The length of Riau coastlines, Indonesia were approximately 900 km long. Hence, there has been difficulty in prioritizing managing various locations of the coastline damages based on a systematic approach. The objectives of this paper are to apply the state of art in the identification of 16 major coastlines vulnerability index in Riau, and to prioritizing which coastlines should be managed in terms of 4 main aspects such as; technical aspect, economic, environmental, and strategic one. The methodology applied in this paper utilized the combination of the Coastal Vulnerability Index (CVI) and social economic approaches using a Likert’s scale of 1 (low) to 5 (very high). This study has recommended a priority in managing the coastlines in Riau was as follow; Pambang Pesisir, Bengkalis and Tanah Merah, Meranti Islands. These coastlines were calculated as the very high level of vulnerability indexes of 75.3 and 74.9 respectively. This study also simulated the use of shoreline protection structure by Genesis software utilizing a revetment construction. The results showed that the construction of revetment structure in Pambang pesisir beach may reduce the shore erosion rate from 10 m/14 year to 0 m /14 year.

The annual peat fire disasters have suffered human life, deteriorated peat land ecosystems, and caused severe economic losses in Indonesia, Malaysia, Brunei, and Singapore during a period of 2014-2016. The objective of this study is to investigate to what extent the weather modification technology (WMT) may play its roles in increasing the precipitation rates in order to mitigate the peat fires disaster in Bengkalis, Riau Province, Indonesia. The study obtained the precipitation rates data from the tropical rainfall measuring mission (TRMM) satellite during the period of 2014, 2015 and 2016. The data then statistically analyzed using the Grads software package. While the process of WMT at the designated research location was evaluated together between the Artificial Rain Unit of BPPT (Agency for the Assessment and Application Technology), and the Engineering Faculty, University of Riau, 2016. The research showed that the WMT increased the rainfall rates during the dry season within the study area by 8% (520.7 mm to 557 mm) in the 3 months period (July 14 -October 6, 2016), and reducing significantly hotspots by 88.6% from 6.725 in 2014 to 770 in 2016. Hence, it confirmed that the application of technical WMT procedures may increase precipitation rates and reduce the number of hot spots in Bengkalis.

Purpose We conducted this project to develop a feasible method for mapping tropical peat lands of Bengkalis Island—as a test site—in Indonesia. Materials and methods The method based on limited availability of field measurements and a wide range of remotely sensed spatial datasets like radar elevation product, MODIS, and Landsat imageries. We applied land use category based sampling to extend existing field data of peat thickness. New peat thickness data was collected by boring and simultaneous electrical resistivity tomography (ERT). Based on remotely sensed and field data sets, peat maps were compiled by simulated spatial annealing. Peat map statistics were derived after 500 runs including mean, median, minimum, maximum, and percentile values. Results and discussion The resulted maps represent the limiting values of expected peat thickness using 90% confidence level. Results showed that ERT is suitable for determining peat layer thickness. Using independent samples, we found that peat thickness predictions tend to overestimate peat thickness by ca. 2 m in general. Conclusions According to predictions, the peat volume of Bengkalis Island is estimated to be in the range of 3.28–3.58 km³.

This article objective was to identify, assess, simulate, and mitigate risks of delay for the construction of new pressure maintenance (NPM) project located in Duri, Indonesia, based on the combination of stochastic and sensitivity analyses. These both analyses methods are not new but relatively unique to be applied in the area of oil industry especially in Indonesia in generating specific result findings. There were identified 16 major activities are sensitive causing the construction delay. Five significant risks such as; delay in procuring labors, material, and equipment, as well as changes in design and specifications, contributed to the project delay. Based on the stochastic risk analyses, it was identified that an 80% probability of the project would delay for 48 working days. These risks were classified as a high-risk project (delay > 20% from the initial construction project schedule). After conducting risk simulation and risk mitigation measures there were 80% probabilities for reducing the construction delay up to 52.08%. The application of these methods and 6 stages in managing risks would be as an important reference for the oil industry stakeholders in the identification, assessing, and mitigating any possible delays and risks during the construction phase systematically.