Time of concentration
In hydrology, the time of concentration measures the response of a watershed to a rain event. It is defined as the time needed for water to flow from the most remote point in a watershed to the watershed outlet.[1] It is a function of the topography, geology, and land use within the watershed. A number of methods can be used to calculate time of concentration, including the Kirpich (1940)[2] and NRCS (1997)[3] methods.
Time of concentration is useful in predicting flow rates that would result from hypothetical storms, which are based on statistically derived return periods through IDF curves.[4][5] For many (often economic) reasons, it is important for engineers and hydrologists to be able to accurately predict the response of a watershed to a given rain event. This can be important for infrastructure development (design of bridges, culverts, etc.) and management, as well as to assess flood risk such as the ARkStorm-scenario.
Representation
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Much like a topographic map showing lines of equal elevation, a map with isolines can be constructed to show locations with the same travel time to the watershed outlet.
The spatial representation of travel time can be transformed into a cumulative distribution plot detailing how travel times are distributed throughout the area of the watershed.
References
[edit]- ^ C.T. Haan, B.J. Barfield, J.C. Hayes, 1994, Design Hydrology and Sedimentology for Small Catchments, Academic Press
- ^ Kirpich, Z.P. (1940). "Time of concentration of small agricultural watersheds". Civil Engineering. 10 (6): 362.
- ^ NRCS (National Research Conservation Service) (1997). Ponds—Planning, design, construction (PDF) (Report). Agriculture Handbook Number 590. US Department of Agriculture. p. 20. Archived from the original (PDF) on May 6, 2021.
- ^ Sherman, C. (1931): Frequency and intensity of excessive rainfall at Boston, Massachusetts, Transactions, American Society of Civil Engineers, 95, 951–960.
- ^ Monjo, R. (2016). "Measure of rainfall time structure using the dimensionless n-index". Climate Research. 67 (1): 71–86. Bibcode:2016ClRes..67...71M. doi:10.3354/cr01359. (pdf)