DROUGHT MITIGATION IN LIMBOTO BULANGO BONE RIVER BASIN IN GORONTALO PROVINCE

According to the 5th Assessment Report of the Intergovernmental Panel on Climate Change, one of the key risks is increasing risk of drought-related water and food shortage. The recommended adaptation is disaster preparedness including early-warning systems and local coping strategies. Indonesia as an archipelago country which is located around the equator has three types of climate. Being inhabited by 267 million people, Indonesia is vulnerable to be affected by climate change including drought. Adaptation to drought is not only carried out through a structural approach but also needs to be supplemented by a non-structural approach based on risk management. Drought disaster management requires a model that is capable of monitoring while at the same time predicting drought for enhancing anticipatory actions to reduce the risk. Limboto-Bulango-Bone (LBB) River Basin is selected in this study to represent other regional conditions due to its data availability. In order to monitor the meteorological drought, the data should be spread evenly in a space with the same length of observation period at all stations, at least 20 years. Major problems in data availability are (1) most rainfall stations are usually located in downstream area; (2) the length or data period is not the same at one station with another station; (3) monthly rainfall data series contain missing record; and (4) most of available data have not been verified through the quality control process. To overcome these obstacles, global data with a 28 km x 28 km grid, called TRMM. Naturally, the TRMM data should be corrected in advance for the selected ground stations that have been selected after going through a simple quality control process. The magnitude, duration, and intensity of drought is estimated by SPI Method on basis of real time monthly rainfall. Validation of the drought index in the form of magnitude, duration and drought intensity is conducted by comparing it with the total area of rice fields that is affected by crop failure due to drought obtained from the Ministry of Agriculture. LBB River Basin with the equatorial type of rainfall experiences a dry season twice a year spread around February-March and July-October. This type of rain is prone to drought, especially agricultural drought. The drought index for 20 years (1998-2017) showed that the worst drought was occurred in 2015 with a duration of more than 10 months. The drought index has a strong relationship with the teleconnection index called Oceanic Nino Index or ONI especially in the dry season. ONI predictions for the next 6 months can be downloaded every month, so the drought index predictions for the next 6 months can also be estimated as long as the equation used is quite reliable. The worst correlation coefficient in January is less than 0.2 then in May and June it is less than 0.6 and in other months the correlation is more than 0.6, the best in March and October is approaching 0.9. Relationship between ONI and the Drought Index: the worst correlation coefficient in January is less than 0.2 then in May and June is less than 0.6 and in other months the correlation is more than 0.6, the best in March and October is approaching 0.9. The drought monitoring and forecast model is the main basis for drought mitigation measures.