Parameter sensitivity in calibration and validation of an annualized agricultural non-point source model

Baginska, Barbara; Milne-Home, William

doi:10.1029/ws006p0331

Cited by 7 publications

(6 citation statements)

References 14 publications

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“…The hydrologic component was adjusted at the beginning of the calibration process (Baginska and Milne-Home, 2003;Muleta and Nicklow, 2005). The amount of runoff was primarily determined by the effective hydraulic conductivity (Nearing et al, 1990;Schoeneberger and Wysocki, 2005).…”

Section: Wepp Model Calibration and Quasi Validationmentioning

confidence: 99%

Long‐term effects of management practices on water‐driven soil erosion in an intense agricultural sub‐watershed: monitoring and modelling

Abaci

Papanicolaou

2009

Hydrological Processes

104

138

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Abstract:The overarching objective of this research was to provide an improved understanding of the role of land use and associated management practices on long-term water-driven soil erosion in small agricultural watersheds by coupling the established, physically based, distributed parameter Water Erosion Prediction Project (WEPP) model with long-term hydrologic, land use and soil data. A key step towards achieving this objective was the development of a detailed methodology for model calibration using physical ranges of key governing parameters such as effective hydraulic conductivity, critical hydraulic shear stress and rill/inter-rill erodibilities. The physical ranges for these governing parameters were obtained based on in situ observations within the South Amana Sub-Watershed (SASW) (¾26 km 2 ) of the Clear Creek, IA watershed where detailed documentation of the different land uses was available for a period of nearly 100 years. A quasi validation of the calibrated model was conducted through long-term field estimates of water and sediment discharge at the outlet of SASW and also by comparing the results with data reported in the literature for other Iowa watersheds exhibiting similar biogeochemical properties. Once WEPP was verified, 'thought experiments' were conducted to test our hypothesis that land use and associated management practices may be the major control of long-term erosion in small agricultural watersheds such as SASW. Those experiments were performed using the dominant 2-year crop rotations in the SASW, namely, fall till corn-no till bean (FTC-NTB), no till bean-spring till corn (NTB-STC) and no till corn-fall till bean (NTC-FTB), which comprised approximately 90% of the total acreage in SASW. Results of this study showed that for all crop rotations, a strong correspondence existed between soil erosion rates and high-magnitude precipitation events during the period of mid-April and late July, as expected. The magnitude of this correspondence, however, was strongly affected by the crop rotation characteristics, such as canopy/residue cover provided by the crop, and the type and associated timing of tillage. Tillage type (i.e. primary and secondary tillages) affected the roughness of the soil surface and resulted in increases of the rill/inter-rill erodibilities up to 35% and 300%, respectively. Particularly, the NTC-FTB crop rotation, being the most intense land use in terms of tillage operations, caused the highest average annual erosion rate within the SASW, yielding quadrupled erosion rates comparatively to NTB-STC. The impacts of tillage operation were further exacerbated by the timing of the operations in relation to precipitation events. Timing of operations affected the 'life-time' of residue cover and as a result, the degree of protection that residue cover offers against the water action on the soil surface. In the case of NTC-FTB crop rotation, dense corn residue stayed on the ground for only 40 days, whereas for the other two rotations, corn residue provided a protective layer for...

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Section: Wepp Model Calibration and Quasi Validationmentioning

confidence: 99%

Long‐term effects of management practices on water‐driven soil erosion in an intense agricultural sub‐watershed: monitoring and modelling

Abaci

Papanicolaou

2009

Hydrological Processes

104

138

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show abstract

“…This analysis reflects the capability of AnnAGNPS to estimate runoff that would be typical for ungauged watersheds, where data for calibration are usually not available. Furthermore, process based models are designed to characterize watershed processes well enough to enable the use of measurable properties and conditions without require formal calibration [44]. AnnAGNPS is one such model that has been developed to include processes that utilize input parameters from databases, e.g., climate, soil information, and crop management operations, developed by NRCS for any location in the U.S.…”

Section: Model Evaluationmentioning

confidence: 99%

AnnAGNPS Model Application for Nitrogen Loading Assessment for the Future Midwest Landscape Study

Yuan

Mehaffey

Lopez

et al. 2011

Water

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Abstract:The Future Midwest Landscape (FML) project is part of the US Environmental Protection Agency (EPA)'s new Ecosystem Services Research Program, undertaken to examine the variety of ways in which landscapes that include crop lands, conservation areas, wetlands, lakes, and streams affect human well-being. The goal of the FML project is to quantify current and future ecosystem services across the region and to examine changes expected to occur as a result of the growing demand for biofuels. This study is one of several pilots taking place under the umbrella of the FML research project. In this study, the USDA Annualized Agricultural Non-Point Source Pollution (AnnAGNPS) model was applied to the East Fork Kaskaskia River watershed (289. future biofuel target were also simulated and analyzed. All delineations of the study area (coarser to finer) produced satisfactory results in simulating monthly and annual runoff. However, the size of the delineation does impact the simulation results. Finer delineations better represented the actual landscape and captured small critical areas that would be homogenized in coarser delineation. Those small critical areas are important to target to achieve maximum environment benefit. Simulations of alternative future scenarios showed that as corn production increases to meet future biofuel needs, total nitrogen loss increases. For this watershed, total N loss would be more than doubled if converting all corn/soybean rotation (15,871.2 ha) to continuous corn comparing with the base year total N loss which is 11.2 kg/ha. Conservation practices are needed to reduce total nitrogen loss from the watershed. This study provides an important foundation for the larger FML region modeling effort by addressing challenging FML landscape modeling issues such as model selection, need for further model development, and spatial resolution.

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“…Uncertainty analysis was performed to quantify and describe the effect of input parameter variability into the output results. The AnnAGNPS model is an evolving and complex model with a large number of input basic variables and parameters and has been extensively evaluated with sensitivity analyses (Baginska and Milne‐Home, 2003; Chahor et al, 2014; Das et al, 2008; Licciardello et al, 2007; Yuan et al, 2003, 2005, 2006; Zema et al, 2012). Therefore, a detailed uncertainty investigation of the entire AnnAGNPS model is beyond the scope of this study.…”

Section: Methodsmentioning

confidence: 99%

Spatial Characterization of Riparian Buffer Effects on Sediment Loads from Watershed Systems

et al. 2014

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Understanding all watershed systems and their interactions is a complex, but critical, undertaking when developing practices designed to reduce topsoil loss and chemical/nutrient transport from agricultural fields. The presence of riparian buffer vegetation in agricultural landscapes can modify the characteristics of overland flow, promoting sediment deposition and nutrient filtering. Watershed simulation tools, such as the USDA-Annualized Agricultural Non-Point Source (AnnAGNPS) pollution model, typically require detailed information for each riparian buffer zone throughout the watershed describing the location, width, vegetation type, topography, and possible presence of concentrated flow paths through the riparian buffer zone. Research was conducted to develop GIS-based technology designed to spatially characterize riparian buffers and to estimate buffer efficiency in reducing sediment loads in a semiautomated fashion at watershed scale. The methodology combines modeling technology at different scales, at individual concentrated flow paths passing through the riparian zone, and at watershed scales. At the concentrated flow path scale, vegetative filter strip models are applied to estimate the sediment-trapping efficiency for each individual flow path, which are aggregated based on the watershed subdivision and used in the determination of the overall impact of the riparian vegetation at the watershed scale. This GIS-based technology is combined with AnnAGNPS to demonstrate the effect of riparian vegetation on sediment loadings from sheet and rill and ephemeral gully sources. The effects of variability in basic input parameters used to characterize riparian buffers, onto generated outputs at field scale (sediment trapping efficiency) and at watershed scale (sediment loadings from different sources) were evaluated and quantified. The AnnAGNPS riparian buffer component represents an important step in understanding and accounting for the effect of riparian vegetation, existing and/or managed, in reducing sediment loads at the watershed scale.

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Parameter sensitivity in calibration and validation of an annualized agricultural non-point source model

Cited by 7 publications

References 14 publications

Long‐term effects of management practices on water‐driven soil erosion in an intense agricultural sub‐watershed: monitoring and modelling

Long‐term effects of management practices on water‐driven soil erosion in an intense agricultural sub‐watershed: monitoring and modelling

AnnAGNPS Model Application for Nitrogen Loading Assessment for the Future Midwest Landscape Study

Spatial Characterization of Riparian Buffer Effects on Sediment Loads from Watershed Systems

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