94 research outputs found
On a Logarithmic Deformation of the Supersymmetric bc-system on Curved Manifolds
E. Frenkel, A. Losev and N. Nekrasov claim that a certain class of theories
on compact Kahler manifolds and in particular the "gauged" supersymmetric
bc-system on CP^1 are logarithmic conformal field theories. We discuss that
proposition on a classical level for the bc-system on CP^1. The outcome of our
investigation conforms to their conjecture. The property of being a logarithmic
CFT thus can be interpreted as an effect of gravity
How important is the description of soil unsaturated hydraulic conductivity values for simulating soil saturation level, drainage and 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 â10 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 Zealandâs national soil database. The K-10 values were then varied in a sensitivity analysis from 0.02 to 5 mm dâ1 for well-drained soils, from 0.02 to 1 mm dâ1 for moderately well-drained soils, and from 0.008 to 0.25 mm dâ1 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.Ministry of Business, Innovation and Employmentâs
Endeavour Fund, through the Manaaki Whenua-led âNext Generation S-mapâ research
programme, C09X161
Simulating water and nitrogen runoff with APSIM
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
Modeling coupled nitrificationâdenitrification in soil with an organic hotspot
The emission of nitrous oxide (N2O) from agricultural soils to the atmosphere is a significant contributor to anthropogenic greenhouse gas emissions. The recycling of organic nitrogen (N) in manure and crop residues may result in spatiotemporal variability in N2O production and soil efflux which is difficult to capture by process-based models. We propose a multi-species, reactive transport model to provide detailed insight into the spatiotemporal variability in nitrogen (N) transformations around such N2O hotspots, which consists of kinetic reactions of soil respiration, nitrification, nitrifier denitrification, and denitrification represented by a system of coupled partial differential equations. The model was tested with results from an incubation experiment at two different soil moisture levels (â30Â and â100âhPa) and was shown to reproduce the recorded N2O and dinitrogen
(N2) emissions and the dynamics of important carbon (C) and N components in soil reasonably well. The simulation indicated that the four different
microbial populations developed in closely connected but separate layers,
with denitrifying bacteria growing within the manure-dominated zone and
nitrifying bacteria in the well-aerated soil outside the manure zone and
with time also within the manure layer. The modeled N2O production
within the manure zone was greatly enhanced by the combined effect of oxygen
deficit, abundant carbon source, and supply of nitrogenous substrates. In the
wetter soil treatment with a water potential of â30âhPa, the diffusive flux of nitrate (NO3-) across the manureâsoil interface was the main
source of NO3- for denitrification in the manure zone, while at a
soil water potential of â100âhPa, diffusion became less dominant and
overtaken by the co-occurrence of nitrification and denitrification in the
manure zone. Scenarios were analyzed where the diffusive transport of dissolved
organic carbon or different mineral N species was switched off, and they
showed that the simultaneous diffusion of NO3-, ammonium
(NH4+), and nitrite (NO2-) was crucial to simulate the
dynamics of N transformations and N2O emissions in the model. Without
considering solute diffusion in process-based N2O models, the rapid
turnover of C and N associated with organic hotspots can not be accounted
for, and it may result in the underestimation of N2O emissions from soil
after manure application. The model and its parameters allow for new
detailed insights into the interactions between transport and microbial
transformations associated with N2O emissions in heterogeneous soil
environments.</p
Recommended from our members
Terrain and vegetation structural influences on local avian species richness in two mixed-conifer forests
Using remotely-sensed metrics to identify regions containing high animal diversity and/or specific animal species or guilds can help prioritize forest management and conservation objectives across actively managed landscapes. We predicted avian species richness in two mixed conifer forests, Moscow Mountain and Slate Creek, containing different management contexts and located in north-central Idaho. We utilized general linear models and an AIC model selection approach to examine the relative importance of a wide range of remotely-sensed ecological variables, including LiDAR-derived metrics of vertical and horizontal structural heterogeneities of both vegetation and terrain, and Landsat-derived vegetation reflectance indices. We also examined the relative importance of these remotely sensed variables in predicting nesting guild distributions of ground/understory nesters, mid-upper canopy nesters, and cavity nesters. All top models were statistically significant, with adjusted RÂČs ranging from 0.05 to 0.42. Regardless of study area, the density of the understory was positively associated with total species richness and the ground/understory nesting guild. However, the relative importance of ecological predictors generally differed between the study areas and among the nesting guilds. For example, for mid-upper canopy nester richness, the best predictors at Moscow Mountain included height variability and canopy density whereas at Slate Creek they included slope, elevation, patch diversity and height variability. Topographic variables were not found to influence species richness at Moscow Mountain but were strong predictors of avian species richness at the higher elevation Slate Creek, where species richness decreased with increasing slope and elevation. A variance in responses between focal areas suggests that we expand such studies to determine the relative importance of different factors in determining species richness. It is also important to note that managers using predictive maps should realize that models from one region may not adequately represent communities in other areas.This is the publisherâs final pdf. The published article is copyrighted by Elsevier and can be found at: http://www.sciencedirect.com/science/journal/00344257Keywords: Avian nesting guilds, Predictive maps, Species richness modeling, Landsat, Forest birds, LiDARKeywords: Avian nesting guilds, Predictive maps, Species richness modeling, Landsat, Forest birds, LiDA
An adjoint method for the assimilation of statistical characteristics into eddy-resolving ocean models
The study investigates perspectives of the parameter estimation problem with the adjoint method in eddy-resolving models. Sensitivity to initial conditions resulting from the chaotic nature of this type of model limits the direct application of the adjoint method by predictability. Prolonging the period of assimilation is accompanied by the appearance of an increasing number of secondary minima of the cost function that prevents the convergence of this method. In the framework of the Lorenz model it is shown that averaged quantities are suitable for describing invariant properties, and that secondary minima are for this type of data transformed into stochastic deviations. An adjoint method suitable for the assimilation of statistical characteristics of data and applicable on time scales beyond the predictability limit is presented. The approach assumes a greater predictability for averaged quantities. The adjoint to a prognostic model for statistical moments is employed for calculating cost function gradients that ignore the fine structure resulting from secondary minima. Coarse resolution versions of eddy-resolving models are used for this purpose. Identical twin experiments are performed with a quasigeostrophic model to evaluate the performance and limitations of this approach in improving models by estimating parameters. The wind stress curl is estimated from a simulated mean stream function. A very simple parameterization scheme for the assimilation of second-order moments is shown to permit the estimation of gradients that perform efficiently in minimizing cost functions
Modeling Denitrification : Can We Report What We Don't Know?
Funding Information: This study is the products of a workshop funded by the Deutsche Forschungsgemeinschaft through the research unit DFGâFOR 2337: Denitrification in Agricultural Soils: Integrated Control and Modelling at Various Scales (DASIM), and by the German Federal Ministry of Education and Research (BMBF) under the âMake our Planet Great AgainâGerman Research Initiativeâ, Grant 306060, implemented by the German Academic Exchange Service (DAAD). This work was supported by the European Union's Horizon 2020 research and innovation programme project VERIFY (grant agreement no. 776810). We would like to thank the contribution of all workshop participants of the II. DASIM Modeler Workshop. Publisher Copyright: © 2023. The Authors.Peer reviewedPublisher PD
- âŠ