Predictability of Annual Sediment Loads Based on Flood Events

Water resources managers always are searching for cost-effective monitoring programs that provide maximum information for minimum cost. Monitoring of sediment discharges from streams and rivers is one of the expensive efforts that is always reduced or cut when financial resources are limited. This has resulted in a very limited number of long-term sediment monitoring sites in the United States. Instead of long-term continuous monitoring programs, alternative monitoring approaches could potentially provide reliable estimates of sediment loads at reduced cost. One of those approaches is monitoring sediment loads during flood events and then using that information to estimate annual sediment loads. To test this approach, annual suspended sediment loads calculated based on continuous sediment monitoring were compared with the loads calculated based on monitoring the major floods only. Streams transport large percentages of the annual sediment loads from a watershed during a small number of floods that occur over relatively short time periods in a year. It was found that in Illinois, on average, the single highest, two highest, three highest, and four highest floods in a year transport 32, 49, 61, and 68% of the annual load, respectively. Consequently, the annual sediment loads were correlated highly with sediment transported during the highest floods. Thus, annual sediment loads can be predicted based on the sediment data during the highest floods. The predictions were tested on 27 small and medium streams in Illinois, for the period 1977–2000. The median error for predicting the annual load ranged from 42% for the single highest flood to 16% for the four highest floods. When resources are limited and the main purpose of the monitoring is estimation of annual sediment loads, a monitoring program based on flood events represents a more economical option. DOI: 10.1061/ ASCE 1084-0699 2006 11:4 354 CE Database subject headings: Sediment; Monitoring; Predictions; Floods.