Abstract
Groundwater is an important natural resource in arid and semi-arid environments, where discharge from karst springs is utilized as the principal water supply for human use. The occurrence of karst springs over large areas is often poorly documented, and interpolation strategies are often utilized to map the distribution and discharge potential of springs. This study develops a novel method to delineate karst spring zones on the basis of various hydrogeological factors. A case study of the Bojnourd Region, Iran, where spring discharge measurements are available for 359 sites, is used to demonstrate application of the new approach. Spatial mapping is achieved using ensemble modelling, which is based on certainty factors (CF) and logistic regression (LR). Maps of the CF and LR components of groundwater potential were generated individually, and then, combined to prepare an ensemble map of the study area. The accuracy (A) of the ensemble map was then assessed using area under the receiver operating characteristic curve. Results of this analysis show that LR (A = 78%) outperformed CF (A = 67%) in terms of the comparison between model predictions and known occurrences of karst springs (i.e., calibration data). However, combining the CF and LR results through ensemble modelling produced superior accuracy (A = 85%) in terms of spring potential mapping. By combining CF and LR statistical models through ensemble modelling, weaknesses in CF and LR methods are offset, and therefore, we recommend this ensemble approach for similar karst mapping projects. The methodology developed here offers an efficient method for assessing spring discharge and karst spring potentials over regional scales.
Highlights
Groundwater has been considered the most important resource in arid and semi-arid areas.Population increases and economic growth have resulted in water shortages around the globe, especially in developing countries, leading to greater exploitation and reliance on groundwater resources [1,2]
The ensemble map was compared with each individual map using the receiver operating characteristic (ROC) analysis to find if there is any improvement in combining the models
A positive value of certainty factor (CF) means that the groundwater potential is higher, while a negative value illustrates a decrease in the certainty of groundwater occurrence [126]
Summary
Groundwater has been considered the most important resource in arid and semi-arid areas. Population increases and economic growth have resulted in water shortages around the globe, especially in developing countries, leading to greater exploitation and reliance on groundwater resources [1,2]. Among the various forms of subsurface freshwater, karst groundwater is a major resource for water supply in many regions, including China, Turkey, Iran, Mexico, and the United. Karst aquifers are relatively high-yielding, heterogeneous systems that are characterized by complex groundwater flow paths [8,9,10]. They store and supply drinking water for approximately. The characterization of karst aquifers is hampered by their complex character, and the often limited number of wells available to support hydrogeological observations and geological descriptions [12]
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