Data, models, and outputs for an agent-based hydro-economic modeling study in an intensively irrigated region of the U.S. High Plains

In this dataset, we include all the models developed for the study "An integrated modeling approach to simulate human-crop-groundwater interactions in intensively irrigated regions", which is published in Environmental Modelling & Software (https://doi.org/10.1016/j.envsoft.2024.106120). Additionally, we provide all the data used in this study. Below, you will find a description of the contents of each file: abm_modflow.zip: This file includes the agent-based hydro-economic model (ABM-MODFLOW), including model inputs and outputs, Python post-processing scripts, and the Windows batch script for the integration process. modflow.zip: This file contains the standalone MODFLOW model files. Each folder includes files for individual simulation periods, starting with a steady-state model for the predevelopment period, followed by seven transient models. modflow_rs.zip: This file contains the MODFLOW-RS model files. Given that remote sensing data is provided for years from 1984 onwards, only models for the post-1980 simulation periods are included. For model files corresponding to years prior to 1980, refer to modflow.zip. Figurers.zip: This file includes all data and Python scripts used to produce the figures in the main text. Tables.zip: This file contains all tables and the associated data included in the main text. Supporting_Info_Figures: This file includes all data and Python scripts used to produce the figures in the Supporting Information. Supporting_Info_Tables: This file contains all tables and the associated data included in the Supporting Information. Supporting_Info_Videos: This file stores Videos S1 and S2 of the Supporting Information, displaying the historical development of irrigation wells and groundwater-fed irrigated lands in the study area from 1946 to 2018. Notes:This work was supported by the National Institute of Food and Agriculture, U.S. Department of Agriculture, under award number 2016-68007-25066, "Sustaining agriculture through adaptive management to preserve the Ogallala aquifer under a changing climate."