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The Taiyuan formation limestone water in the Huaibei coalfield is not only the water source for coal mining, but also the water source for industry and agriculture in mining areas. Its hydrogeochemical characteristics and water quality are generally concerning. In this paper, conventional ion tests were carried out on the Taiyuan formation limestone water of 16 coal mines in the Sunan and Linhuan mining areas of the Huaibei coalfield. Piper trigram, Gibbs diagram and an ion scale coefficient map were used to analyze the hydrogeochemical characteristics of the Taiyuan formation limestone water. The water quality was evaluated in a fuzzy comprehensive manner. The results show that the main cation and anion contents in the Taiyuan formation limestone water were Na+ > Mg2+ > Ca2+ > K+, SO42− > HCO3− > Cl−. There were differences in the hydrogeochemical types of the Taiyuan formation limestone water in the two mining areas; HCO3-Na type water was dominant in the Sunan mining area and SO4·Cl-Na type water was dominant in the Linhuan mining area. The chemical composition of the Taiyuan formation limestone water is mainly affected by the weathering of the rock and is related to the dissolution of the evaporated salt and the weathering of the silicate. The fuzzy comprehensive evaluation results show that the V-type water accounts for a large proportion of the Taiyuan formation limestone water in the study area and the water quality is poor. This study provides a basis for the development and utilization of the Taiyuan formation limestone water and water environmental protection in the future.

To study the disparity of river hydrochemical characteristics and water quality in different regions of the city, this paper took the Tuo River in the center of Suzhou, Northern Anhui, China and the Bian River on the edge of the urban area as the research objects, used Piper trigram, Gibbs diagram, and hydrogen and oxygen isotope content characteristics to analyze the geochemical characteristics of surface water in the study area, and then the improved fuzzy comprehensive evaluation method was used to evaluate the water quality. The results showed that the hydrochemical types of the two rivers were SO4-Cl-Na type, and the contents of Na+, K+, SO42−, Cl−, Ca2+, total phosphorus (TP) in the Bian River at the edge of the city were much higher than those in the Tuo River at the center of the city (ANOVA, p < 0.001). Gibbs diagram showed that the ion composition of the two rivers was mainly affected by rock weathering. The results of correlation analysis and water quality evaluation showed that Bian River was greatly affected by agricultural non-point source pollution, and its water quality was poor, class IV and class V water account for 95%, while, for Tuo River, due to the strong artificial protection, class II and class III accounted for 40.74% and 59.26%, respectively, and the overall water quality was better than that of Bian River. The evaluation results of irrigation water quality showed that the samples from Tuo River were high in salt and low in alkali, which could be used for irrigation when the soil leaching conditions were good, while Bian River water samples were high in salt and medium in alkali, which was suitable for irrigation of plants with strong salt tolerance.

Introduction China is rich in coal resources and is the world's largest coal producer and consumer. However, with the development and utilization of coal resources, a large number of wastes, such as coal gangue, mine water and fly ash, will be generated, causing pollution to the surrounding environment of the mining area [1-5]. In particular, under the action of spontaneous combustion, rainwater leaching and wind blowing, the trace heavy metal elements in the coal gangue and fly ash piled in the open air diffuse and migrate to the surrounding environment media, polluting the soil and leading to

With wetlands categorized as one of the three major ecosystems, the study of wetland health has global environmental implications. Multiple regression models were employed to establish relationships between Landsat-8 images, vegetation indices and field measured biomass in the Yellow River Delta Nature Reserve. These models were then used to estimate the spatial distribution of wetland vegetative biomass. The relationships between wetland vegetative biomass and soil factors (organic matter, nitrogen, phosphorus, potassium, water soluble salt, pH and moisture) were modeled. We were able to achieve higher correlations and improved model fits using vegetative indices and spectral bands 1–5 as independent variables. Several important soil factors were isolated, including soil moisture and salt concentrations, which affect wetland biomass spatial distributions. Overall, wetland biomass decreased from land to the ocean and from the river courses outward.