Integration of Remote Sensing and Mexican Water Quality Monitoring System Using an Extreme Learning Machine.

Remote Sensing, as a driver for water management decisions, needs further integration with monitoring water quality programs, especially in developing countries. Moreover, usage of remote sensing approaches has not been broadly applied in monitoring routines. Therefore, it is necessary to assess the efficacy of available sensors to complement the often limited field measurements from such programs and build models that support monitoring tasks. Here, we integrate field measurements (2013-2019) from the Mexican national water quality monitoring system (RNMCA) with data from Landsat-8 OLI, Sentinel-3 OLCI, and Sentinel-2 MSI to train an extreme learning machine (ELM), a support vector regression (SVR) and a linear regression (LR) for estimating Chlorophyll-a (Chl-a), Turbidity, Total Suspended Matter (TSM) and Secchi Disk Depth (SDD). Additionally, OLCI Level-2 Products for Chl-a and TSM are compared against the RNMCA data. We observed that OLCI Level-2 Products are poorly correlated with the RNMCA data and it is not feasible to rely only on them to support monitoring operations. However, OLCI atmospherically corrected data is useful to develop accurate models using an ELM, particularly for Turbidity (R2 = 0.7). We conclude that remote sensing is useful to support monitoring systems tasks, and its progressive integration will improve the quality of water quality monitoring programs.

Morphometric and water quality features of Lake Cajititlán, Mexico.

Lake Cajititlán is a shallow water body located in an endorheic basin in western Mexico at 1551 m a.s.l. The surface area is 1744 ha, maximum storage volume achieved is 70.89 Hm3, and maximum depth is 5.4 m at its maximum capacity. The lake has experienced significant changes in its level because of drought conditions in recent years. Because the lake has shallow features and is settled in a closed basin with rapid population growth, the lake water has suffered severe anthropogenic contamination causing damages in its intrinsic esthetic, social, environmental, and economic values.

Mercury concentrations in common carp (Cyprinus carpio) in Lake Chapala, Mexico: a lakewide survey.

Previous studies, based on limited data, found elevated levels of mercury in carp in Lake Chapala, Mexico. The extent of mercury contamination in carp throughout the Lake has not been determined. In order to obtain reliable information about total mercury concentration in carp (Cyprinus carpio), 262 fish from 27 sites (approximately 10 fish per site) throughout the lake were analyzed. Results were expressed as the mean and median of the results at each site. Only one of the samples exceeded Mexican National Standard (1.0 ppm) for mercury in fish flesh. We discuss these results in comparison to World Health Organization (WHO), US Food and Drug Administration (FDA) and US Environmental Protection Agency (US EPA) criteria; many of our samples exceed these criteria based on Tolerable Daily Intake (TDI) or Reference Dose (RfD). ANOVA of four groups of mercury results clustered by distance from the Lerma showed statistically significant differences (P = 0.0071) between the group closest to, versus farthest from, the Lerma River.