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United States Department of Agriculture

Agricultural Research Service

Title: Modeling Spatial-Temporal Soil Water and Overland Flow in a Dryland Wheat-Fallow Field Using Maria-Gis

Authors
item Green, Timothy
item Ascough, James
item Erskine, Robert
item Vandenberg, Bruce
item Ahuja, Lajpat

Submitted to: World Congress of Soil Science
Publication Type: Abstract Only
Publication Acceptance Date: May 1, 2006
Publication Date: July 10, 2006
Citation: Green, T.R., Ascough II, J.C., Erskine, R.H., Vandenberg, B.C., Ahuja, L.R. 2006. Modeling spatial-temporal soil water and overland flow in a dryland wheat-fallow field using maria-gis. World Congress of Soil Science. Philadelphia, PA. 7/9-7/15/2006

Interpretive Summary: Crop production and environmental fluxes vary in space and time and over a range of scales in agricultural systems. Process interactions between soil hydrology, plant growth and development, nutrient cycling and chemical transport are tightly coupled such that the soil water dynamics reflect the crop status, and vice versa. Such complex interactions are explored using a vertically complex agricultural systems model (MARIA – Management of Agricultural Resources through Integrated Assessment, based on the Root Zone Water Quality Model, and the DSSAT 3.5 crop growth model) with kinematic wave overland flow between delineated land units. A hierarchy of land units (LU’s) allows simulation of runoff and run-on along flow paths. The model is applied to a dryland wheat-fallow field (109-ha) in eastern Colorado, USA that is strip cropped. Various temporal and spatial data have been collected since 2001 to characterize meteorological variables, soil and canopy-level air temperature, crop emergence, development, biomass, and final grain yield, soil properties and water content, and edge-of-field surface water runoff. Spatial data within each LU are scaled up for comparison with simulation results. Issues of model calibration, parameter estimation, and uncertainty analysis will be discussed in a spatial scaling context. In addition, we examine integration of spatial data collection, scaling, and simulation – issues that have important implications for addressing soil degradation and sustainable agricultural management.

Technical Abstract: Crop production and environmental fluxes vary in space and time and over a range of scales in agricultural systems. Process interactions between soil hydrology, plant growth and development, nutrient cycling and chemical transport are tightly coupled such that the soil water dynamics reflect the crop status, and vice versa. Such complex interactions are explored using a vertically complex agricultural systems model (MARIA – Management of Agricultural Resources through Integrated Assessment, based on the Root Zone Water Quality Model, and the DSSAT 3.5 crop growth model) with kinematic wave overland flow between delineated land units. A hierarchy of land units (LU’s) allows simulation of runoff and run-on along flow paths. The model is applied to a dryland wheat-fallow field in eastern Colorado, USA that is strip cropped, such that a crop is growing every year on approximately half of the whole 109-ha field. Data collection since 2001 includes basic meteorological variables at one location, rainfall rate at five locations, soil and canopy-level air temperature at multiple locations, spatial crop grain yield from a calibrated yield monitor, nested spatial samples of plant emergence, development and biomass, synoptic maps of surface (top 300 mm) soil water content on several dates, 18 profiles of hourly soil water content primarily along two transects, edge-of-field surface water runoff events, and distributed soil texture. Land units of a few ha each are delineated based on 5-m elevation data (cm vertical accuracy), and spatial data within each LU are scaled up for comparison with simulation results. Issues of model calibration, parameter estimation, and uncertainty analysis will be discussed in a spatial scaling context. In addition, we examine integration of spatial data collection, scaling, and simulation – issues that have important implications for addressing soil degradation and sustainable agricultural management.

Last Modified: 10/25/2014
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