E3S Web Conf.
Volume 125, 2019The 4th International Conference on Energy, Environment, Epidemiology and Information System (ICENIS 2019)
|Number of page(s)||9|
|Published online||28 October 2019|
Estimation of Waste Generation from Tidal Flood in North Semarang Sub-District
1 Department of Urban and Regional Planning, Faculty of Engineering, Diponegoro University, 50275 Semarang – Indonesia
* Corresponding author: firstname.lastname@example.org
Tidal floods often occur in North Semarang Sub-District due to rising sea levels. One of the impacts is waste generation. Waste management is needed to prevent environmental degradation. An important factor is quantity of waste for the management plan. The purpose of this study to estimate waste generation from tidal floods. Scenario models are needed to find out the area affected because there is no existing data. Scenario data uses DEMNAS, land subsidence data, tidal data, and Sea Level Rise data. The Admiralty method is used to determine the Highest High Water Level (HHWL) value, the quantitative spatial method for the tidal flood scenario and the estimated quantity of waste. Calculation of the HHWL value of 1.16 m is added to the SLR data. The result of tidal flood height is 1.27 m. There are three affected villages (Panggung Lor, Bandarharjo, and Tanjungmas) and affected area is 55.95 Ha. The accuracy rate is 82.86% which is tested using Confusion Matrix. The results of the scenario model are arranged in a grid and then sampled. The estimated waste yield is 70,095.26 kg. The benefits of this data are to facilitate cleaning agent in waste management including cost and technical planning.
Key words: tides / sea levels rise / tidal floods / disaster waste generation
© The Authors, published by EDP Sciences, 2019
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.