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

A plugin for the open-source GIS software that allows users to download WaPOR data directly onto the QGIS canvas and offers the possibility of calculating some water accounting and productivity indicators based on WaPOR data.   

Type: Resource,WaterPIP

Application: Assessing/monitoring changes in agricultural production, Assessing/monitoring the water consumption of crops, Assessing/monitoring water and/or land productivity, Monitoring and supporting decisions to improve irrigation, Understanding spatial variability of water-related and plant activity-related variables

Layers used: AETI (Actual Evapotranspiration and Interception), 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: Various

Language: English

In this paper, WaPOR data was agronomically validated and used to compute seasonal indicators for the period 2015 to 2018 in a sugar estate in Mozambique. The WaPOR-based yield estimates were found to be comparable to the estate-measured yields The assessment highlights that in Xinavane no single irrigation method performs the best across all performance indicators.  While this study is done for sugarcane in one irrigation scheme, the approach can be broadened to compare other crops across fields or irrigation schemes across Africa with diverse management units in the different agroclimatic zones within FAO WaPOR coverage. The authors of the study conclude that the framework is useful for assessing irrigation performance using the WaPOR dataset.

Type: Case study,WaterPIP

Location: Mozambique

Application: Analyzing yield and/or water productivity gaps, Assessing/monitoring changes in agricultural production, Assessing/monitoring the water consumption of crops, Assessing/monitoring water and/or land productivity, 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), GBWP (Gross Biomass Water Productivity), I (Interception), NPP (Net Primary Production), T (Transpiration)

Scale used: 100m

Organization/institution: IHE Delft Institute for Water Education, Delft University of Technology, Wageningen University & Research, Xinavane estate, Inclusive Agri-Food Value Chain Development Programme (PROCAVA), VanderSat B. V.

Language: English

MAPME is an initiative by KfW, MapTailor Geospatial Consulting, and Agence Française de Développement to provide free and open access to GIS tools and Earth observation in international development cooperation. MAPME repositories contain R codes allow the users to generate various statistics on land use / land cover and vegetation trends to gain insights in a given project area. Currently there are 3 repositories; mapme.agriculture is the R package that supports users to query, download and process data from the FAO WaPOR API. The package helps to quickly query and download the necessary data files to conduct an analysis of agricultural productivity related to biomass production and the amount of water used by crops and other vegetation types.

Type: Resource

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

Organization/institution: KfW, MapTailor Geospatial Consulting, Agence Française de Développement

Language: English