This study aims to assess whether spatial variability in biomass and evapotranspiration (ETa) as shown by the WaPOR database (version 2.1) could be attributed to human-influenceable factors, local climate variations, or methodological inaccuracies. The researchers conducted agronomic linear regression analyses on five growing seasons of data from two large-scale irrigated sugarcane estates in Ethiopia (Wonji) and Mozambique (Xinavane). The study found that 82–94% of the variation in biomass and ETa was attributed to the crop's photosynthetic efficiency and local climate. The influence of irrigation technology on this variation was small. The remaining unexplained spatial variability (6–18%) fell within an estimated accuracy range of +/- 9% for WaPOR data outputs.

Type: Resource

Location: Ethiopia, Mozambique

Application: Evaluation

Layers used: E (Evaporation), NPP (Net Primary Production), RET (Reference Evapotranspiration), T (Transpiration)

Scale used: 30m, 100m

Organization/institution: Wageningen University & Research, IHE Delft, MetaMeta Research

Language: English

The objective of this repository is to calculate irrigation performance indicators using WaPOR data. It can accomodate two options for the water use and production data, the WaPOR version 3 data (downloaded using download_WaPORv3_data script) or data created using pyWaPOR.

Type: Resource

Application: Monitoring and supporting decisions to improve irrigation

Layers used: AETI (Actual Evapotranspiration and Interception), AGBP (Above Ground Biomass Production) [no longer offered], E (Evaporation), GBWP (Gross Biomass Water Productivity), I (Interception), LCC (Land Cover Classification), NBWP (Net Biomass Water Productivity), NPP (Net Primary Production), P (Precipitation), Phe (Phenology), qLCC (quality Land Cover Classification), qLST (quality Leaf Surface Temperature), qNDVI (quality Normalized Difference Vegetation Index), RET (Reference Evapotranspiration), T (Transpiration), TBP (Total Biomass Production)

Scale used: 30m, 100m, 250m

Organization/institution: IHE Delft

Language: English

Crop modeling and remote sensing (RS) technologies are essential for assessing crop conditions and predicting yields at larger scales. In this study, RS and a crop growth model are combined to assess phenology, evapotranspiration (ET), and yield dynamics at grid and sub-county scales in Kenya. WaPOR data was synthesized to retrieve sowing date information for driving the model simulations.

Type: Case study

Application: Analyzing yield and/or water productivity gaps, Supporting solutions to reduce yield and productivity gaps

Layers used: Phe (Phenology)

Scale used: 100m

Organization/institution: Jomo Kenyatta University, Leibniz Centre for Agricultural Landscape Research, ...

Language: English

This protocol focuses on analyses that can be conducted to explain the reasons behind spatial and temporal biophysical water productivity (BWP) variations. BWP is defined here as the relation between crop production (biomass or yield) and water consumption; i.e. evapotranspiration (ETa). To conduct such analysis, the factors that affect BWP need to be delineated. For this reason, the first aim of this protocol is to delineate the agronomic principles that affect water productivity (section 2). Second, this protocol aims to show how to make use of various existing tools that can provide diagnostic insights (section 3).  WaPOR data is combined with field survey data and the outputs of the AquaCrop simulation model to understand the causative factors of the variability.  

Type: Case study,Resource

Location: Jordan

Application: Understanding spatial variability of water-related and plant activity-related variables

Organization/institution: Wageningen University and Research, WUR

Language: English

A rapid assessment was conducted in July, August, and September 2023 to estimate the extent of cultivated cropland in Sudan, considering the disruption caused by armed conflict, using geospatial data to inform immediate and long-term food security management. The assessment carried out by the FAO Geospatial Unit uses dekadal (10-days) Net Primary Productivity (NPP) data from the remote sensing for water productivity (WaPOR) level-2 data (100 m resolution) to extract the information at the locality level and further aggregate at state and national levels. The same reason that motivated this assessment, made it also very challenging to perform the data collection necessary for field validation, yet, this work shows the suitability of the use of remote-sensing as a source of data in a situation of political instability. 

Type: Case study

Location: Sudan

Application: Analyzing yield and/or water productivity gaps, Assessing/monitoring changes in agricultural production, Assessing/monitoring the impact of a stressor (drought conflict … ) on agriculture

Layers used: NPP (Net Primary Production)

Scale used: 100m

Organization/institution: FAO

Language: English

The World Bank realized a desktop water accounting study in Kenya for the years 2010-2021. WaPOR data was used alongside a variety of other data sources. The objective was to attempt to quantify the water flows of the country and their trends for that time period as well as estimate metrics that can assist with management decisions such as: water scarcity disaggregated in two types of water: blue and green as well as economic water scarcity.

Type: Case study

Location: Kenya

Application: Assessing/monitoring water resources

Layers used: AETI (Actual Evapotranspiration and Interception), RET (Reference Evapotranspiration)

Scale used: 250m

Organization/institution: The World Bank

Language: English

SOSIA+ will expand on the scope of SOSIA by completing the satellite-based data with real time ground data from weather stations and soil moisture sensors provided by TAHMO (Trans-African Hydro-Meteorological Observatory). One of the major outputs of the project will be an irrigation scheduling tool, similar to SOSIA that will have increased usability for small-scale farmers due to the nature of the input data. 

Type: Case study,Resource

Application: Monitoring and supporting decisions to improve irrigation

Layers used: RET (Reference Evapotranspiration)

Scale used: 100m

Organization/institution: TU Delft, Holland Greentech, TAHMO

Language: English

The WaterPIP Project has developed a drought monitoring system using the FAO WaPOR datasets and machine learning, named DroughtObserve. It offers maps of drought intensities at two administrative levels over Africa and MENA region as well as timeseries of historical drought (2009 - near real time). The tool also contains a 6-month forecast of the drought intensity.

Type: Resource

Location: Algeria, Angola, Benin, Botswana, Burkina Faso, Cameroon, Chad, Congo, Democratic Republic of the Congo, Djibouti, Egypt, Equatorial Guinea, Eswatini, Ethiopia, Gabon, Gambia, Ghana, Guinea, Guinea-Bissau, Iran (Islamic Republic of), Iraq, Israel, Jordan, Kenya, Lebanon, Lesotho, Liberia, Libya, Madagascar, Malawi, Mali, Mauritania, Mauritius, Morocco, Mozambique, Namibia, Niger, Nigeria, Palestine, Qatar, Rwanda, Réunion, Saudi Arabia, Senegal, Seychelles, Sierra Leone, Somalia, South Africa, South Sudan, Sudan, Syrian Arab Republic, Togo, Tunisia, Uganda, United Arab Emirates, United Republic of Tanzania, Western Sahara, Yemen, Zambia, Zimbabwe

Application: Assessing/monitoring water resources

Layers used: AETI (Actual Evapotranspiration and Interception), LCC (Land Cover Classification), NPP (Net Primary Production), P (Precipitation)

Scale used: 250m

Organization/institution: IHE Delft

Language: English

This report provides an overview of changes in agricultural indicators from 2009 to 2020 in a selection of Islamic Development Bank member countries. The data can also be viewed interactively in Google Earth Engine. The data includes the following agricultural indicators: actual evapotranspiration and interception (AETI), total biomass production, gross biomass water productivity, reference evapotranspiration (RefET), precipitation (P), AETI/RefET and AETI/P over irrigated or rainfed areas.

Type: WaterPIP

Location: Algeria, Benin, Burkina Faso, Cameroon, Chad, Côte d'Ivoire, Egypt, Gambia, Guinea, Iran (Islamic Republic of), Iraq, Jordan, Kuwait, Lebanon, Libya, Mali, Mauritania, Morocco, Mozambique, Niger, Nigeria, Oman, Palestine, Qatar, Saudi Arabia, Senegal, Somalia, Sudan, Syrian Arab Republic, Togo, Tunisia, Uganda, Yemen

Application: Assessing/monitoring changes in agricultural production, Assessing/monitoring water and/or land productivity

Layers used: AETI (Actual Evapotranspiration and Interception), LCC (Land Cover Classification), NPP (Net Primary Production)

Scale used: 250m

Organization/institution: MetaMeta

Language: English

WaPOR4Awp is a web-based tool that computes and visualizes agricultural water productivity data for countries in Africa and the Near-East using WaPOR data in support of monitoring SDG 6.4.1- Change in Water Use Efficiency (CWUE). It offers an alternative approach to estimating water use efficiency in the form of water productivity.

Type: Case study,Resource

Location: Algeria, Angola, Benin, Botswana, Burkina Faso, Cabo Verde, Cameroon, Central African Republic, Chad, Comoros, Congo, Côte d'Ivoire, Democratic Republic of the Congo, Djibouti, Egypt, Eritrea, Eswatini, Ethiopia, Gabon, Gambia, Ghana, Guinea, Iran (Islamic Republic of), Iraq, Israel, Jordan, Kenya, Lebanon, Lesotho, Liberia, Libya, Madagascar, Malawi, Mali, Mauritania, Mauritius, Morocco, Mozambique, Namibia, Niger, Nigeria, Oman, Palestine, Rwanda, Réunion, Sao Tome and Principe, Saudi Arabia, Senegal, Sierra Leone, Somalia, South Africa, South Sudan, Sudan, Syrian Arab Republic, Togo, Tunisia, Uganda, United Arab Emirates, United Republic of Tanzania, Western Sahara, Zambia, Zimbabwe

Application: Assessing/monitoring water and/or land productivity

Layers used: AETI (Actual Evapotranspiration and Interception), LCC (Land Cover Classification), P (Precipitation)

Scale used: 250m

Organization/institution: IHE Delft

Language: English