DOI: 10.5061/dryad.5tb2rbpfd
title: Data from: A model-based evaluation of the effects of irrigation expansion on regional and global land surface climate

description: Irrigation is essential for enhancing agricultural productivity and
 satisfying global food demand. The challenge of feeding a growing
 population without increasing cultivated land can be addressed partly by
 expanding irrigation into currently rain-fed croplands. At the same time,
 water-scarce regions with currently unsustainable irrigation practices may
 experience a reduction in irrigated area. While the evaporative cooling
 effect of irrigation on regional climate has been extensively studied, it
 is still unclear how different irrigation expansion (or contraction)
 scenarios would affect global and regional near-surface climatic
 conditions. Here we evaluate the hydro-climatic impacts of several
 irrigation expansion scenarios. To assess changes in evapotranspiration
 (ET) and land surface temperature (LST) under various irrigation
 scenarios, we incorporated and validated an irrigation model representing
 four main irrigation methods: sprinkler, drip, furrow, and flood-paddy,
 into the NASA Catchment land surface model. Globally, the increase in ET
 from irrigation and the associated impact on average yearly LST are
 negligible, with an average global cooling of -0.03°C in the case of
 current irrigation (with respect to a baseline without irrigation).
 Compared to the current irrigation scenario, the maximum irrigation
 expansion scenario can lead to an additional LST cooling of -0.01°C, while
 the net irrigation contraction in a sustainable irrigation scenario is
 associated with a 0.02°C warming. While global and regional impacts of
 irrigation on LST are relatively modest, locally, the cooling effect can
 be substantial, with a maximum yearly average LST cooling as strong as
 -5°C and monthly cooling peaks of up to -10.2°C in heavily irrigated
 periods.
description: # Data from: A model-based evaluation of the effects of irrigation
 expansion on regional and global land surface climate Dataset DOI:
 [10.5061/dryad.5tb2rbpfd](10.5061/dryad.5tb2rbpfd) ## Description of the
 data and file structure These data are used in "A model-based
 evaluation of the effects of irrigation expansion on regional and global
 land surface climate", Earth's Future. ### Files and variables
 **Validation.nc4** contains: * SiteID refers to the flux tower identifiers
 from the datasets by Pastorello et al. (2020)
 [https://doi.org/10.1038/s41597-020-0534-3](https://doi.org/10.1038/s41597-020-0534-3) and Volk et al. (2023) [https://doi.org/10.5281/zenodo.7636781](https://doi.org/10.5281/zenodo.7636781), which were used for the validation. * Latitude_fluxT, Longitude_fluxT, Latitude_CLSM, Longitude_CLSM: respectively latitude, longitude for each flux tower site (fluxT), and for the 9km EASE grid V2 used with Catchment Land Surface Model (CLSM) containing the flux tower site. * PRECTOTLAND: monthly average precipitation (mm/month) from Merra2 (Gelaro et al., 2017) * EVLAND_No_Irr, EVLAND_Sprinkler, EVLAND_Drip, EVLAND_Flood, EVLAND_Furrow: simulated evapotranspiration monthly averages (mm/month) assuming, respectively, no irrigation, sprinkler, drip, flood, and furrow irrigation * SPRINKLERRATE_Sprinkler, DRIPRATE_Drip, FLOODRATE_Flood, FURROWRATE_Furrow, simulated monthly irrigation rates (mm/month) according to different methods (sprinkler, drip, flood, and furrow irrigation) **NoIrr.nc4**, **C.nc4**, **C_U_S.nc4**, **C_S.nc4**, **Cs_S.nc4** contain: * Global Simulated monthly average Land Surface Temperature (TSURF, °C) and Evapotranspiration (EVLAND, mm/month) for each Irrigation Expansion scenario. * In addition, C.nc4, C_U_S.nc4, C_S.nc4, and Cs_S.nc4 contain the respective simulated total Irrigation rates (IRRLAND, mm/month) for each Irrigation Expansion scenario. **SupplementaryMaterial.xlsx** contains a Model Evaluation Spreadsheet: This spreadsheet contains: * Details about the flux towers used for model evaluation (Tab FluxTowersDetails); It includes: * SiteID: source dataset flux tower ID, * Site_Name: source dataset flux tower Name, * Latitude, Longitude": coordinates of the flux tower, * IGBP: Land cover classification (CRO = Cropland), * Source of the data, * Original source of the data, * land cover details: detailed description of the land cover from the flux tower meta data, * Irrigated?: column indicating wether the site is irrigated either from flux towers metadata or visual detection using imagery. "nan" indicates that no information about the irrigation status is available. * Validation summaries using different metrics are reported in the following Validation Summary tabs: * Validation Summary – MBE (Mean Bias Error, Unit: ET mm/month) * Validation Summary – Slope (Slope OLS, Unit: –) * Validation Summary – r (Pearson Correlation Coefficient, Unit: –) * Validation Summary – RMSE (Root Mean Squared Error, Unit: mm/month) * Validation Summary – ubRMSE (Unbiased Root Mean Squared Error, Unit: mm/month) Each validation summary tab contains: * SiteID – The flux tower ID. * Metric values – Computed for simulated monthly ET under each irrigation method (No_Irr, Sprinkler, Drip, Flood, Furrow) compared to monthly ET from flux towers. * Best_"Metric" – Indicates the best-performing simulation for that metric. * Improvement from No Irrigation – Maximum improvement in the selected metric when adding irrigation. * Irrigation Method Observed – Method observed from flux tower metadata or imagery. * Agreement – Whether the best-performing simulation matches the observed method (1 = yes, 0 = no, NaN = no observed method available). * Agreement within Error – Whether the simulation using the observed method falls within ±30 mm/month of error (1 = yes, 0 = no, NaN = no observed method available). * Look-up table IGBP (Tab LookUpTable) The boxes at the top of each tab show quantiles and percentages summarizing the overall evaluation across all flux tower sites used for validation. The highlighted colors link the question in the top box to the corresponding statistics: (i.e., Green: Does Irrigation Improve ET according to the selected *metric? Blue: Is there agreement between the observed irrigation method and the simulated with the best *metric? Orange: If we simulate ET using the observed irrigation method, does the simulation fall within an error range (i.e., threshold)?) **Model Evaluation Plots with Irrigation Methods: EvalIrrMethods.zip** This zip file contains the model evaluation plots. Each plot shows the name of the flux tower, the type of irrigation (i.e., flood, sprinkler, drip, unknown, or non-irrigated rainfed), and simulations for the same grid using different irrigation methods. The observed flux tower evapotranspiration (ET) is represented with a black, dashed line; each continuous line represents the simulated ET using different irrigation methods for the 9 km grid containing the flux tower. The bars indicate the amount of irrigation provided by each method. **Sensitivity Analysis Plots: Sensitivity.zip** This zip file contains the sensitivity analysis plots for Evapotranspiration and Irrigation rate for the irrigated flux towers over CONUS. The sensitivity of ET and irrigation rate to different model configurations has been performed by varying, one at a time, four key parameters (LAI threshold, Irrigation threshold, H start, and duration. Starting from the default configuration LAI_threshold = 0.6, with remaining parameters set as in Table 1 (Casirati et al., 2025), an additional 16 simulations were performed by varying each parameter individually: * LAI_threshold = 0, 0.2, 0.4, 0.8 * Irrigation threshold = 0, 0.3, 0.5, 0.9 * H_start = 1am, 11am, 4pm, 9pm * Duration = 1h, 4h, 8h, 16h ET simulations with different model configurations were performed for the U.S. and compared with monthly empirical ET estimates obtained from a set of Ameriflux eddy covariance flux towers (Volk et al., 2023). The continuous line represents the default configuration, the black dashed line represents the flux tower ET, and the shaded area represents the range of the target variables (ET or irrigation rate) by varying the model parameters. **Version Changes:** 13-Aug-2025: Added: * *SupplementaryMaterial.xlsx* – Model evaluation spreadsheet * *EvalIrrMethods.zip* – Model evaluation plots for irrigation methods * *Sensitivity.zip* – Sensitivity analysis plots