Trida Ridho Fariz, Andin Vita Amalia, Abdul Jabbar, Rifa’ Atunnisa

Estimation Of Changes in Water Quality Parameters in Rawa Pening Lake Based on Remote Sensing Data

Introduction

Estimation of changes in water quality parameters in rawa pening lake based on remote sensing data. Analyze Rawa Pening Lake's water quality changes (TSS, water hyacinth) using remote sensing and Google Earth Engine. Reveals hypereutrophic conditions from 2017-2021.

Abstract

Lake Rawa Pening, in Indonesia, is one of the super lakes of revitalization priority. The factor that causes Lake Rawa Pening to become a priority lake is high sedimentation, which is triggered by the expansion of land cover such as settlement, agriculture, and industry in the Rawa Pening Catchment Area. This study examines changes in water quality parameters in Rawa Pening Lake from remote sensing data with Google Earth Engine (GEE). The physical parameters used to assess water quality are the concentration of Total Suspended Solid (TSS) and the area of water vegetation (water hyacinth). The results indicate that the water quality of Rawa lake has changed in the TSS level and the distribution area of aquatic vegetation. In general, from 2017, 2019 and 2021 there were fluctuations in the percentage of water hyacinth and TSS. Modeling results indicate that Lake Rawa Pening is mostly hypereutrophic.

Review

This study addresses the critical issue of water quality degradation in Rawa Pening Lake, Indonesia, identified as a national revitalization priority due to significant sedimentation. Utilizing remote sensing data processed through the Google Earth Engine (GEE) platform, the authors aim to estimate changes in key water quality parameters. Specifically, the research focuses on Total Suspended Solid (TSS) concentrations and the spatial extent of aquatic vegetation, particularly water hyacinth. The findings indicate fluctuations in both parameters over the period of 2017, 2019, and 2021, ultimately classifying the lake as predominantly hypereutrophic. The topic is highly relevant given the environmental challenges faced by many freshwater ecosystems globally, and the chosen methodology offers a powerful approach to monitor such changes. A notable strength of this work lies in its application of advanced remote sensing techniques and the Google Earth Engine platform, which offers a powerful and efficient means for analyzing large-scale temporal changes in water bodies. The selection of TSS and water hyacinth cover as indicators is appropriate, as both are direct visual and ecological manifestations of eutrophication and sedimentation, which the abstract identifies as primary issues for Rawa Pening. Focusing on a "super lake of revitalization priority" also underscores the practical importance and potential policy relevance of the study's outcomes. The explicit mention of temporal fluctuations (2017, 2019, 2021) suggests a valuable time-series analysis, providing essential insights into the lake's dynamic state. While the abstract presents compelling initial findings, it leaves several methodological details to be desired for a comprehensive review. The abstract mentions "modeling results" for hypereutrophication, but the specific models or algorithms used to derive TSS concentrations and water hyacinth area from remote sensing data, or to classify trophic status, are not elaborated upon. Clarity on the type of remote sensing data (e.g., satellite missions like Landsat, Sentinel) and the specific techniques employed for parameter estimation (e.g., band ratios, spectral indices, machine learning) would significantly enhance the abstract's scientific rigor. Furthermore, while changes and fluctuations are noted, the abstract does not quantify these changes or explicitly discuss the observed relationships between land cover changes in the catchment and the water quality parameters, which would strengthen the analysis of causality. Nevertheless, the study offers a timely and valuable contribution to understanding the ecological status of Rawa Pening Lake, providing essential data for conservation efforts.

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