I am sure you have heard about the

I am sure you have heard about the farmer in Sidell, Illinois. After that fiasco with the cheese being left standing alone taking the blame for the failure of the pumpkin crop, he decided to install an irrigation system. He was advised to determine water requirements based on expected rainfall. However, he is a bit confused. How much rain falls in Sidell in April for example? He found historic rainfall data for Sidell online at an Illinois State Water Survey site, and found that April rainfall varies from year to year. Please help the farmer and save him from another

Estimating Rainfall Quantity for Design The design of water management systems is based more on extreme values than on average values. If the mean value is used in the design of an irrigation system then on average, in one out of every two years there will not be enough water to meet the demands of the crop and yield will be reduced. If the mean is used in drainage design, then one out of every two years the crops will be flooded. It is better to use design values with lower associated risk.

Estimating 80% Dependable Rainfall and 80% Maximum Rainfall from mean and standard If only the mean and standard deviation of monthly rainfall are known then 80% Dependable Rainfall = Mean - 0. 84 x Standard Deviation 80% Maximum Rainfall = Mean + 0. 84 x Standard Deviation.

80% Dependable Rainfall The value of period rainfall (monthly, seasonal, etc. ) that will be exceeded 80% of the time. This value ensures that on average, there will be enough water to meet the crop's need four out of every five years. 80% Maximum Rainfall The value of period rainfall that on average, will not be exceeded 80% of the time. This value ensures that on average, a drainage system or a sedimentation pond will have adequate capacity four out of every five years.

Example : For Sidell the mean rainfall for April is 3. 75" and the standard deviation is 1. 78“ 80% Dependable Rainfall = 3. 75 - 0. 84 x 1. 78 = 2. 25“ 80% Maximum Rainfall = 3. 75 + 0. 84 x 1. 78 = 5. 25" -0. 84 s 20%

Return Period (Recurrence Interval) The frequency with which, on average, a given precipitation event is equaled or exceeded. Return Period (T) = P = probability of exceedance 1 P Example: If there is a 12. 5 percent chance that a storm of a certain magnitude will occur, the return period for that storm is 1. 0 = 8 yrs 12. 5

Multi-year Chance of Exceedance (R) The probability of a given return period storm being equaled or exceeded within a given number of years. )n 1 R=1 -(1 T Example: The chance that an 8 -year return period storm will occur over the 5 year life of a project is 1 - ( 1 - 1 )5 = (49%) 0. 49 8

10 Step Procedure for Rainfall Frequency Analysis

1. Locate Data Source

2. Extract as Specific Data as Required

3. Import into Excel and convert to columns

4. Sort, and Extract Targeted Data

5. Graph, and check for jumps, trends or cycles

6. Sort the data in ascending order and determine the non-exceedance probability of each data value

7. Plot Probability of Nonexceedance vs Precipitation (Empirical Distribution Function)

8. Determine the mean and standard deviation of the logs of the precipitation values

9. Determine the cumulative log normal values for the precipitation data

10. Plot the cumulative distribution function for the fitted log. Normal Distribution