The mining industry is a significant asset to the development of countries. Ghana, Africa’s second-largest gold producer, has benefited from gold mining as the sector generates about 90% of the country’s total exports. Just like all industries, mining is associated with benefits and risks to indigenes and the host environment. Small-scale miners are mostly accused in Ghana of being environmentally disruptive, due to their modes of operations. As a result, this paper seeks to assess the environmental impacts of large-scale gold mining with the Nzema Mines in Ellembelle as a case study. The study employs a double-phase mixed-method approach—a case study approach, consisting of site visitation, key informant interviews, questionnaires, and literature reviews, and the Normalized Difference Vegetation Index (NDVI) analysis method. The NDVI analysis shows that agricultural land reduced by −0.98%, while the bare area increases by 5.21% between the 2008 and 2015 periods. Our results show that forest reserves and bare area were reduced by −4.99% and −29%, respectively, while residential areas increased by 28.17% between 2015 and 2020. Vegetation, land, air, and water quality are highly threatened by large-scale mining in the area. Weak enforcement of mining policies, ineffective stakeholder institution collaborations, and limited community participation in decision-making processes were also noticed during the study. The authors conclude by giving recommendations to help enhance sustainable mining and ensure environmental sustainability in the district and beyond.

Innovative solutions are needed for urban flooding exacerbated by climate change. In light of this, this study developed an integrated framework for urban wetland flood control that combines Morphospatial Pattern Analysis (MSPA), minimum cumulative resistance (MCR) modeling, and complex network theory for optimizing an ecological network of flood control and mitigation wetlands in Changchun, China. The results show that the optimized ecological network significantly improved connectivity and flood mitigation efficiency. The node degree increased from 2.737 to 3.433, and the average clustering coefficient exhibited an increase from 0.074 to 0.231, enhancing material flow efficiency. Robustness analysis revealed that the optimized network’s connectivity robustness improved by 12.6%, 18.4%, and 24.1% under random, malicious, and controlled attack scenarios, respectively. Additionally, ecological corridors with a width of 30–50 m were identified as the optimal range for water conveyance potential, effectively dispersing peak runoff and reducing flood risk. This study provides both a transferable methodology for flood-resilient planning and specific policy actions, including priority conservation of high-betweenness nodes and restoration of fragmented wetlands, offering practical solutions for high-density cities facing similar climate challenges.