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Implications of spatial averaging weather and soil moisture data for broad scale modelling activities

Implications of spatial averaging weather and soil moisture data for broad scale modelling activities

Soil Use & Management 8(2): 74-79

Spatial averaging of data before or after modelling has important implications for large area land evaluation studies. Two procedures are evaluated are evaluated for the spatial averaging of weather and soil moisture data before and after modelling (procedures A and B, respectively). The Thiessen polygon weighting technique is applied to a network of weather stations to derive daily whether values for the period 1955 to 1985 for 12 selected Ageocological Resource Areas (ARAs) on the Canadian prairies. These values are used in the model for procedure A. The components of the soil moisture balance for spring wheat are estimated with a budgeting model, assuming wheat is grown continuously for 30 years on soils with available water-holding capacities (AWCs) of 150 and 250 mm. In procedure B, the data from individual stations are used as input to the model and the same Thiessen polygon weighting coefficients are applied to the output variables. A comparison of the two procedures shows no significant difference for temperature-related variables such as frost dates, harvest date and cumulative potential evapotranspiration. The differences for moisture-related variables (soil moisture content at sowing, cumulative actual evapotranspiration, runoff and deep drainage) are often statistically significant, but the absolute differences are less than 10 mm at probability levels ranging from 10 to 90%. For many practical applications the two procedures give similar results.

Accession: 002404748

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DOI: 10.1111/j.1475-2743.1992.tb00898.x

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