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.

本栅格数据集为应用于佛罗里达狭长地带11个县域的空间产水量模型提供输入数据。本次使用的产水量模型改编自Acharya等人2022年的研究成果，空间建模流程详见相关发表文献。本次产水量分析所需的5项输入数据集如下：1. 松树种断面积模型，命名为"ARSA_PineBA_10m"；2. 二值化地下水位埋深栅格数据集，命名为"DTW_cm_binary2"；3. 基于潜在蒸散发与降水量栅格数据集生成的3项空间干旱指数栅格数据集，分别为"Aridity_Min"、"Aridity_Max"与"Aridity_Mean"。其中最小值、最大值与均值对应本次7年时间跨度数据集内的干旱指数取值范围，数据源自MODIS潜在蒸散发与PRISM年降水量数据集。所有输入与输出数据均采用WGS 1984 UTM Zone 16N坐标系，空间水平分辨率为10米。