Search

• Inverse modelling is a valuable tool for the determination of the soil hydraulic conductivity. • Hydraulic conductivities of slowly permeable horizons were determined with APSIM. • Inverse modelling highlighted the importance of the conductivity at field capacity. • Conductivity values were related to morphology characteristic and soil drainage classes. • Water retention parameters predicted by S-map are less important for slowly permeable soils. Soil hydraulic properties play a primary role in water infiltration and movement, and transport of nutrients and contaminants through the soil profile. However, the determination of soil hydraulic properties, especially the hydraulic conductivity at lower depths within the soil profile is very challenging. We investigated the use of inverse modelling based on APSIM (Agricultural Production Simulation Model) to determine likely ranges of the hydraulic conductivity at saturation (K sat) and field capacity (K DUL) for a slowly permeable subsurface horizon. Simulations were run for the poorly drained Otokia silt loam, in the Otago region of New Zealand. APSIM simulations were set up either according to the site specific soil profile description or based on the national soils database (S-map) pedotransfer functions. Simulated temporal soil moisture data were compared to measurements from a field experiment. Within a sensitivity analysis K sat values of the subsurface soil were varied from 2.4 to 192 mm/d, and values for K DUL from 0.05 to 1 mm/d. Finally simulations were run over 45 years using three climatic conditions, with annual rainfall amounts of 582, 628 and 730 mm. The effect of varying the hydraulic conductivity of the subsurface fragipan horizon (C x) on the wetness status of the overlying B 2g horizon was determined by calculating the average annual duration of soil moisture above field capacity. These were then used to estimate ranges of the hydraulic conductivity that contributes to a soil being imperfectly or poorly drained. The results highlight the significant influence that K DUL has on the reliability of modelling the hydraulic behaviour of soils with slowly permeable subsoils. [ABSTRACT FROM AUTHOR]

Purpose: Photolith morphotypes differ between plant species which can be utilized to reconstruct past vegetation. More recently, the role of phytoliths in soil carbon (C) storage and soil C and silicon (Si) cycling has received increasing attention. The aim of this study was to investigate the impact of recent land cover change on soil phytolith assemblage, soil phytolith concentration, and phytolith-occluded carbon (PhytOC) storage.Materials and methods: Mineral soil samples (0-10 cm) were collected from a tussock grassland (n = 18) and an adjacent 32-year-old pine forest (n = 21) in Otago, New Zealand. The pine forest was established on tussock grassland. Microwave digestion was followed by sedimentation and flotation procedures to obtain a purified phytolith extract to identify soil phytolith morphotypes by microscopy and to quantify PhytOC concentrations using an elemental analyzer.Results and discussion: Soil phytolith assemblage was similar under tussock grassland and pine forest. Bulliform and short cells which were derived from grass species accounted for more than 80% of the phytoliths. Woody plant-derived phytoliths found under tussock grassland (1) may originate from shrubs which are encroaching into the tussock grassland and/or (2) are a legacy of the past woody-dominated vegetation. Soil phytolith concentration ranged between 1 and 3%. Soil PhytOC storage was 0.15 kg C/m2 and 0.14 kg C/m2 under tussock grassland and pine forest, respectively, and accounted for around 3% of total soil carbon storage.Conclusions: Soil phytolith assemblage, soil phytolith concentration, and soil PhytOC storage did not differ significantly between the tussock grassland and the pine forest that was converted from tussock grassland recently. The dominance of grass-derived phytoliths under the pine forest may reflect the legacy of the tussock vegetation which dominated the study site before the afforestation with pine in 1992. This study also revealed that the intrinsic feature of tussock grass species and the accumulation of phytoliths over centuries is likely the cause for the high soil phytolith and PhytOC concentrations. [ABSTRACT FROM AUTHOR]

To determine the impact of potential reductions of terrain-targeted nitrogen (N) fertilisation rates on N losses a simulation study was carried out using the Agricultural Production Systems Simulator (APSIM). To simulate N runoff a simple approach was used, in which runoff is based on the N concentration in the soil solution and an extraction coefficient. Firstly, APSIM parameters that have the largest effect on runoff of water and N were determined for terrains with different slopes for a poorly drained silt loam. A sensitivity analysis was then conducted to assess the effect of soil hydraulic properties and soil organic carbon content on runoff losses. Finally, APSIM was set up to simulate pasture production and water and N dynamics (including pasture N uptake, leaching and N runoff) for a farm on rolling hills in South Canterbury, New Zealand. Two different fertilisation approaches were used, either scheduled or based on the aboveground N concentration of the pasture. For the poorly drained silt loam, the rainfall intensity and the surface conductance had the highest effect on the amount of water lost by runoff. Soil hydraulic conductivity at saturation and field capacity, as well as plant available water content also controlled runoff of water and N, while the organic carbon content of the topsoil had less effect on N runoff. Both the extraction coefficient and the depth considered to exchange N with the runoff water affected the amount of N lost via runoff. Using the aboveground pasture N concentration prior to fertilisation had positive effects on pasture yield and reduced N runoff losses. • a simple approach was developed to include N runoff in APSIM. • the approach is based on the soil solution's N content and an extraction coefficient. • both the extraction coefficient and the depth considered influenced N runoff. • hydraulic conductivity and surface conductance highly affected water runoff. • Rainfall intensity should be considered sub-daily for simulating water runoff. [ABSTRACT FROM AUTHOR]

The simultaneous retention of both cations and anions due to ion-pair adsorption (IPA) has been identified in several soils. The mechanism controlling IPA is nor yet understood, however, and the mathematical description of this phenomenon is only incipient. In this study, a parameterization analysis was performed using a recently proposed adsorption model that considers the occurrence of IPA. The model, which has two alternative approaches to describe IPA, has been shown in a previous study to describe experimental data reasonably well. That analysis was incomplete, however, as the parameter uncertainties were not estimated. In this study, with the paramererization procedure using the maximum-likelihood method, a robust estimation of the model parameters, including the analysis of their uncertainties, was developed. The model was fitted to a data set obtained in batch experiments using the variable-charge Egmont soil, from New Zealand, and a comprehensive combination of SO4 and Ca concentrations. This procedure allowed the analysis of some of the underlying model characteristics and also some inferences about the IPA phenomenon. Overall, it was shown that the proposed adsorption model is a useful tool for the modeling of solutes in soils where IPA occurs. [ABSTRACT FROM AUTHOR]

To evaluate the long-term effect of wastewater application on soil physical properties, two treatment sites, close to Taupo and Levin, New Zealand, and non-irrigated control sites were compared. The soil at Taupo was a silt loam and has received wastewater application for 12 years. The soil at Levin is a sand, and has been wastewater irrigated for 22 years. The disposal blocks at both sites had a higher pH, a higher organic matter (OM) content, a lower bulk density, and thus higher total porosity, but a lower macroporosity than the control sites. The disposal block at the Levin site showed a higher hydrophobicity than the control block, which coincided with the higher soil carbon. In contrast, the Taupo soil showed a higher hydrophobicity at the control site, the site with the lower OM content. Long-term wastewater irrigation resulted in a higher aggregate stability, and changes of the total porosity following stress application were lower, suggesting higher internal soil strength. The hydraulic conductivity close to saturation was also higher in the disposal blocks. The soil mechanical strength, as determined by the precompression stress value was, however, slightly lower in the disposal blocks and not correlated with the aggregate stability. [ABSTRACT FROM AUTHOR]

The article presents information on a study which examined a method for quantifying the impact of soil carbon management on biophysical soil properties, using two apple orchard systems in New Zealand. The soil carbon management is a significant factor for soil quality. The study analyzed the impact of the soil carbon management on biological soil properties, such as microbial biomass carbon, basal respiration, dehydrogenase activity, respiratory quotient, and physical soil properties such as aggregate stability, amount of plant-available water, conductive mean pore diameter near water saturation.

• Hydraulic conductivity at field capacity (FC) is important for bimodal pore system. • Hydraulic conductivity at FC should be adjusted for soil drainage classes/texture. • Saturated hydraulic conductivity is less important for the temporal soil saturation. • Hydraulic conductivity at FC affects pasture yield. Accurate simulation of soil water dynamics is a key factor when using agricultural models for guiding management decisions. However, the determination of soil hydraulic properties, especially unsaturated hydraulic conductivity, is challenging and measured data are scarce. We investigated the use of APSIM (Agricultural Production Simulation Model) with SWIM3 as the water module, based on Richards equation and a bimodal pore system, to determine likely ranges of the hydraulic conductivity at field capacity (K -10 ; assumed at a matric potential of −10 kPa) for soils representing different drainage characteristics. Hydraulic conductivity measurements of soils with contrasting soil drainage characteristics and values for K -10 were extracted from New Zealand's national soil database. The K -10 values were then varied in a sensitivity analysis from 0.02 to 5 mm d−1 for well-drained soils, from 0.02 to 1 mm d−1 for moderately well-drained soils, and from 0.008 to 0.25 mm d−1 for poorly drained soils. The value of K -10 had a large effect on the time it took for the soil to drain from saturation to field capacity. In contrast, the saturated hydraulic conductivity value had little effect. Simulations were then run over 20 years using two climatic conditions, either a general climate station for all seven different soils, or site-specific climate stations. Two values for K -10 were used, either the APSIM default value, or the soil-specific measured K -10. The monthly average soil saturation level simulated with the latter has a better correspondence with the morphology of the seven soils. Finally, the effect of K -10 on drainage and pasture yield was investigated. Total annual drainage was only slightly affected by the choice of K -10 , but pasture yield varied substantially. [ABSTRACT FROM AUTHOR]

Background: Nitrogen (N) fertiliser used on crops is among the main sources of water pollution. Reliable measurement of N losses from land uses in catchments is key to designing effective management strategies that minimise those losses at the same time as keeping farms profitable. In the present study, we used a management simulation tool within the Agricultural Production Systems sIMulator (APSIM) to assess the effect of fertiliser management on N leaching from croplands in the Aparima catchment in Southland, New Zealand. The assessment was based on two N-fertiliser regimes: (i) Scheduled (conventional) where, N-fertiliser rates and timing of application followed a prescribed programme, and (ii) Soil-test where, N-fertiliser rates and timing depended on daily analysis of simulated soil N levels. Four rotations (continuous wheat, pasture-wheat-grain oats, wheat-fodder beet-peas and wheat-green oats-fodder beet-peas) were used in the evaluation., Results: APSIM simulated crop productivity with reasonable accuracy. Yields were 2% greater, fertiliser N input was 11% lower and leaching was 20% lower under the Soil-test compared to the Scheduled fertiliser management. These results show the potential of a Soil-test based fertiliser application to increase fertiliser-N use efficiency and reduce the risk of N loss to the Southland catchment water systems., Conclusion: The present study demonstrates a dynamic farm systems model can be a viable tool to generate valuable data for assessing the productivity and environmental effects of cropping systems at a catchment scale. © 2021 Society of Chemical Industry., (© 2021 Society of Chemical Industry.)

Plant-derived lipid molecular proxies can provide insight into present-day soil carbon input and to what extent organic carbon is degraded within soil. To explore whether soil characteristics of 'primary' (i.e., native grasslands above the historic treeline) and 'secondary' (i.e., human-modified grasslands below the historic treeline) grasslands reflect recent and/or past vegetation input we compared lipid characteristics in modern vegetation and soil from 30 locations around the historic treeline (1150 m) in Central Otago, New Zealand. At each location the dominant plant species and the mineral topsoil (0-10 cm) were analyzed for a range of n-alkane and n-fatty acid proxies. Grass/herbs and trees differed in their total n-alkane concentration (88.9 vs 232.6 μg/g plant dry weight), even-over-odd predominance (EOP, 10.2 vs 18.3) and n-C 20 /n-C 24 ratio (2.2 vs 6.4). Soil samples under all plant growth forms had considerably lower n-alkane and n-fatty concentrations than the corresponding plant samples. Soil under grass/herbs had lower (4.1) odd-over-even predominance (OEP) values compared to soil under trees (10.1) indicating that lipid degradation under grass/herbs cover was higher. Principle component analysis demonstrated that soil lipid characteristics reflected the current vegetation cover. Principal component analysis also revealed a separation between 'primary' and 'secondary' grasslands. However, further evaluations are required to confirm the validity of lipid proxies in reconstructing the vegetation history of secondary grasslands., (Copyright © 2018 Elsevier B.V. All rights reserved.)

Farm system and nutrient budget models are increasingly being used to inform and evaluate policy options on the impacts of land use change on regional environmental and economic performance. In this study, the common approach of up-scaling representative farm systems to a regional scale, with a limited input of resource information, was compared with a new approach that links a geospatial land resource information data base (NZLRI, Agribase™) that includes independent estimates of the productive capacity of land parcels, with individual farm-scale simulation (Farmax® Pro and Farmax® Dairy Pro) and nutrient budgeting models (Overseer®). The Southland region of New Zealand, which is currently undergoing enormous land use change, was used as a case study. Model outputs from the new approach showed increased profit of about 75% for the region if the current land area under dairying increases from 16% to 45%, with the shift to dairy constrained to high pasture production classes only. Environmental impacts associated with the change were substantial, with nitrate leaching estimated to increase by 35% and greenhouse gas emissions by 25%. Up-scaling of representative farm systems to the regional scale with limited input of resource information predicted lower potential regional profit and higher N leaching from dairy conversion. The new approach provides a farm scale framework that could easily be extended to include different systems, different levels of farming performance and the use of mitigation technologies., (Copyright © 2014 Elsevier B.V. All rights reserved.)