Quantifying leachate discharge and assessing environmental risks of gully-type coal-based solid waste dumps in small watersheds: A refined hydrological modeling approach for mitigation strategies

IF 11.4 1区环境科学与生态学 Q1 ENGINEERING, ENVIRONMENTAL

Water Research Pub Date : 2025-04-16 DOI:10.1016/j.watres.2025.123655

Xiaofei Wang , Chaoli Zhao , Guowei Huang , Hu Liu , Xiaofang Zhu , Jiu Huang

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Abstract

Rainfall-induced leaching from extensive coal-based solid waste storage results in a long-term risk to watershed's water quality and safety. The leachate carries heavy metals and other contaminants, which migrate and accumulate through the watershed, leading to a persistent deterioration of downstream water environment. However, the lack of systematic research on the release, accumulation, and spatial-scale migration dynamics of leachate limits effective management of diffused leachate pollutions. This study presents a novel cross-scale coupling framework which integrates multi-source remote sensing data with Soil and Water Assessment Tool (SWAT) model, employing a strategy that transfers parameters from large basins to accurately quantify the hydrological processes in coal waste sub-basins. Additionally, a comprehensive analysis is performed on the hydrological characteristics, leachate generation, and watershed migration dynamics in gangue dump sub-watersheds, providing a new methodological framework for managing mining-related leachate pollution. The large basin model demonstrated strong performance (R² = 0.79, NSE = 0.66 for calibration; R² = 0.74, NSE = 0.59 for verification), while the sub-basin model exhibited excellent accuracy (R² = 0.94, NSE = 0.92 for calibration; R² = 0.81, NSE = 0.77 for verification). High-resolution drone data estimated the annual leachate production to be 3366.87 m³. Simulations revealed that leachate migration peaks in the summer months (July to September), significantly increasing downstream pollution risks. Risk assessments indicate that vegetation in land restoration areas reduces leachate production and migration via evapotranspiration and other processes. This study provides an adaptable methodological framework for managing mining-related leachate pollution and highlights the critical importance of optimal reclamation strategies for mitigating pollution and restoring degraded landscapes.

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小流域沟型煤基固体废物填埋场渗滤液排放量化与环境风险评估：一种用于缓解策略的精细水文建模方法

广泛的煤基固体废物储存导致的降雨淋滤对流域水质和安全造成长期风险。渗滤液中含有重金属和其他污染物，这些污染物通过流域迁移和积累，导致下游水环境持续恶化。然而，由于缺乏对渗滤液释放、积累和空间尺度迁移动态的系统研究，限制了对弥漫性渗滤液污染的有效管理。本研究提出了一种新的跨尺度耦合框架，该框架将多源遥感数据与水土评价工具（SWAT）模型相结合，采用从大流域转移参数的策略来准确量化煤矸子流域的水文过程。此外，本文还对矸石排土场流域的水文特征、渗滤液生成和流域迁移动态进行了综合分析，为管理采矿相关渗滤液污染提供了新的方法框架。大流域模型具有较强的标定性能（R² = 0.79,NSE = 0.66）；R² = 0.74,NSE = 0.59进行验证)，子盆地模型具有较好的精度(R² = 0.94,NSE = 0.92进行定标；R² = 0.81,NSE = 0.77进行验证)。高分辨率无人机数据估计每年的渗滤液产量为3366.87 m³。模拟结果表明，夏季（7 - 9月）为渗滤液迁移高峰，显著增加了下游污染风险。风险评估表明，土地恢复区的植被通过蒸散和其他过程减少了渗滤液的产生和迁移，其中作物最有效，其次是草本植物和灌木。这项研究为管理与采矿有关的渗滤液污染提供了一个适应性的方法框架，并强调了最佳开垦战略对减轻污染和恢复退化景观的重要性。

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来源期刊

Water Research 环境科学-工程：环境

CiteScore

20.80

自引率

9.40%

发文量

1307

审稿时长

38 days

期刊介绍： Water Research, along with its open access companion journal Water Research X, serves as a platform for publishing original research papers covering various aspects of the science and technology related to the anthropogenic water cycle, water quality, and its management worldwide. The audience targeted by the journal comprises biologists, chemical engineers, chemists, civil engineers, environmental engineers, limnologists, and microbiologists. The scope of the journal include: •Treatment processes for water and wastewaters (municipal, agricultural, industrial, and on-site treatment), including resource recovery and residuals management; •Urban hydrology including sewer systems, stormwater management, and green infrastructure; •Drinking water treatment and distribution; •Potable and non-potable water reuse; •Sanitation, public health, and risk assessment; •Anaerobic digestion, solid and hazardous waste management, including source characterization and the effects and control of leachates and gaseous emissions; •Contaminants (chemical, microbial, anthropogenic particles such as nanoparticles or microplastics) and related water quality sensing, monitoring, fate, and assessment; •Anthropogenic impacts on inland, tidal, coastal and urban waters, focusing on surface and ground waters, and point and non-point sources of pollution; •Environmental restoration, linked to surface water, groundwater and groundwater remediation; •Analysis of the interfaces between sediments and water, and between water and atmosphere, focusing specifically on anthropogenic impacts; •Mathematical modelling, systems analysis, machine learning, and beneficial use of big data related to the anthropogenic water cycle; •Socio-economic, policy, and regulations studies.