Agricultural Policy Environmental eXtender Simulation of Three Adjacent Row-Crop Watersheds in the Claypan Region

Understanding the effects of pasture type and stocking rate on the hydrology of the Southern Great Plains

Grassland is one of the major biomes in the United States (US) and the world. In the US, the majority of grasslands are concentrated in the Great Plains and has undergone through significant interventions or management changes over the last few decades. A key economy-driven intervention in the Southern Great Plains (SGP) include the introduction of new forage species and conversion of native grassland to introduced pasture to increase productivity and its nutritive value for improved cattle production. Since water is one of the fundamental resources needed to sustain grassland productivity, it is important to understand how such pasture conversion and prevailing cattle grazing practices affect water balance and biomass production in a given pasture system. In this study, the Nutrient Tracking Tool (NTT) with its core APEX (Agricultural Policy Environmental eXtender) model was used to assess the hydrological impacts of the pasture introduction, i.e., native pasture (little bluestem, Schizachyrium halapense) vs. introduced pasture (old world bluestem, Bothriochloa caucasica), and the stocking rate in the SGP. Monthly evapotranspiration (ET) and biomass estimates from NTT compared well with observed data at two USDA-ARS experimental pastures (native and introduced) near El Reno, Oklahoma, for the years 2015 and 2016. Simulated long-term average annual hydrologic fluxes (i.e., ET, runoff, and groundwater recharge) from the introduced pasture were slightly lower than the observed data but not significantly different than those from the native pasture under the current management conditions. NTT predicted higher water yield (runoff and recharge) and significantly lower ET for the introduced pasture than the native pasture. Results suggest that grazing has the potential to alter the hydrological balance in the SGP. For example, the increase in stocking rate within the carrying capacity of the farm decreases ET and increases runoff and groundwater recharge for both pastures. Comparison of estimated biomass production between native and introduced pastures indicated that introduced pastures are more efficient in using the available water and thus produce a higher forage biomass per unit of water in the SGP. This study highlighted the potential significance of considering hydrological and other biophysical impacts of new forage introduction and stocking rate changes for the sustainable management of grazing and pasture systems in the SGP.

Multisite Evaluation of APEX for Water Quality: I. Best Professional Judgment Parameterization

The Agricultural Policy Environmental eXtender (APEX) model is capable of estimating edge-of-field water, nutrient, and sediment transport and is used to assess the environmental impacts of management practices. The current practice is to fully calibrate the model for each site simulation, a task that requires resources and data not always available. The objective of this study was to compare model performance for flow, sediment, and phosphorus transport under two parameterization schemes: a best professional judgment (BPJ) parameterization based on readily available data and a fully calibrated parameterization based on site-specific soil, weather, event flow, and water quality data. The analysis was conducted using 12 datasets at four locations representing poorly drained soils and row-crop production under different tillage systems. Model performance was based on the Nash-Sutcliffe efficiency (NSE), the coefficient of determination () and the regression slope between simulated and measured annualized loads across all site years. Although the BPJ model performance for flow was acceptable (NSE = 0.7) at the annual time step, calibration improved it (NSE = 0.9). Acceptable simulation of sediment and total phosphorus transport (NSE = 0.5 and 0.9, respectively) was obtained only after full calibration at each site. Given the unacceptable performance of the BPJ approach, uncalibrated use of APEX for planning or management purposes may be misleading. Model calibration with water quality data prior to using APEX for simulating sediment and total phosphorus loss is essential.

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.

Multisite Evaluation of APEX for Water Quality: II. Regional Parameterization

Phosphorus (P) Index assessment requires independent estimates of long-term average annual P loss from fields, representing multiple climatic scenarios, management practices, and landscape positions. Because currently available measured data are insufficient to evaluate P Index performance, calibrated and validated process-based models have been proposed as tools to generate the required data. The objectives of this research were to develop a regional parameterization for the Agricultural Policy Environmental eXtender (APEX) model to estimate edge-of-field runoff, sediment, and P losses in restricted-layer soils of Missouri and Kansas and to assess the performance of this parameterization using monitoring data from multiple sites in this region. Five site-specific calibrated models (SSCM) from within the region were used to develop a regionally calibrated model (RCM), which was further calibrated and validated with measured data. Performance of the RCM was similar to that of the SSCMs for runoff simulation and had Nash-Sutcliffe efficiency (NSE) > 0.72 and absolute percent bias (|PBIAS|) < 18% for both calibration and validation. The RCM could not simulate sediment loss (NSE < 0, |PBIAS| > 90%) and was particularly ineffective at simulating sediment loss from locations with small sediment loads. The RCM had acceptable performance for simulation of total P loss (NSE > 0.74, |PBIAS| < 30%) but underperformed the SSCMs. Total P-loss estimates should be used with caution due to poor simulation of sediment loss. Although we did not attain our goal of a robust regional parameterization of APEX for estimating sediment and total P losses, runoff estimates with the RCM were acceptable for P Index evaluation.

Sensitivity Analysis of the Agricultural Policy/Environmental eXtender (APEX) for Phosphorus Loads in Tile-Drained Landscapes

Numerical modeling is an economical and feasible approach for quantifying the effects of best management practices on dissolved reactive phosphorus (DRP) loadings from agricultural fields. However, tools that simulate both surface and subsurface DRP pathways are limited and have not been robustly evaluated in tile-drained landscapes. The objectives of this study were to test the ability of the Agricultural Policy/Environmental eXtender (APEX), a widely used field-scale model, to simulate surface and tile P loadings over management, hydrologic, biologic, tile, and soil gradients and to better understand the behavior of P delivery at the edge-of-field in tile-drained midwestern landscapes. To do this, a global, variance-based sensitivity analysis was performed, and model outputs were compared with measured P loads obtained from 14 surface and subsurface edge-of-field sites across central and northwestern Ohio. Results of the sensitivity analysis showed that response variables for DRP were highly sensitive to coupled interactions between presumed important parameters, suggesting nonlinearity of DRP delivery at the edge-of-field. Comparison of model results to edge-of-field data showcased the ability of APEX to simulate surface and subsurface runoff and the associated DRP loading at monthly to annual timescales; however, some high DRP concentrations and fluxes were not reflected in the model, suggesting the presence of preferential flow. Results from this study provide new insights into baseline tile DRP loadings that exceed thresholds for algal proliferation. Further, negative feedbacks between surface and subsurface DRP delivery suggest caution is needed when implementing DRP-based best management practices designed for a specific flow pathway.

Long-term agroecosystem research in the central Mississippi river basin: goodwater creek experimental watershed weather data

Knowledge of weather, particularly precipitation, is fundamental to interpreting watershed and hydrologic processes. The long-term weather record in the Goodwater Creek Experimental Watershed (GCEW) complements hydrologic and water quality data in the region. The GCEW also is the core of the Central Mississippi River Basin (CMRB) node of the Long-Term Agroecosystem Research network. Our objectives are to (i) describe the climatological context of the GCEW and CMRB settings, (ii) document instrumentation and the data collection, quality assurance, and reduction processes; (iii) provide examples of the data obtained and descriptive statistics; and (iv) document the availability of and access methods to obtain the data from the web-based data access portal at . These objectives support an overall goal to make these long-term data available to the public for use in further analyses and modeling in support of research and public policy on watershed management.

Evaluation of a Stepwise, Multiobjective, Multivariable Parameter Optimization Method for the APEX Model

Hydrologic models are essential tools for environmental assessment of agricultural nonpoint-source pollution. The automatic calibration of hydrologic models, though efficient, demands significant computational power, limiting their application. The study objective was to develop and evaluate a stepwise, multiobjective, multivariable automatic calibration method for the Agricultural Environmental Policy eXtender (APEX) model for simulating runoff, sediment, total phosphorus (TP), and total nitrogen (TN). The most sensitive parameters were grouped according to the process they primarily affect (runoff, sediment transport, soil biological activity, TP transport, and TN transport) and were optimized separately and consecutively. Two multiobjective functions comprising combinations of coefficient of determination (), regression slope, and Nash-Sutcliffe coefficient (NSC) and a global objective function, the Generalized Likelihood Uncertainty Estimation, were considered to select the optimal parameter combination. A previously manually calibrated and validated APEX model for three adjacent row-crop field-size watersheds in northeast Missouri was used as the baseline. The greatest improvements in model performance for sediment, TP, and TN, but not for runoff, were found after runoff parameter optimization, indicating that runoff parameter optimization was crucial for good simulation of sediment and nutrients. The values for sediment, TP, and TN improved from 0.59-0.87 to 0.77-0.94. The NSC values for TP also improved after soil biological activity and TP parameter optimizations, but subsequent optimizations did not improve sediment or TN simulations. The objective function based on , slope, and NSC outperformed the other objective functions. Modelers can benefit from this cost-efficient optimization technique (2570 runs for 23 parameters).