Water And Nitrogen Management Model Research Articles

Response of CH4 emissions to straw and biochar applications in double-rice cropping systems: Insights from observations and modeling.

Paddy soil plays an essential role in contributing to the emission of methane (CH4), a potent greenhouse gas, to the atmosphere. This study aimed to demonstrate the effects of straw incorporation and straw-derived biochar amendment on CH4 emissions from double-rice cropping fields and to explore their potential mechanisms based on in-situ field measurements conducted for a period of three years (2012-2014) and model analysis. The results showed that the improved soil aeration due to biochar amendment resulted in low CH4 emissions and that sufficient substrate carbon availability in straw amendment treatments caused high CH4 emissions. The newly developed CH4 emission module for the water and nitrogen management model (WNMM), a process-based biophysical model, performed well when simulating both daily CH4 fluxes and the annual cumulative CH4 emissions under straw incorporation and biochar amendment. Results of our study indicate that the model has a great potential for upscaling and could benefit mechanism analyses about the factors regulating CH4 emissions. Application of biochar into paddy fields provides a great opportunity to reduce CH4 emissions, and the decrease in CH4 emissions following biochar amendment with repeated crop cycles would sustain for a prolonged period.

Analysis of water and nitrogen use efficiency for maize (Zea mays L.) grown on soft rock and sand compound soil.

Maize was grown on compound soils constituted from mixtures of soft rock and sand at different ratios, and water use efficiency (WUE), nitrogen use efficiency (NUE) and fertilizer nitrogen use efficiency (FNUE) were quantified. The data were used to assist in designing strategies for optimizing water and nitrogen management practices for maize on the substrates used. Maize was sown in composite soil prepared at three ratios of soft rock and sand (1:1, 1:2 and 1:5 v/v) in Mu Us Sandy Land, Yuyang district, Yulin city, China. Yields, amount of drainage, nitrogen (N) leaching, WUE and NUE were calculated. Then a water and nitrogen management model (WNMM) was calibrated and validated. No significant difference in evapotranspiration of maize was found among compound soils with soft rock/sand ratios of 1:1, 1:2 and 1:5, while water drainage increased significantly with increasing soft rock/sand ratio. WUE increased to 1.30 kg m-3 in compound soil with 1:2 soft rock/sand ratio. Nitrogen leaching and ammonia volatilization were the main reason for nitrogen loss, and N reduction mainly relied on crop uptake. NUE and FNUE could reach 33.1 and 24.9 kg kg-1 N respectively. Water drainage and nitrogen leaching occurred mostly during heavy rainfall or irrigation. Through a scenario analysis of different rainfall types, water and fertilizer management systems were formulated each year. This study shows that soft rock plays a key role in improving the WUE, NUE and FNUE of maize. © 2016 Society of Chemical Industry.

Evaluating four nitrous oxide emission algorithms in response to N rate on an irrigated corn field

In this study, the RZWQM2 (Root Zone Water Quality Model) was used to simulate the responses of N2O emissions to different Nitrogen application rates on an irrigated corn field from 2003 to 2006, in eastern Colorado, USA. Four different algorithms from the literature were coupled with RZWQM2 and compared for simulating N2O emissions during nitrification and denitrification processes. The RZWQM2 was first calibrated for corn yield, N uptake, soil water (0–10 cm) and soil Nitrate-N content (0–180 cm) and the simulated daily nitrification and denitrification rates were used to calculate N2O emission using the algorithms from DAYCENT, NOE (Nitrous Oxide Emissions),WNMM (Water and Nitrogen Management Model), and FASSET models. The best N2O emission was simulated when the fraction of N2O release from nitrification was modified by water filled pore space (WFPS) as in the NOE model and the fraction N2O release from denitrification was adopted from the DAYCENT model.

Simulation of N2O emissions and mitigation options for rainfed wheat cropping on a Vertosol in the subtropics

The Water and Nitrogen Management Model (WNMM) was applied to simulate nitrous oxide (N2O) emissions from a wheat-cropped Vertosol under long-term management of no-till, crop residue retention, and nitrogen (N) fertiliser application in southern Queensland, Australia, from July 2006 to June 2009. For the simulation study, eight treatments of combinations of conventional tillage (CT) or no-till (NT), stubble burning (SB) or stubble retention (SR), and N fertiliser application at nil (0N) or 90 (90N) kg N/ha.year were used. The results indicated that WNMM satisfactorily simulated the soil water content of the topsoil, mineral N content of the entire soil profile (0–1.5 m), and N2O emissions from the soil under the eight treatments, compared with the corresponding field measurements. For simulating daily N2O emissions from soil, WNMM performed best for the treatment CT-SB-90N (R2 = 0.48, P < 0.001; RMSE = 10.2 g N/ha.day) and worst for the treatment CT-SB-0N (R2 = 0.03, P = 0.174; RMSE = 1.2 g N/ha.day). WNMM predicted N2O emissions from the soil more accurately for the fertilised treatments (i.e. 90N v. 0N), and for the residue retained treatments (SR v. SB). To reduce N2O emissions from the no-till and fertilised treatments, three scenarios were examined: application of nitrification inhibitor, application of controlled-release fertiliser, and deep placement of liquid fertiliser (UAN32). Only the deep placement of UAN32 below the 35 cm depth was effective, and could reduce the N2O emissions from the soil by almost 40%.

Nitrogen leaching under corn cultivation stabilized after four years application of pig manure to red soil in subtropical China

The impact of long-term pig manure application to a red soil in subtropical China on nitrate leaching was investigated in a field lysimeter experiment from 2002 to 2009. Simultaneously, nitrate leaching was simulated by water and nitrogen management model (WNMM) basing on these observed data to determine the environmental threshold of manure application. Nitrate concentrations in the drainage and nitrate leaching under low manure application (150 kg N ha −1 y −1) did not increase during the study period. Interestingly, the nitrate concentrations in drainage water following high manure application (600 kg N ha −1 y −1) increased exponentially in the first four years and then remained at 13 mg l −1 for the next four years. Addition of lime based on high manure application had no significant effect on nitrate concentrations or total nitrate leaching. WNMM simulated the variation in corn yields and nitrate leaching well. The environmentally safe threshold for long-term application of pig manure was 360 kg N ha −1.

Modeling of water and nitrogen utilization of layered soil profiles under a wheat–maize cropping system

Understanding water and nutrient utilization in agricultural layered soil is very important for the improvement of agricultural management and protection of the environment. The objective of this paper is to determine the effect of layered soil profiles on crop yield and water and fertilizer nitrogen (N) utilization. Firstly a water and nitrogen management model (WNMM) was calibrated and validated under a wheat–maize cropping system in an alluvial plain using published data of two soil profiles (named A and B). The results showed that the model can be used to simulate the water movement and N transport, as well as crop growth in the study area. Then, another three very different soil profiles (named C, D and E) near to profiles A and B were studied. The profile C had a silt loam–clay profile; the profile D had a silty loam–clay–silt profile and the profile E had a clay–silty loam–silt profile. The soil hydraulic parameters of these profiles were obtained by pedo-transfer functions using measured soil properties. Given the same initial conditions and field management practices, the WNMM was then used to simulate water and Nitrogen balance and crop yield for the three profiles. Simulated results showed that the profiles (C, D and E) have similar water and fertilizer N use efficiencies (WUE, FNUE), while the crop yields of profiles C and D were higher than that of the profile E. Compared with profiles D and E, the profile C has least water drainage (127 mm) and total N loss (117 kg N ha−1). We concluded that layering of soil profiles has a strong effect on water and fertilizer N utilization and crop yield. Such an effect of layered property of soil profiles, therefore, needs to be taken into account in precision agriculture related research.

Simulating response of N2O emissions to fertiliser N application and climatic variability from a rain‐fed and wheat‐cropped soil in Western Australia

Besides land management and soil properties, nitrous oxide (N(2)O) emissions from the soil may be responsive to climatic variation. In this study the Water and Nitrogen Management Model (WNMM) was calibrated and validated to simulate N(2)O emissions from a rain-fed and wheat-cropped system on a sandy duplex soil at Cunderdin, Western Australia, from May 2005 to May 2007, then it was deployed to simulate N(2)O emissions for seven scenarios of fertiliser N application under various climatic conditions (1970-2006). The WNMM satisfactorily simulated crop growth, soil water content and mineral N contents of the surface soil (0-10 cm), soil temperatures at depths and N(2)O emissions from the soil compared with field observations in two fertiliser treatments during calibration and validation. About 70% of total N(2)O emissions were estimated as nitrification-induced. The scenario analysis indicated that the WNMM-simulated annual N(2)O emissions for this rain-fed and wheat-cropped system were significantly correlated with annual average minimum air temperature (r = 0.21), annual pan evaporation (r = 0.20) and fertiliser N application rate (r = 0.80). Both annual rainfall and wheat yield had weak and negative correlations with annual N(2)O emissions. Multiple linear regression models for estimating annual N(2)O emissions were developed to account for the impacts of climatic variation (including temperature and rainfall), fertiliser N application and crop yield for this rain-fed and wheat-cropped system in Western Australia, which explained 64-74% of yearly variations of the WNMM-estimated annual N(2) O emissions. The WNMM was tested and capable of simulating N(2) O emissions from the rain-fed and wheat-cropped system. The inclusion of climatic variables as predictors in multiple linear regression models improved their accuracy in predicting inter-annual N(2)O emissions.

Modification of a spatially referenced crop model to simulate the effect of spatial pattern of subsoil salinity

High levels of subsoil salinity limit the growth and yield of dryland cereals in the Victorian southern Mallee, Australia. Currently available crop simulation models of wheat production perform poorly in this region, presumably due to their inability to account for subsoil limitations, mainly salinity. The objective of this work was to modify a spatially referenced Water and Nitrogen Management Model (WNMM) to account for the spatial pattern of subsoil salinity, by adjusting crop water uptake, in order to explain the spatial variation in wheat yield in this area. Measurements of above-ground biomass and yield of wheat, and the profile of soil salinity (0–80 cm) were made at 40 locations across an 88 ha paddock (35.78°S, 142.98°E) in the Victorian southern Mallee. The S-shaped water stress response function for crop water uptake proposed by van Genuchten (1987) was explored to modify the WNMM by adjusting the water uptake due to salinity, which significantly improved yield simulation over the original WNMM. The improvement in the model's ability to simulate wheat yield indicates that the subsoil salinity limits crop performance in the area. The incorporation of a salinity function in spatial crop models offers potential for simulating yield across a landscape and thus practicing precision agriculture provided salinity impact is considered dynamically.

A modified checkbook irrigation method based on GIS-coupled model for regional irrigation scheduling

In this study, a regional irrigation schedule optimization method was proposed and applied in Fengqiu County in the North China Plain, which often suffers serious soil water drainage and nitrogen (N) leaching problems caused by excessive irrigation. The irrigation scheduling method was established by integrating the ‘checkbook irrigation method’ into a GIS-coupled soil water and nitrogen management model (WNMM) as an extension. The soil water and crop information required by the checkbook method, and previously collected from field observations, was estimated by the WNMM. By replacing manually observed data with simulated data from WNMM, the application range of the checkbook method could be extended from field scale to regional scale. The WNMM and the checkbook irrigation method were both validated by field experiments in the study region. The irrigation experiment in fluvo–aquic soil showed that the checkbook method had excellent performance; soil water drainage and N leaching were reduced by 83.1 and 85.6%, respectively, when compared with local farmers’ flood irrigation. Using the validated WNMM, the performance of checkbook irrigation in an entire winter wheat and summer maize rotation was also validated: the average soil water drainage and N leaching in four types of soils decreased from 331 to 75 mm year−1 and 47.7 to 9.3 kg ha−1 year−1, respectively; and average irrigation water use efficiency increased from 26.5 to 57.2 kg ha−1 mm−1. The regional irrigation schedule optimization method based on WNMM was applied in Fengqiu County. The results showed a good effect on saving irrigation water, decreasing soil water drainage and then saving agricultural inputs. In a typical meteorological year, it could save >110 mm of irrigation water on average, translating to >7.26 × 107 m3 of agricultural water saved each year within the county. Annual soil water drainage was reduced to <143 mm and N leaching to <27 kg ha−1 in most soils, all of which were significantly lower than local farmers’ flood irrigation. In the mean time, crop yield also had an average increase of 2,890 kg ha−1 when checkbook irrigation was applied.

Modeling Nitrate Leaching and Optimizing Water and Nitrogen Management under Irrigated Maize in Desert Oases in Northwestern China

Understanding water and N transport through the soil profile is important for efficient irrigation and nutrient management to minimize nitrate leaching to the groundwater, and to promote agricultural sustainable development in desert oases. In this study, a process-based water and nitrogen management model (WNMM) was used to simulate soil water movement, nitrate transport, and crop growth (maize [Zea mays L.]) under desert oasis conditions in northwestern China. The model was calibrated and validated with a field experiment. The model simulation results showed that about 35% of total water input and 58% of the total N input were leached to <1.8 m depth under traditional management practice. Excessive irrigation and N fertilizer application, high nitrate concentration in the irrigation water, together with the sandy soil texture, resulted in large nitrate leaching. Nitrate leaching was significantly reduced under the improved management practice suggested by farm extension personnel; however, the water and nitrate inputs still far exceeded the crop requirements. More than 1700 scenarios combining various types of irrigation and fertilizer practices were simulated. Quantitative analysis was conducted to obtain the best management practices (BMPs) with simultaneous consideration of crop yield, water use efficiency, fertilizer N use efficiency, and nitrate leaching. The results indicated that the BMPs under the specific desert oasis conditions are to irrigate the maize with 600 mm of water in eight times with a single fertilizer application at a rate of 75 kg N ha(-1).

Simulation of N 2O emissions from an irrigated dairy pasture treated with urea and urine in Southeastern Australia

The irrigated dairy pasture system in Australia is a high input–high output production system associated with intensive irrigation and nitrogen (N) fertilizer applications. The environmental impacts of such systems are attracting increasing attention in terms of greenhouse gas emissions, such as carbon dioxide (CO 2), methane (CH 4) and nitrous oxide (N 2O). In this study, the daily and total chamber-measured N 2O emissions from an intensively-irrigated pasture grown on a clay loam-textured soil for non-fertilized (CK), urea and urine treated plots at Kyabram in Southeastern Australia were measured over a period of 20 months and compared with the predictions by a process-based agroecosystems model, water and nitrogen management model (WNMM). WNMM was capable of estimating daily and annual N 2O emissions but with different levels of success during different seasons and at different temporal scales. The simulations and statistical analysis indicated that the performance of WNMM in predicting the daily and monthly N 2O emissions for the three treatments is in the order: CK < urea < urine. The periodically-summed correlation analysis showed that WNMM was most reliable in predicting N 2O emissions from an intensively-irrigated dairy pasture system at a time scale of around 35 days. The WNMM-estimated N 2O emission factor for this ecosystem was around 0.5%. WNMM has the potential to test agricultural practices, in this case irrigation and fertilizer N application, for mitigating direct N 2O emissions for an irrigated pasture system.

Simulation of N2O emissions from rain-fed wheat and the impact of climate variation in southeastern Australia

The Water and Nitrogen Management model (WNMM) was applied to simulate N2O emissions from a rain-fed wheat cropping system on a loam-textured soil for two treatments, conventional cultivation with residue burn (CC + BURN + N) and direct drill with residue retention (DD + RET + N), at Rutherglen in southeastern Australia from January 2004 to March 2005. Both treatments received the same amount of nitrogen (N) fertiliser. The WNMM satisfactorily simulated the soil water content, mineral N contents and N2O emissions from the soil, as compared with the field observations for both treatments. The simulated nitrification-induced N2O emissions accounted for 45% and 34% of total N2O emissions for the treatments CC + BURN + N and DD + RET + N, respectively. The calibrated WNMM was used to simulate N2O emissions from this soil using historic daily weather data from 1968 to 2004 and applying seven scenarios of fertiliser N application. Correlation analysis found that the annual N2O emissions for this rain-fed wheat cropping system were significantly correlated to the annual average of daily maximum air temperature (r = 0.51 for CC + BURN + N and 0.56 for DD + RET + N), annual rainfall (r = −0.56 for CC + BURN + N and −0.59 for DD + RET + N) and fertiliser N application rate (r = 0.43 for CC + BURN + N and 0.31 for DD + RET + N). Based on the 37-year historic simulations, multivariate regression models for estimating annual N2O emissions were developed to account for climatic variation, and explained about 50% of variations of annual N2O emissions estimated by WNMM.

Nitrogen leaching in an upland cropping system on an acid soil in subtropical China: lysimeter measurements and simulation

The effect of rainfall and nitrogen (N) input on nitrate leaching in a rain-fed peanut–oilseed rape system on an acidic soil in subtropical China was investigated in a field lysimeter experiment from 1997 to 2000. Drainage and nitrate leaching were simulated using the Water and Nitrogen Management Model (WNMM). Nitrate concentrations in the drainage water and nitrate leaching increased with increasing N application rate. Annual leaching losses ranged from 21.1 to 46.3 kg N ha−1 (9.5–16.8%) for inputs between 0 and 150 kg N ha−1. Growth of oilseed rape decreased the nitrate concentration in the drainage water, but growing N fixing peanuts did not. Rainfall had a greater impact on nitrate leaching than crop uptake. Nitrate concentrations in the drainage water were relatively low (1.95–4.33 mg N l−1); this was caused by the high precipitation, the low nitrification rate, and the low residual nitrate in the soil. The loss of nitrate was low during the dry season (October–February) and in the dry year (rainfall 17% below average) mainly as a result of reduced drainage. WNMM satisfactorily simulated the inter-monthly variation in drainage and total nitrate leached, with respective relative root mean square errors of 42.7% and 70.2%, mean modelling efficiencies of 0.88 and 0.67, and mean relative errors of −3.82% and 21.8%. The modelled annual N losses were only 1–7% less than the observed values.

A spatially referenced water and nitrogen management model (WNMM) for (irrigated) intensive cropping systems in the North China Plain

A spatially referenced biophysical model, the water and nitrogen management model (WNMM), was developed and shown to simulate dynamic soil water movement and soil–crop carbon (C) and nitrogen (N) cycling under a given agricultural management, for the purpose of identifying optimal strategies for managing water and fertiliser N under intensive cropping systems (mainly wheat–maize) in the North China Plain and other regions in the world. A uniform data structure, ARC GRID ASCII format, was used both in GIS and WNMM for achieving a close Model-GIS coupling. A significant part of WNMM adopts and modifies concepts and components from widely used models, with a focus on soil N transformations. WNMM simulates the key processes of water dynamics in the surface and subsurface of soils: including evapotranspiration, canopy interception, water movement and groundwater fluctuations; heat transfer and solute transport; crop growth; C and N cycling in the soil–crop system; and agricultural management practices (crop rotation, irrigation, fertiliser application, harvest and tillage). The model runs on a daily time step at any desired scale and is driven by lumped variables (meteorological and crop biological data) in text data format, and spatial variables (soil and agricultural management) in ARC GRID ASCII format. In particular, WNMM simulates all key N transformations in agricultural fields, including mineralisation of fresh crop residue N and soil organic N, formation of soil organic N, immobilisation in biomass, nitrification, ammonia (NH 3) volatilisation, denitrification and nitrous oxide (N 2O) emissions. WNMM has been successfully applied in Fengqiu County, Henan Province and Luancheng County, Hebei Province, China at site and regional scales. The key WNMM components were intensively calibrated and verified against comprehensive field measurements of soil water content, evapotranspiration, crop leaf area index and yield, NH 3 volatilisation, denitrification and N 2O emissions as well as nitrate (NO 3 −)–N concentrations in the soil solution. A sensitivity analysis showed that WNMM was sensitive to changes in meteorological variables, soil hydraulic properties, land use and agricultural management. At the site scale, WNMM simulated well soil water content, crop growth and yield, NH 3 volatilisation and soil NO 3 −–N concentration. There was uncertainty in simulating soil denitrification and N 2O emissions, when the predicted peaks of denitrification and N 2O emissions at very wet conditions could not be confirmed because of limitations in the acetylene-inhibition method for measuring denitrification. At county scale, WNMM simulation of crop yield in Fengqiu County explained 22% of the variation in observed crop yields, and 31% of crop yield variation in Luancheng County where soil variation was less. These results are considered acceptable because factors such as soil salinity and other nutrient deficiencies, which have not been considered in this version of WNMM, may play a role. The source code for the WNMM is available on request.

Comparison of three modeling approaches for simulating denitrification and nitrous oxide emissions from loam‐textured arable soils

Soil denitrification fluxes and nitrous oxide (N2O) emissions from the soil surface simulated by a Water and Nitrogen Management Model (WNMM), with three different gas modules, are compared to measurement data sets from two irrigated wheat‐maize systems at two locations in the North China Plain (NCP) (2 years of measurement at the Luancheng site and 1 year of measurement at the Fengqiu site). The three gas modules are the WNMM gas module, the DAYCENT gas module, and the DNDC gas module. The term gas module used in this paper refers to the model component which simulates N2O emission from the processes of soil nitrification and denitrification. Soil water, temperature, organic matter decomposition, other nitrogen (N) transformations, such as mineralization and immobilization, and crop growth are simulated by the WNMM platform. For the 2‐year data set from Luancheng, the three gas modules generate similar soil mineral N dynamics in the 0–20 cm topsoil. The daily time step, simply structured WNMM gas module consistently performs the best among the three gas modules for predicting soil denitrification fluxes (R2 = 0.28, n = 39, p = 0.0006) and N2O emissions (R2 = 0.45, n = 36, p &lt; 0.0001). Up to 73, 43, and 22% of total N2O emissions are nitrification‐induced as simulated by the DNDC, DAYCENT, and WNMM gas modules respectively, in this well‐drained loam soil during the 2‐year simulation. When applied to the 1‐year data set at the Fengqiu site, the WNMM gas module consistently performs better in estimating N2O emissions (R2 = 0.54, n = 35, p &lt; 0.0001) compared to the other two modules. Simulations using the DNDC and DAYCENT gas modules explain over 40% of the temporal variation of N2O emission from the soil. Further testing on different soils and different agroecosystems is needed to confirm the superior performance of the WNMM gas module observed in this simulation study.