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Welcome to the wiki of the WaPOR version 3 methodology.

WaPOR methodology

Version 3.0
12 February 2024

Achieving Food Security in the future while using water resources in a sustainable manner will be a major challenge for current and future generations. Increasing population, economic growth and climate change all add to increasing pressure on available resources. Agriculture is a key water user and careful monitoring of water productivity in agriculture and exploring opportunities to increase it is required. Improving water productivity often represents the most important avenue to cope with increased water demand in agriculture. Systematic monitoring of water productivity through the use of Remote Sensing techniques can help to identify water productivity gaps and evaluate appropriate solutions to close these gaps.

The FAO portal to monitor Water Productivity through Open access of Remotely sensed derived data (WaPOR) provides access to at least 6 years of continued observations with global coverage. The portal provides open access to various spatial data layers related to land and water use for agricultural production and allows for direct data queries, time series analyses, area statistics and data download of key variables to estimate water and land productivity gaps in irrigated and rain fed agriculture.

The beta release of WaPOR was launched on 20 April 2017 covering the whole of Africa and the Near East region. WaPOR Version 1 became available starting from June 2018 and WaPOR Version 2 was launched in June 2019. Version 3 expanded to global coverage and was released end of 2023. Each version of the data was improved based on extensive internal and external validation and quality assessment.

This document provides a detailed description of the processing chain applied for the production of the WaPOR version 3 data components and the theory that underlies the applied methodology, used to produce version 3 of the WaPOR database at 300m (level 1), 100m (level 2) and 20m (level 3) resolution. References are included throughout the document so that additional information on specific aspects of the methodology can be found.

Wiki content

Getting started for Abbreviations and Definitions

Understanding the WaPOR pipeline for a general overview of the produced WaPOR database components, the Technical Approach to produce these components, the WaPOR intermediate Data Components and Related Inputs produced and pre-processing applied, and the Code Repository with links to all relevant documentation.

Intermediate data components for detailed documentation on Albedo, fAPAR, Land Surface Temperature, Light Use Efficiency (LUE), NDVI , Precipitation, Solar radiation, Statics and Weather data

Data Sources for an overview of all input data (both model and sensor data) used to produce the (intermediate) data components: CHIRPS Precipitation, Copernicus DEM, (Ag)ERA5 Meteorological Data, GEOS-5 Meteorological Data, IMERG Precipitation, Landsat satellites, MODIS sensors, MSG satellites, Sentinel-2 satellites, VIIRS sensors and WorldCover Land Cover.

WaPOR data components and methodology described in more detail and also includes the underlying methodology as well as the scripts used: Evapotranspiration (AETI)), Net Primary Productivity (NPP), Precipitation (PCP), Quality layers (QUAL), Reference Evapotranspiration (RET), Soil moisture (RSM), Total Biomass Production (TBP) and Water Productivity (WP)

References provides all literature references

Release Notes

3.0 2024/02/27

• Static layers added with link in description

3.0 2024/02/12

• Updated Pipeline description on PCP and RET spatial resolution and extent
• Added solar radiation and precipitation inputs to Pipeline description
• Tenacity factor to 2 (RSM)
• Soil resistance to -1.5 (AETI)
• Dynamic nd_max value (AETI)

3.0 2024/02/09

• Updated Data Source Landsat (from primary to secondary source for most L3 areas)
• Added Data Source IMERG precipitation
• Updated Data Source VIIRS (inputs used)
• Added Data Source MODIS
• Improved Intermediate Statics text (added statics z_oro and z_coarse)
• Improved Intermediate Solar Radiation text (text on transmissivity)

3.0 2023/06/05

• Remove CERES as input
• Remove Fengyun as input
• Updated description of (Ag)ERA5
• Updated sourcing link and description of GEOS-5
• Updated sourcing of MSG
• Updated preprocessing of Landsat (cloud masking)
• Updated preprocessing of Sentinel-2 (preparation of thermal sharpening inputs)
• Added reference to Kappa Mask in Sentinel-2 description
• Added description of VIIRS for L1 Albedo and NDVI
• Added description on atmospheric correction of VIIRS brightness temperature
• Replace land cover map inputs (World Cover)
• Updated values for minimum stomatal resistance and maximum obstacle height (World Cover))
• Updated thermal sharpening description
• Added information on Light Use Efficiency correction
• Updated smoothening procedure albedo
• Updated Light Use Efficiency section due to new land cover inputs
• Updated smoothening procedure NDVI
• Updated description of R0_bare and R0_full in Statics
• Quality layer units changed to dekads

3.0 2022/07/20

• Emissivity estimates added to VIIRS

3.0 2022/07/12

• Updated and added albedo weights

3.0 2022/07/01

• Replaced figures related to (instantaneous_air_density.png and instantaneous_atmospheric_emissivity.png in RSM, meteo.png in RET, net_radation.png in AETI

3.0 2022/06/29

• Added functions to to include functions on vapour pressure from dewpoint temperature

3.0 2022/05/10

• Daily AgERA5 meteorological data replaces GEOS-5 for final processing
• Hourly ERA5 meteorological data replaces GEOS-5 for final processing
• VIIRS LST replaces MODIS LST at level 2 and complements Landsat LST at level 3
• Sentinel-2 replaces Proba-V at level 2 and complements Landsat at level 3
• Sentinel-3 LST put in place as VIIRS LST backup
• L2 masks updated (0.05 degree buffer for land and 0.10 degree buffer for water)
• Statics lwslope and lwoffset for the calculation of longwave radiation have been recalibrated using ERA5 (previous calibration based on MERRA)
• fAPAR coefficients adapted
• Albedo weights adapted
• Thermal sharpening approach added for L2 and L3
• Aerodynamic resistance calculations for soil moisture adjusted
• Tenacity factor in soil moisture stress calculations can be adjusted (implementation depending on testing)


FAO, in partnership with and with funding from the Government of the Netherlands, is currently implementing the second phase of the WaPOR programme to monitor and improve water productivity in agriculture. This document is part of the second phase of the programme: the further improvement of the operational methodology to produce an open-access database to monitor land and water productivity (version 3 of the WaPOR database).

The original methodology was developed by the FRAME consortium, consisting of eLEAF, VITO, ITC, University of Twente and Waterwatch foundation, commissioned by and in partnership with the Land and Water Division of FAO. The publication describing Version 2 of the methodology is available here.

Version 3 was developed in the framework of a Long Term Agreement (2020-2022) with FAO consortium members eLEAF and VITO. The data is being produced by eLEAF under a Long Term Agreement with FAO (2023 and onwards).

Substantial contributions to the methodology updates were provided during several methodology review meetings by experts including from the FAO, IHE Delft, IWMI, ITC-UTwente, eLEAF and VITO.

FAO also received feedback from several users of WaPOR database in project countries. Furthermore, two quality assessments were executed, one by ITC-UTwente (FAO, 2020) and one by IHE Delft (FAO, 2019).

Table of Content

Getting Started


Understanding the WaPOR pipeline

WaPOR database
Technical Approach
WaPOR intermediate Data Components and Related Inputs
Code Repository

Intermediate Data Components

Land Surface Temperature (LST)
Light Use Efficiency (LUE)
Solar Radiation
Static data
Weather data

Data Sources

CHIRPS Precipitation
Copernicus DEM
(Ag)ERA5 Meteorological Data
GEOS-5 Meteorological Data
IMERG Precipitation
Landsat satellites
MODIS sensors
MSG satellites
Sentinel-2 satellites
VIIRS sensors
WorldCover Land Cover

WaPOR data components and methodology

Evapotranspiration (AETI)
Land Cover Classification (LCC)
Net Primary Productivity (NPP)
Precipitation (PCP)
Phenology (PHE)
Quality layers (QUAL)
Relative Evapotranspiration (RET)
Soil moisture (RSM)
Total Biomass Production (TBP)
Water Productivity (WP)