干旱区生态环境知识资源中心(Arid): Groundwater potential modeling over the eastern part of Ghana's Northern Region using evidence belief functions and weight of evidence

Arid

DOI	10.1007/s12145-024-01317-3
	Groundwater potential modeling over the eastern part of Ghana's Northern Region using evidence belief functions and weight of evidence
	Forson, Eric Dominic; Dzikunoo, Elikplim Abla; Amponsah, Prince Ofori; Menyeh, Aboagye; Nunoo, Samuel; Amponsah, Theophilus Yaw
通讯作者	Dzikunoo, EA
来源期刊	EARTH SCIENCE INFORMATICS
ISSN	1865-0473
EISSN	1865-0481
出版年	2024
卷号	17 期号:3 页码:2737-2753
英文摘要	In arid and semi-arid areas such as Ghana's northern regions, water scarcity is prevalent particularly during the dry seasons (between the middle of November to April) and thus, the yearly demand for groundwater during these periods is very high in these areas. Hence, the delineation of prospective zones of groundwater resource occurrence offers an invaluable response towards the mitigation of the water scarcity issues that arise particularly during the dry seasons. In view of this, the employability capacity of the evidence belief functions (EBF) and weight of evidence (WOE) approaches towards the preparation of groundwater prospectivity models (GPM) have been assessed and compared in the eastern part of Ghana's Northern Region. In carrying out the aforesaid task, multiple groundwater-related geospatial layers comprising drainage density (DD), digital elevation model (DEM), geology, lineament density (LD), slope, soil type, stream power index (SPI), topographic position index (TPI), topographic roughness index (TRI) and topographic wetness index (TWI) sourced from geophysical, geological, geomorphological and remote sensing datasets were used as inputs for both the EBF and WOE models. Inventory data comprising 230 existing locations of productive groundwater boreholes and wells, obtained from historical data and field surveys were applied. 161 of the groundwater inventory data prepared were randomly selected to train and subsequently generate groundwater prospectivity models based on the EBF and WOE approaches. The remaining 69 groundwater inventory data points were used as testing data to determine the efficacy of the GPM produced based on the two aforementioned data integration approaches using the receiver operating characteristics (ROC) curve. From the area under the ROC (AUC) scores obtained, the predictive performance of the GPM based on the EBF and WOE approaches were respectively 0.96 and 0.98. The validation results of the models show the ability of the models to correctly predict the potential of groundwater sources in relation to the geology, with the Bunya sandstone member and the Afram formation towards the eastern part of the study area verified as the most producible lithologies for groundwater occurrence. It is envisaged that the outputs developed in this study would be useful for planners to plan and manage groundwater resources effectively, especially in difficult geologic terranes with limited success of boreholes.
英文关键词	Groundwater potential modeling Evidence belief function Weight of evidence Receiver operating characteristics Voltaian Basin
类型	Article
语种	英语
收录类别	SCI-E
WOS记录号	WOS:001205426700002
WOS关键词	GIS ; BASIN
WOS类目	Computer Science, Interdisciplinary Applications ; Geosciences, Multidisciplinary
WOS研究方向	Computer Science ; Geology
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/403312
推荐引用方式 GB/T 7714	Forson, Eric Dominic,Dzikunoo, Elikplim Abla,Amponsah, Prince Ofori,et al. Groundwater potential modeling over the eastern part of Ghana's Northern Region using evidence belief functions and weight of evidence[J],2024,17(3):2737-2753.
APA	Forson, Eric Dominic,Dzikunoo, Elikplim Abla,Amponsah, Prince Ofori,Menyeh, Aboagye,Nunoo, Samuel,&Amponsah, Theophilus Yaw.(2024).Groundwater potential modeling over the eastern part of Ghana's Northern Region using evidence belief functions and weight of evidence.EARTH SCIENCE INFORMATICS,17(3),2737-2753.
MLA	Forson, Eric Dominic,et al."Groundwater potential modeling over the eastern part of Ghana's Northern Region using evidence belief functions and weight of evidence".EARTH SCIENCE INFORMATICS 17.3(2024):2737-2753.