Globally, natural hazards have become more destructive in recent times because of rapid urban development and exposure. Consequently, significant human life loss, the damage to property and infrastructure, and the collapse of the environment directed the attention of geoscientists to control the consequences and risk management in relation to geo-hazards. In this research, an effort was made to produce a compound map, geo-visualizing the susceptibility of multi-hazards, to select suitable sites for sustainable future development and other economic activities in the region. Muzaffarabad District was chosen as a case research area due to the high magnitude of hydro-meteorological and geological hazards. On the one hand, both selected geo-hazard inventories were developed using the field survey and remote sensing data. The subjective and objective weight of all the causative factors and their classes were calculated using the assembled geospatial techniques, such as the Analytical Hierarchy Process (AHP) and Frequency Ratio (FR) in the Geographic Information System (GIS). The results reveal that the most suitable areas are distributed in the southern and northwestern parts, which can be used for future sustainable development and other economic activities. In contrast, the eastern and western regions, including Muzaffarabad City, are within high and very susceptibility zones. Finally, more than 50% of the land area is located in very low and low susceptibility zones. The validation of the proposed model was checked by using three different techniques: the Receiver Operative Characteristic (ROC) curve, Seed Cell Area Index (SCAI), and Frequency Ratio (FR). Both ROCs, the Success Rate Curve (SRC) and the Predictive Rate Curve (PRC), showed the goodness of fit for both the selected geo-hazards: landslides (81.3%) and floods (93.2%), at 80.1% and 91.7%, respectively. All the validation techniques showed good fitness for both the individual and multi-hazard maps. The proposed model sets a baseline for policy implementation for all the stakeholders to minimize the risk and sustainable future development in areas of high frequent geo-hazards.

The history of forest cover dynamics in Pakistan reveals an unsatisfactory environmental situation. In the past 5 decades, particularly during the period between 1990 and 2010, the country lost an average of 41,100 hectares of green cover with a deforestation rate of 1.6% per year. The factors behind that this high deforestation rate is numerous including socio-economic transformation after the major political change during the 1970s in the mountainous areas of Pakistan, demographic changes, accessibility improvements, and land use changes. Several social forestry campaigns have been launched over time to cope with this socioecological and environmental issue. However, most of them have not been very effective due to certain shortcomings. This study aims to evaluate the effectiveness of the most recent and history’s biggest forest restoration program initiated by the government of the Khyber Pakhtunkhwa Province called the Billion Trees Tsunami Afforestation Project (BTTAP). This project was announced in 2013 when a new political party, Pakistan Tehreek-e-Insaf, came into power. The study is focused on one of the main forest hubs of the country in the Hindukush Mountains spanning five districts. Forest cover in this study area decreased from 20 to 2% between 1990 and 2010. After the launch of the BTTAP, the forest cover increased considerably from 2 to 35% by the year 2021. This growth was achieved through planting new trees, banning forest cutting, practicing surveillance, and enhancing community participation. If the project continues and the protection measures are not suspended, it can play a historical role in forest restoration.

Mountain communities globally are experiencing increasing challenges as climate-induced glacier changes disrupt water resources and agricultural systems. The Hindukush-Karakoram-Himalayan region of Pakistan has been witnessing environmental changes over the last few decades with widespread impacts on different sectors of life. In the Shigar Valley of the Karakoram region, communities face socio-economic challenges partly attributed to changes in glacier dynamics, which directly affect water availability and agricultural productivity. This study investigates the impacts of glacial changes on community livelihoods by integrating glacier modeling with a comprehensive socioeconomic survey. Glaciological change was analyzed from 1970 to 2020 using the Open Global Glacier Model, with projections under SSP-126, SSP-370, and SSP-585 scenarios for 2020–2100. Glacier mass balance simulations driven by historical climatological data from 1970 to 2020 reveal an overall negative trend, despite shorter periods of glacier growth driven by regional hydroclimatic anomalies. Future projections indicate glacier volume could decline by over 60% under SSP-585 by 2100, compared to approximately 30% under SSP-126. A questionnaire survey was conducted across 20 villages, engaging 375 respondents to understand the extent of dependence on glacier-fed resources, migration dynamics, and adaptive strategies to socioenvironmental conditions. The findings reveal that while 42% of respondents reported high dependence on glacier-fed and snow melt, 46% are facing challenges due to irregular water supplies. These challenges have been affecting the socio-economic fabric of the community as 71% of respondents reported that migrations were driven by declining local productivity, with 66% of migration destinations being international. The communities are aware of the challenges, and they have been adopting various strategies to cope with it. These include rainfed farming (32%), adoption of drought-resistant crops (19%), and expansion into proglacial (recently deglaciated areas and areas closer to glaciers’ termini) lands (52%).

The Hindukush-Himalayan (HKH) region, known for its eco-environmental importance, has been witnessing transformations in recent years governed by factors such as climate variability, land use shifts, and population growth. These changes have profound implications for regional sustainability, water resources, and livelihood. This study attempts to explore the spatial and temporal variability in selected environmental parameters including land surface temperature (LST), normalized difference vegetation index (NDVI), precipitation patterns, and normalized difference snow index (NDSI), and land use land cover (LULC) from 1990 to 2022 using Landsat imageries (30 m spatial resolution), CHIRPS precipitation data at 0.05° spatial resolution. The study area spans 32,000 km² covering two major political/administrative divisions (Malakand and Hazara) in the HKH region of Pakistan. The study area was selected primarily because of the unprecedented changes over the last three decades. For detailed spatial analysis, the area was divided into five elevation zones and LST, NDVI, NDSI, and LULC analyses were conducted utilizing primarily the Google Earth Engine (GEE) platform and climate engine. The study results revealed a notable rise in LST in the lowest elevation zone. The NDVI and LULC analyses revealed a noticeable decline in vegetation cover from 5988 km² in 1990, to 4225 km² by 2010, followed by a growth to 7669 km² in 2022, since 2010 after the launching of the Billion Tree Tsunami Afforestation Project (BTTAP) in 2013. Likewise, the precipitation patterns exhibit transitioning from low to high precipitation levels. However, the most notable finding of the study is the marked decline in snow covered area 7000 km² to 3800 km² between 1990 and 2022.