Abstract:
The August, 2006 flood event was one of the most significant and damaging natural
disasters ever hit Diredawa. The total damages to public and private property were
estimated 94,327,416.21Birr, 256 people died,244 people missing, crops on 256.7 ha of
land were destroyed, rural water supply schemes were damaged in 17 rural kebeles,
irrigation schemes were damaged and thousands of people evacuated and sheltered in
temporary camps and fed for months there.
This emphasizes the need for more reliable predictions of floods and their causes. This
study focuses on the investigation of the cause and magnitude of flood in Diredawa area.
Hydro-meteorological, topographic, land use and soil data of the study area have been
used for the study. Various time scale rainfall data (monthly, daily or less than daily)
have been examined to establish the causes of the flood. The aerial coverage, duration
and intensity of the rainfall data were used. Accordingly the result revealed that the
extreme daily rainfall which occurred on August 6, 2006 was found to be the cause of the
flooding. Rational method was used to calculate peak discharge. This flood has produced
/sec which flooded the densely settled suburb of
Diredawa town.
The destruction caused by this flood reveals the high cost imposed upon life and property
by floods, and thus highlights the importance of preparing for such occurrences. It is
possible to predict and contain a flood to a reasonable extent. The paper discuses some of
the details of the flood, the precipitation event caused the flood and the mitigation
measures.
The rational method predicts peak runoff rates from data on rainfall intensity and
drainage basin characteristics. In
application of the rational method, design values of time
of concentration and runoff coefficient was estimated.
IDF curve was developed to find the intensity used in the rational formula .The predicted
frequensy is determined by finding the intersection of the lines defined by the measured
intensity and storm duration .The basic data used for intensity- duration-frequensy
analysis of point rainfall consists of the largest events of each year. The point rainfall
3
an estimated discharge of 642.32m
v
estimate obtained from IDF curves were adjusted for large areas because the point
estimates represent extreme values.
