# Monthly Archives: August 2015

# Protected: Synthetic rainfall series using Poisson (Matlab Code)

# Calculate Flood/Rainfall Frequency from cumulative distribution function (CDF) of the distribution

Specifically, we will use the cumulative distribution function (CDF) of the fitted distribution to calculate the annual exceedance probability (AEP), or the probability that the event is equaled or exceeded in any single year. For example, considering a 200,000 cfs level, the exceedance probability is calculated in the following way:

**Exceedance_P = P{X≥200} = 1 – P{X<200} = 1 – F(200) = 1 – 0.975 = 0.025** *Note: F(200) is the CDF at 200.*

To obtain the return period (also known as the recurrence interval) of the event, we should calculate the reciprocal of the exceedance probability:

**Return_Period = 1 / Exceedance_P = 1 / 0.025 = 40 years.**

The interpretation is that in a very long series, the 40-year flood value would be exceeded every 40 years on the average. For example, about twenty-five 40-year floods can be expected during a 1000 year period (on the average).

Source: http://www.mathwave.com/applications/flood_frequency.html

# Exceedance Probability

**Introduction**

Sometimes a hydrologist may need to know what the chances are over a given time period that a flood will reach or exceed a specific magnitude. This is called the probability of occurrence or the exceedance probability.

Let’s say the value “p” is the exceedance probability, in any given year. The exceedance probability may be formulated simply as the inverse of the return period. For example, for a two-year return period the exceedance probability in any given year is one divided by two = 0.5, or 50 percent. Continue reading →

# Source of General Circulation Models

I obtain several questions regarding to the SDSM model. Here some of questions:

Am writing this email from Ethiopia and am doing my thesis work regarding impact of climate change on hydrology. am pleased to ask you about climate scenarios where to download like HadCM3 A2 and B2. Currently am planning to use SDSM-DC 5.2, predictor variable 1948-2014. please send me the link.

and

where will we get the data for HadCM3 A1, A1B, B2 for for Ethiopia region. please guide me in this regards.

We able to directly obtain the General Circulation Models (GCMs) from the https://esg.llnl.gov:8443/home/publicHomePage.do. Those data in-term of raw data and are required to extract to be suitable applied with the SDSM model.

The alternative source of GCMs that being used by me (detail in my publications: http://link.springer.com/article/10.1007/s12665-015-4054-y or http://link.springer.com/article/10.1007/s00704-013-0951-8) published by Canadian Climate Data and Scenarios (CCDS). Data published by the CCDS contain normalized NCEP and GCMs. We able to directly used to the SDSM model (or other statistical approaches).Below are some GCMs published by CCDS:

HadCM3 (http://www.cccsn.ec.gc.ca/?page=pred-hadcm3), CGCM2 (http://www.cccsn.ec.gc.ca/?page=pred-cgcm2), and CGCM3 (http://www.cccsn.ec.gc.ca/?page=pred-cgcm3).