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Title: SIMULATING SURFACE SOIL AND RESIDUE TEMPERATURES WITH INCOMPLETE COVER

Author
item Aiken, Robert
item Flerchinger, Gerald
item Farahani, Hamid
item JOHNSEN, KAREN - COLORADO STATE UNIVERSITY

Submitted to: Agronomy Journal
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 11/21/1996
Publication Date: N/A
Citation: N/A

Interpretive Summary: Accurate simulation of crop residue effects on soil warming can guide tillage and crop residue management alternatives for soil, water, nutrient conservation, pest management and plant development. We developed a simple, yet robust computer program predicting crop residue effects on soil warming, and compared it's predictive accuracy against field observations. PENFLUX, a Penman-type energy balance module, implemented within the Root Zone Water Quality Model, solves for soil and residue temperatures within the microclimate of standing crop residues. PENFLUX predictions exhibited small random error, with predictive efficiencies generally exceeding 90%. The predictive accuracy, simplified parameterization requirements and modular structure of PENFLUX suggest application to a variety of land management problems.

Technical Abstract: Simple, yet robust algorithms quantifying soil-atmosphere energy exchanges under a range of crop residue architectures are lacking. Our research objective was to develop a simplified soil-residue energy balance module and compare it's predictive accuracy and efficiency against field observations. We collected hourly radiation, temperature and wind profile data following the 1994 wheat harvest on a level Ulm clay soil (Fine, montmorillonitic, mesic Aridic Argixeroll). PENFLUX, a Penman-type energy balance module, implemented within the Root Zone Water Quality Model, solves for surface temperatures of a soil slab and a single flat residue layer, adjusting for aerodynamic resistances of standing residue stems. PENFLUX provides surface boundary conditions for simulations of energy transfer in a one-dimensional soil profile. We evaluated the predictive accuracy of PENFLUX by regressing simulated values on field observations and computed a predictive efficiency measure relative to variability inherent in the data. PENFLUX predictions exhibited a low degree of random error, though systematic bias in surface soil temperature and negative bias in net radiation could result from low parameter values for long-wave emissivity of the atmosphere. Uncertain quantification of convective and radiative exchange processes near the soil surface confounded evaluation of systematic bias in surface soil temperature. The predictive accuracy, simplified parameter requirements and modular structure of PENFLUX suggest application to a variety of land management problems.