TY - JOUR
T1 - Integrating spatially explicit sensitivity and uncertainty analysis in a multi-criteria decision analysis-based groundwater potential zone model
AU - Fildes, Stephen Geoffrey
AU - Bruce, David
AU - Clark, Ian Francis
AU - Raimondo, Tom
AU - Keane, Robert
AU - Batelaan, Okke
PY - 2022/7
Y1 - 2022/7
N2 - This study presents a spatially explicit sensitivity and uncertainty analysis approach to a GIS-based multi-criteria groundwater potential zone model. The study addressed a deficiency in the way groundwater potential mapping results are typically presented using discrete class outputs without assessment of their certainty with respect to variations in criteria weighting, one of the main contributors to output uncertainty in GIS-based multi-criteria decision analysis studies. We argue, moderating groundwater potential mapping results with localised uncertainty levels will help to refine and prioritise groundwater exploration efforts. The approach also enables a better understanding of the underlying factors influencing uncertainty in model outputs, which can help to inform the calibration of input parameters to improve model performance. Although the procedures presented in this study have been applied to other types of multi-criteria evaluations, its integration in GIS-based groundwater potential modelling has received little attention. We provide a case study focused on a fractured rock environment surrounding the township of Hawker in South Australia where new groundwater resources are sought. Small incremental weight changes were applied one-at-a-time and automated as a task in ArcGIS Pro, built using the ArcPy Python module that interacts with spatial tools allowing geographical analysis. The approach is applicable to both continuous and discrete class-based mapping outputs and enabled a deeper understanding of model output behaviour with respect to criteria weighting alternatives. The case study findings demonstrate the potential value of the approach in mitigating uncertainty and improving confidence in locating sites with high groundwater potential.
AB - This study presents a spatially explicit sensitivity and uncertainty analysis approach to a GIS-based multi-criteria groundwater potential zone model. The study addressed a deficiency in the way groundwater potential mapping results are typically presented using discrete class outputs without assessment of their certainty with respect to variations in criteria weighting, one of the main contributors to output uncertainty in GIS-based multi-criteria decision analysis studies. We argue, moderating groundwater potential mapping results with localised uncertainty levels will help to refine and prioritise groundwater exploration efforts. The approach also enables a better understanding of the underlying factors influencing uncertainty in model outputs, which can help to inform the calibration of input parameters to improve model performance. Although the procedures presented in this study have been applied to other types of multi-criteria evaluations, its integration in GIS-based groundwater potential modelling has received little attention. We provide a case study focused on a fractured rock environment surrounding the township of Hawker in South Australia where new groundwater resources are sought. Small incremental weight changes were applied one-at-a-time and automated as a task in ArcGIS Pro, built using the ArcPy Python module that interacts with spatial tools allowing geographical analysis. The approach is applicable to both continuous and discrete class-based mapping outputs and enabled a deeper understanding of model output behaviour with respect to criteria weighting alternatives. The case study findings demonstrate the potential value of the approach in mitigating uncertainty and improving confidence in locating sites with high groundwater potential.
KW - Analytic hierarchy process (AHP)
KW - Geographical information system (GIS)
KW - Groundwater potential
KW - Multi-criteria decision analysis (MCDA)
KW - Sensitivity analysis
KW - Uncertainty analysis
UR - http://www.scopus.com/inward/record.url?scp=85130114929&partnerID=8YFLogxK
U2 - 10.1016/j.jhydrol.2022.127837
DO - 10.1016/j.jhydrol.2022.127837
M3 - Article
AN - SCOPUS:85130114929
SN - 0022-1694
VL - 610
JO - Journal of Hydrology
JF - Journal of Hydrology
M1 - 127837
ER -