Flow Duration Curve Calculator
Calculate flow duration curve statistics including exceedance probabilities, Q90, flow variability index, and slope index for streamflow analysis.
Flow Duration Curve Calculator
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Formula: Exceedance Probability = rank / (n + 1) x 100
Worked example โ Q80 ~ 17.4 m3/s | Mean: 52.5 | Highly variable stream
Formula
Exceedance Probability = rank / (n + 1) x 100
For each flow value, sort all values from highest to lowest and assign ranks. The exceedance probability for each rank is calculated using the Weibull plotting position: P = m / (n + 1) x 100, where m is the rank and n is the total number of data points. The flow at any target exceedance is found by interpolation between adjacent ranked values.
Worked Examples
Example 1: Perennial Stream Analysis
Problem:Monthly average flows (m3/s): 120, 95, 80, 65, 50, 40, 30, 22, 15, 8. Find Q80.
Solution:Sort descending: 120, 95, 80, 65, 50, 40, 30, 22, 15, 8 Exceedance probabilities: 9.1%, 18.2%, 27.3%, ..., 90.9% Q80 by interpolation falls between 15 and 22 m3/s Mean flow: 52.5 m3/s | CV: 63.7%
Result:Q80 ~ 17.4 m3/s | Mean: 52.5 | Highly variable stream
Example 2: Hydropower Feasibility
Problem:Design flow at Q30, mean annual flow 50 m3/s, catchment area 100 km2.
Solution:Q30 from FDC gives the flow exceeded 30% of time. This represents the upper range for turbine sizing. Specific discharge = (50/100) x 1000 = 500 L/s/km2 The steep FDC slope suggests seasonal generation variability.
Result:Design at Q30 for optimal energy balance | Seasonal operation likely
Frequently Asked Questions
What is a flow duration curve?
A flow duration curve (FDC) is a cumulative frequency curve that shows the percentage of time a given streamflow was equaled or exceeded over a historical period. The x-axis shows the percentage of time (exceedance probability) and the y-axis shows discharge. The curve summarizes the complete range of flow conditions at a site in a single graph. It is one of the most useful tools in hydrology for water supply planning, hydropower design, ecological flow assessment, and water quality management.
How do I interpret Q90 and Q95 values?
Q90 is the flow that is equaled or exceeded 90% of the time, representing a low-flow condition. Q95 is even lower, exceeded 95% of the time. These are commonly used as reference flows for environmental regulations and water allocation. In the UK, Q95 is the standard low-flow index for licensing water abstractions. In many countries, minimum environmental flows are set at Q90 or Q95 to protect aquatic habitat during drought. If Q90 is very low relative to the mean flow, the stream is highly variable and drought-sensitive.
What does the slope of a flow duration curve indicate?
A steep FDC slope indicates highly variable flow with large differences between wet and dry periods, typical of flashy catchments with impervious surfaces or steep terrain. A flat FDC slope indicates stable flow with small differences between high and low flows, typical of groundwater-dominated catchments or those with significant reservoir storage. The slope index is often calculated as the difference between log(Q10) and log(Q90) divided by 80, providing a single number that characterizes flow variability across the middle range of the distribution.
How is a flow duration curve used in hydropower design?
For hydropower, the FDC determines the optimal design flow and expected energy generation. The design flow is typically chosen between Q20 and Q40, balancing turbine size against annual energy output. Flow below the minimum turbine operating threshold (usually 30-40% of design flow) cannot generate power. The area under the FDC between the minimum and design flows represents the energy-generating potential. A flat FDC means more consistent power generation, while a steep FDC means seasonal variability requiring storage or grid backup.
Can flow duration curves predict future conditions?
Historical FDCs assume stationarity, meaning past flow patterns will continue. However, climate change, land use change, and water management alterations can shift the FDC significantly. Climate change may flatten or steepen the curve depending on how precipitation patterns shift. Urbanization typically steepens the curve by increasing high flows and reducing baseflow. Reservoir construction flattens the curve by storing high flows and augmenting low flows. Periodically updating FDCs with recent data is essential for reliable water planning.
Why is the Weibull plotting position m/(n+1) used instead of m/n?
Ranking n flows and dividing rank m by n would assign the largest observation an exceedance of 1/n and the smallest exactly 100 percent, implying no flow in the historical record was ever lower, which a finite sample cannot establish. Dividing by n + 1 keeps every plotted probability strictly between 0 and 100 percent and makes the estimate unbiased for the underlying exceedance probability. With ten values the points fall at 9.1, 18.2 and so on up to 90.9 percent, leaving room in the tails for events not yet observed. Alternative positions such as Gringorten or Cunnane shift the tails slightly and are preferred for extreme-value fitting.
Why can a flow duration curve not be used on its own to size reservoir storage?
The curve is built by ranking flows, which discards the order in which they occurred. A record containing one continuous three-year drought and a record with the same low-flow days scattered singly across thirty years produce an identical curve, yet the storage volume needed to maintain a yield differs enormously. Storage design therefore uses chronological methods that preserve sequence, such as a Rippl mass curve or a sequent-peak algorithm run on the actual time series, or stochastically generated series of the same length. Use the duration curve to choose a target yield or design flow, then test that target against the chronological record.
How does the time step of the input data change the curve?
Averaging smooths extremes, so a curve built from monthly means sits well inside the one built from daily discharge at the same gauge: the high-flow tail is truncated because flood peaks lasting hours vanish into a monthly average, and the low-flow tail is raised because brief recession minima are averaged with wetter days. Q95 from monthly data can therefore overstate the genuinely available dependable flow. Daily records are the standard basis for abstraction licensing and environmental flow work, while monthly data are acceptable for broad water-balance screening. Never compare indices between sites unless both curves were built at the same time step and over a comparable record length.
What do the coefficient of variation and the variability index add beyond the curve itself?
The coefficient of variation, the standard deviation divided by the mean and expressed as a percentage, condenses the spread of the whole sample into one figure, with values under about 30 percent indicating a dependable, groundwater-supported regime and values above 60 percent a flashy one. The variability index used here, maximum minus minimum divided by the median, instead measures the full observed range relative to typical conditions and is dominated by the two extreme observations, so it can jump when a single flood or drought year enters the record. Read them together with the log Q10 to Q90 slope, which ignores the extremes and characterises the mid-range only.
What is specific discharge and why is it reported per square kilometre?
Specific discharge, also called unit runoff, is the mean flow divided by catchment area, converted here to litres per second per square kilometre. A mean of 50 m3/s from a 100 km2 catchment is 0.5 m3/s per km2, or 500 L/s/km2. Normalising by area removes catchment size from the comparison, so a small headwater basin and a large lowland one can be judged on the same footing and the residual differences reflect rainfall, evapotranspiration, geology and land cover. It is the standard currency of regionalisation, where indices measured at gauged sites are transferred to an ungauged catchment of known area within the same hydrological region.
References
Background & Theory
History
Reviewed for accuracy by Daniel Agrici, Founder & Lead Developer ยท Editorial policy
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