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You searched for subject:(Data poor environment). Showing records 1 – 2 of 2 total matches.

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Delft University of Technology

1. Keulers, Bob (author). Siltation Mitigation In A Data Poor Environment: Assessing The Influence Of A Sluice On Siltation Rates In The Nga Moe Yeik Creek, Yangon.

Degree: 2018, Delft University of Technology

The typically mild slopes of the muddy coastline in the south of Myanmar, enable the tide to propagate deep into the mainland, carrying muddy and saline water. The Nga Moe Yeik Creek (a tributary of the Yangon River) is closed off at the upstream end during the dry season and is subject to high siltation rates. Extensive dredging is necessary to ensure navigability. However, dredging activities stopped in 2015 because dredging appeared to be insufficient. Flushing the creek, by opening the Nga Moe Yeik Creek Sluice Gates more often could contribute to a solution to minimise the siltation rates, leading to lowered dredging volumes and an improved navigability of the creek. However, it may decrease the availability of irrigation and drinking water behind the sluice in the dry season. The responsible authorities are looking for an optimal solution. The current insight in the siltation problem is limited due to a lack of measured data collected in the Nga Moe Yeik Creek. The general consensus is that siltation rates can be decreased by an improved operating scheme of the Nga Moe Yeik Sluice Gates. Since data resources are scarce or not available at all, data on bathymetry, water levels and suspended sediment concentration is collected from the field between May and July 2017. The observed water levels show a flood-dominant tidal wave with a tidal range in the order of 4 - 6 meters. Depths are measured in a zigzag pattern in the creek stretch between mouth and sluice. Suspended sediment concentrations are measured between 0.3 and 1 gram/L. Tidally and depth averaged concentrations in the order of 0.5 gram/L and 0.4 gram/L are observed at respectively 2 and 17 km from the mouth of the creek. Part of this data is used to set up a Delft3D-flow model of the system that simulates the main sediment transport processes in the Nga Moe Yeik Creek. The initial hydrodynamic model is calibrated against observed water levels. In the next phase, the sediment transport model is used in a qualitative analysis to determine best suitable sediment parameters. Using a combination of model and collected data it is aimed to increase the insight in the siltation problem. Both model and data showed similar hydrodynamic and sediment transport processes. The water level observations showed that the tidal wave deforms asymmetrically and becomes more flood-dominant as it propagates into the creek. A similar phenomenon is observed in the model results. Forced with a constant 2 gram/L the model generated tidally and depth averaged sediment concentrations in the same order of magnitude as the observations. From field observations and personal communication with local authorities, it is known that the siltation is most severe in the upstream end of the creek. This is also confirmed by the model results. In the scope of this work it is assumed that the model gives reliable results on the assessment of water levels and siltation. The final model was used to assess several flushing scenarios (continuously or… Advisors/Committee Members: Aarninkhof, Stefan (mentor), van Maren, Bas (graduation committee), Hendriks, Erik (graduation committee), Commandeur, Alwin (graduation committee), Rutten, Martine (mentor), Delft University of Technology (degree granting institution).

Subjects/Keywords: Siltation; Tidal basin; Data poor environment; D3D-flow; Fieldwork; Yangon

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Keulers, B. (. (2018). Siltation Mitigation In A Data Poor Environment: Assessing The Influence Of A Sluice On Siltation Rates In The Nga Moe Yeik Creek, Yangon. (Masters Thesis). Delft University of Technology. Retrieved from http://resolver.tudelft.nl/uuid:02a70eb1-e9cd-402a-958a-284e93571176

Chicago Manual of Style (16th Edition):

Keulers, Bob (author). “Siltation Mitigation In A Data Poor Environment: Assessing The Influence Of A Sluice On Siltation Rates In The Nga Moe Yeik Creek, Yangon.” 2018. Masters Thesis, Delft University of Technology. Accessed October 20, 2020. http://resolver.tudelft.nl/uuid:02a70eb1-e9cd-402a-958a-284e93571176.

MLA Handbook (7th Edition):

Keulers, Bob (author). “Siltation Mitigation In A Data Poor Environment: Assessing The Influence Of A Sluice On Siltation Rates In The Nga Moe Yeik Creek, Yangon.” 2018. Web. 20 Oct 2020.

Vancouver:

Keulers B(. Siltation Mitigation In A Data Poor Environment: Assessing The Influence Of A Sluice On Siltation Rates In The Nga Moe Yeik Creek, Yangon. [Internet] [Masters thesis]. Delft University of Technology; 2018. [cited 2020 Oct 20]. Available from: http://resolver.tudelft.nl/uuid:02a70eb1-e9cd-402a-958a-284e93571176.

Council of Science Editors:

Keulers B(. Siltation Mitigation In A Data Poor Environment: Assessing The Influence Of A Sluice On Siltation Rates In The Nga Moe Yeik Creek, Yangon. [Masters Thesis]. Delft University of Technology; 2018. Available from: http://resolver.tudelft.nl/uuid:02a70eb1-e9cd-402a-958a-284e93571176


University of Southern California

2. Valenti, Adrianna D. Estimating populations at risk in data-poor environments: a geographically disaggregated analysis of Boko Haram terrorism 2009-2014.

Degree: MS, Geographic Information Science and Technology, 2015, University of Southern California

The increasing threat and globalization of terrorism has heightened the need for estimating the geographical extent of population at risk to terrorist attacks. These estimations provide effective and efficient analyses to support various organizations for estimating necessary aid resources as well as identifying areas that require military and governmental involvement. With no consistent framework available for studying terrorism risk or handling data gaps, the goal of this study is to provide a baseline methodology for spatially estimating population at risk within a data-poor environment (Willis et al. 2005). This thesis examines the Islamic insurgent group, Boko Haram, and their historical attacks within Borno State, Nigeria over a five year period from July 2009 to June 2014. Data is disaggregated using a dasymetric mapping method designed to increase spatial quality to provide a more intimate look at risk throughout the state. Cox Regression, a statistical method to analyze time between events in accordance with covariates’ relationships, estimates risk through hazard ratios which are applied to spatial cells. Classified risk cells are used to estimate population at risk in areas through this model. Results depict detailed areas and population at risk to Boko Haram terrorism, the spread of Boko Haram from Borno State to nearby areas over time, and geographic variables which increase odds of Boko Haram attacks to occur. These results are useful to understand the areas and amount of people affected by Boko Haram terrorism and aim to improve methods and techniques using geographic information systems (GIS) and statistical methods for risk analysis. Geographically disaggregating data in data-poor countries provides previously unknown insights to analytical problems potentially facilitating solutions for various subjects such as medical and environmental crises, terrorism, and urban development. Advisors/Committee Members: Warshawsky, Daniel N. (Committee Chair), Oda, Katsuhiko (Committee Member), Lee, Su Jin (Committee Member).

Subjects/Keywords: Boko Haram; terrorism; data-poor environment; data quality; estimating population; estimate population at risk; risk; risk analysis; dasymetric; regression; Cox regression

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Valenti, A. D. (2015). Estimating populations at risk in data-poor environments: a geographically disaggregated analysis of Boko Haram terrorism 2009-2014. (Masters Thesis). University of Southern California. Retrieved from http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/545402/rec/2501

Chicago Manual of Style (16th Edition):

Valenti, Adrianna D. “Estimating populations at risk in data-poor environments: a geographically disaggregated analysis of Boko Haram terrorism 2009-2014.” 2015. Masters Thesis, University of Southern California. Accessed October 20, 2020. http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/545402/rec/2501.

MLA Handbook (7th Edition):

Valenti, Adrianna D. “Estimating populations at risk in data-poor environments: a geographically disaggregated analysis of Boko Haram terrorism 2009-2014.” 2015. Web. 20 Oct 2020.

Vancouver:

Valenti AD. Estimating populations at risk in data-poor environments: a geographically disaggregated analysis of Boko Haram terrorism 2009-2014. [Internet] [Masters thesis]. University of Southern California; 2015. [cited 2020 Oct 20]. Available from: http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/545402/rec/2501.

Council of Science Editors:

Valenti AD. Estimating populations at risk in data-poor environments: a geographically disaggregated analysis of Boko Haram terrorism 2009-2014. [Masters Thesis]. University of Southern California; 2015. Available from: http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/545402/rec/2501

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