Agricultural Policy/Environmental eXtender Model Research Articles

GeoAPEXOL, a web GIS interface for the Agricultural Policy Environmental eXtender (APEX) model enabling both field and small watershed simulation

Nonpoint source (NPS) pollution is a common problem faced in many places around the world. On-site evaluation of NPS pollution is helpful in deciding how serious the pollution is and where a controlling practice can potentially be implemented with the best effectiveness. In this study, a web GIS interface for the Agricultural Policy Environmental eXtender (APEX) model named GeoAPEXOL was developed. The interface serves as a tool to automatically setup the APEX model for a watershed or field and conduct a rapid evaluation of the NPS pollution. A background database including DEM, landuse, soil, climate, and agricultural management was prepared for automating the process of model setup. One important feature of the interface is that NPS pollution can be evaluated for a field boundary considering contribution from upstream areas, which may be located outside the field boundary and is generally ignored by traditional NPS evaluation methods at the field scale.

Improving Modeling of Quinoa Growth under Saline Conditions Using the Enhanced Agricultural Policy Environmental eXtender Model

Cultivation of highly salt-tolerant plants (i.e., halophytes), may provide a viable alternative to increase productivity compared to conventional salt-sensitive crops, increasing the economic potential of salt-affected lands that comprise ~20% of irrigated lands worldwide. In this study the Agricultural Policy/Environmental eXtender (APEX) model was adapted to simulate growth of the halophyte quinoa, along with salt dynamics in the plant-soil-water system. Model modifications included salt uptake and salt stress functions formulated using greenhouse data. Data from a field site were used to further parameterize and calibrate the model. Initial simulation results were promising, but differences between simulated and observed soil salinity and plant salt values during the growing season in the calibration suggest that additional improvements to salt uptake and soil salinity algorithms are needed. To demonstrate utility of the modified APEX model, six scenarios were run to estimate quinoa biomass production and soil salinity with different irrigation managements and salinities. Simulated annual biomass was sensitive to soil moisture, and root zone salinity increased in all scenarios. Further experiments are needed to improve understanding of crop salt uptake dynamics and stress sensitivities so that future model updates and simulations better represent salt dynamics in plants and soils in agricultural settings.

Scaling-Up Conservation Agriculture Production System with Drip Irrigation by Integrating MCE Technique and the APEX Model

The conservation agriculture production system (CAPS) approach with drip irrigation has proven to have the potential to improve water management and food production in Ethiopia. A method of scaling-up crop yield under CAPS with drip irrigation is developed by integrating a biophysical model: APEX (agricultural policy environmental eXtender), and a Geographic Information System (GIS)-based multi-criteria evaluation (MCE) technique. Topography, land use, proximity to road networks, and population density were considered in identifying potentially irrigable land. Weather and soil texture data were used to delineate unique climate zones with similar soil properties for crop yield simulation using well-calibrated crop model parameters. Crops water demand for the cropping periods was used to determine groundwater potential for irrigation. The calibrated APEX crop model was then used to predict crop yield across the different climatic and soil zones. The MCE technique identified about 18.7 Mha of land (16.7% of the total landmass) as irrigable land in Ethiopia. Oromia has the highest irrigable land in the nation (35.4% of the irrigable land) when compared to other regional states. Groundwater could supply a significant amount of the irrigable land for dry season production under CAPS with drip irrigation for the various vegetables tested at the experimental sites with about 2.3 Mha, 3.5 Mha, 1.6 Mha, and 1.4 Mha of the irrigable land available to produce garlic, onion, cabbage, and tomato, respectively. When comparing regional states, Oromia had the highest groundwater potential (40.9% of total potential) followed by Amhara (20%) and Southern Nations, Nationalities, and Peoples (16%). CAPS with drip irrigation significantly increased groundwater potential for irrigation when compared to CTPS (conventional tillage production system) with traditional irrigation practice (i.e., 0.6 Mha under CTPS versus 2.2 Mha under CAPS on average). Similarly, CAPS with drip irrigation depicted significant improvement in crop productivity when compared to CTPS. APEX simulation of the average fresh vegetable yield on the irrigable land under CAPS with drip irrigation ranged from 1.8–2.8 t/ha, 1.4–2.2 t/ha, 5.5–15.7 t/ha, and 8.3–12.9 t/ha for garlic, onion, tomato, and cabbage, respectively. CAPS with drip irrigation technology could improve groundwater potential for irrigation up to five folds and intensify crop productivity by up to three to four folds across the nation.

Agricultural Policy Environmental eXtender (APEX) Simulation of Spring Peanut Management in the North China Plain

Spring peanut is a valuable alternative crop to mitigate water scarcity caused by excessive water use in conventional cropping systems in the North China Plain (NCP). In the present study, we evaluated the capability of the Agricultural Policy Environmental eXtender (APEX) model to predict spring peanut response to sowing dates and seeding rates in order to optimize sowing dates, seeding rates, and irrigation regimes. Data used for calibration and validation of the model included leaf area index (LAI), aboveground biomass (ABIOM), and pod yield data collected from a field experiment of nine sowing dates and seeding rate combinations conducted from 2017 to 2018. The calibrated model was then used to simulate peanut yield responses to extended sowing dates (5 April to 4 June with a 5-day interval) and seeding rates (15 plants m−2 to 50 plants m−2 with a 5 plants m−2 interval) using 38 years of weather data as well as yield, evapotranspiration (ET), and water stress days under different irrigation regimes (rainfed, one irrigation before planting (60 mm) or at flowering (60 mm), and two irrigation with one time before planting and one time at flowering (60 mm each time) or at pod set (60 mm each time)). Results show that the model satisfactorily simulates pod yield of peanut based on R2 = 0.70, index of agreement (d value) being 0.80 and percent bias (PBIAS) values ≤4%. Moreover, the model performed reasonably well in predicting the emergence, LAI and ABIOM, with a R2 = 0.86, d = 0.95 and PBIAS = 8% for LAI and R2 = 0.90, d = 0.97 and PBIAS = 1% for ABIOM, respectively. Simulation results indicate that the best combination of sowing dates and seeding rates is a density of 35–40 plants m−2 and dates during early-May to mid-May due to the influence of local climate and canopy structure to the growth and yield of peanut. Under the optimal sowing date and plant density, an irrigation depth of 60 mm during flowering gave a pod yield (5.6 t ha−1) and ET (464 mm), which resulted in the highest water use efficiency (12.1 kg ha−1 mm−1). The APEX model is capable of assessing the effects of management practices on the growth and yield of peanut. Sowing 35–40 plants m−2 during early-May to mid-May with 60 mm irrigation depth is the recommended agronomic practice for peanut production in the water-constrained NCP.

Comparison of Evapotranspiration Simulation Performance by APEX Model in Dryland and Irrigated Cropping Systems

AbstractAccurate estimation of evapotranspiration (ET) is essential to improve water use efficiency of crop production systems managed under different water regimes. The Agricultural Policy/Environmental eXtender (APEX) model was used to simulate ET using four potential ET (ETp) methods. The objectives were to determine sensitive ET parameters in dryland and irrigated cropping systems and compare ET simulation in the two systems using multiple performance criteria. Measured ET and crop yield data from lysimeter fields located in the United States Department of Agriculture‐Agricultural Research Service Bushland, Texas were used for evaluation. The number of sensitive parameters was higher for dryland (11–14) than irrigated cropping systems (6–8). Only four input parameters: soil evaporation plant cover factor, root growth soil strength, maximum rain intercept, and rain intercept coefficient were sensitive in both cropping systems. Overall, it is possible to find a set of robust parameter values to simulate ET accurately in APEX in both cropping systems using any ETp method. However, more computation time is required for dryland than irrigated cropping system due to a relatively larger number of sensitive input parameters. When all inputs are available, the Penman–Monteith method takes the shortest computation time to obtain one model run with robust parameter values in both cropping systems. However, in areas with limited datasets, one can still obtain reasonable ET simulations using either Priestley–Taylor or Hargreaves. Editor's note: This paper is part of the featured series on Optimizing Ogallala Aquifer Water Use to Sustain Food Systems. See the February 2019 issue for the introduction and background to the series.

Evaluation of the agricultural policy environmental extender (APEX) for the Chesapeake Bay watershed

The Agricultural Policy/Environmental Extender (APEX) is a complex mechanistic simulation model designed to evaluate agricultural management strategies and their effects on yields, water and soil quality, and resource use. It is one of the main models used in the Conservation Effects Assessment Project (CEAP) assessment program and has been employed to evaluate the effects of conservation practices in the Chesapeake Bay Watershed (CBW). Calibration of model parameters is an important process in order to apply a simulation model to a particular area. The APEX model is normally parameterized for each application using selected datasets from the region. However, the APEX application area is usually very large and all areas may not be well represented by the calibration. Thus, additional tests of APEX without site-specific calibration for crop yield and soil water content can provide information on the stability of the parameters related to these variables in the CBW. The objective of this study is to evaluate the performance of APEX for corn yields and water balance in a new location using parameters previously developed for the CBW. This study used observations from the OPE3 site (Optimizing Production Inputs for Economic and Environmental Enhancement) located at the US Department of Agriculture, Henry A. Wallace Agricultural Research Center, Beltsville, Maryland, USA. Data from the OPE3 site consists of water content at various layers, corn yields, and ET covering the period from 1998 to 2013. The results for total water in the soil profile (up to 100 cm deep) showed that the simulated water amounts were about 4.4 cm higher than the observed values, but the trends were very similar to the observed trends. The statistical error analysis of R-square (RSQ), Nash-Sutcliffe (ENS) efficiency coefficient and Root Mean Square Error (RMSE) are 0.59, 0.51 and 0.21 cm•day−1, respectively. The average simulated yields were 0.3 t•ha−1 (4%) lower than observed yields with an average absolute deviation between APEX and OPE3 of 1.3 t•ha1 where the average observed yields over the period was 5.18 t•ha−1, The year-to-year trends were very similar to the measured trends. The monthly evapotranspiration data also showed reasonable trends between observed data and model results with the model RSQ, ENS and RMSE being 0.56, 0.41 and 4.49 mm•month−1, respectively. These results suggest that APEX parameters for yield and water use simulations calibrated for the CBW can be considered applicable to other areas of the CBW where calibration data are not available.

APEXeditor: A Spreadsheet-Based Tool for Editing APEX Model Input and Output Files

The APEXeditor, an Excel-based tool has been developed using the Visual Basic for Applications (VBA) to provide a graphical user interface (GUI) to the Agricultural Policy Environmental eXtender (APEX) model. APEX, in its native form, requires users to edit text files for modifying input files; therefore a GUI interface can aid users in modification of these files and reduce errors. Microsoft Excel is a popular spreadsheet program that has the largest user base among scientists and researchers, thus providing a relatively common platform in which stages the tool. The APEXeditor requires minimal additional learning to operate the tool for those who already have basic level of knowledge in Excel. The user can load APEX input files into the spreadsheet tool and the GUI offers meta information and provides functions to edit, write, and run the APEX model. Ultimately, the APEXeditor substitutes existing GUI programs such as WinAPEX or ArcAPEX that require installation or additional licensing. A series of scripts were developed as a back-end engine that automates data formatting and editing of linked APEX input ASCII files including database libraries. The simple architecture of the tool helps users maintain the quality of the data and allows error-free editing of APEX model inputs to characterize the system under study. This tool is suitable for all kinds of applications and has been successfully used for the creation of APEX model runs in numerous studies.

APEXSENSUN: An Open‐Source Package in R for Sensitivity Analysis and Model Performance Evaluation of APEX

AbstractThe Agricultural Policy/Environmental eXtender (APEX) model is used to evaluate the impact of different land management strategies associated with water availability, soil and water quality, plant growth, and economics. This article presents APEXSENSUN, an open‐source software package that automates global sensitivity analysis and assists with calibration of the APEX model. APEXSENSUN was developed in R programming language and includes regression‐based, derivative‐based, and variance‐based methods, as well as a regional sensitivity analysis method. Evapotranspiration data measured at a research field located at the United States Department of Agriculture‐Agricultural Research Service Conservation and Production Research Laboratory in Bushland, Texas were utilized to illustrate the main features of APEXSENSUN, which are to identify important parameters and assist with calibration. The results from variance‐based methods were in agreement regarding the ranking of top five sensitive parameters including the soil evaporation‐plant factor, root growth‐soil strength, and the coefficient for adjusting the microbial activity function in the top soil layer. The Fourier amplitude sensitivity testing method required the least number of simulations for calculation of the total‐effect sensitivity indices. The Monte Carlo‐based calibration feature of the package was also tested for calculating the posterior parameter distributions and prediction intervals with a desired level of confidence for output predictions.

Simultaneous calibration of evapotranspiration and crop yield in agronomic system modeling using the APEX model

Reliable estimation of ET is especially important in semi-arid conditions where ET prediction is instrumental in cost-effective management of scarce water resources and crop production. In addition to the role of climate variables and soil characteristics, the actual ET is influenced by dynamic crop characteristics during the growing season. Therefore, accounting for the interaction between crop growth and actual ET can significantly improve the performance of models. In this study, an efficient approach is presented for simultaneous calibration of ET and crop growth parameters for the Agricultural Policy/Environmental eXtender (APEX) model for daily, weekly, and monthly ET. The proposed approach involves the development of an objective function based on a compounded time series comprising of scaled annual ET and crop yield data. An efficient search algorithm based on the DiffeRential Evolution Adaptive Metropolis (DREAM) algorithm was implemented in R language to find the parameter values that minimizes the defined objective function. The simultaneous calibration approach, which utilized annual data, improved ET prediction for annual and finer time scales (25% in RMSE reduction for 3-month, 18% for monthly, 17% for 2-week, 19% for weekly, 17% for 3-day, and 13% for daily time scales). The average of absolute relative error for crop yield predictions was also reduced from 43% to 16% for the calibrated model. The simulated leaf area index (LAI) for the calibrated model (i.e. calibrated using annual ET and crop yield data) was also consistent with the measured LAI values, confirming the validity of the calibrated parameter values.

Evaluating evapotranspiration estimation methods in APEX model for dryland cropping systems in a semi-arid region

Evapotranspiration (ET), is a major component of the hydrologic budget and therefore it requires accurate estimation. The Agricultural Policy/Environmental eXtender (APEX), a hydrologic and water quality model developed for evaluating the effect of agricultural production management practices on the environment. It has five different methods to simulate ET. The objectives of this study were to: determine the impact of using different ET methods in APEX on sensitive ET parameters in semi-arid environments, determine reasonable range of values for sensitive parameters, and compare performance of these methods using multiple criteria. ET and crop yield data measured in the Lysimeter fields located in the USDA-ARS Conservation and Production Research Laboratory, Bushland, Texas were used to calibrate and validate the model. Results indicated that selection of statistical model performance measure and ET method affects the number of sensitive parameters and parameter rank. The number of sensitive parameters remained relatively stable among ET simulation methods but there was large variability in parameter sensitivity ranks. It is also important that users carefully choose appropriate statistical measure to use depending on the goals of their study. With the exception of maximum rainfall intercept, exponent coefficient rainfall, SCS index coefficient, rain intercept coefficient, and root growth soil strength, all methods had similar ranges of values for the sensitive parameters. In general there were no large differences in the performance of ET methods. However, Penman-Monteith method simulated ET relatively better than the other methods, which may be explained by the fact that it is a physically-based method with many weather variables whose data was available for the study area. However, the study findings indicate that the other ET methods can provide satisfactory results in regions with limited weather data.

Soybean crop-water production functions in a humid region across years and soils determined with APEX model

Crop production as a function of water use or water applied, called the crop water production function (CWPF), is a useful tool for irrigation planning, design and management. However, these functions are not only crop and variety specific they also vary with soil types and climatic conditions (locations). Derivation of multi-year average CWPFs through field experiments for different locations and soils is time-consuming and expensive, as it requires careful long-term and multi-location field experiments to obtain them. Process based crop system models provide a useful tool for determining CWPFs using short-term field experimental data for calibration and validation. The aim of this study was to determine soybean CWPFs using the Agricultural Policy/Environmental eXtender (APEX) model across three soil types (Vaiden-silty clay, Cahaba-sandy loam, and Demopolis-clay loam) and three weather conditions (14-year average from 2002 to 2015, dry, and wet) of a humid irrigated region in Mississippi, USA. The results showed that the relationship between simulated soybean grain yield (GY) and the seasonal crop evapotranspiration (ET) for each soil under 14-year average weather condition was linear. Compared with the Vaiden soil, the Cahaba and Demopolis soils had slightly higher water use efficiency (WUE) over 14-year average weather conditions. The CWPFs for GY vs supplemental irrigation were cubic polynomials for all soil types and weather conditions, with varying coefficients. The maximum values of irrigation water use efficiency (IWUEmax) derived from these cubic CWPFs varied from 2.58 to 9.89 kg ha−1 mm−1 across soils and weather conditions. The irrigation amount during the growing season required (Imax) to achieve the maximum GY for soybean also had a wide range of values, from 110 to 405 mm. The IWUE and Imax were related to available water holding capacity of soils. The relationship between GY and total plant available water supply (TWS) was also a cubic function, with coefficients varying with soil types and climatic conditions. The yield response factor (Ky) was 1.24 (greater than 1.00) when averaged over 14 years’ weather data, indicating that soybean was very sensitive to water stress even in a humid region like Mississippi. Thus, supplemental irrigation is necessary to increase GY and ensure stability in yields.

Simulating Runoff from Small Grazed Pasture Watersheds Located at North Appalachian Experimental Watershed in Ohio

Runoff from grazing pasture lands can impact water quality in receiving streams if not well managed. Management consists of conservation practices to reduce runoff and pollutants transport. Simulation models have been effectively used to design and implement these conservation practices. The Agricultural Policy Environmental Extender (APEX), a process-based hydrologic model, was used in this study to simulate the management impacts on surface runoff from three small grazed pasture watersheds located at the North Appalachian Experimental Watersheds near Coshocton, Ohio. Specific objectives of this study were to 1) calibrate the APEX model and test runoff predictions against measured runoff and 2) simulate the long-term impacts of different management scenarios on surface runoff. Results show that the APEX model simulated surface runoff reasonably well with the coefficient of determination (R2) and Nash-Sutcliffe efficiency values varying from 0.49 to 0.72 and from 0.25 to 0.60 for calibration and validation, respectively. After validation, the APEX model was run for 37 yr (1975−2011) for long-term scenarios to analyze the impacts of soil properties and management on surface runoff. Data from this study indicated that keeping the watershed land use as a hay meadow instead of grazing significantly reduced cumulative runoff by 58−67%. Buffer strips of perennial grasses resulted in decreased simulated runoff. To simulate the impacts of soils on runoff, the surface (0−5 cm) soil properties of the toe position were applied to the entire grazed watershed. Subsequently, the increase in soil richness resulted in reduction (≤5%) in surface runoff. The simulation results from the present study demonstrate the benefits of hayed meadow over grazed pasture and further predict the decreased trend of runoff due to soil properties change and buffer strips.

Lysimetric Evaluation of the APEX Model to Simulate Daily ET for Irrigated Crops in the Texas High Plains

Abstract. The NTT (Nutrient Tracking Tool) was designed to provide an opportunity for all users, including producers, to run complex simulation models, such as APEX (Agricultural Policy Environmental eXtender), with the associated required databases. The APEX model currently nested within NTT provides estimates of the changes in nitrogen (N), phosphorus (P), and sediment losses that are associated with management practices specified by the user. Five methods (Penman-Monteith, Penman, Priestley-Taylor, Hargreaves-Samani, and Baier-Robertson) for determining potential evapotranspiration (PET) are available as inputs for estimating actual ET. This study was conducted to evaluate the accuracy of the ET values obtained from the five PET equations currently available in APEX using both onsite measured climate data and data from the NTT standard databases. The mean daily, monthly, and annual ET values predicted by each of the equations in APEX for a lysimeter field at the USDA-ARS Conservation and Production Research Laboratory at Bushland, Texas, was compared to values measured for the 2001-2010 period. APEX generally underestimated ET with all PET methods (mostly during growing seasons) at both the daily and monthly levels but overpredicted for years when cotton was grown as the major cash crop due to overprediction of leaf area index during the senescing stage for cotton. The underprediction of ET in growing seasons was possibly from underprediction of rainfall due to estimation of rainfall for missing data. Overall, APEX was able to adequately (R2 = 0.82 and NSE = 0.80) predict mean monthly ET for major crops grown in the semi-arid Texas High Plains region. These results should reinforce confidence in APEX’s ability to simulate ET accurately for fully irrigated farms. ET predictions with the Hargreaves-Samani and Priestley-Taylor methods, which require limited data compared to the Penman and Penman-Monteith methods, were similar (p > 0.05, one-way ANOVA), with mean errors within 8.7% for measured weather data and 12.6% for NTT-generated weather data for both methods. This is encouraging because of the limited availability of measured climate data for the majority of locations in the world, including the U.S. Keywords: APEX, Evapotranspiration (ET), Irrigation, Lysimeters, NTT, Semiarid regions.

Use of soft data for multicriteria calibration and validation of Agricultural Policy Environmental eXtender: Impact on model simulations

Use of soft data and multiple model performance criteria in model calibration and validation are critical to ensure that environmental models capture major hydrologic and water quality processes. The Agricultural Policy/Environmental eXtender (APEX) is a hydrologic and water quality model widely used for evaluating the effect of agricultural production management practices on the environment. However, there are few studies on the impact of soft data on APEX model outputs. This study sought to determine the impact of soft data (i.e., crop yields, evapotranspiration [ET], and drainage) used to constrain calibration on APEX model to simulate outputs (streamflow, total nitrogen [TN], and total phosphorus [TP] losses), as well as the impact of tile drainage on the model outputs to help identify issues with APEX. Long-term measured water quality and quantity data from Rock Creek watershed, northern Ohio, were used for this purpose. Four calibration scenarios were used: (A) streamflow statistics only, (B) streamflow statistics plus soft data, (C) streamflow plus water quality, and (D) streamflow plus water quality plus yields plus soft criteria. The number of parameter sets that meet the criteria decreased from 3,325 to 2, as the number of calibration criteria increased. In general, when soft data were used to constrain the model, the Nash-Sutcliffe efficiency (NSE) values decreased for all components. For example, NSE for streamflow decreased from 0.79 for scenario A to 0.56 for scenario B when the soft data were used, and NSE for TP decreased from 0.34 for scenario C to 0.30 for scenario D. However, the scenarios that used soft data with lower NSE values simulated the biophysical processes more accurately. For all calibration/validation scenarios, streamflow, TN, and TP values were drastically reduced when the model was run without tile drainage. However, there was hardly any tile drainage impact on ET, surface runoff, or crop yields for all scenarios, indicating that improvements in tile drainage, water table, and crop growth routines may be needed. Overall, the results show the importance of constraining the model parameters to produce reasonable values of crop yield and water balance closure to obtain realistic simulations of various management practices.

Improved APEX Model Simulation of Buffer Water Quality Benefits at Field Scale

Abstract. Watershed models offer cost-effective means to quantify the environmental benefits of conservation practices. This study evaluated the ability of the Agricultural Policy/Environmental eXtender (APEX) model to simulate the effectiveness of upland buffers for reducing event runoff, sediment, and total phosphorus (TP) loadings. The study used 16 years of monitoring data (1993-2008) from three field-scale row crop watersheds. Two watersheds had buffers installed in the fall of 1997, one with upland agroforestry buffers (grass plus trees) and the second with upland grass buffers; the third watershed was maintained as a control. Objectives were to (1) determine the effect of upland buffers on APEX parameters, (2) evaluate the ability of APEX to estimate upland buffer effectiveness, and (3) evaluate the impact of alternative buffer placement options on water quality outcomes. After modification of the APEX code to improve simulation of infiltration in the buffers, we successfully calibrated APEX for no-buffer and upland buffer conditions for event runoff and TP. However, calibrated parameters from the no-buffer model simulated buffer conditions poorly and resulted in an overestimation of buffer effectiveness. Buffer effectiveness estimated with upland buffer parameters was similar to that obtained from measured data. Scenario analysis indicated that a combination of backslope and footslope agroforestry buffers was more effective than contour placement for reducing average annual edge-of-field runoff and total P losses. These results highlight the complexity of using APEX to assess upland buffers as well as potential problems when using APEX to quantify the benefits of conservation practices not included in the calibration dataset. Keywords: Agroforestry buffers, Buffer placement, Modeling, Phosphorus, Practice effectiveness, Watershed discretization.

Evaluation of the APEX Model to Simulate Runoff Quality from Agricultural Fields in the Southern Region of the United States.

The Agricultural Policy Environmental eXtender (APEX) model has been widely applied to assess phosphorus (P) loss in runoff water and has been proposed as a model to support practical decisions regarding agricultural P management, as well as a model to evaluate tools such as the P Index. The aim of this study is to evaluate the performance of APEX to simulate P losses from agricultural systems to determine its potential use for refinement or replacement of the P Index in the southern region of the United States. Uncalibrated and calibrated APEX model predictions were compared against measured water quality data from row crop fields in North Carolina and Mississippi and pasture fields in Arkansas and Georgia. Calibrated models satisfactorily predicted event-based surface runoff volumes at all sites (Nash-Sutcliffe efficiency [NSE] > 0.47, |percent bias [PBIAS]| < 34) except Arkansas (NSE < 0.11, |PBIAS| < 50) but did not satisfactory simulate sediment, dissolved P, or total P losses in runoff water. The APEX model tended to underestimate dissolved and total P losses from fields where manure was surface applied. The model also overestimated sediments and total P loads during irrigation events. We conclude that the capability of APEX to predict sediment and P losses is limited, and consequently so is the potential for using APEX to make P management recommendations to improve P Indices in the southern United States.

Calibration of the APEX Model to Simulate Management Practice Effects on Runoff, Sediment, and Phosphorus Loss.

Process-based computer models have been proposed as a tool to generate data for Phosphorus (P) Index assessment and development. Although models are commonly used to simulate P loss from agriculture using managements that are different from the calibration data, this use of models has not been fully tested. The objective of this study is to determine if the Agricultural Policy Environmental eXtender (APEX) model can accurately simulate runoff, sediment, total P, and dissolved P loss from 0.4 to 1.5 ha of agricultural fields with managements that are different from the calibration data. The APEX model was calibrated with field-scale data from eight different managements at two locations (management-specific models). The calibrated models were then validated, either with the same management used for calibration or with different managements. Location models were also developed by calibrating APEX with data from all managements. The management-specific models resulted in satisfactory performance when used to simulate runoff, total P, and dissolved P within their respective systems, with > 0.50, Nash-Sutcliffe efficiency > 0.30, and percent bias within ±35% for runoff and ±70% for total and dissolved P. When applied outside the calibration management, the management-specific models only met the minimum performance criteria in one-third of the tests. The location models had better model performance when applied across all managements compared with management-specific models. Our results suggest that models only be applied within the managements used for calibration and that data be included from multiple management systems for calibration when using models to assess management effects on P loss or evaluate P Indices.

Modified APEX model for Simulating Macropore Phosphorus Contributions to Tile Drains.

The contribution of macropore flow to phosphorus (P) loadings in tile-drained agricultural landscapes remains poorly understood at the field scale, despite the recognized deleterious impacts of contaminant transport via macropore pathways. A new subroutine that couples existing matrix-excess and matrix-desiccation macropore flow theory and a modified P routine is implemented in the Agricultural Policy Environmental eXtender (APEX) model. The original and modified formulation were applied and evaluated for a case study in a poorly drained field in Western Ohio with 31 months of surface and subsurface monitoring data. Results highlighted that a macropore subroutine in APEX improved edge-of-field discharge calibration and validation for both tile and total discharge from satisfactory and good, respectively, to very good and improved dissolved reactive P load calibration and validation statistics for tile P loads from unsatisfactory to very good. Output from the calibrated macropore simulations suggested median annual matrix-desiccation macropore flow contributions of 48% and P load contributions of 43%, with the majority of loading occurring in winter and spring. While somewhat counterintuitive, the prominence of matrix-desiccation macropore flow during seasons with less cracking reflects the importance of coupled development of macropore pathways and adequate supply of the macropore flow source. The innovative features of the model allow for assessments of annual macropore P contributions to tile drainage and has the potential to inform P site assessment tools.

Sensitivity Analysis of the APEX Model for Assessing Sustainability of Switchgrass Grown for Biofuel Production in Central Texas

Crop simulation models are increasingly being used to understand the feasibility of large-scale cellulosic biofuel production along with the multi-dimensional impacts on environmental sustainability. However, how the uncertainty in model parameters impacts model performance for sustainability is unclear. In this case study, sensitivity analyses were conducted for three switchgrass sustainability metrics: total biomass production, nitrogen loss, and soil carbon change using the APEX (Agricultural Policy/Environmental eXtender) model. Fifteen out of the 45 parameters (25 crop growth (CROP) parameters and 20 additional model parameters (PARM)) were identified as influential for the three sustainability metrics for three lowland genotypes (WBC, AP13, and KAN) across two locations (Temple, TX, and Austin, TX). Our sensitivity results showed that parameter importance was not dependent on the genotypes but depended on the variables of interest, and differed only slightly between locations. Influential belowground-related CROP and PARM parameters were identified for each sustainability metric, indicating that belowground-related parameters are just as important as commonly measured aboveground CROP parameters. Further investigation of the linear or non-linear relationships and the two-way interactions between each of the individual influential parameters with the three sustainability metrics reflected the functions and characteristics within the APEX model and the interrelations among different processes. Strong interactions between the most influential parameters for total biomass, nitrogen loss, and soil carbon change also highlighted the importance of accurately setting these parameters. Identification of influential model parameters for switchgrass sustainability may help guide field measurements and provide further understanding of the interrelated processes in the APEX model. Furthermore, future field experiments can be designed to measure these influential parameters and understand the non-linear relationships identified between influential parameters and response variables. More accurate model parameterization will help improve APEX model performance and our understanding of the possible underlying physiological mechanisms.

Development and evaluation of the bacterial fate and transport module for the Agricultural Policy/Environmental eXtender (APEX) model

The Agricultural Policy/Environmental eXtender (APEX) is a watershed-scale water quality model that includes detailed representation of agricultural management. The objective of this work was to develop a process-based model for simulating the fate and transport of manure-borne bacteria on land and in streams with the APEX model. The bacteria model utilizes manure erosion rates to estimate the amount of edge-of-field bacteria export. Bacteria survival in manure is simulated as a two-stage process separately for each manure application event. In-stream microbial fate and transport processes include bacteria release from streambeds due to sediment resuspension during high flow events, active release from the streambed sediment during low flow periods, bacteria settling with sediment, and survival. Default parameter values were selected from published databases and evaluated based on field observations. The APEX model with the newly developed microbial fate and transport module was applied to simulate fate and transport of the fecal indicator bacterium Escherichia coli in the Toenepi watershed, New Zealand that was monitored for seven years. The stream network of the watershed ran through grazing lands with daily bovine waste deposition. Results show that the APEX with the bacteria module reproduced well the monitored pattern of E. coli concentrations at the watershed outlet. The APEX with the microbial fate and transport module will be utilized for predicting microbial quality of water as affected by various agricultural practices, evaluating monitoring protocols, and supporting the selection of management practices based on regulations that rely on fecal indicator bacteria concentrations.