Integrating spatially explicit sensitivity and uncertainty analysis in a multi-criteria decision analysis-based groundwater potential zone model

This study presents a spatially explicit sensitivity and uncertainty analysis approach to GIS-based multi-criteria groundwater potential zone model. The addressed deficiency in the way mapping results are typically presented using discrete class outputs without assessment of their certainty with respect variations criteria weighting, one main contributors output decision studies. We argue, moderating localised levels will help refine prioritise exploration efforts. also enables better understanding underlying factors influencing model outputs, which can inform calibration input parameters improve performance. Although procedures this have been applied other types evaluations, its integration modelling has received little attention. provide case focused on fractured rock environment surrounding township Hawker South Australia where new resources sought. Small incremental weight changes were one-at-a-time automated as task ArcGIS Pro, built ArcPy Python module that interacts spatial tools allowing geographical analysis. is applicable both continuous class-based enabled deeper behaviour weighting alternatives. findings demonstrate value mitigating improving confidence locating sites high potential.