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General Equation Of Hydrologic Frequency Analysis Calculator

General Equation of Hydrologic Frequency Analysis:

\[ x_T = x_m + K_z \cdot \sigma \]

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1. What is the General Equation of Hydrologic Frequency Analysis?

The General Equation of Hydrologic Frequency Analysis is used to estimate the variate 'X' with a recurrence interval for a random hydrologic series with a return period. It combines the mean of the variate, frequency factor, and standard deviation to predict extreme hydrological events.

2. How Does the Calculator Work?

The calculator uses the general equation:

\[ x_T = x_m + K_z \cdot \sigma \]

Where:

Explanation: The equation accounts for the statistical properties of hydrological data to estimate extreme values with specific return periods.

3. Importance of Hydrologic Frequency Analysis

Details: Accurate hydrological frequency analysis is crucial for water resource planning, flood risk assessment, and designing hydraulic structures with appropriate return periods.

4. Using the Calculator

Tips: Enter the mean of variate X, frequency factor (typically between 5-30), and standard deviation of the Z variate sample. All values must be valid numerical inputs.

5. Frequently Asked Questions (FAQ)

Q1: What is the typical range for frequency factor Kz?
A: The frequency factor typically varies between 5 to 30 depending on rainfall duration and is a function of recurrence interval and coefficient of skew.

Q2: What does the variate X represent in hydrological context?
A: Variate X represents a hydrological variable such as rainfall intensity, flood discharge, or other hydrological measurements in a random series.

Q3: How is the standard deviation of Z variate sample determined?
A: The standard deviation is calculated from sample data that follows a specific probability distribution appropriate for hydrological modeling.

Q4: What are common applications of this equation?
A: This equation is commonly used in flood frequency analysis, drought assessment, and designing water infrastructure with specific return periods.

Q5: Are there limitations to this approach?
A: The accuracy depends on the quality of input data, appropriate selection of probability distribution, and the assumption of stationarity in hydrological time series.

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