Quantifying Variable Rainfall Intensity Events On Runoff And Sediment Losses
Price
Free (open access)
Transaction
Volume
145
Pages
9
Page Range
275 - 283
Published
2011
Size
369 kb
Paper DOI
10.2495/WRM110231
Copyright
WIT Press
Author(s)
C. C. Truman, T. L. Potter & R. C. Nuti
Abstract
Coastal Plain soils in Georgia are susceptible to runoff, sediment, and chemical losses from short duration-high intensity, runoff producing storms at critical times during the growing season. We quantified runoff and sediment losses from a Tifton loamy sand managed under conventional- (CT) and strip- (ST) tillage and planted to peanuts. Simulated rainfall was applied at planting, 30 days after planting, and after harvest during the peanut growing season with rainfall events comprised of variable intensity (Iv) patterns representative of each time or season (spring=IvSPR, summer=IvSUM, fall=IvFALL). Simulated rainfall was applied to 2x3- m plots (n=3) for each treatment. Runoff and sediment were measured from each 6-m2 plot. Runoff ranged from 9-22% of the rainfall applied for the three events. The most runoff occurred from CT-IvFALL plots; the least occurred from ST-IvSUM plots. Maximum runoff rates were 7-20% of the maximum intensity and occurred 3-8 min after maximum intensity peaks. Sediment yields ranged from 105-1420 kg ha-1. The most sediment occurred from CT-IvSPR plots; the least occurred from ST-IvSUM plots. Runoff and sediment curves had similar shapes as their corresponding rainfall intensity pattern. As for tillage, CT plots had 38% more runoff and 2.7-fold more sediment than ST plots over the three events. The largest difference in runoff (2.4-fold) and sediment (3.8-fold) among CT and ST plots occurred in the fall (IvFALL). Results improve our understanding of when runoff, sediment, and chemical losses are highest at critical times during a peanut growing season, and show how ST is effective in limiting those losses. Keywords: erosion, rainfall partitioning, rainfall simulation.
Keywords
erosion, rainfall partitioning, rainfall simulation