Search results for: ANUGA

Authors: Hengki Eko Putra, Dennish Ari Putro, Tri Wahyu Hadi, Edi Riawan, Junnaedhi Dewa Gede, Aditia Rojali, Fariza Dian Prasetyo, Yudhistira Satya Pribadi, Dita Fatria Andarini, Mila Khaerunisa, Raditya Hanung Prakoswa

Abstract:

Catastrophe risk management can only be done if we are able to calculate the exposed risks. Jakarta is an important city economically, socially, and politically and in the same time exposed to severe floods. On the other hand, flood risk calculation is still very limited in the area. This study has calculated the risk of flooding for Jakarta using 2-Dimensional Model ANUGA. 2-Dimensional model ANUGA and 1-Dimensional Model HEC-RAS are used to calculate the risk of flooding from 13 major rivers in Jakarta. ANUGA can simulate physical and dynamical processes between the streamflow against river geometry and land cover to produce a 1-meter resolution inundation map. The value of streamflow as an input for the model obtained from hydrological analysis on rainfall data using hydrologic model HEC-HMS. The probabilistic streamflow derived from probabilistic rainfall using statistical distribution Log-Pearson III, Normal and Gumbel, through compatibility test using Chi Square and Smirnov-Kolmogorov. Flood event on 2007 is used as a comparison to evaluate the accuracy of model output. Property damage estimations were calculated based on flood depth for 1, 5, 10, 25, 50, and 100 years return period against housing value data from the BPS-Statistics Indonesia, Centre for Research and Development of Housing and Settlements, Ministry of Public Work Indonesia. The vulnerability factor was derived from flood insurance claim. Jakarta's flood loss estimation for the return period of 1, 5, 10, 25, 50, and 100 years, respectively are Rp 1.30 t; Rp 16.18 t; Rp 16.85 t; Rp 21.21 t; Rp 24.32 t; and Rp 24.67 t of the total value of building Rp 434.43 t.

Keywords: 2D hydrodynamic model, ANUGA, flood, flood modeling

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Authors: Olivia A. Wilson, Hannah E. Power, Murray Kendall

Abstract:

Sydney Harbour is an iconic location with a dense population and low-lying development. On the east coast of Australia, facing the Pacific Ocean, it is exposed to several tsunamigenic trenches. This paper presents a component of the most detailed assessment of the potential for earthquake-generated tsunami impact on Sydney Harbour to date. Models in this study use dynamic tides to account for tide-tsunami interaction. Sydney Harbour’s tidal range is 1.5 m, and the spring tides from January 2015 that are used in the modelling for this study are close to the full tidal range. The tsunami wave trains modelled include hypothetical tsunami generated from earthquakes of magnitude 7.5, 8.0, 8.5, and 9.0 M_W from the Puysegur and New Hebrides trenches as well as representations of the historical 1960 Chilean and 2011 Tohoku events. All wave trains are modelled for the peak wave to coincide with both a low tide and a high tide. A single wave train, representing a 9.0 M_W earthquake at the Puysegur trench, is modelled for peak waves to coincide with every hour across a 12-hour tidal phase. Using the hydrodynamic model ANUGA, results are compared according to the impact parameters of inundation area, depth variation and current speeds. Results show that both maximum inundation area and depth variation are tide dependent. Maximum inundation area increases when coincident with a higher tide, however, hazardous inundation is only observed for the larger waves modelled: NH90high and P90high. The maximum and minimum depths are deeper on higher tides and shallower on lower tides. The difference between maximum and minimum depths varies across different tidal phases although the differences are slight. Maximum current speeds are shown to be a significant hazard for Sydney Harbour; however, they do not show consistent patterns according to tide-tsunami phasing. The maximum current speed hazard is shown to be greater in specific locations such as Spit Bridge, a narrow channel with extensive marine infrastructure. The results presented for Sydney Harbour are novel, and the conclusions are consistent with previous modelling efforts in the greater area. It is shown that tide must be a consideration for both tsunami modelling and emergency management planning. Modelling with peak tsunami waves coinciding with a high tide would be a conservative approach; however, it must be considered that maximum current speeds may be higher on other tides.

Keywords: emergency management, sydney, tide-tsunami interaction, tsunami impact

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Authors: Thaminda Liyanage, Anuga Liyanage, Chamila Kurukulasuriya, Sidath Bandara

Abstract:

Background: The burden of chronic kidney disease (CKD) is growing rapidly around the world, particularly in Asia. Over the last two decades Sri Lanka has experienced an epidemic of CKD with ever growing number of patients pursuing medical care due to CKD and its complications, specially in the “Mahaweli” river basin in north central region of the island nation. This was apparently a new form of CKD which was not attributable to conventional risk factors such as diabetes mellitus, hypertension or infection and widely termed as “CKD-unknown” or “CKDu”. In the past decade a number of small scale studies were conducted to determine the aetiology, prevalence and complications of CKDu in North Central region. These hospital-based studies did not provide an accurate estimate of the problem as merely 10% or less of the people with CKD are aware of their diagnosis even in developed countries with better access to medical care. Interestingly, similar observations were made on the changing epidemiology of obesity in the region but no formal study was conducted to date to determine the magnitude of obesity burden. Moreover, if increasing obesity in the region is associated with CKD epidemic is yet to be explored. Methods: We will conduct an area wide cross sectional survey among all adult residents of the “Mahaweli” development project area 5, in the North Central Province of Sri Lanka. We will collect relevant medical history, anthropometric measurements, blood and urine for hematological and biochemical analysis. We expect a participation rate of 75%-85% of all eligible participants. Participation in the study is voluntary, there will be no incentives provided for participation. Every analysis will be conducted in a central laboratory and data will be stored securely. We will calculate the prevalence of obesity and chronic kidney disease, overall and by stage using total number of participants as the denominator and report per 1000 population. The association of obesity and CKD will be assessed with regression models and will be adjusted for potential confounding factors and stratified by potential effect modifiers where appropriate. Results: This study will provide accurate information on the prevalence of obesity and CKD in the region. Furthermore, this will explore the association between obesity and CKD, although causation may not be confirmed. Conclusion: Obesity and CKD are increasingly recognized as major public health problems in Sri Lanka. Clearly, documenting the magnitude of the problem is the essential first step. Our study will provide this vital information enabling the government to plan a coordinated response to tackle both obesity and CKD in the region.

Keywords: BMI, Chronic Kidney Disease, obesity, Sri Lanka

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