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Harmful algal blooms (HABs) diminish the utility of reservoirs for drinking water supply, irrigation, recreation, and ecosystem service provision. HABs decrease water quality and are a significant health concern in surface water bodies. Near real‐time monitoring of HABs in reservoirs and small water bodies is essential to understand the dynamics of turbidity and HAB formation. This study uses satellite imagery to remotely sense chlorophyll‐a concentrations (chl‐a), phycocyanin concentrations, and turbidity in two reservoirs, the Grand Lake O′ the Cherokees and Hudson Reservoir, OK, USA, to develop a tool for near real‐time monitoring of HABs. Landsat‐8 and Sentinel‐2 imagery from 2013 to 2017 and from 2015 to 2020 were used to train and test three different models that include multiple regression, support vector regression (SVR), and random forest regression (RFR). Performance was assessed by comparing the three models to estimate chl‐a, phycocyanin, and turbidity. The results showed that RFR achieved the best performance, with R2 values of 0.75, 0.82, and 0.79 for chl‐a, turbidity, and phycocyanin, while multiple regression had R2 values of 0.29, 0.51, and 0.46 and SVR had R2 values of 0.58, 0.62, and 0.61 on the testing datasets, respectively. This paper examines the potential of the developed open‐source satellite remote sensing tool for monitoring reservoirs in Oklahoma to assess spatial and temporal variations in surface water quality.

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Removal of synthetic dyes from wastewater is essential both from the environmental and human health point of view. A small concentration of synthetic dyes can reduce water transparency and consequently influence photosynthesis and alter aquatic ecosystems. Acid black 48 is an Azo dye that falls under the category of synthetic dyes used in the textile industry. With dyes, coffee wastewater has high chemical oxygen demand (COD) that can affect dissolved oxygen (DO) in surface waters. A mixture of wastes in surface waters creates a need to investigate the efficiency of existing treatment methods and optimize them. Adsorption using activated carbon is a conventional method used to remove dyes and heavy metals from wastewater. Industries prefer efficient and economical treatment methods to meet challenging effluent standards regarding COD, BOD, and intensity of color. The adsorption process was optimized using low-cost adsorbents in the current study, including peanut hull and onion peel, to treat a binary mixture of acid black 48 and coffee wastewater. After adsorption, microfiltration was used to remove any suspended solids from the wastewater solution. The performance of combined treatment processes for the color removal of the binary mixture was analyzed and compared using transmittance and absorbance. Treatment efficiency of adsorption using low-cost adsorbents was compared with powdered activated carbon. Apart from absorbance and transmittance, non-purgeable organic carbon (NPOC) values were analyzed to determine organic carbon removal in the combined binary wastewater. Experimental results indicated that Langmuir isotherm was the best fit for a binary mixture with an optimum dosage of 1.2 g using onion peel. The regression coefficient value was 0.82, and the uptake was 58.13 mg of binary mixture per 1 g of onion peel. The effective pH for maximum uptake of acid black 48 using onion peel for adsorption was 5.7. The increasing dosage of low-cost adsorbents adsorption improved in removing binary waste of dyes and coffee waste from wastewater. Adsorption using onion peel improved adsorbent performance up to 1.2 g dosage and steadily decreased beyond that. The adsorption capacity of onion peel was comparatively higher than the peanut hull based on the linear fit.

The application of agro-based adsorbents is growing in the tertiary stage of the wastewater treatment process during the presence of hazardous pollutants. Dye and coffee industries are among the major wastewater pollutant sources negatively affect aquatic ecosystems and human health. The current study attempts to treat a binary mixture of crystal violet (CV) and coffee wastewater using agro-based adsorbents such as peanut hull and onion peel. The performance and efficacy of low-cost adsorbents were evaluated using parameters, including transmittance and non-purgeable organic carbon (NPOC). Batch adsorption studies were conducted to optimize both the adsorbent size and dosage that affect the treatment process. The experimental data obtained from the experiment were analyzed to understand whether Langmuir or Freundlich best fits the treatment process's experimental data. It was observed that Langmuir isotherm seems to fit experimental data using peanut hull and Freundlich isotherm using onion peel. The kinetics of the adsorption process appears to follow the pseudo-first-order kinetic model. The regression coefficient value of onion peel was 0.91, and uptake was 58.14 mg/g. Similarly, using the peanut hull, the regression coefficient was 0.99, and uptake was 57.47 mg/g. It seems that peanut hull appears to perform better as a low-cost adsorbent compared to onion peel. The adsorption capacity increased with the increasing dosage of low-cost adsorbent (peanut hull) until the adsorbent size of 0.6-0.425 mm and steadily decreased after that.