Vegetation patterns governing the competitive relationship between runoff and evapotranspiration using a novel water balance model at a semi-arid watershed.

Vegetation patterns play an important role in precipitation partitioning into hydrological components, especially evapotranspiration and runoff. However, few studies focus on their competitive relationship and the influence of the vegetation on them. In this study, a vegetation threshold was postulated to prevent further decrease of runoff by determining a new hydrological component continuing evapotranspiration (partitioned from total and initial evapotranspiration) through a novel model coupled with the Budyko model (dimensional form) and two-stage partitioning model (nondimensional form) in the semi-arid watershed. The results showed significant correlations between model parameters ε (underlying surface index), λ (ratio of initial evapotranspiration) and vegetation coverage (M) (R2 = 0.95 and 0.97, p < 0.01) b Based on the modified Budyko model and λ. The nondimensional model showed high-precise estimations of KH (Horton index Fraction), KB (Baseflow Fraction), KV (evapotranspiration Fraction), KR (runoff Fraction), and KC (continuing evapotranspiration Fraction) (R2 > 0.98, p < 0.01) as a function of a new aridity index φ. KH, KB, KV, KR, showed symmetrical patterns correlated with φ both at between-subwatershed and between-year scale based on the dimensional model and λ. However, KC showed asymmetrical different correlation with M3 and φ (KC/M3 ∼ φ: in between-subwatershed: R2 = 0.92, p < 0.01; and between-year scale: R2 = 0.74, p < 0.01). Based on the solution of continuing evapotranspiration, the vegetation threshold has been solved with M = 0.73 (+0.09/-0.02) to prevent further decreasing runoff. The framework presented can be applied in other semi-arid watersheds worldwide to better protect the sustainability of the hydro-ecosystems.

Contribution of nonpoint source pollution from baseflow of a typical agriculture-intensive basin in northern China.

Baseflow is an essential component of total surface runoff that is widely considered one of the most influential factors regarding water quality via nonpoint source (NPS) pollution. Previously, many researchers and policy makers have directed their efforts toward surface runoff pollution, largely ignoring nutrient delivery via baseflow. Taking a typical agriculture-intensive basin of northern China as an example, this study explored the spatiotemporal characteristics of baseflow and pollution load in relation to NPS pollution. Baseflow was quantified using digital filtering techniques, and the results together with observed pollution data were used to validate a physically based hydrological model, i.e., the Soil and Water Assessment Tool. Then, the spatial and temporal distribution characteristics of NPS and baseflow pollution were investigated using the modeling results. Results indicated that baseflow contribution to total runoff accounted for more than 70% during the studied years (2016-2018), and 84.15% of the basin area showed non-point source pollution dominated by baseflow pollution; both baseflow and its pollution load were greater in the nonflood seasons (spring, autumn, and winter) than in the flood season (summer); the spatial distribution of baseflow total nitrogen and total phosphorus pollution intensity showed higher values in the east and lower values in the west; the scaling effects of baseflow and its pollution load was found with increasing basin area. The results of our study highlighted the necessity for management of pollution load via baseflow in the river basin and provided reference information for improvement of NPS pollution management in other similar basins.

Critical roles of cyanobacteria as reservoir and source for antibiotic resistance genes.

The widespread occurrence of antibiotic resistance genes (ARGs) throughout aquatic environments has raised global concerns for public health, but understanding of the emergence and propagation of ARGs in diverse environmental media remains limited. This study investigated the occurrence and spatio-temporal patterns of six classes of ARGs in cyanobacteria isolated from Taihu Lake. Tetracycline and sulfonamide resistance genes were identified as dominant ARGs. The abundance of ARGs in cyanobacteria was significantly higher in the bloom period than in the non-bloom period. The contribution and persistence of ARGs were higher in extracellular DNA (eDNA) than in intracellular DNA (iDNA) from cyanobacteria. Cyanobacteria-associated eDNA carrying ARGs was more stable at lower temperature. The relative abundances of ARGs in Microcystis and Synechococcus, the dominant genera of cyanobacterial blooms in Taihu Lake, were significantly higher than those in other cyanobacterial strains. The conjugative transfer efficiency for bacterial assimilation of ARGs in cyanobacteria was facilitated by increasing temperature and cyanobacterial cell concentration. Our results demonstrated that cyanobacteria could act as a significant reservoir and source for the acquisition and dissemination of ARGs in aquatic environments, hence the definition of negative ecological effects of cyanobacterial blooms was expanded.