Water quality monitoring of Lake Burullus (Egypt) using Landsat satellite imageries

Anthropogenic impacts on urban blue space and its reciprocal effect on human and socio-ecological health

Quantifying anthropogenic impacts on blue space (BS) and its effect on human and socio-ecological health was least explored. The present study aimed to do this in reference to the urban BS transformation scenario of Eastern India. To measure BS transformation, Landsat image-based water indices were run from 1990 to 2021. Anthropogenic impact score (AIS) and 7 components scores of 78 selected BS on 70 parameters related data driven from the field. Total 345 respondents were taken for human and socio-ecological health assessment. For this, depression (DEP), anxiety (ANX), stress (STR), physical activities (PA), social capital (SC), therapeutic landscape (TL) and environment building (EB) parameters were taken. The result exhibited that BS was reduced. About 50% of urban core BS was reported highly impacted. Human and socio-ecological health was identified as good in proximity to BS, but it was observed better in the cases of larger peripheral BS. AIS on BS was found to be positively associated with mental health (0.47-0.63) and negatively associated with PA, SC, TL and EB (-0.50 to -0.90). Standard residual in ordinary least square was reported low (-1.5 to 1.5) in 95% BS. Therefore, BS health restoration and management is crucial for sustaining the living environment.

Abnormal fluoride distribution, human health risk assessment, predicted no-effect concentration (PNEC) and environmental hazards in an Egyptian lake connected to the Mediterranean Sea

Fluoride can affect the metabolism and physiological functioning of humans and aquatic organisms like any hazardous substance when it exceeds its permissible limits and PNEC values. The fluoride content of the lake water and sediment samples collected from different locations was determined to assess its risks to humans and its ecological toxicity in Lake Burullus. Statistical analyses show that the proximity of the supplying drains had an impact on the fluoride content. Fluoride ingestion and skin contact in lake water and sediment during swimming for child, female and male were evaluated at 95, 90, and 50%. The values of hazard quotient (HQ) and total hazard quotient (THQ) for children, females and males were less than one, reflecting that exposure to fluoride through ingestion and skin-to-skin contact while swimming poses no risks to human health. PNEC values for fluoride in lake water and sediment were estimated using the equilibrium partitioning method (EPM). The ecological risk assessment of fluoride for acute and chronic toxicity was performed for the three trophic levels based on the PNEC, the half-maximal effective concentration (EC₅₀), the median lethal dose (LC₅₀), the no-observed effect concentration (NOEC), and the 5% lethal concentration (EC₀₅). The risk quotient (RQ), mixture risk characterization ratios (RCR_mix), relative contribution (RC), toxic unit (TU), and sum of toxic units (STU) were estimated. The acute and chronic RCR_mix(STU) and RCR_{mix(MEC/PNEC)} produced similar values for the three trophic levels in lake water and sediment, indicating that invertebrates are the most sensitive species to fluoride. These results of evaluating the environmental risks of fluoride in lake water and sediments reflected its significant impact on aquatic organisms living in the lake area in the long term.

Remote Sensing of Sediment Discharge in Rivers Using Sentinel-2 Images and Machine-Learning Algorithms

The spatio-temporal dynamism of sediment discharge (Qs) in rivers is influenced by various natural and anthropogenic factors. Unfortunately, most rivers are only monitored at a limited number of stations or not gauged at all. Therefore, this study aims to provide a remote-sensing-based alternative for Qs monitoring. The at-a-station hydraulic geometry (AHG) power–law method was compared to the at-many-stations hydraulic geometry (AMHG) method; in addition, a novel AHG machine-learning (ML) method was introduced to estimate water discharge at three gauging stations in the Tisza (Szeged and Algyő) and Maros (Makó) Rivers in Hungary. The surface reflectance of Sentinel-2 images was correlated to in situ suspended sediment concentration (SSC) by support vector machine (SVM), random forest (RF), artificial neural network (ANN), and combined algorithms. The best performing water discharge and SSC models were employed to estimate the Qs. Our novel AHG ML method gave the best estimations of water discharge (Szeged: R2 = 0.87; Algyő: R2 = 0.75; Makó: R2 = 0.61). Furthermore, the RF (R2 = 0.9) and combined models (R2 = 0.82) showed the best SSC estimations for the Maros and Tisza Rivers. The highest Qs were detected during floods; however, there is usually a clockwise hysteresis between the SSC and water discharge, especially in the Tisza River.

Water Quality Variability and Related Factors along the Yangtze River Using Landsat-8

Chlorophyll-a (Chl-a), total nitrogen (TN), and total phosphorus (TP) are important indicators to evaluate water environmental quality. Monitoring water quality and its variability can help control water pollution. However, traditional monitoring techniques of water quality are time-consuming and laborious, and can mostly conduct with sample point-to-point at the edge of lakes and rivers. In this study, an empirical (regression-based) model is proposed to retrieve Chl-a, TN, and TP concentrations in the Yangtze River by Landsat-8 images from 2014 to 2020. The spatial-temporal distribution and variability of water quality in the whole Yangtze River are analyzed in detail. Furthermore, the driving forces of water quality variations are explored. The results show that the mean absolute percentage error (MAPE) of the water quality parameters are 25.88%, 4.3%, and 8.37% for Chl-a, TN, and TP concentrations, respectively, and the root mean square errors (RMSE) are 0.475 μg/L, 0.110 mg/L, and 0.01 mg/L, respectively. The concentrations of Chl-a, TN, and TP in the upstream of the Yangtze River are lower than those in the midstream and downstream. These water quality parameters have a seasonal cycle with a maximum in summer and minimum in winter. The hydrological and meteorological factors such as water level, flow, temperature, and precipitation are positively correlated with Chl-a, TN, and TP concentrations. The larger the impervious surface and cropland area, the greater the cargo handling capacity (CHC), higher ratio of TP to TN will further pollute the water. The methods and results provide essential information to evaluate and control water pollution in the Yangtze River.