Journal
WATER AIR AND SOIL POLLUTION
Volume 154, Issue 1-4, Pages 271-293Publisher
KLUWER ACADEMIC PUBL
DOI: 10.1023/B:WATE.0000022973.60928.30
Keywords
erosion; hydrologic modeling; hydrology; land-use; management practices; nitrogen; scenarios; SWAT
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Changes in land-use or management practices may affect water outflow, sediment, nutrients and pesticides loads. Thus, there is an increasing demand for quantitative information at the watershed scale that would help decision makers or planners to take appropriate decisions. This paper evaluates by a modeling approach the impact of farming practices and land-use changes on water discharge, sediment and NO3-N loads at the outlet of a 51.29 km(2) watershed of central Iowa (Walnut Creek watershed). This intensively farmed (corn-soybean rotation) watershed is characterized by a flat topography with tiles and potholes. Nine scenarios of management practices (nitrogen application rates: increase of current rate by 20, 40%, decrease of current rate by 20, 40 and 60%; no tillage) and land-use changes (from corn-soybean rotation to winter wheat and pasture) were tested over a 30 yr simulated period. The selected model (Soil and Water Assessment Tool, SWAT) was first validated using observed flow, sediment and nutrient loads from 1991 to 1998. Scenarios of N application rates did not affect water and sediment annual budgets but did so for NO3-N loads. Lessening the N rate by 20, 40 and 60% in corn-soybean fields decreased mean NO3-N annual loads by 22, 50 and 95%, respectively, with greatest differences during late spring. On the other hand, increasing input N by 20 and 40% enhanced NO3-N loads by 25 and 49%, respectively. When replacing corn-soybean rotation by winter wheat, NO3-N loads increased in early fall, immediately after harvest. Pasture installation with or without fertilization lessened flow discharge, NO3-N and sediment delivery by 58, 97 and 50%, respectively. No-tillage practices did not significantly affect the water resource and sediment loads. Finally, such realistic predictions of the impact of farming systems scenarios over a long period are discussed regarding environmental processes involved.
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