ANNAGNPS: ACCOUNTING FOR SNOWPACK, SNOWMELT, AND SOIL FREEZE-THAW

2006 
The watershed model, AnnAGNPS (Annualized AGricultural Non-Point Source Pollution model) has been enhanced by incorporating winter climate algorithms that account for frozen soil conditions. The model includes snowpack accumulation and melt, and the freeze-thaw process in the soil. Three major improvements can be expected for watersheds with significant winter climates. First, the model will better account for the lag in runoff from precipitation held for months in snowpack. Second, the model will more accurately account for the movement of water through the soil layers and any resulting runoff. Third, the model will better account for the increase in sheet and rill erosion due to runoff over soil layers that have experienced the freeze-thaw process. These model improvements synthesize the science of the SHAW model (Simultaneous Heat and Water) by Gerald Flerchinger, Agricultural Research Service, Boise Idaho. SHAW, however, is a research model, while AnnAGNPS is a watershed model used by engineers and other practitioners for practical applications. In adapting SHAW, several modifications in computational procedures were made. For example, while the AnnAGNPS heat flux algorithm retains a simultaneous matrix solution of the temperature profile in soil and snow layers, the default timesteps and solution tolerances are larger than in SHAW. In addition, the first release of winter-enhanced AnnAGNPS will not include a full simultaneous matrix solution of soil moisture in thermal layers, as is done in SHAW. AnnAGNPS may adopt this in the future, but presently computes soil moisture in a more simplified manner. Also, SHAW includes a thermal layer for surface residue. This highly desired model component will be incorporated into AnnAGNPS in a future release. The AnnAGNPS winter enhancements improve modeling capability for many more geographic locations and will result in better sediment yield and pollutant loading estimates for water quality improvement in natural resources planning.
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