Author
Submitted to: Transactions of the ASABE
Publication Type: Peer Reviewed Journal Publication Acceptance Date: 12/12/2016 Publication Date: 4/1/2017 Publication URL: https://handle.nal.usda.gov/10113/5801867 Citation: Leytem, A.B., Dungan, R.S., Bjorneberg, D.L. 2017. Spatial and temporal variation in physicochemical properties of dairy lagoons in south-central Idaho. Transactions of the ASABE. 60(2):439-447. Interpretive Summary: There are large quantities of wastewater generated on dairies in south-central Idaho, which can be a source of valuable nutrients as well contribute to air quality and climate change issues via ammonia (NH3) and greenhouse gas (GHG) emissions. The objective of this study was to examine the range of lagoon water properties among dairies in the region and to determine how they varied spatially and temporally. Twenty-seven lagoons were sampled twice in a blind trial to determine physicochemical characteristics, while 6 lagoons were sampled (3 to 27 times) over a longer period of time to determine how these characteristics changed with time and space. Lagoon properties measured consisted of total solids (TS), volatile solids (VS), chemical oxygen demand (COD), total Kjeldahl nitrogen (TKN), total ammoniacal nitrogen (TAN), total phosphorus (P), total potassium (K), temperature, pH, dissolved oxygen (DO), and specific conductivity. Results indicate that all lagoon characteristics varied greatly between dairies and with sampling date. Seasonal trends indicated that N decreased from spring to fall, while specific conductivity, total P, total K, and in some instances TS and VS increased over the same time period. There was an effect of housing on these properties with freestall dairies having higher concentrations of TS, VS, COD, TKN, TAN, and specific conductivity than dry-lot dairies. There was little effect of dairy size on physicochemical characteristics measured. These results suggest that it is important to account for nutrients applied with lagoon waters in nutrient budgets in order to prevent over-application of N and K which could lead to N leaching and forage quality issues. In addition, capturing the temporal variation in lagoon properties is important to accurately model seasonal variations in NH3 and GHG emissions. Technical Abstract: There are large quantities of wastewater generated on dairies in south-central Idaho, which can be a source of valuable nutrients as well contribute to air quality and climate change issues via ammonia (NH3) and greenhouse gas (GHG) emissions. The objective of this study was to examine the range of lagoon water properties among dairies in the region and to determine how they varied spatially and temporally. Twenty-seven lagoons were sampled twice in a blind trial to determine physicochemical characteristics, while 6 lagoons were sampled (3 to 27 times) over a longer period of time to determine how these characteristics changed with time and space. Lagoon properties measured consisted of total solids (TS), volatile solids (VS), chemical oxygen demand (COD), total Kjeldahl nitrogen (TKN), total ammoniacal nitrogen (TAN), total phosphorus (P), total potassium (K), temperature, pH, dissolved oxygen (DO), and specific conductivity. Results indicate that all lagoon characteristics varied greatly between dairies and with sampling date. Seasonal trends indicated that N decreased from spring to fall, while specific conductivity, total P, total K, and in some instances TS and VS increased over the same time period. There was an effect of housing on these properties with freestall dairies having higher concentrations of TS, VS, COD, TKN, TAN, and specific conductivity than dry-lot dairies. There was little effect of dairy size on physicochemical characteristics measured. These results suggest that it is important to account for nutrients applied with lagoon waters in nutrient budgets in order to prevent over-application of N and K which could lead to N leaching and forage quality issues. In addition, capturing the temporal variation in lagoon properties is important to accurately model seasonal variations in NH3 and GHG emissions. |