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Multiscale Effects on Spatial Variability Metrics in Global Water Resources Data

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  • Shama Perveen
  • L. James

Abstract

Spatial scales and methods for dealing with scale have been widely discussed in the water resources literature. Different spatial processes operate at different scales so interpretations based on data from one scale may not apply to another. Understanding the behavior of phenomena at multiple-scales of data aggregation is thus imperative to accurate integrations of data and models at different geographic resolutions. This study tests theoretical concepts of scale by presenting empirical results of multiscale GIS and statistical analyses on gridded water-availability, water use and population data for the Danube Basin in Europe, with results corroborated by similar tests in the Ganges (South Asia) and Missouri (North America) Basins. Fine-resolution datasets were aggregated to coarser grid sizes and standard statistical measures of spatial variability were computed. Statistical analysis of spatial variability demonstrated two distinctly different cases for unscaled and scaled variables. Results show that variance (and standard deviation) in unscaled variables like freshwater supply, use and population increases at coarser scales—contrary to the common assumption of decreasing variability as grid-cell size increases. On the other hand, a decreasing trend in variability with scale is noted for variables scaled to area or population (like population density, water availability per capita etc.). Moreover, relationships between variability and scale show strong non-linear trends. No mention of these relationships has been found in the water resources or socio-economic literature for scale and variability. Regression analyses suggest that power functions are the most appropriate model to fit trends in increasing variability at multiple scales. These results can be applied to interpretations of water-stress and water scarcity data and their locations relative to water sources or topographic barriers. Copyright Springer Science+Business Media B.V. 2010

Suggested Citation

  • Shama Perveen & L. James, 2010. "Multiscale Effects on Spatial Variability Metrics in Global Water Resources Data," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 24(9), pages 1903-1924, July.
    • Handle: RePEc:spr:waterr:v:24:y:2010:i:9:p:1903-1924
    DOI: 10.1007/s11269-009-9530-2
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    References listed on IDEAS

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    1. Surendra Kulshreshtha, 1998. "A Global Outlook for Water Resources to the Year 2025," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 12(3), pages 167-184, June.
    2. ,, 2000. "Problems And Solutions," Econometric Theory, Cambridge University Press, vol. 16(2), pages 287-299, April.
    3. S. V. Ciriacy-Wantrup, 1959. "Philosophy and Objectives of Watershed Development," Land Economics, University of Wisconsin Press, vol. 35(3), pages 211-221.
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    2. Davy Vanham & Stefanie Millinger & Harald Pliessnig & Wolfgang Rauch, 2011. "Rasterised Water Demands: Methodology for Their Assessment and Possible Applications," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 25(13), pages 3301-3320, October.
    3. Zafar Hussain & Zongmin Wang & Jiaxue Wang & Haibo Yang & Muhammad Arfan & Daniyal Hassan & Wusen Wang & Muhammad Imran Azam & Muhammad Faisal, 2022. "A comparative Appraisal of Classical and Holistic Water Scarcity Indicators," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 36(3), pages 931-950, February.
    4. Liem Tran & Robert O’Neill & Elizabeth Smith & Randall Bruins & Carol Harden, 2013. "Application of Hierarchy Theory to Cross-Scale Hydrologic Modeling of Nutrient Loads," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 27(5), pages 1601-1617, March.
    5. Zhang, Chunxiao & Chen, Min & Li, Rongrong & Fang, Chaoyang & Lin, Hui, 2016. "What's going on about geo-process modeling in virtual geographic environments (VGEs)," Ecological Modelling, Elsevier, vol. 319(C), pages 147-154.

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