We can't find the internet
Attempting to reconnect
Something went wrong!
Hang in there while we get back on track
Dispersal of Plastic Waste in Khlong U-tapao Subbasin Towards the Lower Songkhla Lake, Southern Thailand: a Gis-ahp Approach
AI summary Read the abstract
A GIS and Analytic Hierarchy Process analysis of the Khlong U-Tapao watershed in Thailand identified urban centers as the primary source of plastic waste entering the Songkhla Lake system, with monsoon rainfall and flooding significantly increasing leakage rates. The spatial modeling approach provides precise data to guide future sustainable marine debris management strategies.
Plastic waste that is not properly managed and leaks into the sea is becoming a serious problem of marine debris.The aim of this study is to analyze the distribution of plastic waste in the Khlong U-Tapao Sub-basin, which flows into the lower Songkhla Lake, Thailand, by using a geographic information system (GIS) and the Analytic Hierarchy Process (AHP), a multi-criteria decision analysis process (MCDA).Physical factors and different geographic environmental characteristics, for a total of 16 data layers representing the origin of plastic waste, rainfall, wind speed and wind direction, slope, past flood events areas, land use, distance from stream, the flow characteristics of the river and distance from the ocean, were collected from field survey and analyzed using GIS.The results showed that towns and cities are where most plastic waste leaks occurred.The majority of this waste enters the Khlong U-Tapao River.The rate of plastic waste leakage is higher during the monsoon and when there are floods.The output of this GIS-AHP method offers incredibly precise spatial data.This study effectively demonstrates how plastic waste from the land flows into the Khlong U-Tapao River and other streams that are connected to the lower Songkhla Lake.The findings can be used to develop guidelines for sustainable management of marine debris in the future.
More Papers Like This
Analysis of Potential Areas of Plastic Waste Pollution Sources into the Ciliwung River Based on GIS and Multi-Criteria Decision Analysis (MCDA)
AI summary Read the abstract
Researchers used GIS and Multi-Criteria Decision Analysis to map plastic waste pollution risk across the Ciliwung River Basin in Indonesia, finding that 16% of the basin is high-risk, with densely populated informal settlements on disturbed riverbanks identified as the primary contributors to plastic leakage into the river.
A geospatial investigation of microplastics leaching in Ubon Ratchathani province, Thailand: fuzzy logic-based analysis
AI summary Read the abstract
Researchers applied GIS combined with fuzzy logic analysis in Ubon Ratchathani province, Thailand to map microplastic leakage sources and predict pollution transport through river networks, demonstrating that this spatial modeling approach can identify priority catchment areas for microplastic management.
Multicriteria Decision Analysis Addressing Marine and Terrestrial Plastic Waste Management: A Review
AI summary Read the abstract
This systematic review analyzed 20 studies using multicriteria decision analysis (MCDA) to evaluate plastic waste management strategies across three continents, finding that AHP was the most popular method and that multi-strategy combinations consistently outperformed single-approach solutions.
Analisis Karakteristik Sampah Nonorganik Dan Strategi Penguranganya Di Kawasan Suci Laut Provinsi Bali
AI summary Read the abstract
Survey of inorganic litter in four sacred coastal areas of Bali found that 56% was inorganic material with soft plastics dominant in buffer and beach zones, while community perceptions of waste management did not match actual litter conditions. This study directly informs microplastic research by documenting plastic litter accumulation patterns in high-footfall coastal environments, where fragmentation of soft plastics is a primary source of secondary microplastic generation.
Plastic pollution load Model based on Stepwise regression Analytic hierarchy process
AI summary Read the abstract
Researchers developed a plastic pollution load model using stepwise regression and analytic hierarchy process methods to estimate plastic pollution levels across regions based on factors like population density, vegetation cover, and industrial activity. The model aims to quantify plastic pollution burden and identify where intervention will have the greatest impact.
Research digests by email
When a large batch of papers lands in the Atlas, we read through it and send a short write-up of what stood out.