TY  - Data
T1  - Regional datasets of long-term and coarse resolution irrigation estimates from space
A1  - Pierre Laluet
DO  - 10.12072/ncdc.zenodo.db7658.2026
PY  - 2026
DA  - 2026-07-23
PB  - National Cryosphere Desert Data Center
AB  - The products are experimental datasets of long-term (approximately 20 years) Irrigation Water Use at 0.25° resolution. They cover four regions: the Contiguous United States (CONUS), the Ebro River Basin in north-eastern Spain, the Murray-Darling Basin in south-eastern Australia, and India.These datasets are the outcome of the European Space Agency (ESA) Climate Change Initiative Anthropogenic Water Use (CCI-AWU) precursor project (project link). They were produced using three different methods: SM-based (Soil-Moisture-based) Inversion, SM-based Delta, and Model-Observation Integration, which is based on the Noah-Multiparameterization model.The SM-based Inversion method was used to produce five datasets for the four regions, each using a different SM product as input. These include ESA CCI Combined, ESA CCI Passive, ASCAT (Advanced Scatterometer), SMOS (Soil Moisture and Ocean Salinity), and SMAP (Soil Moisture Active Passive).The SM-based Delta method was used to produce six datasets for the four regions, each combining different SM and evapotranspiration (ET) products as input. The combinations include ESA CCI Combined SM & FLUXCOM ET, ESA CCI Passive SM & FLUXCOM ET, ESA CCI Active SM & FLUXCOM ET, ESA CCI Combined SM & SSEBOP ET, ESA CCI Passive SM & SSEBOP ET, and ESA CCI Active SM & SSEBOP ET.The Model-Observation Integration method was applied to the CONUS and Murray-Darling Basin regions, producing three datasets using different irrigated surface maps as input. These maps include the Landsat-Derived Global Rainfed and Irrigated-Cropland Product (referred to as "Landsat", the Relative Bias Approach (referred to as "Method1"), and the Multi-Resolution Analysis Approach (referred to as "Method2").The irrigation products are delivered with monthly temporal aggregation.
DB  - NCDC
UR  - http://www.ncdc.ac.cn/portal/metadata/65052f74-8096-42ca-952f-cffb17281691
ER  -