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Input raster datasets for an application of a fine resolution spatially explicit forest water yield model in Florida's panhandle

Authors: Vernon, Jordan; St. Peter, Joseph;

Input raster datasets for an application of a fine resolution spatially explicit forest water yield model in Florida's panhandle

Abstract

These raster datasets are the inputs for a spatial water yield model applied to an 11 county area in the state of Florida's panhandle. The water yield model is adapted from Acharya, et al. 2022 and the spatial modelling process is detailed in the associated publication. The five input datasets required for this water yield analysis are: 1) a model of pine species basal area, named "ARSA_PineBA_10m" 2) a binary depth to water table raster named "DTW_cm_binary2" , and 3) three spatial aridity index raster dataset named "Aridity_Min", "Aridity_Max" and "Aridity_Mean", created from potential evapotranspiration, and precipitation raster datasets. The min max and mean codifiers relate to the range of aridity values found in our dataset of 7 year temporal range, from MODIS PET and PRISM percipitation yearly data. All input and output data are in the WGS 1984 UTM Zone 16N coordinate system and have 10m horizontal spatial resolution.

This work was funded by the Gulf Coast Ecosystem Restoration Council (RESTORE Council) through an interagency agreement with the USDA Forest Service (17-IA-11083150-001) for the Apalachicola Tate's Hell Strategy 1 Project.

Related Organizations
Keywords

Panhandle, precipitation, Water yield, Florida Gulf Coast, Pine, Water Yield, basal area, PET, aridity, Florida Panhandle, Florida, Aridity, pine

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This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
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