Due to the outbreak of the novel coronavirus disease there is a need for public water supply of the highest quality. Adequate levels of chlorine allow immediate elimination of harmful bacteria and viruses and provide a protective residual throughout the drinking water distribution network (DWDN). Therefore, a residual chlorine decay model was developed to predict chlorine levels in a real drinking water distribution network. The model allowed determining human exposure to drinking water with a deficit of residual chlorine, considering that it is currently necessary for the population to have clean water to combat coronavirus Covid 19. The chlorine bulk decay rates (kb) and the reaction constant of chlorine with the pipe wall (kw) were experimentally determined. Average kb and kw values of 3.7 d− 1 and 0.066 m d− 1 were obtained, respectively. The values of kb and kw were used in EPANET to simulate the chlorine concentrations in a DWDN. The residual chlorine concentrations simulated by the properly calibrated and validated model were notably close to the actual concentrations measured at different points of the DWDN. The results showed that maintaining a chlorine concentration of 0.87 mg L− 1 in the distribution tank, the residual chlorine values in the nodes complied with the Ecuadorian standard (0.3 mg L− 1); meanwhile, about 45% of the nodes did not comply with what is recommended by the WHO as a mechanism to combat the current pandemic (0.5 mg L− 1). This study demonstrated that residual chlorine modeling is a valuable tool for monitoring water quality in the distribution network, allowing to control residual chlorine levels in this pandemic season.

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This document presents the physical-chemical parameters with the objective of evaluating and analyzing the drinking water quality in the Azogues city applying the water quality index (WQI) and to research the water stability in the distribution network using corrosion indexes. Thirty samples were collected monthly for six months throughout the drinking water distribution network; turbidity, temperature, electric conductivity, pH, total dissolved solids, total hardness, calcium, magnesium, alkalinity, chlorides, nitrates, sulfates and phosphates were determined; the physical-chemical parameters were measured using standard methods. The processed data revealed that the average values ​​of LSI, RSI and PSI were 0.5 (±0.34), 6.76 (±0.6), 6.50 (±0.99) respectively. The WQI calculation indicated that 100% of the samples are considered excellent quality water. According to the Langelier, Ryznar and Pukorius indexes showed that drinking water in Azogues is corrosive. The quality of drinking water according to the WQI is in a good and excellent category.

Crop classification within large agricultural regions is challenging owing to the presence of crops with similar phenological variation and intra-class variability. The development of efficient and simple classification methods is needed for more accurate mapping, monitoring, and analysis of land-use categories. Multi-seasonal aggregated statistical variables of Tasseled-Cap (TC) bands (brightness (B), greenness (G), and wetness (W)) obtained from the Landsat 7 Enhanced Thematic Mapper Plus satellite (Landsat 7 ETM+) covering cropped areas in the catchments of the Ica and Grande Rivers of Peru were evaluated to assess the performance of random forest (RF) classifiers in identifying crop type. The effects of various TC band combinations on the classification results were also examined. Seventeen crops (asparagus, cotton, grape, maize, mango, and so on) were included. Overall accuracy and kappa coefficient analyses showed that the three-band combination of B-G-W, using multi-seasonal data, led to more accurate classification than did other combinations, yielding values of 86% and 0.81, respectively. The results indicate that employing aggregated statistical variables of TC bands in conjunction with RF classification techniques by using freely available multi-temporal satellite image data is not only a useful but also more economical and computationally efficient method for crop classification than the current one.

The quality of drinking water flowing in a distribution network can possess corrosive characteristics that may cause the material degradation of pipes and accessories. This problem can result in reduction of the service life of pipes and create a major public health problem. The agreement between the physical-chemical water quality analysis and national standards are not enough to confirm the balance of the water quality in terms of corrosion. In order to predict pipe corrosion in water distribution system networks, the corrosive trend was evaluated using the Langelier (LSI), Ryznar (RSI), and Larson-Skold (LRI) indexes based on measurements of pH, temperature, total dissolved solids, alkalinity, calcium hardness, sulfate and chloride. This study was setup with 180 samples collected in six zones of the distribution network, from July to December of 2017, according to the standard methods for the analysis of drinking water.  The results indicate a variation of the LSI from -1.22 to -1.68; RSI from 9.75 to 10.52 and LRI from 0.46 to 0.77. A linear model was fitted for each index to predict the corrosion with the water quality conditions of this study case. Therefore, the drinking water of the city of Azogues, Ecuador has a corrosive tendency from significant to severe. Corrosion indices were calculated to provide useful information on the water's corrosiveness. These results indicate the need to constantly monitor the corrosion rate in the distribution network and conduct a laboratory study to adjust effective parameters such as pH, in order to control corrosion.