Test of APEX for nine forested watersheds in East Texas

Exploration of a comprehensive versus a regulatory-oriented modeling framework for field pesticide transport assessment

Numerous computer models have been developed for simulating pesticide fate and transport. It is usually hard to choose which model is the best for a particular research or regulatory purpose. Currently, the PRZM (Pesticide Root Zone Model) model is widely used for regulatory purposes regarding runoff and erosion. However, it simplifies many hydrological processes and management practices which affect pesticide fate simulations. In this study, the APEX (Agricultural Policy / Environmental eXtender model) model, which is more comprehensive and may provide a more realistic representation of pesticide fate, was compared with the PRZM model regarding methods and capabilities of characterizing hydrology, management, and pesticide transport. Four case studies were used to compare the performances of the two models for simulating surface runoff, sediment yield, pesticide in runoff, and pesticide in sediment. Results showed that the APEX model performed better than the PRZM model for simulating surface runoff and sediment yield, and performed similarly to the PRZM model for simulating pesticide loads in runoff and erosion. Both models have limitations for capturing the runoff events caused by high intensity rainfall. APEX is superior to PRZM in simulating detailed management operations, considering more hydrological processes, and achieving spatially distributed simulation, but it requires a higher number of inputs and user-selected parameters compared to PRZM. With further validations of the capabilities of APEX in pesticide modeling and the development of web-based platforms to facilitate the set up and use of comprehensive models, a more accurate and reliable pesticide assessment scheme is anticipated by using comprehensive models like APEX.

Development, growth, and biomass simulations of two common wetland tree species in Texas

Monitoring the health and condition of wetlands using biological assessments can serve as an effective tool for environmental managers to better evaluate and monitor the status and trends of their wetland ecosystems. Woody species can be used as conspicuous biological assessment tools due to their direct response to environmental change, such as hydrologic alteration. The purpose of this study is to use field-measured morphological measurement indices to develop and optimize tree growth parameters and growth curves using multi-model combination approach to improve tree biomass estimations. Field morphological investigations were conducted for two common wetland tree species in Texas. A range of morphological characteristics including leaf area index, height, and biomass was measured for black willow (Salix nigra Marsh) and green ash (Fraxinus pennsylvanica) sampled from 15 sites in a wetland near Cameron, Texas. The measured morphological parameters were used to optimize tree growth and development with the ALMANAC model. The developed tree growth parameters and growth curves were subsequently used in the APEX model to simulate tree biomass at the catchment scale. Both models accurately simulated biomass of trees growing in the wetland. This accurate biomass prediction will be useful to advance science to better monitor and assess wetland health on a large scale (e.g. national or global).

A Comparison of Simulated and Field-Derived Leaf Area Index (LAI) and Canopy Height Values from Four Forest Complexes in the Southeastern USA

Vegetative leaf area is a critical input to models that simulate human and ecosystem exposure to atmospheric pollutants. Leaf area index (LAI) can be measured in the field or numerically simulated, but all contain some inherent uncertainty that is passed to the exposure assessments that use them. LAI estimates for minimally managed or natural forest stands can be particularly difficult to develop as a result of interspecies competition, age and spatial distribution. Satellite-based LAI estimates hold promise for retrospective analyses, but we must continue to rely on numerical models for alternative management analysis. Our objective for this study is to calculate and validate LAI estimates generated from the USDA Environmental Policy Impact Climate (EPIC) model (a widely used, field-scale, biogeochemical model) on four forest complexes spanning three physiographic provinces in Virginia and North Carolina. Measurements of forest composition (species and number), LAI, tree diameter, basal area, and canopy height were recorded at each site during the 2002 field season. Calibrated EPIC results show stand-level temporally resolved LAI estimates with R² values ranging from 0.69 to 0.96, and stand maximum height estimates within 20% of observation. This relatively high level of performance is attributable to EPIC's approach to the characterization of forest stand biogeochemical budgets, stand history, interspecies competition and species-specific response to local weather conditions. We close by illustrating the extension of this site-level approach to scales that could support regional air quality model simulations.

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).

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

The Agricultural Policy Environmental Extender (APEX) model is used to evaluate best management practices on pollutant loading in whole farms or small watersheds. The objectives of this study were to conduct a sensitivity analysis to determine the effect of model parameters on APEX output and use the parameterized, calibrated, and validated model to evaluate long-term benefits of grass waterways. The APEX model was used to model three (East, Center, and West) adjacent field-size watersheds with claypan soils under a no-till corn ( L.)/soybean [ (L.) Merr.] rotation. Twenty-seven parameters were sensitive for crop yield, runoff, sediment, nitrogen (dissolved and total), and phosphorous (dissolved and total) simulations. The model was calibrated using measured event-based data from the Center watershed from 1993 to 1997 and validated with data from the West and East watersheds. Simulated crop yields were within ±13% of the measured yield. The model performance for event-based runoff was excellent, with calibration and validation > 0.9 and Nash-Sutcliffe coefficients (NSC) > 0.8, respectively. Sediment and total nitrogen calibration results were satisfactory for larger rainfall events (>50 mm), with > 0.5 and NSC > 0.4, but validation results remained poor, with NSC between 0.18 and 0.3. Total phosphorous was well calibrated and validated, with > 0.8 and NSC > 0.7, respectively. The presence of grass waterways reduced annual total phosphorus loadings by 13 to 25%. The replicated study indicates that APEX provides a convenient and efficient tool to evaluate long-term benefits of conservation practices.

The applications of GIS in the analysis of the impacts of human activities on south Texas watersheds

With water resource planning assuming greater importance in environmental protection efforts, analyzing the health of agricultural watersheds using Geographic Information Systems (GIS) becomes essential for decision-makers in Southern Texas. Within the area, there exist numerous threats from conflicting land uses. These include the conversion of land formerly designated for agricultural purposes to other uses. Despite current efforts, anthropogenic factors are greatly contributing to the degradation of watersheds. Additionally, the activities of waste water facilities located in some of the counties, rising populations, and other socioeconomic variables are negatively impacting the quality of water in the agricultural watersheds. To map the location of these stressors spatially and the extent of their impacts across time, the paper adopts a mix scale method of temporal spatial analysis consisting of simple descriptive statistics. In terms of objectives, this research provides geo-spatial analysis of the effects of human activities on agricultural watersheds in Southern Texas and the factors fuelling the concerns under the purview of watershed management. The results point to growing ecosystem decline across time and a geographic cluster of counties experiencing environmental stress. Accordingly, the emergence of stressors such as rising population, increased use of fertilizer treatments on farm land, discharges of atmospheric pollutants and the large presence of municipal and industrial waste treatment facilities emitting pathogens and pesticides directly into the agricultural watersheds pose a growing threat to the quality of the watershed ecosystem.