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Engineering topics

Artley, J. A.

Publications and source records attributed to Artley, J. A..

Application of thermal model for pan evaporation to the hydrology of a defined medium, the sponge

A technique is presented which estimates pan evaporation from the commonly observed values of daily maximum and minimum air temperatures. These two variables are transformed to saturation vapor pressure equivalents which are used in a simple linear regression model. The model provides reasonably accurate estimates of pan evaporation rates over a large geographic area. The derived evaporation algorithm is combined with precipitation to obtain a simple moisture variable. A hypothetical medium with a capacity of 8 inches of water is initialized at 4 inches. The medium behaves like a sponge: it absorbs all incident precipitation, with runoff or drainage occurring only after it is saturated. Water is lost from this simple system through evaporation just as from a Class A pan, but at a rate proportional to its degree of saturation. The contents of the sponge is a moisture index calculated from only the maximum and minium temperatures and precipitation.

Trenchard, M. H.↗

AgRISTARS: Supporting research. Spring small grains planting date distribution model

A model was developed using 996 planting dates at 51 LANDSAT segments for spring wheat and spring barley in Minnesota, Montana, North Dakota, and South Dakota in 1979. Daily maximum and minimum temperatures and precipitation were obtained from the cooperative weather stations nearest to each segment. The model uses a growing degree day summation modified for daily temperature range to estimate the beginning of planting and uses a soil surface wetness variable to estimate how a fixed number of planting days are distributed after planting begins. For 1979, the model predicts first, median, and last planting dates with root mean square errors of 7.91, 6.61, and 7.09 days, respectively. The model also provides three or four dates to represent periods of planting activity within the planting season. Although the full model was not tested on an independent data set, it may be suitable in areas other than the U.S. Great Plains where spring small grains are planted as soon as soil and air temperatures become warm enough in the spring for plant growth.

Hodges, T.↗

Preliminary evaluation of spectral, normal and meteorological crop stage estimation approaches

Several of the projects in the AgRISTARS program require crop phenology information, including classification, acreage and yield estimation, and detection of episodal events. This study evaluates several crop calendar estimation techniques for their potential use in the program. The techniques, although generic in approach, were developed and tested on spring wheat data collected in 1978. There are three basic approaches to crop stage estimation: historical averages for an area (normal crop calendars), agrometeorological modeling of known crop-weather relationships agrometeorological (agromet) crop calendars, and interpretation of spectral signatures (spectral crop calendars). In all, 10 combinations of planting and biostage estimation models were evaluated. Dates of stage occurrence are estimated with biases between -4 and +4 days while root mean square errors range from 10 to 15 days. Results are inconclusive as to the superiority of any of the models and further evaluation of the models with the 1979 data set is recommended.

Cate, R. B.↗