This study identifies the potential areas for solar based irrigation in Africa. The framework uses a number of publicly available datasets of solar irradiation, land use, water resources, solar pump characteristics, and climates to identify areas that may be suitable for Solar based irrigation.  The maps have been developed as an online, interactive tool to inform and strengthen planning and management of irrigation in Africa.

Type: Case study

Location: Eswatini, Liberia, Madagascar, Malawi, Mali, Mauritania, Mozambique, Namibia, Niger, Nigeria, Rwanda, Sao Tome and Principe, Senegal, Sierra Leone, Somalia, South Africa, South Sudan, Sudan, Togo, Tunisia, Uganda, United Republic of Tanzania, Zambia, Zimbabwe

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

Layers used: AETI (Actual Evapotranspiration and Interception), P (Precipitation)

Scale used: 250m

Organization/institution: International Water Management Institute (IWMI)

Language: English

This study uses the Water Accounting + (WA+) framework to collect and evaluate the water resources status for the Souss Massa River Basin. The framework focuses on the use of a variety of publicly available remote sensing datasets including data from WaPOR to summarize the water resources status of the Souss Massa River Basin for 2009-2019.

Type: Case study

Location: Morocco

Application: Assessing/monitoring water resources

Layers used: AETI (Actual Evapotranspiration and Interception), LCC (Land Cover Classification), RET (Reference Evapotranspiration)

Scale used: 100m, 250m

Organization/institution: International Water Management Institute (IWMI)

Language: English

SOSIA is a tool (a Google Earth Engine app) with two connected components. The first component offers weather data based on virtual weather stations. Currently farmers rely on low-coverage real-time weather stations in Rwanda combined with the now outdated CROPWAT 8.0 method; SOSIA replaces the former with virtual weather stations that use open-source satellite data combined with crop stage, and projected and historical precipitation data: FAO WaPOR, CFSR, CHIRPS, and CFS data. The second component offers farmers a more reliable and accurate indication of their irrigation water requirements than the existing options by replacing the long term average and obsolete ET0 data extracted from CROPWAT with a new one that uses near-real time FAO WaPOR data, to retrieve a location specific crop schedule.

Type: Resource

Location: Rwanda

Application: Providing advisory services to farmers

Layers used: RET (Reference Evapotranspiration)

Scale used: 100m

Organization/institution: Future Water

Language: English

Water Water Accounting + (WA+) is a tool that allows for the collection, analysis, summary and reporting of water related information in river basins. WA+ uses remotely sensed and other open access data, among which WaPOR data, to compute water flows. It was employed in the study of the water resources in 5 bassins in the South East of Morocco (in the Southern part of the Atlas mountains).

Type: Case study,Resource

Location: Morocco

Application: Assessing/monitoring the impact of a stressor (drought, conflict, … ) on agriculture, Assessing/monitoring the water consumption of crops, Assessing/monitoring water and/or land productivity, Assessing/monitoring water resources, Evaluation, Understanding spatial variability of water-related and plant activity-related variables

Layers used: AETI (Actual Evapotranspiration and Interception), GBWP (Gross Biomass Water Productivity), LCC (Land Cover Classification), TBP (Total Biomass Production)

Scale used: 100m, 250m

Organization/institution: BET Ressources ingénierie (RESING)

Language: French

PyWaPOR is a repository that contains a Python implementation of the algorithm used to generate the WaPOR datasets. It can be used to calculate evaporation, transpiration and biomass production maps.

Type: Resource

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, Assessing/monitoring the water consumption of crops, Assessing/monitoring water and/or land productivity, Assessing/monitoring water resources, Monitoring and supporting decisions to improve irrigation, Monitoring the impact of drought, Providing advisory services to farmers, Supporting solutions to reduce yield and productivity gaps, Understanding spatial variability of water-related and plant activity-related variables

Layers used: AETI (Actual Evapotranspiration and Interception), E (Evaporation), NPP (Net Primary Production), T (Transpiration)

Scale used: 30m

Organization/institution: FAO

Language: English

The purpose of this study is the investigation of the relationship between agricultural land-use changes and the decrease of the Lake Urmia water level. This was achieved calculating the actual evapotranspiration and interception in agricultural and non-agricultural lands, investigating the trend of temperature changes and its relationship with ETIa, determining the water balance, and estimating net and gross biomass water productivity in the ULB. The authors of the study arrive at the conclusion that the rise of the temperature, the increase in the area of irrigated croplands, the decrease of precipitation and the negative water balance should be considered as warning signals calling for the proper management of water resources in the Urmia Lake Basin.

Type: Case study

Location: Iran (Islamic Republic of)

Application: Assessing/monitoring water resources, Evaluation

Layers used: AETI (Actual Evapotranspiration and Interception), LCC (Land Cover Classification), NBWP (Net Biomass Water Productivity)

Scale used: 250m

Organization/institution: Urmia University

Language: English

In this study, WaPOR data was used in agricultural water accounting to assess levels of agricultural water consumption and to provide possible solutions for water deficiency in the North Jordan Valley. This study also validates WaPOR data with existing consolidated products and ground data, to evaluate its suitability for such an exercise.

Type: Case study,Resource

Location: Jordan

Application: Assessing/monitoring the water consumption of crops, Assessing/monitoring water resources, Evaluation

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

Scale used: 100m, 250m

Organization/institution: The University of Jordan, University of Naples Federico II, FAO, Ministry of Water and Irrigation

Language: English

The Smart Irrigation App “IREY” was developed to provide real-time irrigation schedules in Tunisia for selected crops (i.e., wheat, barley, sugar beets, oats and corn). Irrigation schedules in the Smartphone App and on the web are based on water balance methodology using weather data from multiple resources. Crop evapotranspiration, ETc, is calculated by multiplying the reference crop evapotranspiration, ETo issued from the WAPOR platform, by a local crop coefficient, Kc which is applied based on time after planting, calendar month, and a crop’s phenological stage. The WaPOR ET data generally has good correlation with ET estimated from in-situ meteorological measurements at each tested site in Tunisia. The correlation at all sites was good to very good (0.85-0.98) and confirms results published by FAO (2020) in the Technical report on the data quality of the WaPOR FAO database version 2. These findings indicate that ET WaPOR is a high quality input for our IREY model.

Type: Case study,Resource

Location: Tunisia

Application: Assessing/monitoring the water consumption of crops, Monitoring and supporting decisions to improve irrigation, Providing advisory services to farmers, Supporting solutions to reduce yield and productivity gaps, Understanding spatial variability of water-related and plant activity-related variables

Layers used: E (Evaporation), T (Transpiration)

Scale used: 250m

Organization/institution: INGC (Institut National des Grandes Cultures)

Language: Arabic, English, French

This web-based app provides the average value of six agricultural indicators over the period 2009-2020 and the percentage change over the period based on WaPOR data.

Type: Resource,WaterPIP

Application: Assessing/monitoring changes in agricultural production, Assessing/monitoring the impact of a stressor (drought, conflict, … ) on agriculture, Assessing/monitoring water and/or land productivity, Understanding spatial variability of water-related and plant activity-related variables

Layers used: AETI (Actual Evapotranspiration and Interception), GBWP (Gross Biomass Water Productivity), P (Precipitation), RET (Reference Evapotranspiration), TBP (Total Biomass Production)

Scale used: 250m

Organization/institution: MetaMeta

Language: English

An operational framework was developed to predict field crop biomass using high resolution multi-source satellite data. Five regression algorithms were tested to assess their suitability to predict field scale sugarcane biomass production in the Wonji-Shoa estate, Ethiopia. The results showed that linear regression models outperformed non-linear machine learning models with 89% accuracy achieved 4 months before harvest.

Type: Resource

Location: Ethiopia

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

Layers used: AETI (Actual Evapotranspiration and Interception), NPP (Net Primary Production)

Scale used: 30m

Organization/institution: IHE Delft, Wageningen University

Language: English