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IDW ‐Plus: An Arc GIS Toolset for Calculating Spatially Explicit Watershed Attributes for Survey Sites
Author(s) -
Peterson Erin E.,
Pearse Alan R.
Publication year - 2017
Publication title -
jawra journal of the american water resources association
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.957
H-Index - 105
eISSN - 1752-1688
pISSN - 1093-474X
DOI - 10.1111/1752-1688.12558
Subject(s) - watershed , surface runoff , land cover , computer science , land use , hydrology (agriculture) , inverse , environmental science , streams , euclidean distance , inverse distance weighting , stream flow , mathematics , geography , geology , civil engineering , multivariate interpolation , drainage basin , geometry , cartography , engineering , artificial intelligence , bilinear interpolation , ecology , computer network , biology , machine learning , computer vision , geotechnical engineering
Watershed characteristics such as land‐use and land‐cover affect stream condition at multiple scales, but it is widely accepted that conditions in close proximity to the stream or survey site tend to have a stronger influence. Although spatially weighted watershed metrics have existed for years, nonspatial lumped landscape metrics ( i.e., areal mean or percentage) are still widely used because relatively few technical skills are needed to implement them. The Inverse Distance Weighted Percent Land Use for Streams ( IDW ‐Plus) custom Arc GIS toolset provides the functionality to efficiently calculate six spatially explicit watershed metrics which account for the Euclidean or flow length distance to the stream or outlet, as well as the probability for overland runoff. These include four distance‐weighted metrics, those being inverse Euclidean distance to the stream or outlet, and the inverse flow length to the stream or outlet. Two tools are also included to generate hydrologically active ( i.e ., runoff potential), inverse flow length to the stream or outlet metrics. We demonstrate the tools using real data from Southeast Queensland, Australia. We also provide detailed instructions, so readers can recreate the examples themselves before applying the tools to their own data.