Sustainable solutions for water scarcity: rehabilitating abandoned coal mine pit lakes through limnological analysis of freshwater resources in mining-affected regions
摘要
The escalating global water crisis necessitates the exploration of non-traditional water sources, particularly in mining-intensive regions that suffer from severe contamination due to mining and industrial activities. This study evaluates the Water Quality Index (WQI) of groundwater (GW), river water (RW), and abandoned coal mine pit lakes (PLs) across seven operational areas of Eastern Coalfields Limited (ECL) within the Raniganj Coalfields (RCF) of Paschim Bardhaman, West Bengal, India, during the period 2022–2024. Limnological assessments revealed that both RW and several PLs are heavily polluted by mining and industrial effluents, rendering them unsuitable for anthropogenic use. Despite this, PLs hold significant potential as alternative water sources, collectively storing approximately 0.4 billion m3 of water. To assess the potential for sustainable reclamation, the phytoremediation capabilities of Ipomoea aquatica Forsk. were tested in situ over a 90-day period. The results indicated notable improvements in PL water quality post-phytoremediation, including a substantial increase in dissolved oxygen (DO) levels, which positively impacted WQI scores across multiple sites. Principal Component Analysis (PCA) confirmed both the detrimental impact of mining on water quality and the effectiveness of phytoremediation. Additionally, Geographic Information System (GIS) mapping facilitated the visualization of pollution levels and water resource potential across the region. This study demonstrates that phytoremediation offers a viable, cost-effective, and sustainable water management strategy for rehabilitating coal mine PLs. It aligns with the objectives of the United Nations Sustainable Development Goals (SDGs). However, successful implementation and long-term scalability require addressing several interlinked challenges—technological, economic, social, policy-related, ecological, and data-driven.