Search

Losses of soluble nutrients from cropland and their transport to surface and groundwater are a continuing water quality concern. In this study, we evaluated tillage impacts on dissolved losses of ammonium (NH4-N), nitrate nitrogen (NO3-N), chloride (Cl), and potassium (K) during rotational cotton and peanut production. Tillage treatments were strip tillage (ST), in which crops were planted into 15 cm strips tilled into cover crop residue mulch, and conventional tillage (CT), in which all crop residues were turned into the soil prior to planting. Winter cover crops were used in both tillage systems. Tillage and irrigation treatments were uniformly applied within two 0.6 ha fields located on a moderately sloping hillslope in the southern Atlantic Coastal Plain region of south-central Georgia. Tile drains were installed at the base of the slope of each field to capture and measure lateral subsurface flow. Each field was subdivided into three 0.2 ha plots, with the three plots making up a single tillage block. H-flumes were used for flow measurement and sample collection. During the five-year study, annual precipitation ranged from 910 to 1488 mm, with an annual average of 1201 mm. Annual surface runoff averaged 17% of annual rainfall from the CT field and 11% from the ST field. Because of relatively low variability in concentrations, surface runoff loads closely tracked surface runoff volumes. Annual surface runoff loadings of NH4-N, NO3-N, and Cl from the ST treatment were found to be significantly less than those from the CT treatment. The total five-year load of N (NH4-N and NO3-N) in surface runoff from CT was 8.3 kg ha-1, while it was 5.6 kg ha-1 from ST, equivalent to 1.5% of the total N applied to CT and 1.0% of that applied to ST. Annual subsurface flow averaged 12% of annual precipitation for CT and 21% for ST. Annual average subsurface flow loadings of NH4-N, NO3-N, and K from ST were significantly greater than from CT. The total five-year load of N (NH4-N and NO3-N) in subsurface flow was 45 kg ha-1 from CT and 99 kg ha-1 from ST, equivalent to 8.3% and 18.4% of the total N applied to CT and ST, respectively. Data showed that subsurface flow was the primary hydrologic pathway for dissolved N and Cl loss in both tillage systems. Overall, ST was found to be an effective method for reducing surface runoff and associated soluble losses, but increased infiltration with this practice significantly increased subsurface losses. This introduces a challenge to nitrogen management in reduced tillage systems such as ST in the region. [ABSTRACT FROM AUTHOR]

The elemental composition of soil plays an essential role in crop nutrition, but losses from croplands can negatively impact soil fertility and water quality. We compared the impact of strip tillage (ST) and conventional tillage (CT) on element concentrations and loads in surface runoff and subsurface flow from plots under rotational cotton (Gossypium hirsutum L.) and peanut (Arachis hypogaea L.) production with winter cover cropping. Total element concentrations (calcium [Ca], iron [Fe], potassium [K], magnesium [Mg], manganese [Mn], sodium [Na], phosphorus [P], sulfur [S], silicon [Si], and zinc [Zn]) in surface runoff and subsurface flow samples were measured using Inductively Coupled Plasma with Optical Emission Spectroscopy (ICP-OES). Element loads were estimated by multiplying the element concentrations by the surface runoff and drainage volumes. Significantly greater (p = 0.05) surface runoff loads for all elements (with the exception of K and Zn) were observed from the CT compared with the ST treatment plots only in 2006, likely due to the combined effects of hydrology and the timing of gypsum amendments that year. Surface runoff was the primary hydrologic pathway for Fe, K, Mn, P, Si, and Zn loss while subsurface flow was the primary hydrologic pathway for Ca, Mg, and S loss with both tillage treatments. Lower concentrations of Ca, Mg, Na, and S in the subsurface flow with ST compared to CT suggest that this tillage practice, in conjunction with the proper timing of fertilizer and soil amendment applications (e.g., poultry litter and gypsum) can be an effective method for reducing element losses from croplands. This finding highlights the importance of conservation practices in sustaining healthy cropland soils while reducing element losses and associated environmental impacts. [ABSTRACT FROM AUTHOR]

The USDA Natural Resource Conservation Service curve number (CN) method for estimating surface runoff is frequently used in natural resource modeling. Water yield and subsequently water quality estimates depend heavily on CN selection. This study was conducted to estimate CNs for a cotton-peanut rotation under conventional and strip tillage (ST) methods for growing and dormant seasons. A comparison between alternative methods for calculating CN and their applicability was also made. Rainfall-runoff data measured from 1999 to 2005 at a field study site in South Georgia were used to calculate CNs by averaging, lognormal, and data-censoring methods. For conventional and STs, CNs by the averaging method using year-round data were 89 and 84, respectively, and by the lognormal method were 89 and 83, respectively. Results from the data-censoring method were 81 and 75, respectively, which matched standard table values developed from a long-term series of annual maximum runoff. Values were also found to vary by season. Curve numbers by the lognormal method for ST were 83 and 88 for growing and dormant seasons, respectively; however, there was no difference between growing and dormant seasons, 89, for conventional tillage. The corresponding CNs by the data-censoring method for ST were 71 and 79 for growing and dormant seasons, respectively, and for conventional tillage were 82 and 79 for growing and dormant seasons, respectively. Based upon errors of the estimates, runoff estimates showed no improvement when separate CNs for the two seasons were used. The data-censoring method CNs yielded lower runoff estimate errors than CNs obtained by the lognormal method. The data-censoring method is recommended for determining CNs from plot rainfall-runoff data pairs. [ABSTRACT FROM AUTHOR]