Multi-scale landscape factors influencing stream water quality in the state of Oregon

Effects of landscape pattern on water quality at multi-spatial scales in Wuding River Basin, China

Urbanization and agricultural land use have led to water quality deterioration. Studies have been conducted on the relationship between landscape patterns and river water quality; however, the Wuding River Basin (WDRB), which is a complex ecosystem structure, is facing resource problems in river basins. Thus, the multi-scale effects of landscape patterns on river water quality in the WDRB must be quantified. This study explored the spatial and seasonal effects of land use distribution on river water quality. Using the data of 22 samples and land use images from the WDRB for 2022, we quantitatively described the correlation between river water quality and land use at spatial and seasonal scales. Stepwise multiple linear regression (SMLR) and redundancy analyses (RDA) were used to quantitatively screen and compare the relationships between land use structure, landscape patterns, and water quality at different spatial scales. The results showed that the sub-watershed scale is the best spatial scale model that explains the relationship between land use and water quality. With the gradual narrowing of the spatial scale range, cultivated land, grassland, and construction land had strong water quality interpretation abilities. The influence of land use type on water quality parameter variables was more distinct in rainy season than in the dry season. Therefore, in the layout of watershed management, reasonably adjusting the proportion relationship of vegetation and artificial building land in the sub-basin scale and basin scope can realize the effective control of water quality optimization.

Study on the Water Quality Characteristics of the Baoan Lake Basin in China under Different Land Use and Landscape Pattern Distributions

Land use and landscape pattern highly affect water quality. Their relationship can assist in land-use management and improve land-use efficiency. In this study, a water quality survey of rivers and lakes was performed in 2020 to analyze the effects of land use and the landscape pattern on the water quality of the rivers and lakes in the Baoan Lake basin and is expected to provide a reference for land use planning. The results demonstrated that the effects of land use on water quality were generally higher during the dry season than during the wet season; however, the opposite was demonstrated for the landscape pattern index. Cropland and urban land were closely correlated with deteriorating water quality, with contributions to total nitrogen, total phosphorous, and ammonia nitrogen in the basin. The impact of the landscape pattern of the basin on water quality was controlled by the original land-use type. In addition, the landscape configuration formed different land-use types to produce different effects on water quality. The basin scale better explained the changes in water quality, especially for construction land, followed by the 250 m and 500 m scales in the buffer zone.

Hydrodynamics and water quality of the Hongze Lake in response to human activities

The hydrodynamics and water quality of a lake in response to human activities is an important yet poorly understood issue. In this study, the responses of flow field, water level, and water quality of the Hongze Lake to changes in land use, project operation, and pollution accident were investigated using the 2D hydrodynamic model, water quality model, and hydrological model. The results show that project operations have more significant effects on the hydrodynamics and water quality of the Hongze Lake than changes in land use. In addition, the construction and operation of various water conservancy projects could increase pollutant diffusion and water exchange, thus contributing to improve the water quality of the Hongze Lake, but there is a need to solve the problem of rising water level in the Lihe depression lake area. The increase of urban and farmland area can significantly affect the flow of the Hongze Lake that could increase the flood risk. The simulations of the loosely coupled model imply that the coupling among the hydrodynamic model, water quality model, and SWAT model for the lake basin is feasible. Furthermore, a model based on the space grid was proposed in the study and combined with the verified loosely coupled model to assess the flood risk in the Hongze Lake, which could improve water resources and flood retarding basin operations.

Spatiotemporal Characteristics of the Water Quality and Its Multiscale Relationship with Land Use in the Yangtze River Basin

The spatiotemporal characteristics of river water quality are the key indicators for ecosystem health evaluation in basins. Land use patterns, as one of the main driving forces of water quality change, affect stream water quality differently with the variations in the spatiotemporal scales. Thus, quantitative analysis of the relationship between different land cover types and river water quality contributes to a better understanding of the effects of land cover on water quality, the landscape planning of water quality protection, and integrated water resources management. Based on water quality data of 2006–2018 at 18 typical water quality stations in the Yangtze River basin, this study analyzed the spatial and temporal variation characteristics of water quality by using the single-factor water quality identification index through statistical analysis. Furthermore, the Spearman correlation analysis method was adopted to quantify the spatial-scale and temporal-scale effects of various land uses, including agricultural land (AL), forest land (FL), grassland (GL), water area (WA), and construction land (CL), on the stream water quality of dissolved oxygen (DO), chemical oxygen demand (CODMn), and ammonia (NH3-N). The results showed that (1) in terms of temporal variation, the water quality of the river has improved significantly and the tributaries have improved more than the main rivers; (2) in the spatial variation respect, the water quality pollutants in the tributaries are significantly higher than those in the main stream, and the concentration of pollutants increases with the decrease of the distance from the estuary; and (3) the correlation between DO and land use is low, while that between NH3-N, CODMn, and land use is high. CL and AL have a negative effect on water quality, while FL and GL have a purifying effect on water quality. In particular, AL and CL have a significant positive correlation with pollutants in water. Compared with NH3-N, CODMn has a higher correlation with land use at a larger scale. The results highlight the spatial scale and seasonal dependence of land use on water quality, which can provide a scientific basis for land management and seasonal pollution control.

Prevalence of Extended-Spectrum β-lactamases in Enterobacteriaceae Isolated from Polluted Wild Fish

Background:

Antibiotic resistance is becoming a major public health concern worldwide. In marine animals, pollution is associated with the emergence of extended-spectrum β-lactamase (ESBL)-expressing bacteria, resulting in antibiotic resistance. However, the prevalence of these bacteria in wild fish has not been reported.

Objective:

Accordingly, in this study, we explored the influence of pollution oxidative stress on the incidence of ESBL-expressing Enterobacteriaceae in the gut of wild fish species from the Red Sea coastal region of Jeddah City, Saudi Arabia. Additionally, we evaluated the incidence of varied ESBL genes contributing to the ESBL+ phenotype.

Methods:

Antibiotic susceptibility tests were performed using cephalosporins and carbapenems against ESBL- and carbapenem-resistant Enterobacteriaceae (CRE)-producing bacteria. Frequent genes contributing to the ESBL+ phenotype were analyzed. Primers targeting ESBLs (e.g., blaCTX, blaSHV, blaTEM, and blaOXA) were used in polymerase chain reaction assays to detect the ESBL+ phenotype.

Results:

Screening results from the polluted site revealed ESBL-resistant Klebsiella pneumoniae B8 and CRE-resistant Morganella morganii A4. The evolution of the blaCTX-M gene in M. morganii was a consequence of aquatic pollution. The other isolates Acinetobacter pittii and Providencia rettgeri were found in the clean reference site. The isolate M. morganii showed resistance to most mutual antibiotics and expressed some β-lactamase genes.

Conclusion:

Our findings provide useful data for selecting marine molecular genomic biomarkers caused by aquatic pollution.

Correlations between water quality and the structure and connectivity of the river network in the Southern Jiangsu Plain, Eastern China

Incorporating the structure and connectivity of the river network to seasonal variations and different land use patterns can help improve the understanding the complex relationship between water quality and environmental factors. The present study first employed the grey relational analysis (GRA) to examine any existing correlations between the water quality and the structure and connectivity of river networks in the Southern Jiangsu Plain in Eastern China. All grey relational degree results were greater than the distinguishing coefficient (ρ = 0.5), and their average value was 0.7551. The average grey relational degrees of the water quality parameters varied between 0.7389 and 0.7744, and those of the characteristic indicators of the river network ranged from 0.6874 to 0.8850. Seasonal variations and different land use patterns were then employed to further analyze these relationships. The average grey relational degrees in the urban, rural, and fringe regions were calculated to be 0.7231, 0.7530, and 0.7124 during the flood season, respectively, and 0.7331, 0.7432, and 0.7052 during the non-flood season. The results suggest strong correlations between the water quality and the structure and connectivity of the river network. The preponderance of the urban land weakened the original correlations more than that of the cultivated land, while the seasonal interactions of the cultivated and urban lands presented opposite. The GRA can be employed as an effective supplement for numerical modeling and statistical analysis of the incomplete data. In addition, the structure and connectivity of the river network should be taken in account to improve water quality.

Geostatistical Prediction of Microbial Water Quality Throughout a Stream Network Using Meteorology, Land Cover, and Spatiotemporal Autocorrelation

Predictive modeling is promising as an inexpensive tool to assess water quality. We developed geostatistical predictive models of microbial water quality that empirically modeled spatiotemporal autocorrelation in measured fecal coliform (FC) bacteria concentrations to improve prediction. We compared five geostatistical models featuring different autocorrelation structures, fit to 676 observations from 19 locations in North Carolina's Jordan Lake watershed using meteorological and land cover predictor variables. Though stream distance metrics (with and without flow-weighting) failed to improve prediction over the Euclidean distance metric, incorporating temporal autocorrelation substantially improved prediction over the space-only models. We predicted FC throughout the stream network daily for one year, designating locations "impaired", "unimpaired", or "unassessed" if the probability of exceeding the state standard was ≥90%, ≤10%, or >10% but <90%, respectively. We could assign impairment status to more of the stream network on days any FC were measured, suggesting frequent sample-based monitoring remains necessary, though implementing spatiotemporal predictive models may reduce the number of concurrent sampling locations required to adequately assess water quality. Together, these results suggest that prioritizing sampling at different times and conditions using geographically sparse monitoring networks is adequate to build robust and informative geostatistical models of water quality impairment.

The Impacts of Spatiotemporal Landscape Changes on Water Quality in Shenzhen, China

The urban landscape in China has changed rapidly over the past four decades, which has led to various environmental consequences, such as water quality degradation at the regional scale. To improve water restoration strategies and policies, this study assessed the relationship between water quality and landscape change in Shenzhen, China, using panel regression analysis. The results show that decreases in natural and semi-natural landscape compositions have had significant negative effects on water quality. Landscape composition and configuration changes accounted for 39⁻58% of the variation in regional water quality degradation. Additionally, landscape fragmentation indices, such as patch density (PD) and the number of patches (NP), are important indicators of the drivers of water quality degradation. PD accounted for 2.03⁻5.44% of the variability in water quality, while NP accounted for -1.63% to -4.98% of the variability. These results indicate that reducing landscape fragmentation and enhancing natural landscape composition at the watershed scale are vital to improving regional water quality. The study findings suggest that urban landscape optimization is a promising strategy for mitigating urban water quality degradation, and the results can be used in policy making for the sustainable development of the hydrological environment in rapidly urbanizing areas.

Combining citizen science and land use data to identify drivers of eutrophication in the Huangpu River system

In recent years, the massive land use changes and urbanization of Shanghai City have coincided with a growing eutrophication and an overall degradation of Huangpu River, with related risks to the city's drinking water supply and economic development. However, there is only limited information to evaluate the spatial and temporal changes to the Huangpu River and its many tributaries. In the present study, 400 citizen scientists were trained to monitor water quality and environmental conditions on a monthly basis over three years in the lower (high urbanized) Huangpu River catchment. Their data were integrated with high resolution land cover data using GIS techniques to characterize water quality dynamics of the Huangpu River system with respect to main environmental drivers. Environmental driver analysis indicated that up-catchment conditions dominate river dynamics while typical urban impacts (first flush, impermeable land cover…) have only limited influence. According to these results, the city's investments to improve wastewater treatment and mitigate lower river impacts need to be extended throughout the catchment to reduce nutrient concentrations that are near or above thresholds for rivers and streams. The positive impact of in-stream vegetation pointed to the possibilities that local scale ecological remediation activities to reduce runoff could be viable approaches to improve river conditions throughout the catchment.

Influences of anthropogenic activities and topography on water quality in the highly regulated Huai River basin, China

Our study analyzed the spatio-temporal trends of four major water quality parameters (i.e., dissolved oxygen (DO), ammonium nitrogen (NH₃-N), total phosphorus (TP) and permanganate index (COD_Mn)) at 17 monitoring stations in one of the most polluted large river basins, Huai River Basin, in China during 2005 to 2014. More concerns were emphasized on the attributions, e.g., anthropogenic actives (land cover, pollution load, water temperature, and regulated flow) and natural factors (topography) to the changes in the water quality. The seasonal Mann-Kendall test indicated that water quality conditions were significantly improved during the study period. The results given by the Moran's I methods demonstrated that NH₃-N and COD_Mn existed a weak and moderate positive spatial autocorrelation. Two cluster centers of significant high concentrations can be detected for DO and TP at the Mengcheng and Huaidian station, respectively, while four cluster centers of significant low concentrations for DO at Wangjiaba and Huaidian station in the 2010s. Multiple linear regression analysis suggested that water temperature, regulated flow, and load of water quality could significantly influence the water quality variations. Additionally, urban land cover was the primary predictor for NH₃-N and COD_Mn at large scale. The predictive ability of regression models for NH₃-N and COD_Mn declined as the scale decreases or the period ranges from the 2000s to the 2010s. Topography variables of elevation and slope, which can be treated as the important explanatory variables, exhibited positive and negative correlations to NH₃-N and COD_Mn, respectively. This research can help us identify the water quality variations from the scale-process interactions and provide a scientific basis for comprehensive water quality management and decision making in the Huai River Basin and also other river basins over the world.

Modeling the relationship between landscape characteristics and water quality in a typical highly intensive agricultural small watershed, Dongting lake basin, south central China

Understanding the relationship between landscape characteristics and water quality is critically important for estimating pollution potential and reducing pollution risk. Therefore, this study examines the relationship between landscape characteristics and water quality at both spatial and temporal scales. The study took place in the Jinjing River watershed in 2010; seven landscape types and four water quality pollutions were chosen as analysis parameters. Three different buffer areas along the river were drawn to analyze the relationship as a function of spatial scale. The results of a Pearson's correlation coefficient analysis suggest that "source" landscape, namely, tea gardens, residential areas, and paddy lands, have positive effects on water quality parameters, while forests exhibit a negative influence on water quality parameters because they represent a "sink" landscape and the sub-watershed level is identified as a suitable scale. Using the principal component analysis, tea gardens, residential areas, paddy lands, and forests were identified as the main landscape index. A stepwise multiple regression analysis was employed to model the relationship between landscape characteristics and water quality for each season. The results demonstrate that both landscape composition and configuration affect water quality. In summer and winter, the landscape metrics explained approximately 80.7 % of the variance in the water quality variables, which was higher than that for spring and fall (60.3 %). This study can help environmental managers to understand the relationships between landscapes and water quality and provide landscape ecological approaches for water quality control and land use management.

Sediment and total phosphorous contributors in Rock River watershed

Total phosphorous (TP) and total suspended sediment (TSS) pollution is a problem in the US Midwest and is of particular concern in the Great Lakes region where many water bodies are already eutrophic. Increases in monoculture corn planting to feed ethanol based biofuel production could exacerbate these already stressed water bodies. In this study we expand on the previous studies relating landscape variables such as land cover, soil type and slope with changes in pollutant concentrations and loading in the Great Lakes region. The Rock River watershed in Wisconsin, USA was chosen due to its diverse land use, numerous lakes and reservoirs susceptible to TSS and TP pollution, and the availability of long-term streamflow, TSS and TP data. Eight independent subwatersheds in the Rock River watershed were identified using United States Geological Survey (USGS) monitoring sites that monitor flow, TSS and TP. For each subwatershed, we calculated land use, soil type, and terrain slope metrics or variables. TSS and TP from the different subwatersheds were compared using Analysis of Variance (ANOVA), and associations and relationships between landscape metrics and water quality (TSS and TP) were evaluated using the partial least square (PLS) regression. Results show that urban land use and agricultural land growing corn rotated with non-leguminous crops are associated with TSS and TP in streams. This indicates that increasing the amount of corn rotated with non-leguminous crops within a subwatershed could increase degradation of water quality. Results showed that increase in corn-soybean rotation acreage within the watershed is associated with reduction in stream's TSS and TP. Results also show that forest and water bodies were associated with reduction in TSS and TP. Based on our results we recommend adoption of the Low Impact Development (LID) approach in urban dominated subwatersheds. This approach attempts to replicate the pre-development hydrological regime by reducing the ratio of impervious area to natural cover wherever possible, as well as recycling or treating stormwater runoff using filter strips, ponds and wetlands. In agriculturally dominated subwatersheds, we recommend increasing corn-soybean rotation, keeping corn on areas with gentle slope and soils with lower erodibility.

Determining E. coli burden on pasture in a headwater catchment: combined field and modelling approach

Empirical monitoring studies of catchment-scale Escherichia coli burden to land from agriculture are scarce. This is not surprising given the complexity associated with the temporal and spatial heterogeneity in the excretion of livestock faecal deposits and variability in microbial content of faeces. However, such information is needed to appreciate better how land management and landscape features impact on water quality draining agricultural landscapes. The aim of this study was to develop and test a field-based protocol for determining the burden of E. coli in a small headwater catchment in the UK. Predictions of E. coli burden using an empirical model based on previous best estimates of excretion and shedding rates were also evaluated against observed data. The results indicated that an empirical model utilising key parameters was able to satisfactorily predict E. coli burden on pasture most of the time, with 89% of observed values falling within the minimum and maximum range of predicted values. In particular, the overall temporal pattern of E. coli burden on pasture is captured by the model. The observed and predicted values recorded a disagreement of >1 order of magnitude on only one of the nine sampling dates throughout an annual period. While a first approximation of E. coli burden to land, this field-based protocol represents one of the first comprehensive approaches for providing a real estimate of a dynamic microbial reservoir at the headwater catchment scale and highlights the utility of a simple dynamic empirical model for a more economical prediction of catchment-scale E. coli burden.

Effects of land cover, topography, and built structure on seasonal water quality at multiple spatial scales

The relationship among land cover, topography, built structure and stream water quality in the Portland Metro region of Oregon and Clark County, Washington areas, USA, is analyzed using ordinary least squares (OLS) and geographically weighted (GWR) multiple regression models. Two scales of analysis, a sectional watershed and a buffer, offered a local and a global investigation of the sources of stream pollutants. Model accuracy, measured by R(2) values, fluctuated according to the scale, season, and regression method used. While most wet season water quality parameters are associated with urban land covers, most dry season water quality parameters are related topographic features such as elevation and slope. GWR models, which take into consideration local relations of spatial autocorrelation, had stronger results than OLS regression models. In the multiple regression models, sectioned watershed results were consistently better than the sectioned buffer results, except for dry season pH and stream temperature parameters. This suggests that while riparian land cover does have an effect on water quality, a wider contributing area needs to be included in order to account for distant sources of pollutants.

Effects of land uses on fecal indicator bacteria in the water and soil of a tropical watershed

Effects of different land uses on densities of Escherichia coli, enterococci, and Clostridium perfringens in the water and soil of a tropical watershed were investigated. Densities of fecal indicator bacteria (FIBs) in the watershed exhibited a clear land-use dependency in the stream water. Significantly higher concentrations were detected in the urban portion of the stream (417, 420, and 44 CFU 100 mL(-1) for E. coli, enterococci, and C. perfringens, respectively) than in the forest portion (54, 32, and 5 CFU 100 mL(-1) for E. coli, enterococci, and C. perfringens, respectively). High concentrations of FIBs were also detected in the soil of the watershed with concentration ranges of 603-1,820,000, 69-17,000, and 0-525 CFU 100 g soil(-1) for E. coli, enterococci, and C. perfringens, respectively, which however were not affected by the different land uses. Prior cumulative rainfall significantly correlated with concentrations of E. coli and enterococci in the urban stream water (r=0.73-0.87, P<0.05), but not with the alternative FIB C. perfringens. Poor correlations were observed in the forest reach of the stream for all FIBs. Furthermore, the concentration of C. perfringens only correlated strongly and significantly with E. coli and enterococci in stream water (r=0.70-0.82, P<0.05), but not in tropical soil, indicating different survival and transport behaviors.