The sediment pollution caused by different metals has attracted a great deal of attention because of the toxicity, persistence, and bio-accumulation. This study focuses on heavy metals in the hyporheic sediment of the Weihe River, China. Contamination levels of metals were examined by using “geo-accumulation index, enrichment factor, and contamination factor” while ecological risk of metals were determined by “potential ecological risk and risk index”. The pollutant accumulation of metals ranked as follows: “manganese (Mn) $>$ chromium (Cr) $>$ zinc (Zn) $>$ copper (Cu) $>$ nickel (Ni) $>$ arsenic (As) $>$ lead (Pb)”. The geo-accumulation index identified arsenic as class 1 (uncontaminated to moderate contamination), whereas Cu, Cr, Ni, Zn, Pb, and Mn were classified as class 0 (uncontaminated). According to the enrichment factor, arsenic originated through anthropogenic activities and Cr, Ni, Cu, Zn, and Pb were mainly controlled by natural sources. The contamination factor elucidated that sediments were moderately polluted by (As, Cr, Cu, Zn, Mn, and Pb), whereas Ni slightly contaminated the sediments of the Weihe River. All metals posed a low ecological risk in the study area. The risk index revealed that contribution of arsenic (53.43 %) was higher than half of the total risk.

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.

Water is a primary element for human life on Earth. Fresh water, which includes rivers, lakes, streams, and ponds, contributes less than one thousandth of a percent of the total water on Earth, but it is critical for the environment and human life. Change in land use and land cover (LULC) is a foremost concern in global environment change. Rapid changes in LULC lead to the degradation of ecosystems and have adverse effects on the environment. There is an urgent need to monitor changes in LULC and evaluate the effects of these changes in order to inform decision makers on how to support sustainable development. This study used Moderate Resolution Imaging Spectroradiometry images to detect and investigate changes in LULC patterns in Gilgit-Baltistan, Pakistan, between 2008 and 2017. Six types of LULC were used to explain the major changes of LULC in the study area. The results showed that there was a reduction of barren lands and an increase of urban areas. It also showed an inconsistent behavior of water bodies during the study. Snow area, which also increased, needs further investigation.