Nowadays, space-borne imaging spectro-radiometers are exploited for many environmental applications, including water quality monitoring. Turbidity is a standout amongst the essential parameters of water quality that affect productivity. The current study aims to utilize Landsat 8 surface reflectance (L8SR) to retrieve turbidity in the Ramganga River, a tributary of the Ganges River. Samples of river water were collected from 16 different locations on 13 March and 27 November 2014. L8SR images from6 March and 17 November 2014 were downloaded from the United States Geological Survey (USGS) website. The algorithm to retrieve turbidity is based on the correlation between L8SRreflectance (single and ratio bands) and insitu data. The b2/b4 and b2/b3 bands ratio are proven to be the best predictors of turbidity, with R² = 0.560 (p < 0.05) and R² = 0.726 (p < 0.05) for March and November, respectively. Selected models are validated by comparing the concentrations of predicted and measured turbidity. The results showed that L8SR is a promising tool for monitoring surface water from space, even in relatively narrow river channels, such as the Ramganga River.

中文翻译：

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Landsat 8 SR的时空尺度浊度反演：以印度恒河盆地拉姆甘加河为例

如今，星载成像光谱辐射仪被用于许多环境应用，包括水质监测。浊度是影响生产率的水质基本参数中的佼佼者。当前的研究旨在利用Landsat 8表面反射率（L8SR）来检索恒河支流Ramganga河中的浊度。2014年3月13日至11月27日在16个不同地点采集了河水样本。2014年3月6日至11月17日的L8SR图像可从美国地质调查局（USGS）网站下载。取回浊度的算法基于L8SR反射率（单个和比率带）与原位数据之间的相关性。事实证明，b2 / b4和b2 / b3谱带比率是浊度的最佳预测指标，R3月和11月分别为² = 0.560（p <0.05）和R ² = 0.726（p <0.05）。通过比较预测浊度和测量浊度的浓度来验证所选模型。结果表明，L8SR是监测太空中地表水的有前途的工具，即使在相对狭窄的河道（如Ramganga河）中也是如此。