An interdisciplinary field investigation of historic glacial lake outburst floods (GLOFs) in the Kanchenjunga region of Nepal was conducted between April and May, 2019. Oral history and field measurements suggested that at least six major GLOFs have occurred in the region since 1921. A remote sensing analysis confirmed the occurrence of the six GLOFs mentioned by informants, including two smaller flood events not mentioned that had occurred at some point before 1962. A numerical simulation of the Nangama GLOF suggested that it was triggered by an ice/debris avalanche of some 800,000 m³ of material, causing a surge wave that breached the terminal moraine and released an estimated 11.2 × 10⁶ m³ ± 1.4 × 10⁶ m³ of water. Debris from the flood dammed the Pabuk Khola river 2 km below the lake to form what is today known as Chheche Pokhari lake. Some concern has been expressed for the possibility of a second GLOF from Nangama as the result of continued and growing landslide activity from its right lateral moraine. Regular monitoring of all lakes and glaciers is recommended to avoid and/or mitigate the occurrence of future GLOF events in the region. Collectively, the paper demonstrates the benefits and utility of interdisciplinary research approaches to achieving a better understanding of past and poorly documented GLOF events in remote, data-scarce high mountain environments.

Several supraglacial ponds are developing and increasing in size and number in the Himalayan region. They are the precursors of large glacial lakes and may become potential for glacial lake outburst floods (GLOFs). Recently, GLOF events originating from supraglacial ponds were recorded; however, the spatial, temporal, and seasonal distributions of these ponds are not well documented. We chose 23 debris-covered glaciers in the Everest region, Nepal, to study the development of supraglacial ponds. We used historical Landsat images (30-m resolution) from 1989 to 2017, and Sentinel-2 (10-m resolution) images from 2016 to 2018 to understand the long-term development and seasonal variations of these ponds. We also used fine-resolution (0.5–2 m) WorldView and GeoEye imageries to reveal the high-resolution inventory of these features and these images were also used as references for accuracy assessments. We observed a continuous increase in the area and number of ponds from 1989–2017, with minor fluctuations. Similarly, seasonal variations were observed at the highest ponded area in the pre- and postmonsoon seasons, and lowest ponded area in the winter season. Substantial variations of the ponds were also observed among glaciers corresponding to their size, slope, width, moraine height, and elevation. The persistency and densities of the ponds with sizes >0.005 km² were found near the glacier terminuses. Furthermore, spillway lakes on the Ngozompa, Bhote Koshi, Khumbu, and Lumsamba glaciers were expanding at a faster rate, indicating a trajectory towards large lake development. Our analysis also found that Sentinel-2 (10-m resolution) has good potential to study the seasonal changes of supraglacial ponds, while fine-resolution (<2 m) imagery is able to map the supraglacial ponds with high accuracy and can help in understanding the surrounding morphology of the glacier.

Understanding vegetation disturbance around protected areas (PAs) is critical as it significantly affects the sustainable conservation of wildlife. However, there is a lack of analyses of consistent long-term data on vegetation disturbance. In this study, the LandTrendr algorithm and Google Earth Engine were used to access satellite data and explore the vegetation dynamics history across the Ruaha–Rungwa landscape, Tanzania. We characterized vegetation disturbance patterns and change attributes, including disturbance occurrence trends, rate, and severity, by using each pixel’s normalized burn ratio index time series. Between 2000 and 2019, 36% of the vegetation was significantly disturbed by anthropogenic activities. The results of this study show that the disturbance trends, severity, and patterns are highly variable and strongly depend on the management approaches implemented in the heterogeneous landscape: Ruaha National Park (RNP), Rungwa–Kizigo–Muhesi Game Reserves (RKMGR), and the surrounding zones. The disturbance rates and severity were pronounced and increased toward the edges of the western RKMGR. However, the disturbance in the areas surrounding the RNP was lower. The characterization of the vegetation disturbance over time provides spatial information that is necessary for policy makers, managers, and conservationists to understand the ongoing long-term changes in large PAs.

Land use land cover (LULC) changes resulting from copper exploration in Kitwe District, Copperbelt Province has adversely impacted the environment. To understand LULC change dynamics associated with mining activities, this study mapped LULC changes using the Google Earth Engine (GEE) from 1990 to 2020. In addition, the Zambian legal framework for mine closure was assessed in terms of adequacy and comprehensiveness. A remote sensing analysis using Landsat TM (1990, 2000, and 2010) and OLI (2020) images was performed and the GEE Random Forest classifier algorithm was employed to detect LULC changes. Then, transition matrices and overall changes were calculated for each LULC class. The LULC classification had an overall accuracy and kappa coefficient of 82.47% and 0.78, respectively. In total, 45.2% of the district area (360.92 km²) experienced LULC changes from 1990 to 2020. The overall change indicates that the areas of built-up area, bare land, and grassland/pasture/agricultural land gained 35.84, 14.67, and 43.53 km², respectively, while forest lost 95.30 km², with the major driver being the privatization of mining companies. Several concerns regarding the mine closure process practiced in Zambia have principally been raised to the government. Although the legislation generally conformed to international best practices, a gap involving various pieces of legislation, overlapping requirements, and different interpretations of the laws by different governmental departments makes the system complex and unmanageable. An area of concern is the government’s capability and competence to implement legislation. Ineffective law enforcement, that is, the inadequacy of the legislation, is to blame for LULC changes in mining areas, resulting in mining corporations not paying attention to the changes made, particularly regarding mine closures. This study provides decision-makers and land use planners with baseline knowledge on LULC changes that can be valuable for future mining legislation and how these legislations can be effectively executed to ensure sustainable mine closure.

The study of spatiotemporal variation in temperature is vital to assess changes in climate, especially in the Himalayan region, where the livelihoods of billions of people living downstream depends on water coming from the melting of snow and glacier ice. To this end, temperature trend analysis is carried out in the Narayani River basin, a major river basin of Nepal, characterized by three climatic regions: tropical, subtropical and alpine. Temperature data from six stations located within the basin were analyzed. The elevation of these stations ranges from 460 to 3800 m a.s.l. and the time period of available temperature data ranges from 1960–2015. Multiple regression and empirical mode decomposition (EMD) methods were applied to fill in missing data and to detect trends. Annual as well as seasonal trends were analyzed and a Mann–Kendall test was employed to test the statistical significance of detected trends. The results indicate significant cooling trends before 1970s, and warming trends after 1970s in the majority of the stations. The warming trends range from 0.028 to 0.035 ${}^{°}$C year${}^{-1}$ with a mean increasing trend of 0.03 ${}^{°}$C year${}^{-1}$ after 1971. Seasonal trends show the highest warming trends in the monsoon season, followed by winter and the premonsoon and postmonsoon season. However, the difference in warming rates between different seasons was not significant. An average temperature lapse rate of −0.006 ${}^{°}$C m${}^{-1}$ with the steepest value (−0.0064 ${}^{°}$C m${}^{-1}$) in the premonsoon season and the least negative (−0.0052 ${}^{°}$C m${}^{-1}$) in the winter season was observed for this basin. A comparative analysis of the gap-filled data with freely available global climate dataset show reasonable correlation, thus confirming the suitability of the gap filling methods.