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This paper reviews simplified process models for denitrification. More than fifty models were considered. The majority of these (simple) models are based on potential denitrification—either measured as a soil's property or computed from organic C dynamics—or consider denitrification as a first-order decay process. As it is generally accepted that environmental soil conditions affect the denitrification process, reduction functions are used. Although denitrification is truly driven by the non-availability of oxygen, most authors argue that oxygen dynamics in soil is hard to simulate (or to measure). Therefore, water content is used as a complementary for oxygen diffusion. The higher the water content, the less...
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This data release contains model input and output files for simulating and predicting thermal spring flows at Hot Springs National Park (HOSP), Hot Springs, Arkansas. A three-dimensional hydrogeologic framework of the Hot Springs anticlinorium beneath Hot Springs National Park was constructed to represent the complex hydrogeology of HOSP and surrounding areas to depths exceeding 9,000 feet below ground surface. The framework, composed of 6 rock formations and 1 vertical fault emplaced beneath the thermal springs, was discretized into 19 layers, 429 rows, and 576 columns and incorporated into a 3-dimensional steady-state groundwater-flow model constructed in MODFLOW-2005. Historical daily mean thermal spring flows...
Often landmark conservation decisions are made despite an incomplete knowledge of system behavior and inexact predictions of how complex ecosystems will respond to management actions. For example, predicting the feasibility and likely effects of restoring top-level carnivores such as the gray wolf (Canis lupus) to North American wilderness areas is hampered by incomplete knowledge of the predator-prey system processes and properties. In such cases, global sensitivity measures, such as Sobol? indices, allow one to quantify the effect of these uncertainties on model predictions. Sobol? indices are calculated by decomposing the variance in model predictions (due to parameter uncertainty) into main effects of model...
The aims of this study were to determine the energy consumption and evaluation of inputs sensitivity for soybean production in Kordkuy county of Iran. The data used in this study were obtained from 32 farmers using a face-to-face questionnaire base of random sampling method. The sensitivity of energy inputs was estimated using the marginal physical productivity (MPP) method and partial regression coefficients on soybean yield. The results indicated that the total input and output energy use was to be 18,026.50 and 71,228.86 MJ ha−1 respectively. With 66.67%, the diesel fuel was the highest within the energy equivalents and followed by chemical fertilizers and water for irrigation with 14.32% and 6.18% respectively....
Using one- and two-dimensional homogeneous simulations, this paper addresses challenges associated with sensitivity analysis and parameter estimation for virus transport simulated using sorptive–reactive processes. Head, flow, and conservative- and virus-transport observations are considered. The paper examines the use of (1) observed-value weighting, (2) breakthrough-curve temporal moment observations, and (3) the significance of changes in the transport time-step size. The results suggest that (1) sensitivities using observed-value weighting are more susceptible to numerical solution variability, (2) temporal moments of the breakthrough curve are a more robust measure of sensitivity than individual conservative-transport...
Vegetative filter strips (VFS) are proposed for protection of receiving water bodies and aquatic organisms from pesticides in runoff, but there is debate regarding the efficiency and filter size requirements. This debate is largely due to the belief that no quantitative methodology exists for predicting runoff buffer efficiency when conducting acute and/or chronic environmental exposure assessments. Previous research has proposed a modeling approach that links the U.S. Environmental Protection Agency’s (EPA’s) PRZM/EXAMS with a well-tested process-based model for VFS (VFSMOD). In this research, we apply the modeling framework to determine (1) the most important input factors for quantifying mass reductions of pesticides...
The aims of this study were to determine the energy consumption and evaluation of inputs sensitivity for soybean production in Kordkuy county of Iran. The data used in this study were obtained from 32 farmers using a face-to-face questionnaire base of random sampling method. The sensitivity of energy inputs was estimated using the marginal physical productivity (MPP) method and partial regression coefficients on soybean yield. The results indicated that the total input and output energy use was to be 18,026.50 and 71,228.86 MJ ha−1 respectively. With 66.67%, the diesel fuel was the highest within the energy equivalents and followed by chemical fertilizers and water for irrigation with 14.32% and 6.18% respectively....
    map background search result map search result map Model Inputs and Outputs for Simulating and Predicting the Effects of Climate and Land-Use Changes on Thermal Springs Recharge—A System-Based Coupled Surface-water and Groundwater Model for Hot Springs National Park, Arkansas Model Inputs and Outputs for Simulating and Predicting the Effects of Climate and Land-Use Changes on Thermal Springs Recharge—A System-Based Coupled Surface-water and Groundwater Model for Hot Springs National Park, Arkansas