Tasnim - The Food and Agriculture Organization of the United Nations (FAO) organized a three-day workshop to equip Iranian experts with operational knowledge and skills required to establish a country-level Agricultural Stress Index System (ASIS).
Designed by FAO to assist the countries in monitoring agricultural drought and managing its risk, ASIS as a part of the Global Information and Early Warning System on Food and Agriculture uses satellite data to detect agricultural areas where crops could be affected by drought and as a result it helps the countries to strengthen their agricultural drought monitoring and early warning systems.
The country-specific version of ASIS once calibrated with field data including land-use maps, sowing dates, crop cycle duration and crop coefficients will detect periods of water stress in crops and forecast crop yields more accurately.
The tool simplifies the results in the form of easy-to-interpret maps enabling decision-makers at national and local levels to implement drought mitigation activities in agriculture, including the payment of parametric crop insurances and the provision of social protection schemes, on a timely basis. These results are also useful for guiding public investments such as water harvesting, irrigation, and water reserves, said Oscar Rojas, FAO Natural Resources Officer who led this three-day workshop held for the Iranian experts.
In this endeavour, and as part of Integrated Programme for Sustainable Water Resources Management in the Urmia Lake Basin project jointly implemented by FAO and Urmia Lake Restoration Program (ULRP) and funded by the Embassy of Japan, the Organization supports Iranian authorities to establish country-level ASIS. ASIS can assist in close monitoring of the agricultural stress within the Urmia Lake basin in order to manage the impact of those stresses on water resources management.
Moreover, adding a probabilistic forecast to the ASIS which is going to be implemented within the extension of the ULRP-FAO project would be a proper tool for decision-makers, said Behdad Chehrenegar, the Head of Research Division of ULRP.