, suggesting that these areas may be responsible for the illegal use of water resources. The study presents tools and protocols for identifying illegal water usage in areas facing water scarcity, providing crucial information for governmental authorities to enforce legal sanctions and undertake personal inspections. Overall, the study provides an effective approach to monitoring and enforcing water usage restrictions in water-scarce areas.

Glaciers worldwide are in retreat, and their meltwater can modulate mountain aquifers. We examined whether mass loss of the Juncal Norte Glacier (central Chile) has affected groundwater storage in the Juncal River basin between 1990 and 2022. Recession-curve modeling of daily streamflow shows no statistically significant trend in basin-scale groundwater reserves (τ = 0.06, p > 0.05). In contrast, glacier volume declined significantly (−3.8 hm³/yr, p < 0.05), and precipitation at the nearby Riecillos station fell sharply during the 2008–2017 megadrought (p < 0.05) but exhibited no significant change beforehand. Given the simultaneous decreases in meteoric inputs (rain + snow) and glacier mass, one would expect groundwater storage to decline; its observed stability therefore suggests that enhanced glacier-melt recharge may be temporarily offsetting drier conditions. Isotopic evidence from comparable Andean catchments supports such glacio-groundwater coupling, although time lags of months to years complicate detection with recession models alone. Hence, while our results do not yet demonstrate a direct glacier–groundwater link, they are consistent with the hypothesis that ongoing ice loss is buffering aquifer storage. Longer records and tracer studies are required to verify this mechanism and to inform sustainable water resources planning.