Hetao Irrigation District Data and Processing Scripts

This is a core dataset and accompanying code set supporting research on "large-scale irrigation water optimization in irrigation districts based on distributed intelligent agents." The data package contains average evapotranspiration raster data for the growing season (August-October) in the Hetao Irrigation District of China from 2001 to 2020, attribute data for 23 sub-regions, and complete Python scripts for remote sensing data processing and spatial statistics. This data package aims to provide directly usable input data, validation benchmarks, and reproducible analysis workflows for the validation and application of hydrological models and irrigation optimization algorithms. File List and Description 1. Subregion Attribute Data File: Hetao_Irrigation_District_Subregion_Attributes/ Format: Folder (containing accompanying Shapefiles) Description: Contains attribute tables for 23 subregions within the Hetao Irrigation District. Key fields include: region ID, distance from water source inlet (distance), drip irrigation ratio (diguan), proportion of wheat/maize/sunflower/potato planting area (wheat/maize/sunflower/potato), and irrigation water demand (DEMAND). Used to drive or validate distributed hydrological and optimization models. 2. Mean Growing Season Evapotranspiration Raster Data File: mean_growing_season_ET_2001_2020.tif Format: GeoTIFF Description: Mean cumulative evapotranspiration (ET) for the growing season (August-October) from 2001-2020, calculated based on the MODIS MOD16A2GF Version 6.1 product. Spatial resolution is 500 meters, units are millimeters per growing season. This data serves as a key input for water balance analysis and model validation. 3. Remote Sensing Data Processing Script File: MOD16A2GF_2001-2020_Hetao_Mean_Growing_Season_ET.py Description: Python script. Uses the Google Earth Engine (GEE) API to extract, calculate, and export the mean growing season ET raster for the Hetao Irrigation District from the original MOD16A2GF dataset. The script includes complete functionality for date filtering, region clipping, statistical calculation, and export. 4. Zonal Statistics Script File: zonal_statistics_et_subregions.py Description: Python script. Used to calculate zonal statistics (minimum, maximum, mean, standard deviation, and pixel count) for the mean ET raster data within 23 subregions (vector polygons). Outputs include a CSV table and a new Shapefile containing a mean ET field. Data Processing Workflow Data Generation: Run the script MOD16A2GF_..._ET.py(requires GEE authorization) to generate mean_growing_season_ET_2001_2020.tif. Spatial Statistics: Run the script zonal_statistics_et_subregions.py, using the TIFF file from the previous step and a subregion vector boundary file as input, to obtain an ET statistical summary for each subregion. Model Application: Use the subregion attribute data along with the ET statistical results as input or validation data for optimization models such as PI-DAO. Dependencies Python 3.7+ Key Python libraries: rasterio, geopandas, pandas, numpy, rasterstats, earthengine-api, geemap Script 3 requires a valid Google Earth Engine account and authentication. Usage Suggestions It is recommended to first read the comments within the code and modify the input/output paths in the scripts according to your local file structure. For the "standardized value" fields in the subregion attribute data, it is advised to refer to the original literature or documentation for interpretation. Acknowledgments and Citation If this data package is helpful for your research, please cite: This data package (suggest using the DOI for this package) The original MODIS data source: Running, S., Mu, Q., Zhao, M. (2017). MOD16A2 MODIS/Terra Net Evapotranspiration 8-Day L4 Global 500m SIN Grid. NASA EOSDIS Land Processes DAAC.