ANALYSIS OF THE EFFECTS OF LAND USE CHANGE ON WATER QUALITY IN THE UPPER CITARUM RIVER USING MULTIPLE LINEAR REGRESSION AND REDUNDANCY ANALYSIS

Water quality is crucial for determining its suitability for various domestic, industrial, agricultural, and environmental needs. Over time, water quality may degrade due to land use changes, including those in water, forest, built-up, farmland and landscape configurations across different catchm...

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Bibliographic Details
Main Author: Nirmayanti
Format: Theses
Language:Indonesia
Subjects:
Online Access:https://digilib.itb.ac.id/gdl/view/84757
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Institution: Institut Teknologi Bandung
Language: Indonesia
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Summary:Water quality is crucial for determining its suitability for various domestic, industrial, agricultural, and environmental needs. Over time, water quality may degrade due to land use changes, including those in water, forest, built-up, farmland and landscape configurations across different catchment areas. This study aims to evaluate the impact of land use changes on the water quality of the Upper Citarum River in the Wangisagara, Koyod, Cisirung, and Nanjung catchment areas, based on land use changes from 2014, 2017, and 2022. The water quality parameters analyzed include EC, WT, pH, TDS, TSS, NH3-N, BOD, COD, DO, NO3-N, and free chlorine, which are influenced by spatial, temporal, and seasonal variations. Multiple Linear Regression identifies a set of land use variables that affect individual water quality parameters. The analysis shows that the water are negatively correlated with WT but positively correlated with free chlorine. EC, and free chlorine are negatively correlated with forest. Built-up are positively correlated with COD, BOD, and WT. Farmland is positively correlated with NO3-N, NH3-N, and TSS, while LSI is negatively correlated with COD. ED is negatively correlated with free chlorine and CONTAG is positively correlated with BOD. Redundancy Analysis provides an overview of a set of land use variables affecting a set of water quality variables. The results reveal that the water is the primary predictor of water quality parameters. The impact of land use in the Cisirung catchment area produces a better model compared to other catchment areas.