Journal
ENVIRONMENTAL EARTH SCIENCES
Volume 78, Issue 13, Pages -Publisher
SPRINGER
DOI: 10.1007/s12665-019-8381-2
Keywords
Artificial recharge; GIS; Random forest; ROC curve; Shabestar region
Ask authors/readers for more resources
One of the most crucial design steps to guarantee the long life and the sustainability of artificial recharge of groundwater projects is to find the best locations. The present study focuses on identifying potential zones of groundwater artificial recharge in Shabestar region, northwest of Iran. For this purpose, random forest (RF) model, a learning method based on ensemble decision trees, was proposed for locating groundwater artificial recharge. Important factors, including slope and slope aspect, soil texture, erosion, land use, groundwater quality, permeability and geological lithology were integrated in a geographic information science (GIS). According to RF model, permeability and unsaturated zone thickness were identified as the most effective parameters for locating groundwater artificial recharge sites. Based on the proposed model, it was found that 14% of the region is located in suitable site for groundwater artificial recharge projects. The accuracy of the model was evaluated with receiver-operating characteristic (ROC) curve and the mean squared error (MSE). Low MSE and ROC curve of the model with the highest area under curve equal to 0.947, indicated high accuracy of random forest in locating groundwater artificial recharge.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available