This project aimed to develop, customise and promote seasonal climate forecast (SCF)
technologies to improve the management of irrigated agricultural production systems in
Lombok, Indonesia. The climate of Lombok is highly variable being significantly influenced
by the El Niño Southern Oscillation (ENSO) phenomenon, which greatly affects the
productivity of the predominantly rice-based local agriculture. By customising ENSO-based
SCF technologies for use in regional agricultural management and planning, there is
significant potential to increase Lombok's agricultural productivity and revenue in favourable
seasons and reduce the risk of crop losses in dry years and prolonged droughts. To achieve
this, the objectives of the project embodied a range of decision support and “systemsmodelling”
development, capacity-building and information dissemination components
including:
• Collecting, synthesising, modelling and collating hydrologic and climatic data for
integration into a climate-based decision support system.
• Developing decision support tools for optimising choice of crop, crop area and irrigation
water allocation based on seasonal climate information.
• Promoting SCF-based planning amongst irrigators, government officials and community
leaders.
• Building local capacity in the development and operational use of decision support
systems.