Volume 15 Issue 4
Dec.  2022
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Dinesh Chammika Ratnayake, Guna A. Hewa, David J. Kemp, Alaa A. Ahmed. 2022: Application of multi-criteria decision-making methods to identification of soil moisture monitoring sites in an urban catchment in South Australia. Water Science and Engineering, 15(4): 294-304. doi: 10.1016/j.wse.2022.09.003
Citation: Dinesh Chammika Ratnayake, Guna A. Hewa, David J. Kemp, Alaa A. Ahmed. 2022: Application of multi-criteria decision-making methods to identification of soil moisture monitoring sites in an urban catchment in South Australia. Water Science and Engineering, 15(4): 294-304. doi: 10.1016/j.wse.2022.09.003
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Application of multi-criteria decision-making methods to identification of soil moisture monitoring sites in an urban catchment in South Australia

doi: 10.1016/j.wse.2022.09.003

  • UniSA STEM, University of South Australia, Mawson Lakes Campus, Mawson Lakes, SA 5095, Australia

  • Received Date: 2020-12-15
  • Accepted Date: 2022-09-13
  • Rev Recd Date: 2021-07-31
    • Available Online: 2022-11-04
    Abstract
  • When choosing sites for monitoring of soil moisture for hydrological purposes, a suitable process that considers the factors influencing soil moisture level should be followed. In this study, two multi-criteria decision-making (MCDM) methods, the multi-influencing factor (MIF) method and the analytical hierarchy process (AHP) method, were used to identify the optimal soil moisture monitoring (SMM) sites in the Dry Creek Catchment in South Australia. The most representative areas for nine SMM sites were obtained using the MIF method, considering the factors of rainfall, soil type, land use, catchment slope, elevation, and upslope accumulated area (UAA). The AHP method was used to select the optimal sites using the site-specific criteria. 30.3% of the catchment area in the Australian Water Resources Assessment Landscape (AWRA-L) Grid_DC2 can be considered acceptable as representative area with the MIF method. Four potential sites were evaluated for each AWRA-L grid using the relative weights of the site-specific criteria with the AHP method. The Grid_DC2 required two sites that had the highest overall weight chosen with the AHP analysis. The procedure was repeated for the remaining four AWRA-L grids within the study area to select the required SMM sites.

     

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