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Erschienen in: Environmental Earth Sciences 10/2020

01.05.2020 | Original Article

Prediction model of water yield property based on GRA, FAHP and TOPSIS methods for Ordovician top aquifer in the Xinwen coalfield of China

verfasst von: Mei Qiu, Fengjun Huang, Ying Wang, Tao Guan, Longqing Shi, Jin Han

Erschienen in: Environmental Earth Sciences | Ausgabe 10/2020

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Abstract

In North China, the exploitation of deep coal seams is seriously threatened by water inrush from Ordovician limestone. Predicting the water yield property of the Ordovician limestone aquifer has been an important and challenging task. Based on accessible geological and hydrological data, a water yield property index (WYPI) model, which integrated four factors including the water inflow of borehole, fault impact factor, drilling fluid consumption and burial depth of the Ordovician top aquifer, was proposed for predicting the spatial distribution of the water yield property of the upper Majiagou group limestone in the Ordovician top (Ordovician top aquifer) in the Xinwen coalfield, Shandong, China. The grey relative analysis (GRA) and fuzzy analytic hierarchy process (FAHP) methods were combined to objectively determine the weights of each factor. Then, the technique for order performance by similarity to ideal solution and the weights calculated by the GRA and FAHP were used to establish the WYPI model. The water yield property zone map, which was built using the WYPI values, displayed three water yield property zones. The WYPI model was further verified by taking into account practical engineering data, which were considered effective in predicting the zonation of the water yield property of the Ordovician top aquifer in the Xinwen coalfield, Shandong, China.

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Metadaten
Titel
Prediction model of water yield property based on GRA, FAHP and TOPSIS methods for Ordovician top aquifer in the Xinwen coalfield of China
verfasst von
Mei Qiu
Fengjun Huang
Ying Wang
Tao Guan
Longqing Shi
Jin Han
Publikationsdatum
01.05.2020
Verlag
Springer Berlin Heidelberg
Erschienen in
Environmental Earth Sciences / Ausgabe 10/2020
Print ISSN: 1866-6280
Elektronische ISSN: 1866-6299
DOI
https://doi.org/10.1007/s12665-020-08954-z

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