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

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.本栅格数据集（raster datasets）为空间水产量模型（spatial water yield model）的输入数据，该模型应用于佛罗里达州狭长地带的11个县域范围。本次使用的水产量模型改编自Acharya等人2022年的研究成果，空间建模流程的详细说明见于相关发表文献。本次水产量分析共需五类输入数据集：1）松树物种断面积模型，命名为"ARSA_PineBA_10m"；2）二值化地下水位埋深栅格数据，命名为"DTW_cm_binary2"；3）三类空间干旱指数栅格数据集，分别为"Aridity_Min"、"Aridity_Max"与"Aridity_Mean"，该类数据由潜在蒸散发（Potential Evapotranspiration，PET）与降水栅格数据集计算生成。其中最小值、最大值与均值三类指标对应本数据集7年时间序列范围内的干旱指数取值区间，数据基于MODIS潜在蒸散发与PRISM年度降水数据计算得到。所有输入与输出数据均采用WGS 1984 UTM Zone 16N坐标系，水平空间分辨率为10米。