The Rural Fires of 2017 and Their Influences on Water Quality: An Assessment of Causes and Effects

Abstract

As water is facing increasing pressures from population and economic growth and climate change, it becomes imperative to promote the protection, restoration and management of this resource and its watersheds. Since water quality depends on multiple factors both natural and anthropic, it is not easy to establish their influences. After the October 2017 fires that affected almost 30% of the Mondego hydrographic basin in Central Portugal, 10 catchments were selected for periodic physical-chemical monitoring. These monitoring campaigns started one month after the fires and lasted for two hydrological years, measuring the electric conductivity (EC), pH, dissolved oxygen (DO), turbidity (Turb), alkalinity (Alk), major and minor ions, and trace elements. The obtained data were then statistically analysed alongside the geomorphological characteristics of each catchment coupled with features of land-use and occupation. From the results, it was possible to establish that fire-affected artificial areas, through the atmospheric deposition and surface runoff of combustion products, had the most impact on surface water quality, increasing As, K−, Ca2+, Mg2+, NO3−, SO42− and Sr, and consequently increasing electrical conductivity. Agricultural land-use seems to play a major influence in raising the water’s EC, Cl, K− and Na2+. Regarding natural factors such as catchment geology, it was found that the extent of igneous exposures influences As, and the carbonate sedimentary units are a source of Ca2+ and HCO32− concentrations and impose an increase in alkalinity. Rainfall seems, in the short term, to increase the water concentration in Al and NO3−, while also raising turbidity due to sediments dragged by surface runoff. While, in the long-term, rainfall reduces the concentrations of elements in surface water and approximates the water’s pH to rainfall features.

Rapid automatic detection of water Ca, Mg elements using laser-induced breakdown spectroscopy

“…However, requirements for professional operation and a complex process lead to timeconsuming detection cycles which cannot satisfy the necessary fast response for practical applications. An electronical conductivity (EC) sensor combined with a pH sensor can be used for online detection of ions in aqueous solution [12,13]. However, EC values can only reflect the total ion concentration of soluble salt and cannot distinguish the type of ions.…”