The 'Farmers Toolkit' as presented in this project contains various geodata tools applicable for farmers to assist their decision-making and adopt climate smart agricultural practices, WaPOR data being one of the them. This project aims at training extension officers in the use of these geodata tools. In addition to WaPOR, other tools are: Flying Sensors, irrigation advisory services (IrriWatch portal), Google Earthengine Apps, and Climate Risk Assessments. The training providers consortium (FutureWater, IrriWatch, Delphy, Cairo University and HiView) are tailoring the activities towards the requirements of the selected beneficiaries which are private companies, consultants, and NGO's active as extension officers in the agricultural sector of Egypt. The training program is a unique combination of face-to-face training, online teaching, and field schools conducted throughout the growing season of 2021. This project trained extension users in the use of the smartphone application IRWI for the irrigation of corn fields in Egypt.  

Type: Case study

Location: Egypt

Application: 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

Organization/institution: IrriWatch, Delphy, Cairo University, HiView, FutureWater

Language: English

It is a suite of Python tools that permit the retrieval, the aggregation, the analysis, the visualization and the dissemination of FAO WaPOR water productivity data. The package is an attempt to provide users with a starting point with which to start producing actionable data from the the WaPOR datasets in a quick and repeatable manner. It provides the building blocks for customized tool development to target specific user needs including a framework for irrigation performance analysis. 

Type: Resource,WaterPIP

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, Monitoring and supporting decisions to improve irrigation, Supporting solutions to reduce yield and productivity gaps, Understanding spatial variability of water-related and plant activity-related variables

Organization/institution: eLEAF

Language: English

  This paper seeks to demontstrate the fitness of Copernicus data in quantifying spatial and temporal patterns of the actual evapotranspiration (ET) which can serve as a direct proxy of crop water use. It posits that, if used to the fullest extent, Copernicus satellite and modelled data can outperform existing ET products derived from remote sensing in terms of spatial-scale consistency, including WaPOR data. 

Type: Resource

Application: Assessing/monitoring the water consumption of crops, Evaluation, Understanding spatial variability of water-related and plant activity-related variables

Layers used: AETI (Actual Evapotranspiration and Interception)

Scale used: 30m, 100m, 250m

Organization/institution: DHI GRAS, COMPLUTIG, University of Castilla-La Mancha, Instituto Técnico Agronómico Provincial (ITAP), Olive Tree Institute, Université de Toulouse

Language: English

Remote sensing data has great potential to change the way we interact with and understand our agricultural systems. Yet, much work and expertise goes from the data to information and from information to actions. This paper presents a framewok for translating open-source remotely-sensed water productivity data (from the WaPOR database) into actionnable information at the field level, it presents a water stress sensitivity index as well as six crucial water productivity factors and discusses key findings relating to the improvement of water productivity.   

Type: Case study

Location: Lebanon

Application: Assessing/monitoring water and/or land productivity, Monitoring and supporting decisions to improve irrigation, 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), LCC (Land Cover Classification), NPP (Net Primary Production), qLCC (quality Land Cover Classification), qNDVI (quality Normalized Difference Vegetation Index)

Scale used: 30m

Organization/institution: IHE Delft Institute for Water Education, Wageningen University and Research

Language: English

This report published by the FAO presents the latest data on the state of climate services for agricultural users with surveys from 36 countries across all FAO regions. The report presents case studies that highlight additional challenges, opportunities and lessons learned from specific interventions across the climate services provision framework. Two applications that use WaPOR data (that are already featured in this catalog as single entries) are presented in this report (page 57). This allows to place efforts that include WaPOR data in the wider picture of all the ecosystem of climate services in agriculture.

Type: Case study

Location: Egypt, Lebanon

Application: Providing advisory services to farmers

Organization/institution: FAO, WMO, GFCS

Language: English

The lack of adequate data is an issue that unfortunately affects many parts of the world. This paper evaluates the adequacy of WaPOR reference evapotranspiration data to be used as a good alternative to the Modified Hargreaves-Samani and Penman-Monteith methods as input for stream flow models (HBV hydrological model for simulating the runoff) where there is a shortage or lack of meteorological data.

Type: Resource

Application: Evaluation

Layers used: RET (Reference Evapotranspiration)

Organization/institution: Shahid Chamran University of Ahvaz (Iran), Shahrekord University (Iran)

Language: English

The authors of this paper seel to map the seasonal and spatial variability of agricultural water productivity of sugarcane crop in three large irrigation schemes of Ethiopia (Wonji, Fincha’a and Metahara) using WaPOR data. 

Type: Case study

Location: Ethiopia

Application: Assessing/monitoring the water consumption of crops, 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), NPP (Net Primary Production)

Scale used: 100m

Organization/institution: Ambo University, Addis Ababa University, ArbaMinch University

Language: English

In this paper, WaPOR data is used, in conjunction with other datasets, as input to compute a national baseline model for mapping water risks across Ethiopia. This model estimates water withdrawal and consumption for irrigation, livestock, domestic, and industrial water use, with 2015 as a baseline. Through four indicators: baseline water stress, months of water scarcity, seasonal variability, and interannual variability, it offers a broad picture of water risk. 

Type: Case study

Location: Ethiopia

Application: Assessing/monitoring water resources, Understanding spatial variability of water-related and plant activity-related variables

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

Scale used: 250m

Organization/institution: World Resources Institute (WRI)

Language: English

Agricultural data occupies a central place in how our food systems are presently managed as well as the resources linked to them such as water or other inputs. In light of that, their collection has to be well distributed both spatially and temporally. Spatially so as to have a complete understanding of the area of interest and temporally, so as to build a database of historical data that allows trends to be identified and changes to be quantified.   Unfortunately, in periods of conflict, the mechanisms for collecting agricultural data can be disrupted as it might be too unsafe for data to be collected in-situ, or crucial data-collecting infrastructure might be damaged. In such cases, remote sensing data (or earth observations data) can constitute a viable data source to turn to as an alternative or a complement.   This case study explores the use of WaPOR data to monitor agricultural activity in conflict areas by focusing on the use of WaPOR data in Syria.

Type: Case study

Location: Syrian Arab Republic

Application: Assessing/monitoring the impact of a stressor (drought conflict … ) on agriculture

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

Scale used: 100m

Organization/institution: FAO

Language: English

To be in a better position to face challenges related to the sustainable use of our finite freshwater resources, especially in countries with rapidly expanding populations, it is crucial to better understand water supply, demand and availability. Water accounting is one tool that can assist with that and it can be supported by easily available open-access data. This case study aims to show how WaPOR (FAO’s portal to monitor Water productivity through open access of remotely sensed derived data) data can be used to support water auditing processes at different scales: the basin, the national scale and the subnational/scheme scale.

Type: Case study

Location: Burundi, Democratic Republic of the Congo, Egypt, Eritrea, Ethiopia, Kenya, Rwanda, South Sudan, Sudan, Uganda, United Republic of Tanzania

Application: Assessing/monitoring water resources

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

Scale used: 100m, 250m

Organization/institution: FAO

Language: English