WIT Press


Quantifying Variable Rainfall Intensity Events On Runoff And Sediment Losses

Price

Free (open access)

Paper DOI

10.2495/WRM110231

Volume

145

Pages

9

Page Range

275 - 283

Published

2011

Size

369 kb

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