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Weather modeling and data analytics empower an island nation to save its natural resources

Nestled in the South China Sea, the island of Borneo is the third largest non-continental island in the world. Brunei, one of three countries located on the island, is an oil-rich country but its leaders are thinking about the future – investing in renewable energy technologies, protecting its citizens from floods and diversifying its economic output beyond oil and gas.

The country also wants to improve food security for its citizens by improving local agriculture. For example, only three percent of Brunei’s rice is grown in the country today, with the rest imported; Brunei hopes to increase domestic rice production by 60 percent by 2015.

While these may seem like separate issues, they all share something in common: analyzing weather data and energy utilization to improve the lives of a nation’s citizenry.

The government partnered with IBM Research – India to apply deep expertise in using data analytics and weather modeling to improve agriculture and energy development. In a three-year joint partnership with the Universiti Brunei Darussalam (UBD), the UBD | IBM Centre will develop precision weather forecast models. Using a Blue Gene-P system, the goal is to show specific conditions in an area as small as 1.5 x 1.5 square kilometers, and reflect changes over 10 minute increments for a 48 hour period.


Improving crops

Brunei’s landscape presents unique challenges to growing rice locally. Rice requires a substantial amount of water to grow and prosper. And while Brunei enjoys heavy rainfall amounts annually, the majority of land is hilly, resulting in serious runoff and heavy accumulations in the lower valleys.

The forecast models developed by the UBD - IBM collaboration, coupled with hydrology and flood modeling, will help farmers know not just when it will rain, but how much, for how long, and where the runoff will go. Depending on the forecast, adjustments can be made to affected parts of fields, including changes to irrigation systems to drain off excess water, or decisions such as holding off on applying fertilizer or insecticide; this is known as precision agriculture. The team is experimenting with a variety of ways to get the forecast information to farmers and government officials, including a desktop interface and smart phone apps.

The forecasts have potential beyond agriculture; Brunei has seen massive floods with destructive effects, but by knowing in advance how rainfall will affect flooding, evacuations can be staged in the right areas and save lives. This is similar to the work IBM has been doing with flood forecasting in Rio de Janeiro.

Forecasting the seasons

While short term forecasts are good enough for making changes in day-to-day farming operations, numerous issues need to be addressed at the seasonal scale. Rice has a three month cultivation cycle and farmers usually start planting in March. However, it’s important to consider how much rain can be anticipated in the coming growing season; too much or too little can have a huge impact on yield. By knowing in advance what the weather should be in April, May and June, farmers can adjust whether they start planting rice earlier, later or on normal schedule.

In fact, the UBD-IBM team is building a model to forecast the climate in Brunei for up to 50 years in the future.

The seasonal forecasts also provide great insight into how various scenarios impact the rainforests and surrounding ecosystem of Brunei; even small changes can have serious affects on human life and activity, as well as the flora and fauna. By building different scenarios into the climate model, different use cases can be tested to determine the potential impact.

Renewable energy

The supply of renewable energy sources such as solar or wind is much more uncertain than oil and gas. The same day-ahead weather forecasts used for agriculture can be used to understand the supply of renewable energy sources such as wind and solar. Once a short term forecast is developed, storage and demand models can be factored in to determine how to best manage the supply of energy that will be available. For example, if the forecast calls for a windy and sunny day and the demand model says there will be low demand, complimentary fossil-fuel based energy generation can be avoided. However, if there will be multiple cloudy days, energy suppliers can make decisions about which reserves or complimentary generation facilities to tap into.

Because of the partnership between IBM Research – India and UBD, Brunei is the first nation in the world to have a national-scale, high-resolution, integrated natural resources models which can be accessed by ordinary people and workers via tablet and smart phone interfaces. In addition, by working with IBM, UBD is able to distinguish itself as a top university.

Our collaboration with IBM reinforces our mission to be a first-class international university, priding ourselves as a research-driven educational enterprise with focus that is aligned with key national priorities to help Brunei Darussalam achieve its vision of a knowledge-based economy.

Dr. Hj Zulkarnain bin Hj Hanafi, vice chancellor, UBD

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