scholarly journals The impact of conifer harvesting on stream water quality: the Afon Hafren, mid-Wales

2004 ◽  
Vol 8 (3) ◽  
pp. 503-520 ◽  
Author(s):  
C. Neal ◽  
B. Reynolds ◽  
M. Neal ◽  
H. Wickham ◽  
L. Hill ◽  
...  

Abstract. Results for long term water quality monitoring are described for the headwaters of the principal headwater stream of the River Severn, the Afon Hafren. The results are linked to within-catchment information to describe the influence of conifer harvesting on stream and shallow groundwater quality. A 19-year record of water quality data for the Hafren (a partially spruce forested catchment with podzolic soil) shows the classic patterns of hydrochemical change in relation to concentration and flow responses for upland forested systems. Progressive felling of almost two-thirds of the forest over the period of study resulted in little impact from harvesting and replanting in relation to stream water quality. However, at the local scale, a six years’ study of felling indicated significant release of nitrate into both surface and groundwater; this persisted for two or three years before declining. The study has shown two important features. Firstly, phased felling has led to minimal impacts on stream water. This contrasts with the results of an experimental clear fell for the adjacent catchment of the Afon Hore where a distinct water quality deterioration was observed for a few years. Secondly, there are localised zones with varying hydrology that link to groundwater sources with fracture flow properties. This variability makes extrapolation to the catchment scale difficult without very extensive monitoring. The implications of these findings are discussed in relation to strong support for the use of phased felling-based management of catchments and the complexities of within catchment processes. Keywords: deforestation, water quality, acidification, pH, nitrate, alkalinity, ANC, aluminium, dissolved organic carbon, Plynlimon, forest, spruce, Afon Hafren, podzol

2020 ◽  
Vol 12 (14) ◽  
pp. 5500 ◽  
Author(s):  
Yu Song ◽  
Xiaodong Song ◽  
Guofan Shao

Intense human activities and drastic land use changes in rapidly urbanized areas may cause serious water quality degradation. In this study, we explored the effects of land use on water quality from a landscape perspective. We took a rapidly urbanized area in Hangzhou City, China, as a case study, and collected stream water quality data and algae biomass in a field campaign. The results showed that built-up lands had negative effects on water quality and were the primary cause of stream water pollution. The concentration of total phosphorus significantly correlated with the areas of residential, industrial, road, and urban greenspace, and the concentration of chlorophyll a also significantly correlated with the areas of these land uses, except residential land. At a landscape level, the correlation analysis showed that the landscape indices, e.g., dominance, shape complexity, fragmentation, aggregation, and diversity, all had significant correlations with water quality parameters. From the perspective of land use, the redundancy analysis results showed that the percentages of variation in water quality explained by the built-up, forest and wetland, cropland, and bareland decreased in turn. The spatial composition of the built-up lands was the main factor causing stream water pollution, while the shape complexities of the forest and wetland patches were negatively correlated with stream water pollution.


2018 ◽  
Vol 27 (3) ◽  
pp. 203 ◽  
Author(s):  
Ashley J. Rust ◽  
Terri S. Hogue ◽  
Samuel Saxe ◽  
John McCray

Wildfires are increasing in size and severity in forested landscapes across the Western United States. Not only do fires alter land surfaces, but they also affect the surface water quality in downstream systems. Previous studies of individual fires have observed an increase in various forms of nutrients, ions, sediments and metals in stream water for different post-fire time periods. In this research, data were compiled for over 24 000 fires across the western United States to evaluate post-fire water-quality response. The database included millions of water-quality data points downstream of these fires, and was synthesised along with geophysical data from each burned watershed. Data from 159 fires in 153 burned watersheds were used to identify common water-quality response during the first 5 years after a fire. Within this large dataset, a subset of seven fires was examined further to identify trends in water-quality response. Change-point analysis was used to identify moments in the post-fire water-quality data where significant shifts in analyte concentrations occurred. Evaluating individual fires revealed strong initial increases or decreases in concentrations, depending on the analyte, that are masked when averaged over 5 years. Evidence from this analysis shows significant increases in nutrient flux (different forms of nitrogen and phosphorus), major-ion flux and metal concentrations are the most common changes in stream water quality within the first 5 years after fire. Dissolved constituents of ions and metals tended to decrease in concentration 5 years after fire whereas particulate matter concentration continued to increase. Assembling this unique and extensive dataset provided the opportunity to determine the most common post-fire water-quality changes in the large and diverse Western USA. Results from this study could inform studies in other parts of the world, will help parameterise and validate post-fire water-quality models, and assist communities affected by wildfire to anticipate changes to their water quality.


2010 ◽  
Vol 61 (12) ◽  
pp. 3216-3220 ◽  
Author(s):  
G. Kim ◽  
H. Lee ◽  
Y. Lim ◽  
M. Jung ◽  
D. Kong

It is a well-known fact that baseflow discharge of rainfall runoff significantly impacts the quality of surface water. In this paper, the impact of nitrates discharged as baseflow on stream water quality were studied using PULSE, a hydrograph separation software developed by USGS, to calculate the monthly baseflow discharge. We took water quality and flow rate data from a monitoring station site (code: Ghapcehon2) in Daejeon city and acquired 2005 groundwater quality data in the watershed from government agencies. Agricultural and forestry land use are dominant in the area. The baseflow contributes 85%–95% of stream flows during the spring and fall, 25%–38% during the summer and winter. The monthly nitrate loading discharged as baseflow for Ghapcheon2 was estimated by using monitored nitrate concentrations of groundwater in the watershed. Nitrate loading induced by baseflow at Ghapcheon2 was estimated as 5.4 tons of NO3−-N/km2, which is about 60% of nitrate loading of surface water, or 9.2 tons of NO3−-N/km2. This study shows that groundwater quality monitoring is important for proper management of surface water quality.


2002 ◽  
Vol 6 (3) ◽  
pp. 421-432 ◽  
Author(s):  
C. Neal

Abstract. A method for examining the impacts of disturbance on stream water quality based on paired catchment "control" and "response" water quality time series is described in relation to diagrams of cumulative flux and cumulative flux difference. The paper describes the equations used and illustrates the patterns expected for idealised flux changes followed by an application to stream water quality data for a spruce forested catchment, the Hore, subjected to clear fell. The water quality determinands examined are sodium, chloride, nitrate, calcium and acid neutralisation capacity. The anticipated effects of felling are shown in relation to reduction in mist capture and nitrate release with felling as well as to the influence of weathering and cation exchange mechanisms, but in a much clearer way than observed previously using other approaches. Keywords: Plynlimon, stream, Hore, acid neutralisation capacity, calcium, chloride, nitrate, sodium, cumulative flux, flux


2010 ◽  
Vol 62 (9) ◽  
pp. 2075-2082 ◽  
Author(s):  
Manoj Jha ◽  
Roy Gu

Seasonal discharge programs, which take advantage of temporal variation of stream assimilative capacity, are cost effective. However, these seasonal discharge control programs should not increase the risk of water quality violations. A method is presented to estimate the allowable pollutant loads under both seasonal and non-seasonal discharge control programs for a single discharger that maintains the same level of risk of water quality violation. An enhanced in-stream water quality model QUAL2E-UNCAS was applied to a 39-km river reach of the Des Moines River below Des Moines Sewage Treatment Plant (DMSTP) in Iowa. The model was calibrated for dissolved oxygen (DO), biological oxygen demand (BOD), and ammonia as nitrogen with standard errors of 10, 17, and 23% by comparing with the observed water quality data. Monte-Carlo simulation technique was then implemented for seasonal and non-seasonal discharge program to assess the water quality violation risk and the allowable pollutant load. The results indicated that the four-seasonal program offers about 136% increase in BOD loading and 61% increase in ammonia loading when compared with the non-seasonal program without any increase in the violation probabilities, whereas the two-seasonal program only offers 13% decrease in BOD loading and 56% increase in ammonia loading. It is found that the multi-discharge program was beneficial for both water quality indicators, and thus provides a way of reducing the overall cost of waste treatment.


2019 ◽  
Author(s):  
Danlu Guo ◽  
Anna Lintern ◽  
J. Angus Webb ◽  
Dongryeol Ryu ◽  
Ulrike Bende-Michl ◽  
...  

Abstract. Degraded water quality in rivers and streams can have large economic, societal and ecological impacts. Stream water quality can be highly variable both over space and time. To develop effective management strategies for riverine water quality, it is critical to be able to predict these spatio-temporal variabilities. However, our current capacity to model stream water quality is limited, particularly at large spatial scales across multiple catchments. This is due to a lack of understanding of the key controls that drive spatio-temporal variabilities of stream water quality. To address this, we developed a Bayesian hierarchical statistical model to analyse the spatio-temporal variability in stream water quality across the state of Victoria, Australia. The model was developed based on monthly water quality monitoring data collected at 102 sites over 21 years. The modelling focused on six key water quality constituents: total suspended solids (TSS), total phosphorus (TP), filterable reactive phosphorus (FRP), total Kjeldahl nitrogen (TKN), nitrate-nitrite (NOx), and electrical conductivity (EC). Among the six constituents, the models explained varying proportions of variation in water quality. EC was the most predictable constituent (88.6 % variability explained) and FRP had the lowest predictive performance (19.9 % variability explained). The models were validated for multiple sets of calibration/validation sites and showed robust performance. Temporal validation revealed a systematic change in the TSS model performance across most catchments since an extended drought period in the study region, highlighting potential shifts in TSS dynamics over the drought. Further improvements in model performance need to focus on: (1) alternative statistical model structures to improve fitting for the low concentration data, especially records below the detection limit; and (2) better representation of non-conservative constituents by accounting for important biogeochemical processes. We also recommend future improvements in water quality monitoring programs which can potentially enhance the model capacity, via: (1) improving the monitoring and assimilation of high-frequency water quality data; and (2) improving the availability of data to capture land use and management changes over time.


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