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Title: SPATIAL VARIABILITY OF SOIL PROPERTIES ON TWO CENTER-PIVOT IRRIGATED FIELDS

Author
item HAN, SHUFENG - WASHINGTON STATE UNIV
item Schneider, Sally
item EVANS, ROBERT - WASHINGTON STATE UNIV
item RAWLINS, STEVEN - ARS RETIRED

Submitted to: International Conference on Precision Agriculture Abstracts & Proceedings
Publication Type: Proceedings
Publication Acceptance Date: 6/23/1996
Publication Date: N/A
Citation: N/A

Interpretive Summary: Soil characteristics are not uniform across large agricultural fields. Differences in soil texture, pH, and levels of nutrients important for plan growth can vary widely across the field and with depth. Irrigating and fertilizing fields as if they were uniform, results in some areas getting too much water and fertilizer and other areas not getting enough. Soil samples were taken every 200 feet, at one foot, two foot, and 3 foot depth across two large fields. We found large differences in soil texture, pH, and levels of nitrogen, phosphorus, potassium, and sulfur across the fields Special statistical methods were used to understand the data. From this information, we are developing management maps so that the right amount of water and nitrogen can be applied to each part of the field. This will result in better crops, reduced waste of money on unnecessary water and nitrogen, and less chance of fertilizer getting into the water supply.

Technical Abstract: The knowledge of soil variability within a field is fundamental to the development of site-specific management strategies to increase crop production and reduce the potential pollutant transport to the groundwater. In March 1995, 738 soil samples were collected from two center-pivot irrigated fields in South Central Washington State on a 61- by 61-m grid at t30-cm depth intervals to a maximum depth of 90-cm. The soil samples were analyzed for texture, nitrate-N, pH, P, K, and sulfate-S. Large spatial variability was observed for most of the soil properties from classical statistical analysis and geostatistical analysis. Most of the empirical probability distribution functions for the measured soil properties were neither normally nor lognormally distributed. Both kriging and nonparametric distance-weighting techniques were used to generate soil texture and nutrient distribution maps from the soil sampling data. These distribution maps, when combined with yield and topographical maps, can be used to define different management zones in the fields for site-specific management of water and nutrients.