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The runoff curve number (also called a curve number or simply CN) is an empirical parameter used in hydrology for predicting direct runoff or infiltration from rainfall excess. [1] The curve number method was developed by the USDA Natural Resources Conservation Service , which was formerly called the Soil Conservation Service or SCS — the ...
This approach is adopted from the NRCS (SCS) curve number method for estimating runoff. It assumes that the total infiltration capacity of a soil can be found from the soil's tabulated curve number. During a rain event this capacity is depleted as a function of cumulative rainfall and remaining capacity.
Among these are the Green and Ampt (1911) [9] method, Parlange et al. (1982). [10] Beyond these methods, there are a host of empirical methods such as SCS method, Horton's method, etc., that are little more than curve fitting exercises.
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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 .
In the standard preregistration format, researchers prepare a research protocol document prior to conducting their research. Ideally, this document indicates the research hypotheses, sampling procedure, sample size, research design, testing conditions, stimuli, measures, data coding and aggregation method, criteria for data exclusions, and statistical analyses, including potential variations ...
A research design typically outlines the theories and models underlying a project; the research question(s) of a project; a strategy for gathering data and information; and a strategy for producing answers from the data. [1] A strong research design yields valid answers to research questions while weak designs yield unreliable, imprecise or ...
Risks of this sort are usually managed with the methods and tools of safety engineering. A safety-critical system is designed to lose less than one life per billion (10 9) hours of operation. [7] [8] Typical design methods include probabilistic risk assessment, a method that combines failure mode and effects analysis (FMEA) with fault tree ...