Reducing denitrification loss with nitrification inhibitors following presowing applications of urea to a cottonfield

1994 ◽  
Vol 34 (1) ◽  
pp. 75 ◽  
Author(s):  
DL Chen ◽  
JR Freney ◽  
AR Mosier ◽  
PM Chalk

The effects of the nitrification inhibitors nitrapyrin, acetylene (provided by wax-coated calcium carbide), and phenylacetylene on nitrogen (N) transformations and denitrification losses following presowing applications of urea were determined in a cottonfield in the Namoi Valley of New South Wales. The study used 0.05-m-diameter microplots to follow the changes in mineral N, and 0.15-m-diameter microplots fertilised with 15N-labelled urea (6 g N/ m2; 5 atom % 15N) to assess losses of applied N. When urea was applied in February (34 weeks before sowing), 84% of applied N was lost from the soil. Loss of applied N was reduced by addition of nitrapyrin and phenylacetylene, to 53 and 57%, respectively. In the absence of nitrification inhibitors, less N was lost (72% of that applied) from an application in May than from the February application. Addition of acetylene, phenylacetylene, and nitrapyrin reduced losses over the 24 weeks to sowing to 57, 52, and 48%, respectively. These experiments show that N loss from presowing applications of urea can be significantly reduced by the use of nitrification inhibitors, but that the losses of N are still substantial.

Soil Research ◽  
2015 ◽  
Vol 53 (2) ◽  
pp. 216 ◽  
Author(s):  
Xihua Yang

The Universal Soil Loss Equation (USLE) and its main derivate, the Revised Universal Soil Loss Equation (RUSLE), are widely used in estimating hillslope erosion. The effects of topography on hillslope erosion are estimated through the product of slope length (L) and slope steepness (S) subfactors, or LS factor, which often contains the highest detail and plays the most influential role in RUSLE. However, current LS maps in New South Wales (NSW) are either incomplete (e.g. point-based) or too coarse (e.g. 250 m), limiting RUSLE-based applications. The aim of this study was to develop automated procedures in a geographic information system (GIS) to estimate and map the LS factor across NSW. The method was based on RUSLE specifications and it incorporated a variable cutoff slope angle, which improves the detection of the beginning and end of each slope length. An overland-flow length algorithm for L subfactor calculation was applied through iterative slope-length cumulation and maximum downhill slope angle. Automated GIS scripts have been developed for LS factor calculation so that the only required input data are digital elevation models (DEMs). Hydrologically corrected DEMs were used for LS factor calculation on a catchment basis, then merged to form a seamless LS-factor digital map for NSW with a spatial resolution ~30 m (or 1 s). The modelled LS values were compared with the reference LS values, and the coefficient of efficiency reached 0.97. The high-resolution digital LS map produced is now being used along with other RUSLE factors in hillslope erosion modelling and land-use planning at local and regional scales across NSW.


Soil Research ◽  
2018 ◽  
Vol 56 (2) ◽  
pp. 158 ◽  
Author(s):  
Xihua Yang ◽  
Jonathan Gray ◽  
Greg Chapman ◽  
Qinggaozi Zhu ◽  
Mitch Tulau ◽  
...  

Soil erodibility represents the soil’s response to rainfall and run-off erosivity and is related to soil properties such as organic matter content, texture, structure, permeability and aggregate stability. Soil erodibility is an important factor in soil erosion modelling, such as the Revised Universal Soil Loss Equation (RUSLE), in which it is represented by the soil erodibility factor (K-factor). However, determination of soil erodibility at larger spatial scales is often problematic because of the lack of spatial data on soil properties and field measurements for model validation. Recently, a major national project has resulted in the release of digital soil maps (DSMs) for a wide range of key soil properties over the entire Australian continent at approximately 90-m spatial resolution. In the present study we used the DSMs and New South Wales (NSW) Soil and Land Information System to map and validate soil erodibility for soil depths up to 100 cm. We assessed eight empirical methods or existing maps on erodibility estimation and produced a harmonised high-resolution soil erodibility map for the entire state of NSW with improvements based on studies in NSW. The modelled erodibility values were compared with those from field measurements at soil plots for NSW soils and revealed good agreement. The erodibility map shows similar patterns as that of the parent material lithology classes, but no obvious trend with any single soil property. Most of the modelled erodibility values range from 0.02 to 0.07 t ha h ha–1 MJ–1 mm–1 with a mean (± s.d.) of 0.035 ± 0.007 t ha h ha–1 MJ–1 mm–1. The validated K-factor map was further used along with other RUSLE factors to assess soil loss across NSW for preventing and managing soil erosion.


1998 ◽  
Vol 49 (3) ◽  
pp. 391 ◽  
Author(s):  
H. Marcellos ◽  
W. L. Felton ◽  
D. F. Herridge

Chickpea has potential as a rotation or break crop in the northern grains region of New South Wales and Queensland. Definition of that potential requires information on chickpea N2 fixation and on effects of chickpea on maintenance of soil N fertility and delivery of mineral N for use by a following cereal crop. Results from 6 experiments in northern NSW in which chickpea and wheat in one season were followed by wheat in subsequent seasons indicated variable N2 fixation by chickpea (mean 73 kg/ha; range 4-116 kg/ha), associated with variable Pfix (percentage of chickpea N derived from N2 fixation) (mean 57%; range 4-79%). There were no consistent differences between chickpea and wheat in effects on soil water, either pre-harvest or after the summer fallow. Chickpea ‘spared’ nitrate, relative to wheat (mean 15 kg/ha; range 1-35 kg/ha), and mineralised additional nitrate during the summer fallow (mean 18 kg/ha; range 5-40 kg/ha). Nitrate-N in the top 1·2 m of the soil profile at sowing of the following wheat crop was on average 89 kg/ha after chickpea (range 63-113 kg/ha) and 56 kg/ha after wheat (range 33-94 kg/ha). Nitrogen mineralisation rates during the summer fallow at 2 sites of 0·17 and 0· 21 kg N/ha · day (after chickpea), although greater than the rates after wheat (0· 07 and 0·12 kg N/ha · day), were not sufficient to meet the N requirements of a moderate to high yielding cereal crop. We concluded that chickpea did not fix sufficient N2 or mineralise sufficient N from residues either to maintain soil N fertility or to sustain a productive chickpea{wheat rotation without inputs of additional fertiliser N.


Soil Research ◽  
2014 ◽  
Vol 52 (3) ◽  
pp. 253 ◽  
Author(s):  
Xihua Yang

Soil loss due to water erosion, in particular hillslope erosion, can be estimated using predictive models such as the Revised Universal Soil Loss Equation (RUSLE). One of the important and dynamic elements in the RUSLE model is the cover and management factor (C-factor), which represents effects of vegetation canopy and ground cover in reducing soil loss. This study explores the potential for using fractional vegetation cover, rather than traditional green vegetation indices (e.g. NDVI), to estimate C-factor and consequently hillslope erosion hazard across New South Wales (NSW), Australia. Values of the C-factor were estimated from the emerging time-series fractional cover products derived from Moderate Resolution Imaging Spectroradiometer (MODIS). Time-series C-factor and hillslope erosion maps were produced for NSW on monthly and annual bases for a 13-year period from 2000 to 2012 using automated scripts in a geographic information system. The estimated C-factor time-series values were compared with previous study and field measurements in NSW revealing good consistency in both spatial and temporal contexts. Using these time-series maps, the relationship was analysed between ground cover and hillslope erosion and their temporal variation across NSW. Outcomes from this time-series study are being used to assess hillslope erosion hazard, sediment and water quality (particularly after severe bushfires) across NSW at local, catchment and regional scales.


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