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Sensitivity analysis assessment of remotely based vegetation indices to improve water resources management

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Abstract

Normalized Difference Vegetation Index (NDVI) is estimated from Landsat 8 sensor acquired in June 2013 to drive four different water-related indices calculated as NDVI derivatives. Different vegetation indices (VIs) have been extracted exclusively in estimation of different VIs: Leaf Area Index, Water Supply Vegetation Index, Crop Water Shortage Index, and Drought Severity Index in addition to estimation of daily evapotranspiration (ET). Sensitivity analysis assesses the contributions of the inputs to the total uncertainty in the analysis outcomes. Vegetation indices are complex and intercepted, therefore the interceptions of the five different vegetation indices are considered in the current study. A comparative analysis of Gaussian process emulators for performing global sensitivity analysis was used to conduct a variance-based sensitivity analysis to identify which uncertain inputs are driving the output uncertainty. The results showed that the interconnections between different VIs vary, but the extent of the features sensitivity is uncertain. Findings from the current work conducted are anticipated to contribute decisively toward an inclusive VIs assessment of its overall verification. Daily ET is the less sensitive and more certain index followed by Drought Vegetation Index.

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Authors and Affiliations

  1. Department of Hydrology and Water Resources Management, Faculty of Meteorology, Environment and Arid Land Agriculture, King Abdulaziz University, Jidda, 21589, Kingdom of Saudi Arabia

    Mohamed Elhag

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  1. Mohamed Elhag
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Correspondence to Mohamed Elhag.

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Elhag, M. Sensitivity analysis assessment of remotely based vegetation indices to improve water resources management. Environ Dev Sustain 16, 1209–1222 (2014). https://doi.org/10.1007/s10668-014-9522-0

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  • DOI: https://doi.org/10.1007/s10668-014-9522-0

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