A novel framework for pixel-wise estimation of irrigation water use by integrating remote sensing and reanalysis data

Accurate and spatially explicit estimates of irrigation water use (IWU) are essential for understanding the earth system dynamics in the Anthropocene. Recent advances in remote sensing have spurred growing interest in satellite-based IWU estimation. However, large-scale IWU estimates remain limited in both accuracy and spatial resolution due to inherent deficiencies in satellite observations and methodological constraints. Here, we present a novel framework for spatially explicit IWU estimation by integrating satellite-based soil moisture and evapotranspiration (ET) products with reanalysis data. Within this framework, we developed two alternative models: one based on root zone soil moisture (RSM) and the other on surface soil moisture (SSM), both grounded in soil water balance principles. The models estimate IWU by quantifying differences in soil moisture, ET, and drainage between natural and irrigated conditions. Both the RSM- and SSM-based models perform well in predicting prefecture-level IWU during the validation period, achieving coefficients of determination (R²) between 0.72 and 0.90 and root mean square errors (RMSE) of 0.55–0.66 km³ /year, depending on the spatial scale of calibration (i.e., province, prefecture, or subregion). By combining our framework with different satellite products, we produce ensemble IWU estimates at 1 km resolution across China. The resulting dataset reveals a clear increasing trend in China’s IWU from 2001 to 2020, primarily driven by the expansion of irrigated area, while its interannual variability is largely controlled by fluctuations in IWU per unit irrigated area. This dataset shows a significant advancement in both accuracy and spatial detail over existing datasets and will be useful for irrigation-related research and agricultural water management in China. • A novel framework is proposed for spatially explicit estimation of irrigation water use (IWU). • IWU is quantified from changes in soil moisture, ET, and drainage between natural and irrigated conditions. • Our model is a suitable and general form, well-suited for large-scale applications.

Publication Details

Journal
Agricultural Water Management
Published
2025-12-13
DOI
https://doi.org/10.1016/j.agwat.2025.110077
Citations
2
Primary Topic
Soil Moisture and Remote Sensing
Type
article
Field-Weighted Citation Impact
1.60
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

A novel framework for pixel-wise estimation of irrigation water use by integrating remote sensing and reanalysis data

2 citations
Agricultural Water Management
Soil Moisture and Remote Sensing
1.60
article

A novel framework for pixel-wise estimation of irrigation water use by integrating remote sensing and reanalysis data

article en
2 citations

Abstract

Accurate and spatially explicit estimates of irrigation water use (IWU) are essential for understanding the earth system dynamics in the Anthropocene. Recent advances in remote sensing have spurred growing interest in satellite-based IWU estimation. However, large-scale IWU estimates remain limited in both accuracy and spatial resolution due to inherent deficiencies in satellite observations and methodological constraints. Here, we present a novel framework for spatially explicit IWU estimation by integrating satellite-based soil moisture and evapotranspiration (ET) products with reanalysis data. Within this framework, we developed two alternative models: one based on root zone soil moisture (RSM) and the other on surface soil moisture (SSM), both grounded in soil water balance principles. The models estimate IWU by quantifying differences in soil moisture, ET, and drainage between natural and irrigated conditions. Both the RSM- and SSM-based models perform well in predicting prefecture-level IWU during the validation period, achieving coefficients of determination (R²) between 0.72 and 0.90 and root mean square errors (RMSE) of 0.55–0.66 km³ /year, depending on the spatial scale of calibration (i.e., province, prefecture, or subregion). By combining our framework with different satellite products, we produce ensemble IWU estimates at 1 km resolution across China. The resulting dataset reveals a clear increasing trend in China’s IWU from 2001 to 2020, primarily driven by the expansion of irrigated area, while its interannual variability is largely controlled by fluctuations in IWU per unit irrigated area. This dataset shows a significant advancement in both accuracy and spatial detail over existing datasets and will be useful for irrigation-related research and agricultural water management in China. • A novel framework is proposed for spatially explicit estimation of irrigation water use (IWU). • IWU is quantified from changes in soil moisture, ET, and drainage between natural and irrigated conditions. • Our model is a suitable and general form, well-suited for large-scale applications.

Agricultural Water ManagementVol. 323
Clean water and sanitation
Openalex Percentile: Top 15%
Soil Moisture and Remote Sensing
1.60
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.