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ARS Home » Midwest Area » Morris, Minnesota » Soil Management Research » Research » Publications at this Location » Publication #183553


item Spokas, Kurt
item Forcella, Frank

Submitted to: Weed Science
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 10/21/2005
Publication Date: 1/17/2006
Citation: Spokas, K.A., Forcella, F. 2006. Estimating hourly incoming solar radiation from limited meteorological data. Weed Science. 54:182-189.

Interpretive Summary: The amount of incoming radiation from the sun is a major driving force for soil temperature and moisture profiles in the shallow soil surface. This is critical for weed germination modeling as solar radiation controls growth and microclimate conditions present within the soil. Soil microclimate conditions of soil temperature and moisture content are what ultimately control the potential germination of weed seeds. However, a majority of field sites lack the instrumentation to measure the solar radiation directly. Therefore, a model is needed to predict this pivotal property. The developed solar radiation model fills this need by utilizing limited meteorological data (maximum and minimum air temperatures as well as precipitation events) along with the latitude, longitude, and elevation of the study site to predict hourly incoming radiation intensity. This model was primarily developed for the future incorporation into the next generation of weed seed germination models. Based on the validation conducted in this study, there is reasonable agreement between the model and measured incoming short-wave radiation achieved without site-specific model calibration. Scientists, extension educators and agricultural industry personnel will benefit from using this model for ecological modeling efforts to predict incoming radiation where solar radiation is not measured directly.

Technical Abstract: Two major properties which determine weed seed germination are soil temperature and moisture content. Incident radiation is the primary variable controlling energy input to the soil system and thereby influences both moisture and temperature profiles. However, a majority of agricultural field sites lack proper instrumentation to measure solar radiation directly. To overcome this shortcoming, an empirical model was developed to estimate total incident solar radiation (beam and diffuse) with hourly time steps. Input parameters for the model are latitude, longitude and elevation of the field site along with daily precipitation with daily minimum and maximum air temperatures. Field validation of this model was conducted at a total of 18 sites where sufficient meteorological data were available for validation, allowing a total of 42 individual yearly comparisons. The model performed well with an average Pearson correlation of 0.92, d-index of 0.95, modeling efficiency of 0.80, root mean square error of 111 W m-2 and a mean absolute error of 56 W m-2. These results compare favorably to other developed empirical solar radiation models, but with the advantage of predicting hourly solar radiation for the entire year based on limited climatic data and no site-specific calibration requirement. This solar radiation prediction tool can be integrated into seed germination and growth models to improve microclimate-based simulation of weed development. It can be used by scientists, extension educators and agricultural industry personnel.