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Herr Soeryantono
Department of Civil Engineering, Faculty of Engineering, Universitas Indonesia
Agriculture, Biological Sciences & Forestry Humanities Energy Environmental Science Social Sciences

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A QUANTITATIVE DYNAMIC MODEL FOR MANAGING LITTER ABUNDANCE IN THE TRASH TRAP OF AN URBAN LAKE IN INDONESIA Muhsin, Muhammad; Soeryantono, Herr
Journal of Environmental Science and Sustainable Development Vol. 2, No. 1
Publisher : UI Scholars Hub

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Abstract

In Indonesia, urban litter is threatening the role of urban lakes as a part of green infrastructures in cities. To overcome this issue, Kenanga Lake—an urban lake with a surface area of 2.8 ha located within the Universitas Indonesia Campus—has been equipped with a trash trap unit on its inlet. However, the large amount of litter and its unpredictable pattern have made trash trap management difficult. The previous study illustrated the conceptual diagram of this problem. As a continuation in terms of looking further for sustainable solutions to this problem, this study aimed to establish its quantitative dynamic model, which is expressed as the mathematical equations of the interrelations among elements. We developed the model using the system dynamics modeling method with the Powersim Studio 10 software and validated it using the Average Mean Error (AME) method. To help calibrate the model, several supporting methods, i.e., field observation, load–weight analysis continuous sampling, and Theory of Planned Behavior (TPB)-based questionnaire survey, were used. Results showed that, on a sunny day, the maximum inlet lake litter load is 33 g/m3/h. Meanwhile, if rain falls, the maximum inlet lake litter load increases tenfold and reaches 346 g/m3/h. Then, the survey found that 22% of the citizens living in the location have a strong intention to dump their waste into the waterway. Moreover, the model has been validated, with the AME value of 0.1079 or confidence level of 89.21%. Finally, we conclude that the TPB-based questionnaire survey method can be combined with the system dynamics modeling method to capture the human sociocultural aspect of the system quantitatively. The applied methods can be used to solve the typical litter abundance problem in other urban lakes.
Soil Erosion Prediction Using GIS and Remote Sensing on Manjunto Watershed Bengkulu, Indonesia Gunawan, Gusta; Sutjiningsih, Dwita; Soeryantono, Herr; Widjanarko, Soelistiyoweni
JOURNAL OF TROPICAL SOILS Vol. 18 No. 2: May 2013
Publisher : UNIVERSITY OF LAMPUNG

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5400/jts.2013.v18i2.141-148

Abstract

The study aims to assess the rate of erosion that occurred in Manjunto Watershed and financial loss using Geographic Information System and Remote Sensing. Model used to determine the erosion is E30 models. The basis for the development of this model is to integrate with the slope of the slope between NDVI. The value of NDVI obtained from satellite imagery. Slope factor obtained through the DEM processing. To determine the amount of economic losses caused by erosion used the shadow prices. The amount of nutrients lost converted to fertilizer price. The results showed that the eroded catchment area has increased significantly. The rate of average annual erosion in the watershed Manjunto in 2000 amounted to 3 Mg ha-1 yr-1. The average erosion rate in the watershed Manjunto annual increase to 27 Mg ha-1 yr-1 in the year 2009. Economic losses due to erosion in 2009 was Rp200,000,- for one hectare. Total losses due to erosion for the total watershed area is Rp15,918,213,133, -. The main factor causing the high rate of erosion is high rainfall, slope and how to grow crops that do not pay attention to the rules of conservation.Keywords: Soil erosion, digital elevation model, GIS, remote sensing, valuation erosion[How to Cite: Gunawan G, D Sutjiningsih, H Soeryantono and S Widjanarko. 2013.Soil Erosion Prediction Using GIS and Remote Sensing on Manjunto Watershed Bengkulu-Indonesia. J Trop Soils 18 (2): 141-148. Doi: 10.5400/jts.2013.18.2.141][Permalink/DOI: www.dx.doi.org/10.5400/jts.2013.18.2.141]REFERENCESAksoy E, G Ozsoy and MS Dirim. 2009. Soil mapping approach in GIS using Landsat satellite imagery and DEM data. Afr J Agric Res 4: 1295-1302.Ananda J and G Herath. 2003. Soil erosion in developing countries: a socio-economic appraisal. J Environ Manage 68: 343-353.Ananda J, G Herath and A Chisholm. 2001. Determination of yield and Erosion Damage Functions Using Subjectivly Elicited Data: application to Smallholder Tea in Sri Lanka. 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Co-Authors Dwita Sutjiningsih Evi Anggraheni, Evi Gusta Gunawan Muhammad Muhsin, Muhammad Sulistioweni W. Widjanarko, Soelistiyoweni