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PARTNERSHIPS FOR ENHANCED ENGAGEMENT IN RESEARCH (PEER)
Cycle 5 (2015 Deadline)


Strengthening resilience to extreme weather related events in Indonesia through improving the predictability of drought risk within the Drought Cycle Management Model


PI: Heri Kuswanto (kuswanto.its@gmail.com), Institut Teknologi Sepuluh Nopember
U.S. Partner: Justin Sheffield, Princeton University
Project Dates: December 2016 - August 2020

Project Overview

This project focuses on drought as one of the major natural hazards in Indonesia. The primary aim is to improve the predictability of drought events as part of disaster risk reduction within the framework of the Drought Cycle Management (DCM) model. The DCM has proven to be a robust and practical approach for drought management in Africa for more than 30 years, but it has never been implemented in Indonesia. Differences in drought characteristics and community profiles between Indonesia and Africa will introduce interesting challenges for formulating novel strategies towards DCM implementation. One of the challenges will be how to predict future drought events under Indonesia’s unique tropical climate variability. This project will develop a Drought Monitoring and Forecasting System (DMFS) and formulate scenarios to reduce drought risk, based on approaches previously applied by U.S. partner Dr. Sheffield and colleagues. The DMFS will be developed by drawing from methods developed by the Terrestrial Hydrology Group of Princeton University, integrated with seasonal drought forecasting derived from downscaled climate forecasts from the North America Multi-Model Ensemble (NMME)-II for predicting drought events in Indonesia.

Specifically, the goals of the project are (1) to improve the predictability of drought by developing a reliable monitoring and forecasting system; (2) to formulate a best framework for implementing a DCM model in Indonesia that incorporates local drought characteristics and community profiles; and (3) to test the effectiveness of the DCM model to reduce drought risk. To answer these questions, Dr. Kuswanto and his team will collect historical climate and hydrology data to characterize drought and use this to develop a drought prediction model based on climate prediction and statistical models. The two most vulnerable districts have been identified as the site for the pilot study for implementation of DCM: Probolinggo, East Java, and Lombok Utara, Nusa Tenggara Barat. They are listed as top priority districts due to their vulnerability to drought impacts. Based on participatory evaluations conducted on these two districts, statistical evidence will be evaluated to confirm the effectiveness of DCM. The U.S. collaborators will assist with the development of the DMFS for Indonesia, as well as with DCM implementation in the targeted districts. They will also provide remote sensing data required to build the system.

The Government of Indonesia (GoI) has made climate change mitigation and adaptation a national priority. Climate change resilience has been the focus of the GoI as part of the commitment to implementing the Sendai Framework for the Disaster Risk Reduction Framework. Climate change resilience has also become one of the focuses of the USAID mission in Indonesia. This PEER project supports these interests by focusing on a parallel strategy to strengthen extreme weather and climate resilience. The Meteorological Office Indonesia (BMKG) issues drought information from a simple monitoring system but with very low predictive capacity and hence drought forecasts have never been made properly. Moreover, the provided drought information is difficult for smallholders and communities to access directly, which has led to lack of actions to reduce the risk. Therefore, the DMFS coupled with an effective strategy for easy access to information by communities/smallholders, is urgently required. The DCM will frame how decisions are currently made at the smallholder and community levels in response to drought and determine whether decisions can be made (based on forecast information) to reduce drought risk. The project will ensure that communities and smallholders will have access to the drought information generated from the system, which is consistent with the idea of the DCM model.


Summary of Recent Activities


5-125 Andalas Award
Dr. Kuswanto (left) receives an award following his presentation and outreach at Andalas University (photo courtesy of Dr. Kuswanto).
The activities within the last quarter of 2019 were mainly devoted to data analysis and system development. The team members worked on system development of their program, which requires accounting for several details, especially surrounding code integration with raw data sources. Beyond that, the team conducted several workshops and meetings to further develop the project and build capacity in the region. At the end of October, the PEER team and ITS Department of Statistics organized a workshop on predictive analytics. The workshop was led by two professors from UiTM Malaysia and was presented to PEER project assistants and the general student body. The project assistants also attended The International Conference on Combinatoric, Graph Theory and Network Topology, organized by Jember University Indonesia that same month. A paper has been presented and accepted to be published in the conference proceedings. This was then followed by a workshop on scientific writing in December, where experts from Malaysia worked with and taught students best practices to produce good scientific publications.

Beyond the students, the PI also had an excellent quarter. Dr. Kuswanto was promoted to Director of Postgraduate Program and Academic Development and was also recognized by MIT. He was appointed as a board member of the MIT-Indonesia Research Alliance (MIRA) program. Through MIRA, the team was visited by MIT discuss improvements on the PEER project that can be done in the future. The team identified a collaborative research topic that they hope to explore with their colleagues in the near future.

On the outreach front, the team met with the Environmental Office as part the project’s objective to help the local government address issues related to climate change. Together with the Environmental Office of Surabaya City, the team carried out a study about the effectiveness of the Car Free Day program and its contribution to local climate issues. An intensive field survey was done and the team simultaneously promoted its results based sub-seasonal forecast to improve the societal awareness of extreme events. This was crucial, as October was the transition period from the dry to wet seasons, and historical records show that the probability of extreme rainfall occurrence is very high. Several intensive meetings with the EO have allowed the team formulate a significant policy recommendation for the government.

As the project approaches its conclusion (now extended through the end of August 2020), the team has several papers in preparation and plans to submit them to highlight their work on PEER. They also hope to finish with their system development and begin testing by the end of the project.

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