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EN
West Papua province in eastern Indonesia is positioned in a dynamic tectonic zone along with the collision of the Australian, Pacific, and Eurasian plates. The interaction resulted in the formation of strike-slip faults such as Koor, Sorong, Ransiki, and Yapen, that are prone to earthquakes in the region. The rocks of West Papua in the northern part are a contribution to the Pacific Ocean plate consisting of ophiolite and volcanic arcs of the archipelago, even while the rocks of the Australian plate in the southern part are dominated by quaternary and siliciclastic sedimentary. It has a wide variety of resources, including oil and gas. This study combines the interpretation of regional gravity and magnetic data derived from satellite observations to identify the subsurface structure of West Papua. This is performed since most studies were conducted on the surface and did not significantly focus on the subsurface. The composition of subsurface is determined through three-dimensional (3-D) unconstrained inversion modeling using the iterative reweighting inversion of regional gravity and magnetic anomalies as a function of density contrast and magnetic susceptibility of rocks. In depth variations, gravity inversion produces density contrast ranging from −0.348 to 0.451 gr/cm3 , whereas magnetic inversion provides rock susceptibility varying between −0.363 and 0.223 SI. Gravity and magnetic inversions characterize the subduction of the Pacific Ocean plate in the north, extensive intrusion of igneous rocks, and low density-susceptibility contrast in the Bintuni basin as a source of oil and natural gas. The boundary between the sediment layer and the basement is believed to be 15–20 km deep, with rocks from the uplifted mantle in the north and a Silur-Devon aged Kemum formation in the south.
EN
This study aims to utilise Climate Hazards Group Infrared Precipitation with Stations (CHIRPS) data and Standardised Precipitation Index (SPI) method to assess agricultural drought in West Papua, Indonesia. The data used in this study is monthly CHIRPS data acquired from 1996 to 2019, daily precipitation data recorded from 1996 to 2019 from the five climatological stations in West Papua, Indonesia located at Sorong, Fakfak, Kaimana, Manokwari, and South Manokwari. 3-month SPI or quarterly SPI are used to assess agricultural drought, i.e., SPI January-March, SPI February-April, SPI March-May, SPI April-June, SPI May-July, SPI June-August, SPI July-September, SPI August-October, SPI September-November, and SPI October-December. The results showed that in 2019 agricultural drought in West Papua was moderately wet to severely dry. The most severely dry occurred in September-December periods. Generally, CHIRPS data and SPI methods have an acceptable accuracy in generating drought information in West Papua with an accuracy of 53% compared with climate data analysis. Besides, the SPI from CHIRPS data processing has a moderate correlation with climate data analysis with an average R2= 0.51.
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