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E-Agriculture Strategy Guide

Development of an Enhanced Production and Risk Management in Agriculture Integrated Decision Support System (EPRiMA)

WHAT THE PROJECT DOES

Philippines is exposed to multiple hazards which include periodic typhoons, tropical cyclones, floods, droughts, earthquakes, tsunamis, volcanic eruptions, landslides, forest-fires and pandemics. It is also facing agricultural and natural resource risks including those associated with rapid urbanization, migration and socio-economic changes. The country has a history of large-scale disasters, including the Mindanao Tsunami, the 1990 Luzon earthquake, the Mt. Pinatubo Eruption in 1991, the 2009 typhoons Ondoy and Pepeng, and the 2013 Typhoon Yolanda.

This project is expected to increase resilience against multiple-threats to the agriculture sector by facilitating the Development of an Integrated Decision Support System for Enhanced Production and Risk Management in Agriculture which will allow key actors in the Department of Agriculture to make more effective and timely decisions through more comprehensive and near-real time access to crop production, and risk and damage assessment information and tools. 

THE 3 IMPORANT DIMENSIONS

The project will support three important dimensions of disaster risk reduction (DRR):

  • Reducing existing risks,
  • Avoiding new risks, and
  • Addressing underlying vulnerabilities.

EXPECTED RESULTS

The proposed action include an Integrated Decision Support System consisting of new and existing tools related to enhancing crop production and disaster risk reduction and management in agriculture. This will include the development of:

  • dynamic cropping (planting and harvesting) calendars;
  • rapid Production Support and Risk and Damage Assessment Methodology and
  • acquisition and analysis protocols involving freely available high-resolution satellite imagery to support risk and damage assessment planning.

The development of a dynamic cropping calendar entails the development of the country's technical capacity on sub-seasonal to seasonal (S2S) forecasting. It addresses the forecast gap between 10-day and monthly forecasts, which could prove critical in medium-term risk management decisions in agriculture, water management, as well as when ascertaining sudden shifts in hydro-met conditions that should trigger time-sensitive, live-saving preparatory and response-activities.