Spatial interpolation of rainfall data using ArcGIS: A comparative study.
Many GIS models for environmental and watershed management decision-making require rainfall as an input, in discrete or continuous format. The objective of this study was to evaluate spatial interpolation techniques for interpreting 2km OneRain data into 30m resolution using ArcGIS Spatial Analyst. The 30m interpolated surfaces from OneRain were compared to 30m interpolated surfaces generated from rain gauge stations in and around the drainage basin. The interpolation methods used in this study were inverse distance weighting (variable & fixed), spline (regularized and tension) and kriging (Ordinary: spherical, circular, exponential, Gaussian, Linear, and Universal: linear with linear drift and linear with quadratic drift). The drainage basin studied was Charlie Creek, Central Florida, U.S.A., a basin largely untouched by urbanization but expected to undergo rapid change in the next 10 years. This expectation has driven residents and the local water management district to be proactive in planning the use of water resources.
Earls, J. & Dixon, B. (2007). Spatial interpolation of rainfall data using ArcGIS: A comparative study. 27th Annual ESRI International User Conference. San Diego, CA.
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