Submitted to: Soil Science Society of America Journal
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 8/18/1997
Publication Date: N/A
Citation: N/A Interpretive Summary: Not all storms produce like amounts of erosion. Erosion amounts are not proportional to storm size. In most cases, very few large storms produce a disproportionately high percent of the overall erosion from a field or construction site. In the past, study was limited by time and resources necessary to collect data over long periods; at least 10 to 20 years of measured erosion data are necessary. New computer based tools calculate erosion rates by mimicking basic erosion processes. We are now able to simulate erosion on a storm-by-storm basis to study which storms cause the most erosion from different locations, soils, and most importantly, different cropping and erosion control management systems. This information helps conservation planners develop erosion control strategies, target the most important or influential storm size. One important finding of this research was that the erosion model used in the study: the Water Erosion Prediction Project (WEPP) model accurately re- produces the statistical distributions of storm erosion amounts for the limited data that exists under long-term monitoring. Also, the integrity of the computer model predictions was not compromised when the CLIGEN weather generator model was used to produce long-term weather sequences. This is important because of the difficulty and time required to develop long-term weather records from measured historical weather records. The study also showed that the influence of the occasional large storm event was greater for highly erodible conditions as compared to sites with lower erosion rates. In other words, erosion control and land management systems, which control the total erosion from a field, tend also to reduce the disproportionate influence of the larger storm.
Technical Abstract: Frequency distributions of daily soil losses caused by water erosion provide information, such as the amount of soil loss corresponding to a given return period, which may be valuable for making soil conservation decisions. The objective of this study was to investigate and analyze frequency distributions of daily soil loss at different sites with varying soil types, weather sequences, and cropping scenarios. A Log- Pearson type III distribution was fitted to each sampling of measured soil loss values for seven sites with data monitored during periods ranging from six to fifteen years. Soil losses were also predicted using the Water Erosion Prediction Project (WEPP) model over the same periods. We found that it was possible to calibrate the WEPP soil erodibility parameters by visual comparison of the frequency distributions of measured and predicted soil loss. Distributions are often used to estimate the frequency of extreme events. By comparison of the distributions obtained with measured and generated weather data, we found that the CLIGEN model generated weather files which were suitable to obtain representative long-term series of soil loss values with the WEPP model. Finally, a methodology was suggested to calculate the percentage of total soil loss caused by events within different frequency ranges using the frequency distribution of daily soil loss.