spatio temporal rainfall analysis at wadi fatima for flood risk assessment
TRANSCRIPT
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05/03/2023
Spatio-temporal Rainfall Analysis at Wadi Fatima for Flood Risk Assessment
1Water Research Center – King Abdulaziz University, P.O. Box 80208-Jeddah 21589-Saudi Arabia.
2Dept. of Hydrology and Water Resources Management ,Faculty of Meteorology, Environment & Arid Land Agriculture, King Abdulaziz University, P.O. Box 80208-Jeddah 21589-Saudi
Arabia.
Burhan Niyazi1,2, Amro Elfeki2, Milad Masoud1and Syed Zaidi
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Research Objectives Study Area Rainfall Stations Data Methodology Results Conclusions
Burhan Niyazi1,2, Amro Elfeki2, Milad Masoud1and Syed Zaidi (ICWRAE 2014)
Outline
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05/03/2023
Developing a systematic approach for the analysis of rainfall data for flood risk assessment in arid basins.
The presented approach takes into consideration the temporal and spatial variation of the rainfall data over the catchment.
Burhan Niyazi1,2, Amro Elfeki2, Milad Masoud1and Syed Zaidi (ICWRAE 2014)
Research Objective
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05/03/2023Burhan Niyazi1,2, Amro Elfeki2, Milad Masoud1and Syed Zaidi (ICWRAE 2014)
Study AreaWadi Fatima: located in the western part of Saudi Arabia
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05/03/2023Burhan Niyazi1,2, Amro Elfeki2, Milad Masoud1and Syed Zaidi (ICWRAE 2014)
Rainfall Sations
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05/03/2023Burhan Niyazi1,2, Amro Elfeki2, Milad Masoud1and Syed Zaidi (ICWRAE 2014)
Time Series of Annual Rainfall Data
Annual Stations:J113J114J204J205J214J239
Max daily:J102J208
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The systematic approach: (1) daily rainfall is collected from the available stations in the
study area, (2) frequency analysis is applied to the maximum daily rainfall
depths,(3) the common probability distribution functions for extreme
values are fitted to the data, (4) the best probability distribution function is selected based on
the root mean square error (RMSE) criterion, and (5) spatial analysis using GIS techniques is applied for mapping
the isohyets of rainfall depths over the study area for different return periods.
Burhan Niyazi1,2, Amro Elfeki2, Milad Masoud1and Syed Zaidi (ICWRAE 2014)
Methodology
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•Common probability distributions that are considered in the study:
•Normal Distribution. •Gumbel Distribution.•2-parameter Log-Normal Distribution.•3-Parameter Log-Normal Distribution. •Pearson Type III Distribution.•Log-Pearson Type III Distribution.
Burhan Niyazi1,2, Amro Elfeki2, Milad Masoud1and Syed Zaidi (ICWRAE 2014)
Probability Distributions
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05/03/2023Burhan Niyazi1,2, Amro Elfeki2, Milad Masoud1and Syed Zaidi (ICWRAE 2014)
The best distribution is chosen based on the root mean square error criterion, RMSE:
where, Ri is the observed rainfall depth at the station, Rˆi is the expected rainfall depth from the
probability distribution, and n is the number of data points at the station
Selection Criterion of the Type of Distribution
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05/03/2023Burhan Niyazi1,2, Amro Elfeki2, Milad Masoud1and Syed Zaidi (ICWRAE 2014)
Statistical Decision of the Type of Rainfall Distribution
Distribution TypeStations
J 102 J 113 J 114 J 204 J 205 J 208 J 214 J 239Normal 7.83 15.60 7.94 6.69 6.33 4.52 9.50 4.42
2 Parameter Log Normal 4.67 8.82 7.56 4.29 6.27 3.08 5.34 4.72
3 Parameter Log Normal 4.44 9.04 6.27 3.87 4.34 3.15 5.24 3.18
Pearson Type III 4.34 9.12 6.07 3.57 3.99 3.06 4.74 2.86Log Pearson Type III 6.73 9.13 6.43 5.77 10.25 3.86 7.65 3.63
Gumbel Type I 5.00 10.61 5.08 3.96 4.63 2.92 5.91 3.13
The best distribution is chosen based on the minimum RMSE
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05/03/2023Burhan Niyazi1,2, Amro Elfeki2, Milad Masoud1and Syed Zaidi (ICWRAE 2014)
Results of The Frequency Analysis
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The method of the inverse square distance weighting is used to map estimated rainfall for different return periods over the wadi area.
Burhan Niyazi1,2, Amro Elfeki2, Milad Masoud1and Syed Zaidi (ICWRAE 2014)
Spatial Analysis of Rainfall Data
0 0( , )P x y 0 0( , )x y
iP
iw
( , )i i ix yx
is the estimated rainfall at coordinates
i the rainfall at the given station i,
i the station weight, and
is the coordinates of the station.
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05/03/2023Burhan Niyazi1,2, Amro Elfeki2, Milad Masoud1and Syed Zaidi (ICWRAE 2014)
Spatial Distribution of 5 years Return Period
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05/03/2023Burhan Niyazi1,2, Amro Elfeki2, Milad Masoud1and Syed Zaidi (ICWRAE 2014)
Spatial Distribution of 10 years Return Period
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05/03/2023Burhan Niyazi1,2, Amro Elfeki2, Milad Masoud1and Syed Zaidi (ICWRAE 2014)
Spatial Distribution of 25 years Return Period
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05/03/2023Burhan Niyazi1,2, Amro Elfeki2, Milad Masoud1and Syed Zaidi (ICWRAE 2014)
Spatial Distribution of 50 years Return Period
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05/03/2023Burhan Niyazi1,2, Amro Elfeki2, Milad Masoud1and Syed Zaidi (ICWRAE 2014)
Spatial Distribution of 100 years Return Period
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The spatial analysis shows that the northern part of the basin and the south western part have high potential of flood risk since expected rainfall depths are high in those regions.
This analysis proofs that not all rainfall data follow Gumbel distribution, which is the common practice in the Kingdom of Saudi Arabia.
Burhan Niyazi1,2, Amro Elfeki2, Milad Masoud1and Syed Zaidi (ICWRAE 2014)
Conclusions
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05/03/2023
Thank you
Burhan Niyazi1,2, Amro Elfeki2, Milad Masoud1and Syed Zaidi (ICWRAE 2014)