James R. Kiniry

The EPIC crop growth model

ABSTRACT The EPIC plant growth model was developed to estimate soil productivity as affected by erosion throughout the U.S. Since soil productivity is expressed in terms of crop yield, the model must be capable of simulating crop yields realistically for soils with a wide range of erosion damage. Also, simulation of many crops is required because of the wide variety grown in the U.S. EPIC simulates all crops with one crop growth model using unique parameter values for each crop. The processes simualted include leaf interception of solar radiation; conversion to biomass; division of biomass into roots, above ground mass, and economic yield; root growth; water use; and nutrient uptake. The model has been tested throughout the U.S. and in several foreign countries.

Radiation-use efficiency in biomass accumulation prior to grain-filling for five grain-crop species☆

Abstract A commonly applied technique of modeling net increase in crop dry-matter in non-stress environments assumes that the amount of dry plant biomass produced is proportional to the intercepted photosynthetically active radiation ( ipar ). The slope of this relationship or ‘radiation-use efficiency’ is often assumed to be constant for a non-stressed crop species. The objective of this study was to test the consistency of this slope both among and within grain-crop species. Published and unpublished data on sorghum ( Sorghum bicolor (L.) Moench), rice ( Oryza sativa L.), wheat ( Triticum aestivum L.), maize ( Zea mays L.), and sunflower ( Helianthus annuus L.) were analyzed in terms of amount of above-ground dry biomass produced per unit ipar . Mean values for sunflower, rice, and wheat were 2.2, 2.2, and 2.8 g/MJ ipar , respectively. For sorghum and maize the means were 2.8 and 3.5 g/MJ ipar , respectively. The within-species variability in the values did not generally appear to be due to differences in temperature or incident solar radiation for the data sets examined.

A general, process-oriented model for two competing plant species

Simulation models for the interaction between weeds and crops generally are simple, empirical equations which lack generality across locations or species or are so complex and difficult to apply that their use by independent researchers is not feasible. The objective of this article is to describe and demonstrate a user-oriented model for weed-crop competition with enough detail to be general across locations and species but not so complex that independent users cannot apply it to their situations. The ALMANAC model described in this article contains the detailed functions for water balance, nutrient cycling, and plant growth as in the EPIC model, and additional detail for light competition, population density effects, and vapor pressure deficit effects which enable it to simulate the growth and seed yield of two competing plant species in a wide range of environments. It reasonably simulates the impact of infestations of johnsongrass, foxtail species, or cocklebur on yields of maize, soybean, and wheat. This model should be a useful tool for simulating management strategies related to weed control.

Variability in crop radiation-use efficiency associated with vapor-pressure deficit

Abstract The ratio of the amount of crop dry-matter produced per unit of intercepted photosynthetically active radiation is usually referred to as radiation-use efficiency ( rue ). Large within-species variability in rue has been reported for a number of species growing with adequate moisture and nutrients. This variability raises questions concerning the generality of the approach for plant-growth analysis and modeling. Available data suggest that increased vapor-pressure difference between substomatal air and the air surrounding the leaves may lead to reductions in leaf conductance and photosynthetic capacity of well-watered plants, and therefore to rue reductions. The coefficient of determination ( r 2 ) of linear regressions of reported rue values as a function of daily saturation vapor-pressure deficit ( Δe ) were calculated for sorghum ( Sorghum bicolor (L.) Moench) and maize ( Zea mays ). Decreased rue was associated with increased Δe in well-watered conditions, explaining a large portion of the rue variability. Effects of Δe should be considered when the rue concept is used to estimate biomass accumulation.

EPIC: An operational model for evaluation of agricultural sustainability

Abstract In the early 1980s, a mathematical model called EPIC (Erosion-Productivity Impact Calculator) was developed as part of the United States Soil and Water Resources Conservation Act to assess the relationship between soil erosion by wind or water and crop productivity throughout the United States. The model uses a daily time step to simulate weather, hydrology, soil temperature, erosion-sedimentation, nutrient cycling, tillage, crop management and growth, and field-scale costs and returns. Since 1985, an interactive data entry system; flexible graphical output utilities; extensive soil and weather generation databases; crop and tillage parameter databases; and alternative methods to simulate erosion, weather, irrigation, fertilization and tillage have been added. The expanded model and associated software can now be considered an operational, microcomputer-based, decision support system to analyze the productivity and sustainability of complex cropping systems.

Projecting Yield and Utilization Potential of Switchgrass as an Energy Crop

The potential utilization of switchgrass (Panicum virgatum L.) as a cellulosic energy crop was evaluated as a component of a projected future national network of biorefineries designed to increase national reliance on renewable energy from American farms. Empirical data on yields of switchgrass from a network of experimental plots were coupled with data on switchgrass physiology and switchgrass breeding progress to provide reasonable expectations for rates of improvement over current yields. Historical breeding success with maize (Zea mays L.) was found to provide a reasonable model for projected linear rates of yield improvement of switchgrass based on documented progress to date. A physiologically based crop production model, ALMANAC, and an econometric model, POLYSYS, were utilized to estimate variability in switchgrass yield and resource utilization across the eastern two‐thirds of the United States. ALMANAC provided yield estimates across 27 regional soil types and 13 years of weather data to estimate variability in relative rates of production and water use between switchgrass and maize. Current and future yield projections were used with POLYSYS to forecast rates of adaptation and economic impacts on regional agricultural markets. Significant positive impacts on US markets, including significant increases in farm income and significant reduction in the need for government subsidies, were projected. This was based on expected technological progress in developing biorefineries that will significantly increase national energy self‐sufficiency by producing feed protein, transportation fuel, and electrical power from cellulosic feedstocks.

EPIC and APEX: Model Use, Calibration, and Validation

The Environmental Policy Integrated Climate (EPIC) and Agricultural Policy/Environmental eXtender (APEX) models have been developed to assess a wide variety of agricultural water resource, water quality, and other environmental problems. The EPIC model is designed to be applied at the field scale. APEX is a direct extension of EPIC that can also be applied to fields as well as to more complex multi-subarea landscapes, whole farms, and watersheds. This article describes key model components of EPIC and APEX, including different options for simulating surface runoff, evapotranspiration, soil erosion, and other processes. Field-scale calibration and validation procedures are then described for both models, with an emphasis on important calibration parameters and guidance regarding logical sequences of calibration steps. Additional calibration and validation guidance is further provided for applications of APEX at the landscape and watershed scales. Two calibration and validation case studies are presented: one for an EPIC plot study and one for an APEX study of a 35 ha field in north-central Missouri. Research and development needs for both models are also discussed.

History of model development at Temple, Texas

Abstract Model development at Temple, Texas, USA has a long history. Prior to the actual model development research, a hydrological data collection programme was established at Riesel, Texas (about 60 km northeast of Temple) in 1937. Data collected from the Riesel watersheds during 1937–2006 have been valuable in developing and testing models at Temple, as well as at other locations. Actual modelling research began in the mid-1960s with the development of single event models that served as building blocks for the comprehensive models of today. The focus of the early models was on surface water hydrology (rainfall excess, unit hydrographs and flood routing) and sediment yield. The models currently supported at Temple (ALMANAC, EPIC, APEX and SWAT) are continuous and operate on spatial scales ranging from individual fields to river basins. These models have been used worldwide in many projects dealing with soil and water resources and environmental management.

Radiation-use efficiency response to vapor pressure deficit for maize and sorghum

Variability within a crop species in the amount of dry mass produced per unit intercepted solar radiation, or radiation-use efficiency (RUE), is important for the quantification of plant productivity. RUE has been used to integrate (1) leaf area, (2) solar radiation interception, and (3) productivity per unit leaf area into crop productivity. Responsiveness of RUE to vapor pressure deficit (VPD) should relate closely to responsiveness of CO2 exchange rate (CER) to VPD. The objective of this study was to compare independent RUE measurements to published response functions relating VPD with RUE of maize (Zea mays L.) and grain sorghum [Sorghum bicolor L. (Moench)]. Data sets from five locations covering a wide range of mean VPD values were compared to published response functions. Predicted RUE values were nearly always within the 95% confidence intervals of measurements. Measured RUE of maize decreased as VPD increased from 0.9 to 1.7 kPa. For sorghum, measured values of RUE agreed closely with predictions. RUE of sorghum decreased as VPD increased from 1.1 to 2.2 kPa. The relative RUE:VPD responses for these two species were similar to CER:VPD responses reported in the literature. Thus, these RUE:VPD responses may be general and appear to be related to carbon exchange rates. We calculated the expected impacts of VPD on RUE at three USA locations during maize and sorghum growing seasons. The RUE:VPD equations offer hope in describing location effects and time-of-year effects on RUE.

Chamber and micrometeorological measurements of CO2 and H2O fluxes for three C4 grasses

Accurate measurements of surface fluxes of carbon dioxide (CO2) and water (H2O) are important for several reasons and can be made using several types of instrumentation. For three C4 grasses—bermudagrass (Cynodon dactylon (L.) Pers.), a mixed species native tallgrass prairie, and sorghum (Sorghum bicolor (L.) Moench.)—we measured evapotranspiration (ET) using a canopy chamber (CC) and Bowen ratio/energy balance (BREB) instrumentation and we measured leaf CO2 uptake using a leaf chamber (LC), and, after accounting for soil CO2 fluxes, we calculated leaf uptake using a CC and BREB instrumentation. In addition, soil CO2 fluxes from bare soil were measured using a CC and soil chamber (SC). Measurements were made on 4 and 5 May 1994 at the Blackland Research Center, Temple, TX. Flux of CO2 into the leaf was considered positive and was expressed per unit ground area. Half-hour CC ET measurements were consistently and substantially greater than BREB measurements for all grasses, perhaps because of increased soil evaporation due to greater turbulence inside the CC. Leaf CO2 uptake measured using the three methods showed similar diurnal trends for all grasses (responding, primarily, to changes in photosynthetic photon flux density), but consistently tended to be greatest for BREB measurements. The regression equation for LC CO2 uptake as a function of BREB uptake had a slope not statistically different from 1.0, with large scatter likely because of limited leaf area sampled. CC CO2 uptake was consistently the least, partly because we may have underestimated soil CO2 flux in the CC. Half-hour soil CO2 fluxes from the CC were significantly greater (P < 0.05) than those from the SC for about two-thirds of the day on bare soil, perhaps because of large chamber ventilation rates. Differences of daytime soil CO2 fluxes averaged 0.07 mg m−2 s−1 (1.0 mg m−2 s−1 ≈ 22.7 μ mol m−2 s−1). These results show the consistency, repeatability and, we believe, accuracy of leaf CO2 uptake and soil CO2 flux measurements made using all methods.