Water and soil quality in an Otago deer farm

This paper outlines findings for three experiments on the AgResearch Invermay deer farm that quantified soil and water quality via fence-line pacing and wallowing, and water quality in streams draining the farm. Five weeks after winter grazing (28 hinds/ha), fence-line pacing decreased soil macroporosity and saturated hydraulic conductivity, and increased suspended sediment (SS; 0.226 g/100ml), total phosphorus (P) (TP; 2.0 mg/l), mainly as particulate P (up to 90% of TP), and E. coli (3.52 log10 cfu/100ml) concentrations in a simulated overland flow 1 day after grazing had stopped compared to soils from the rest of the paddock (0.148 g/100ml, 0.86 mg/l and 2.86 log10/100ml). Six weeks following a first simulated rainfall event, and without interim grazing, concentrations in the second simulated event had decreased but losses of P, especially in fence-line paced soils, were still high and above recommended limits for surface water quality (TP = 0.033 mg/l). A survey of visible erosion in 6 deer paddocks with topography (2- 10o) yielded a mean erosion rate of 1.08 t/ha/yr (range, 0.41-2.01 t/ha/yr), 43% associated with fence-lines, troughs or gateways and 57% associated with wallows. Data from three waterways indicated that mean values for two sites that drain 100% deer farmed land, exceeded current lowland surface water limits for dissolved (0.01 mg/l) and TP (0.033 mg/l) and ammoniacal-nitrogen (N) (0.021 mg N/l). Limits for E. coli (126 E. coli/100ml) and nitrate-N (0.444 mg N/l) were also exceeded at another site, which drained a wallow. All guideline values were exceeded during storm flow when ephemeral streams, commonly draining wallows, were flowing to permanent waterways. However, loads of P, N and SS were below average for mixed-grazing pasture catchments in New Zealand. This was attributed to a dry year (rainfall

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Assessment of Anthropogenic Impact of Surface Water Quality, South Africa

Aquatic Science and Technology ◽

10.5296/ast.v6i2.12837 ◽

2018 ◽

Vol 6 (2) ◽

pp. 12

Author(s):

Dipitseng Manamela ◽

Omotayo Awofolu

Keyword(s):

South Africa ◽

Water Quality ◽

Surface Water ◽

Anthropogenic Activities ◽

Treatment Plant ◽

Surface Water Quality ◽

Total Coliform ◽

Mean Values ◽

Physico Chemical ◽

The Impact

This article investigates the impact of anthropogenic activities on an important surface water from physico-chemical, chemical and microbial perspectives. The surface water, referred to as Blesbokspruit is in the West Rand District of South Africa. Potential impactors include wastewater treatment plant, mines, farmlands and informal settlements. Water samples were collected from nine purposively selected sampling points and analysed in 2014. The mean values of analysed variables across sampling sites and periods ranged from pH: 7.4-8.4; EC: 93.0 - 146.6 mS/m; TSS: 11.3 – 39.0 mg/L; TDS: 590.3 - 1020.3 mg/L; COD: 15.6- 34.8 mg/L. Those for anions varied from NO3-: 0.2- 2.1 (mg/L) N; PO43- : 0.4-0.9 mg/L and SO42-: 118.6 - 379.5 mg/L. The metallic variables ranged from As: 0.01-0.06 mg/L; Cd: 0.02-0.06 mg/L; Fe: 0.04-0.73 mg/L; Cu: 0.02 – 0.05 mg/L and Zn: 0.05 – 0.15 mg/L. The Faecal coliform varied from 15.9-16878.5 cfu/100 ml; Total coliform: 92.9-430294 cfu/100 ml and HPC from 4322.5-39776 cfu/1ml. Detection of toxic metals and pathogenic organisms above target safety limits indicate unsuitability of the water for domestic use with impact on the health of aquatic ecosystem. The study generally revealed the impact of anthropogenic activities on the surface water quality.

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Spatiotemporal Analysis of Surface Water Quality in Dong Thap Province, Vietnam Using Water Quality Index and Statistical Approaches

Water ◽

10.3390/w13030336 ◽

2021 ◽

Vol 13 (3) ◽

pp. 336

Author(s):

Nguyen Thanh Giao ◽

Phan Kim Anh ◽

Huynh Thi Hong Nhien

Keyword(s):

Water Pollution ◽

Water Quality ◽

Surface Water ◽

Water Quality Index ◽

Quality Index ◽

Oxygen Demand ◽

Surface Water Quality ◽

Quality Parameters ◽

Water Quality Parameters ◽

E Coli

The study was conducted to spatiotemporally analyze the quality, location and critical water variables influencing water quality using water monitoring data from the Department of Environment and Natural Resources, Dong Thap province in 2019. The water quality parameters including turbidity, pH, temperature, dissolved oxygen (DO), total suspended solids (TSS), biological oxygen demand (BOD), chemical oxygen demand (COD), nitrite (N-NO2−), nitrate (N-NO3−), ammonium (N-NH4+), total nitrogen (TN), orthophosphate (P-PO43−), chloride (Cl−), oil and grease, sulfate (SO42−), coliforms, and Escherichia coli (E. coli) were collected at 58 locations with the frequency of four times per year (February, May, August, and November). These parameters were compared with national technical regulation on surface water quality—QCVN 08-MT: 2015/BTNMT. Water quality index (WQI) was calculated and spatially presented by geographical information system (GIS) tool. Pearson correlation analysis, cluster analysis (CA), and principal component analysis (PCA) were used to evaluate the correlation among water quality parameters, group and reduce the sampling sites, and identify key parameters and potential water pollution sources. The results showed that TSS, BOD, COD, N-NH4+, P-PO43−, coliforms, and E. coli were the significant concerns impairing the water quality. Water quality was assessed from poor to medium levels by WQI analysis. CA suggested that the current monitoring locations could be reduced from 58 sites to 43 sites which can be saved the total monitoring budget up to 25.85%. PCA showed that temperature, pH, TSS, DO, BOD, COD, N-NH4+, N-NO2−, TN, P-PO43−, coliforms, and E. coli were the key water parameters influencing water quality in Dong Thap province’s canals and rivers; thus, these parameters should be monitored annually. The water pollution sources were possibly hydrological conditions, water runoff, riverbank erosion, domestic and urban activities, and industrial and agricultural discharges. Significantly, the municipal and agricultural wastes could be decisive factors to the change of surface water quality in the study area. Further studies need to focus on identifying sources of water pollution for implementing appropriate water management strategies.

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