Plot-scale Model Research Articles

Pesticide fate modeling in soils with the crop model STICS: Feasibility for assessment of agricultural practices

Numerous pesticide fate models are available, but few of them are able to take into account specific agricultural practices, such as catch crop, mixing crops or tillage in their predictions. In order to better integrate crop management and crop growth in the simulation of diffuse agricultural pollutions, and to manage both pesticide and nitrogen pollution, a pesticide fate module was implemented in the crop model STICS. The objectives of the study were: (i) to implement a pesticide fate module in the crop model STICS; (ii) to evaluate the model performance using experimental data from three sites with different pedoclimatic contexts, one in The Netherlands and two in northern France; (iii) to compare the simulations with several pesticide fate models; and (iv) to test the impact of specific agricultural practices on the transfer of the dissolved fraction of pesticides. The evaluations were carried out with three herbicides: bentazone, isoproturon, and atrazine. The strategy applied in this study relies on a noncalibration approach and sensitivity test to assess the operating limits of the model. To this end, the evaluation was performed with default values found in the literature and completed by sensitivity tests. The extended version of the STICS named STICS-Pest, shows similar results with other pesticide fate models widely used in the literature. Moreover, STICS-Pest was able to estimate realistic crop growth and catch crop dynamic, which thus illustrate agricultural practices leading to a reduction of nitrate and a change in pesticide leaching.The dynamic plot-scale model, STICS-Pest is able to simulate nitrogen and pesticide fluxes, when the hydrologic context is in the validity range of the reservoir (or capacity) model. According to these initial results, the model may be a relevant tool for studying the effect of long-term agricultural practices on pesticide residue dynamics in soil and the associated diffuse pollution transfer.

Development and validation of a basin scale model PCPF-1@SWAT for simulating fate and transport of rice pesticides

The objective of this study was to develop, verify, and validate a new GIS-based model for simulating the fate and transport of rice pesticides in river basins. A plot scale model simulating pesticide fate and transport in rice paddies (PCPF-1) was incorporated into the Soil and Water Assessment Tool (SWAT) basin scale water and pollutant transport model. The new combined model, [email protected] model, was first used on some base-case scenarios to verify that the PCPF-1 algorithm and the routing of variables were correctly implemented. Next, the [email protected] model was calibrated and validated on the Sakura River basin (Ibaraki prefecture, Japan) using mefenacet concentrations measured during the rice growing season in 2008. The modeling procedures for simulating pesticide fate and transport in a Japanese river basin were demonstrated by providing model parameters related to hydrology, land use, pesticide fate, and rice field managements methods. The water flows predicted by the [email protected] model in the Sakura River basin were accurate throughout the whole simulation year, with R2 and ENS statistics exceeding 0.74 and 0.71, respectively for daily flow. The use of different seepage rates had appreciable influence on the simulations. High seepage rates gave a slight overestimation of the predicted base flow during the rice growing period, whereas the base flow predictions using lower seepage rates were comparable to measured data. The [email protected] model successfully simulated the fate and transport of mefenacet in the Sakura River in which measured mefenacet concentrations peaked soon after the initial herbicide application in May, and decreased gradually during the months of June and July. Occasional major precipitation events caused the mefenacet concentration in streams to peak quickly due to a corresponding loss of mefenacet from paddy areas, and then rapidly decrease due to dilution by excess rainfall discharge. The simulation using a seepage rate of 0.12 cm day−1 had the most accurate prediction of mefenacet concentration in river water with an R2 of 0.61 and an ENS of 0.65.

Representing effects of micro-topography on runoff generation and sub-surface flow patterns by using superficial rill/depression storage height variations

An adequate representation of micro-topography in spatially explicit, physically based models can be crucial in modeling runoff generation, surface/subsurface flow interactions or subsurface flow patterns in hydrological systems with pronounced micro-topography. However, representation of micro-topography in numerical models usually requires high grid resolutions to capture relevant small scale variations in topography at the range of centimeters to meters. High grid resolutions usually result in longer simulation times, especially if fully integrated model approaches are used where the governing partial differential equations for surface and subsurface flow are solved simultaneously. This often restricts the implementation of micro-topography to plot scale models where the overall model domain is small to minimize computational cost resulting from a high grid resolution. In this study an approach is presented where a highly resolved digital elevation model (DEM) for a hummocky topography in a plot scale wetland model (10 m × 21 m × 2 m), is represented by spatially distributed rill/depression storage zones in a numerical model with a planar surface. By replacing the explicit micro-topography with spatially distributed rill/depression storage zones, important effects of micro-topography on surface flow generation and subsurface transport characteristics (e.g. residence time distributions) are being preserved, while at the same time the number of computational nodes is reduced significantly. We demonstrate that the rill/depression storage concept, which has been used for some time to represent time delays in the generation of surface runoff, can also be used to mimic subsurface flow patterns caused by micro-topography. Results further indicate that the rill/depression storage concept is an efficient tool to represent micro-topography in plot scale models because model computation times drop significantly. As important aspects of surface and subsurface flows induced by micro-topography can be mimicked adequately by applying the rill/depression storage concept on a coarser grid, it may also be a useful tool to represent micro-topography in numerical flow models beyond the plot scale.

Plot-scale modeling of soil water dynamics and impacts of drought conditions beneath rainfed maize in Eastern Nebraska

Intermittent drought periods pose major challenges to the management of rainfed agricultural systems because their productivity is sensitive to water stress during crop development. The objective of this study was to assess soil water dynamics and crop stress patterns during the drought year of 2012, which was among the most severe on record in the US Corn Belt. The study utilized a continuous matric potential profile monitoring record from June 2008–December 2012 beneath a rainfed corn plot in Eastern Nebraska to provide a direct comparison of the 2012 growing season with moderate to relatively wet periods within 2008–2011. The analysis was based on a transient unsaturated zone model that was calibrated with laboratory-measured water retention functions and matric potential measurements from heat dissipation sensors. In each year of the model simulation, soil water storage volumes steadily decreased during the growing season and increased episodically following precipitation events outside of the growing season. Precipitation during the 2012 growing season was <50% of the mean for growing seasons 2009–2012 consequently, soil water storage loss during 2012 was ∼14% of initial storage in comparison to 8–9% in 2009–2011. Model results suggest that the 2012 soil water deficit was partially buffered by upward flux of deep soil moisture, with approximately 17% of root water uptake in 2012 deriving from moisture redistributed from below the root zone. Nevertheless, root zone matric potentials exceeded the crop wilting point (ψ=−8000cm) in 2012 for the first time within the monitoring record. These results highlight the need for heightened attention to drought resilience of rainfed cropping systems given future climate predictions that involve increase rainfall intermittency.

Modeling nitrogen loss from switchgrass agricultural systems

Abstract A water quality modeling study was conducted to determine and compare nitrogen loss from water flow to surface water and ground water from agricultural systems growing switchgrass and cotton in the southeastern USA. The Soil and Water Assessment Tool (SWAT) was used to replicate field conditions observed at switchgrass research plots at Pee Dee Research and Educational Center at Florence, South Carolina. The plot scale modeling suggested that in the early years of growth there is significant nitrogen loss from switchgrass to streamflow and groundwater but the loss is significantly less as the switchgrass matures. During the second year of growth the modeled nitrogen loss from switchgrass was approximately 50% that of cotton. The long term nitrogen loss over the lifetime of switchgrass was approximately 10% that of cotton. The results also indicate that the use of computational models to quantify nitrogen fluxes in Life Cycle Assessment (LCA) of agricultural systems growing switchgrass gives a more accurate representation of the system than using constant emission factors.

Simulating concentration of bensulphuron‐methyl in a drainage canal of a paddy block using a rice pesticide model

A pesticide fate and transport model (PCPF‐B) was developed to predict the runoff of pesticides from paddy plots to a drainage canal in a paddy block based on the plot scale model (PCPF‐1). The block‐scale model now comprises three modules: (1) a module for pesticide application, (2) a module for pesticide behaviour in paddy fields, and (3) a module for pesticide concentration in the drainage canal. The PCPF‐B model was first evaluated using published data in a single plot and then was applied to predict the concentration of bensulphuron‐methyl in one paddy block in the Sakura river basin, Ibaraki, Japan, where a detailed field survey was conducted. The PCPF‐B model simulated well the concentration of bensulphuron‐methyl in individual paddy plots. It also reflected the runoff pattern of bensulphuron‐methyl at the block outlet, although overestimation of bensulphuron‐methyl concentrations occurred due to uncertainty in water balance estimation. A sensitivity analysis showed that the soil adsorption coefficient of the herbicide had the greatest influence on the concentrations and cumulative loss of bensulphuron‐methyl to the drainage canal.

Coffee agroforestry systems in Central America: II. Development of a simple process-based model and preliminary results

Research on coffee agroforestry systems in Central America has identified various environmental factors, management strategies and plant characteristics that affect growth, yield and the impact of the systems on the environment. Much of this literature is not quantitative, and it remains difficult to optimise growing area selection, shade tree use and management. To assist in this optimisation we developed a simple dynamic model of coffee agroforestry systems. The model includes the physiology of vegetative and reproductive growth of coffee plants, and its response to different growing conditions. This is integrated into a plot-scale model of coffee and shade tree growth which includes competition for light, water and nutrients and allows for management treatments such as spacing, thinning, pruning and fertilising. Because of the limited availability of quantitative information, model parameterisation remains fraught with uncertainty, but model behaviour seems consistent with observations. We show examples of how the model can be used to examine trade-offs between increasing coffee and tree productivity, and between maximising productivity and limiting the impact of the system on the environment.

Dynamics of grass–clover mixtures—An analysis of the response to management with the PROductive GRASsland Simulator (PROGRASS)

A dynamic plot-scale model PROGRASS was developed to simulate the seasonal and inter-annual dynamics of productive, cut grass/clover mixtures in response to management, and specifically to examine the role of root development on grass/clover interactions. The model was parameterized by virtue of data for dry matter yield, leaf area index, root mass, soil mineral N uptake and biological N fixation from a long-term field trial in north-eastern Switzerland. It was tested using 5 years of independent data for yield and clover fraction from a field experiment with two management regimes carried out on the Swiss Central Plateau. The results of transient simulations indicated that under intensive fertilization grass dominance was initiated by preferential allocation of assimilates to the roots. The rapid growth of the grass root system lowered the substrate C:N ratio, favouring carbon allocation to the shoot, which eventually provided competitive advantages with respect to light interception. Under extensive management, limited N acquisition capacity of the grass root system maintained preferential allocation to the roots, limiting shoot development in the grass and leading to clover dominance. Co-existence regimes with dominance by one of the components were also found in equilibrium experiments, with a transition regime from clover to grass dominance for annual N applications in the range 100–200 kg N ha −1 y −1 that reflected adjustments of the root system to fertilization. It is concluded that the dynamics of grass/clover mixtures is driven by negative and positive feedbacks in the soil–plant system that are strongly controlled by root development and therefore by the allocation patterns of the grass component.