Kabul, Afghanistan - Since its inception two year ago, the “Strengthening Afghanistan Institutions Capacity for Assessment of Agriculture Production and Impact Scenarios Development” project has working to build the capacity of government institutions to create, manage and use agricultural data. While the idea behind it may sound simple, good data and proper use of that data is essential for making good decisions - in any field.  And after four decades of war, the institutions of this agrarian country are not always as well-equipped as they should be with such data.   

The project, like all FAO Afghanistan projects, was designed in response to institutional capacity building priorities outlined in Afghanistan’s National Comprehensive Agriculture Development Priority Programme (2016 – 2020). Goals of the program ranged from developing new tools for agriculture monitoring, to outlining procedures for monitoring natural hazards and water scarcity to providing technical support to Afghan institutions to generate agriculture statistics and use data for sustainable land-use planning and natural resources management.

The project just had its’ third steering committee meeting, so we thought it was time to have a check-in on its’ progress.

 First, the project has successfully established National Agricultural Ecological Zones (NAEZ) and a Land Resource Information Management System (LRIMS) for monitoring and analysing agricultural production systems. These two products allow users to assess how suitable land is for different types of crops and compare the advantages and disadvantages of different land and water use options.  Further descriptions of these tools are available at: http://www.fao.org/in-action/agricultural-assessment-scenario-afghanistan/en/

Under these two subprojects a geodatabase was established, a gap analysis of what type of data is needed for mapping agro-ecological indicators under various climactic conditions was conducted, and future climate trajectories and their impacts on crops for the years 2020, 2050 and 2080 were mapped. Soil suitability for specific crops, based on seven major soil qualities was assessed, and agro-climatic yield simulations for historical climate and future climate scenarios was completed for 24 major crops. All results were based on soil mapping units of the Harmonized World Soil Data base and United States Geological Survey (USGS) and United States Department of Agriculture (USDA) soil data sets, ensuring the results met international quality standards. Finally, production costs and possible net revenues under rainfed and irrigated conditions were estimated on crop-by-crop basis.

Under another project component, climate change scenarios on water availability, crop yields and socio-economic factors for all major agro-ecological zones were completed, and evidence-based adaptation strategies for the agriculture and natural resources sectors were developed. Results unsurprisingly showed that climate change will have impacts, largely negative, and driven by increases in heat and decreases in water availability. However, though negative, the results can be used as a basis for capacity-building programs, so that a cadre of national climate change and agricultural modelling specialists can be grown.

Remote-sensing, using satellites, drones, and other airborne technology is the way of the future in land use monitoring, especially in a country like Afghanistan with difficult and dangerous terrain. Therefore, the third component of the project has been working using updated technology for agriculture monitoring, including remote sensing methods and geographical information systems (GIS). For example, the rice and cotton crop area was estimated for 2017 using these methods. And, approximately 90 survey staff from the Management Information System (MIS) and Statistics directorates of DAILs in 65 districts have been trained on data collection and the Land Resources Information Management System (LRIMS) in Cairo. These staff also received training on the use of GIS and remote sensing technologies, mobile computing, mapping and analysis of specific crops, crop modelling concepts, statistical analysis, and how to use LRIMS/NAEZ to plan land use and water interventions.