Quantifying turbidity dynamics in lake water using OLS regression: A landsat 8 OLI-based remote sensing approach

IF 4.7 2区地球科学 Q1 WATER RESOURCES

Journal of Hydrology-Regional Studies Pub Date : 2025-06-20 DOI:10.1016/j.ejrh.2025.102523

Imran Ahmad , Amnah A. Alasgah , Martina Zelenakova , Mithas Ahmad Dar , Minwagaw Damtie , Marshet Berhan

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引用次数: 0

Abstract

Study region

Lake Tana, Ethiopia’s largest freshwater lake, has experienced a notable increase in water turbidity. This issue highlights the need for an in-depth understanding of how human activities and environmental changes are impacting its ecological balance. Addressing these turbidity challenges is crucial for safeguarding the sustainability of this vital resource.

Study focus

This research utilized Landsat 8 satellite imagery to examine turbidity levels in Lake Tana. Six bands from Landsat OLI—band 2, band 3, band 4, band 5, band 6, and band 7—were analyzed both individually and in combination. Ordinary least squares (OLS) regression modeling was applied to investigate the relationships between these bands and in-situ turbidity data.

New hydrological insights

Our findings reveal that the combined use of specific bands—particularly band 2 + band 5 - band 6—accounted for 87 % of the variance in turbidity as explained by the OLS regression model. Additionally, the Koenker- (Breusch-Pagan) statistic indicated no conflicting relationships (p > 0.005) within the model, affirming its reliability. To further validate the model’s impartiality, the Jarque-Bera test was performed. Polynomial and exponential regression analyses were also conducted, leading to the identification of an optimal regression equation for predicting the spatial distribution of turbidity in Lake Tana.

查看原文本刊更多论文

利用OLS回归定量湖泊水体浊度动态：基于landsat 8 oli的遥感方法

埃塞俄比亚最大的淡水湖塔纳湖的水浑浊度显著增加。这一问题突出了深入了解人类活动和环境变化如何影响其生态平衡的必要性。解决这些浊度挑战对于保护这一重要资源的可持续性至关重要。本研究利用Landsat 8卫星图像来检查塔纳湖的浊度水平。分别分析了Landsat oli的6个波段，即波段2、波段3、波段4、波段5、波段6和波段7。应用普通最小二乘（OLS）回归模型研究了这些波段与原位浊度数据之间的关系。新的水文见解我们的研究结果表明，结合使用特定波段-特别是波段2 + 波段5 -波段6 -占浊度方差的87 %，由OLS回归模型解释。此外，Koenker- (Breusch-Pagan)统计表明模型内没有冲突关系（p >； 0.005），证实了其可靠性。为了进一步验证模型的公正性，我们进行了Jarque-Bera检验。通过多项式回归和指数回归分析，确定了预测塔纳湖浑浊度空间分布的最优回归方程。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Journal of Hydrology-Regional Studies Earth and Planetary Sciences-Earth and Planetary Sciences (miscellaneous)

CiteScore

6.70

自引率

8.50%

发文量

284

审稿时长

60 days

期刊介绍： Journal of Hydrology: Regional Studies publishes original research papers enhancing the science of hydrology and aiming at region-specific problems, past and future conditions, analysis, review and solutions. The journal particularly welcomes research papers that deliver new insights into region-specific hydrological processes and responses to changing conditions, as well as contributions that incorporate interdisciplinarity and translational science.