Water quality assessment for organic matter load in urban rivers considering land cover dynamics.

The strategy of considering a model that is comparable to the Soil Conservation Service Curve-Number (SCS-CN) method that employs land use maps to estimate the effects of land use on the water quality has considerable potential for application. This paper presents the LUPC (Land Use Pollutant Contribution) Model to estimate water pollution from the watershed land use obtained by satellite image classification (Sentinel-2). It defines that each land use produces a specific pollutant load per unit area, called Pollutant Standard Index (PSI), which undergoes degradation and/or retention until it reaches the river. This decay estimate is based on a Kernel Function. Organic matter (OM) was the pollutant chosen for the definition of the LUPC model and fractions of labile and refractory organic matter (LOM, ROM). The model was applied to the Barigüi River basin, and five samples were collected at 12 points along the river. Water quality parameters such as dissolved organic carbon (DOC) and UV-Visible absorbance in addition to chemical and biological oxygen demand (COD and BOD), dissolved oxygen (DO), and nitrogen and phosphorus fractions were the reference for modeling purposes. The results indicate that organic loads can be estimated from watershed characteristics, despite influence from seasonal influences captured by the PSI values and the basin shape parameter. Considering its versatile response, the LUPC model can be used for integrated water resources and land use planning and management and be indicator of the potential pollution of rivers by OM.

Determination of antibiotic resistance genes in a WWTP-impacted river in surface water, sediment, and biofilm: Influence of seasonality and water quality.

Many pathogenic bacteria are adapted to live in aquatic habitats, which makes rivers possible sources and spread pathways of antibiotic resistance, since they usually receive effluents from wastewater treatment plants (WWTP), possibly containing antibiotic residues and also antibiotic-resistant bacteria. This study investigates different monitoring strategies to identify the occurrence of antibiotic-resistant bacteria in rivers. We analyzed the presence of 13 antibiotic resistance genes (ARGs) and seven gene markers for facultative pathogenic bacteria (FPB) with qPCR in sampling sites upstream and downstream of a small WWTP in Southern Germany. Five sampling campaigns were conducted from February to June 2019. Surface water, sediment, and biofilm samples were analyzed. The biofilm was collected from an artificial sampler placed in the river. blaTEM, ermB, tetM, and sul1 genes were detected in all samples analyzed. The results showed there was a previous background in the river, but the WWTP and the water quality of the river influenced the concentration and occurrence of ARGs and FPB. Genes representing resistance against strong or last-resort antibiotics, such as mecA, blaCMY-2, blaKPC-3, and mcr-1, and multidrug resistance were also detected, mainly in samples collected downstream of the WWTP. Downstream of the WWTP, the occurrence of ARG and FPB correlated with ammoniacal nitrogen, while upstream of the WWTP correlated with turbidity, suspended solids, and seasonal factors such as UVA radiation and the presence of macrophytes. Biofilm samples presented higher abundances of ARGs and FPB. The biofilm sampler was efficient and allowed to collect biofilms from specific periods, which helped to identify seasonal patterns.