UNIVERSITI PUTRA MALAYSIA - psasir.upm.edu.mypsasir.upm.edu.my/34086/1/FK 2012 9R.pdf · Abstract...

UNIVERSITI PUTRA MALAYSIA

MAJID MIRZAEI

FK 2012 9

UNCERTAINTY ANALYSIS OF EXTREME HYDROLOGICAL EVENTS IN THE SEMI-ARID ZAYANDEROOD BASIN, CENTRAL IRAN

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UNCERTAINTY ANALYSIS OF EXTREME HYDROLOGICAL EVENTS IN

THE SEMI-ARID ZAYANDEROOD BASIN, CENTRAL IRAN

By

MAJID MIRZAEI

Thesis Submitted to the School of Graduate Studies, Universiti Putra Malaysia,

in Fulfilment of the Requirement for the Degree of Doctor of Philosophy

May 2012

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Dedication

This work is dedicated to my parents

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Abstract of thesis presented to the Senate of Universiti Putra Malaysia in fulfilment

of the requirement for the degree of Doctor of Philosophy

UNCERTAINTY ANALYSIS OF EXTREME HYDROLOGICAL EVENTS IN

THE SEMI-ARID ZAYANDEROOD BASIN, CENTRAL IRAN

By

MAJID MIRZAEI

May 2012

Chairman: Professor Ir. Lee Teang Shui, PhD

Faculty: Engineering

Stream flow, which is a part of the integrated process of atmospheric and topographic

processes, is of prime importance to water resources planning. Hydrologic simulation

models for stream flow have implicit uncertainty in their handling of processes.

Uncertainty may occur during data collection, modeling, and analysis of the

engineering system and model predictions. Common methods for stream flow

forecasting use historical discharge data series at some reach of the river in the

watershed. It is universally believed that climate and landuse change can affect the

spatial and temporal distribution of water resources and also change hydrological

parameters such as intensities and frequencies of extreme hydrological events.

Distributed watershed models are increasingly being used to support decisions about

alternative management strategies in the areas of land use change and climate change.

In this study, the kinematic runoff and erosion model KINEROS2 which is an event

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oriented, physically based model was used for rainfall-runoff simulation. The main

objective of this study is to investigate the effects of uncertainty in rainfall and models

input parameters for extreme events in a semi-arid region and quantifying the

uncertainties in frequency analysis of extreme rainfall events which are associated

with Depth Duration Frequency (DDF) curves. The calibration scheme is carried out

under the Generalized Likelihood Uncertainty Estimation (GLUE) framework to

quantify uncertainty in the rainfall-runoff modelling process. These uncertainties are

presented in the rainfall-runoff modeling for investigation of uncertainty effects in

discharge and volumes of extreme hydrological events and subsequently embedded

into guidelines for risk based design and management of urban water infrastructure.

The uncertainty in the rainfall input data was studied using the rainfall data of 16

gauging stations in the Zayanderood basin, central Iran. The 36 rainfall series were

generated based on rainfall at each of the gauging stations. Statistical evaluations for

stream flow prediction indicate that there is good agreement between the measured

and simulated flows with Nash Sutcliffe values of efficiency of 0.85 and 0.79 for

calibration and validation periods respectively. Uncertainty analysis was carried out

on the new distribution of input parameters and various duration and frequency of

rainfall for extreme events are considered. The watershed was simulated for each event

using Monte Carlo sampling from statistical distribution of input parameters.

Uncertainty analysis applied to the hydrologic model indicated that uncertainty in

input parameters affects the results significantly. The uncertainty in output is

expressed through peak discharge values and stream flow volumes. For peak

discharges the amounts of upper uncertainty is reduced with increasing rainfall

duration, for all return periods. Maximum reduction was with the return period of 100

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years that was reduced from 1327m3/s for 24 hour rainfall duration to 582m3/s for 120

hours rainfall duration. By increasing rainfall duration, the difference between upper

limit of uncertainty and predicted value declines. In fact, model accuracy in discharge

calculation increases with rainfall duration. However for stream volumes, the variation

of upper uncertainty band does not have a recognizable trend with increased rainfall

duration for all return periods. The difference between upper limit of uncertainty and

predicted values is significant for all return periods and rainfall durations. This

difference slightly increases with increase of rainfall duration for all return periods.

The validated KINEROS2 model enables predicting streamflow volume for extreme

events with reliable accuracy without uncertainty analysis. The findings pointed out

that extreme discharges prediction should not be static tools but instead should

undergo continuous adaptation with uncertainty analysis, relative to possible changes

in watershed hydrology.

Abstrak tesis yang dikemukakan kepada Senat Universiti Putra Malaysia sebagai

memenuhi keperluan untuk Ijazah Doktor Falsafah

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ANALISIS KETIDAKPASTIAN PERISTIWA HIDROLOGI LAMPAU DI

LEMBANGAN SEPARA GERSANG ZAYANDEROOD, IRAN TENGAH

oleh

MAJID MIRZAEI

Mai 2012

Pengerusi: Profesor Ir. Lee Teang Shui, PhD

Fakulti: Kejuruteraan

Aliran sungai, sebahagian proses sepadu proses atmosfera dan proses topografi,

penting kepada perancangan sumber air. Model penyelakuan hidrologi untuk aliran

sungai berketidakpastian tersirat dalam prosesnya, ketidakpastian yang mana boleh

berlaku semasa proses pengumpulan data, pemodelan, dan analisis ramalan model

sistem kejuruteraan. Kaedah biasa untuk ramalan aliran sungai menggunakan sejarah

data aliran pada sebahagian sungai di dalam lembangan. Adalah dipercayai

semestanya bahawa perubahan iklim dan kegunaan tanah berpengaruh terhadap

pengedaran ruang dan masa sumber air serta juga mengubah parameter hidrologi

selain daripada keamatan dan kekerapan peristiwa hidrologi melampau. Model teragih

legeh semakin banyak diguna demi menyokong keputusan strategi pengurusan pilihan

di kawasan kegunaan tanah berubah dan iklim berubah. Dalam kajian ini, air larian

kinematik dan model hakisan KINEROS2 sebagai model yang berasas fizikal dan

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terperistiwa guna untuk perselakuan hujan-air larian. Kajian ini bertujuan menyiasat

kesan ketidakpastian berkaitan hujan dan ketidakpastian parameter input model

hidrologi peristiwa melampau di kawasan separa gersang dan menilaikan

ketidakpastian dalam analisis kekerapan peristiwa hujan melampau yang berkaitan

dengan lengkung Dalaman-Jangkamasa-Kekerapan. Skema tentukur yang

dilangsungkan bawah rangkaian Anggapan Ketidakpastian Kebolehjadian Umum

untuk menilaikan ketidakpastian dalam proses permodelam hujan-air larian.

Ketidakpastian kemudian dipakai dalam permodelan hujan-air larian untuk menyiasat

kesan ketidakpastian keatas aliran dan isipadu peristiwa hidrologi melampau dan

berikutannya dimasuk ke dalam garispanduan untuk rekabentuk berdasar risiko dan

pengurusan infrastruktur air bandar.

Ketidakpastian data input hujan dikaji menggunakan data hujan sebanyak 16 stesyen

ukuran di Lembangan Zayanderood, Pusat Iran. 36 siri hujan dijana berdasarkan hujan

di setiap stesyen ukuran. Penilaian statistik untuk ramalan aliran sungai menunjuk

bahawa ujudnya bandingan keputusan baik di antara aliran yang diukur dan yang

terselaku dengan nilai kecekapan Nash Sutcliffe sebanyak 0.85 dan 0.79 untuk

penentukuran dan pengesahan masing masing. Analisis ketidakpastian dibuat ke atas

pengedaran baru parameter input dan berbagai jangkamasa dan kekerapan hujan

peristiwa melampau dikaji. Legeh itu diselaku bagi setiap peristiwa mengguna

pengsampelan Monte Carlo daripada pengedaran statistik parameter input. Analisis

ketidakpastian dibuat keatas model hidrologi menggambarkan bahawa ketidakpastian

parameter input berkaitan berkesan ke atas keputusan. Ketidakpastian dalam hasil

dihuraikan melalui nilai aliran kemuncak dan isipadu aliran sungai. Bagi aliran

kemuncak banyaknya ketidakpastian had teratas dikurangkan berkadar dengan naik

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jangkamasa hujan untuk semua kala kembali. Penurunan maksimum berlaku untuk

kala kembali 100 tahun di mana ianya dikurangkan daripada 1327 m3/s bagi 24 jam

jangakmasa hujan ke 582 m3/s bagi 120 jam jangkamasa hujan. Dengan tambahan

jangkamasa hujan maka perbezaan di antara had teratas ketidakpastian dan nilai

diramalkan turun, bahkan kejituan model dalam kiraan aliran bertambah dengan

tambahan jangka masa hujan. Akan tetapi, bagi isipadu sungai, perubahan jalur had

atas ketidakpastian tidak bersifat jelas tren bagi tambahan jangkamasa hujan untuk

semua kala kembali. Perbezaan diantara had teratas dan nilai diramalkan bermakna

bagi semua kala kembali dan jangkamasa hujan. Perbezaan ini bertambah sedikit

sekadar dengan tambahan jangkamasa hujan bagi semua kala kembali. Model tersebut

membolehkan ramalan isipadu sungai untuk peristiwa melampau dengan kejituan

bolehharap tanpa analisis ketidakpastian. Keputusan menggambarkan bahawa ramalan

aliran melampau tidak saja sebagai alat statik bahkan sebaliknya diubahsuai

berterusan dengan analisis sekadar dengan segala perubahan boleh di dalam hidrogi

legeh.

ACKNOWLEDGEMENTS

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Foremost, I would like to express my sincere gratitude to my Supervisor Professor Ir.

Lee Teang Shui, PhD for the continuous support of my PhD study and research, for

his patience, motivation, enthusiasm, and immense knowledge. His guidance helped

me in all the time of research and writing of this thesis. I could not have imagined

having a better advisor and mentor for my PhD study.

Besides my advisor, I would like to thank the rest of my thesis committee: Prof. Madya

Dr. Abdul Halim Bin Ghazali, Professor Teymour Sohrabi and Dr. Badronnisa

bt.Yusuf, for their encouragement, insightful comments, and hard questions.

I am especially thankful to my parents for their financial and strong mental supports.

Also thanks my dear brother Ali and my dear sisters Maryam and Sara for their words

of encouragement in the hard time of my study.

I would like to thank my dear friends: Dr. Ehsan Goodarzi in Georgia Institute of

Technology, Ehsan Bakhshipour in University Technology of Petronas, Dr. Mehdi

Zieai in Universiti Teknologi Malaysia, Dr. Behnam Ababaei in University of Tehran

and Mina Faghih in University Putra Malaysia.

My deep acknowledgement is duly expressed to my dear friend Azadeh Bakhshipour

in University Putra Malaysia for her help at each stage of my work.

APPROVAL

I certify that an examination committee has met on date of viva to conduct the final

examination of Majid Mirzaei on his Doctor of Philosophy thesis entitled “Uncertainty

http://profile.upm.edu.my/nisa/en/profile.html


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Analysis of Extreme Hydrological Events in The Semi-Arid Zayanderood Basin,

Central Iran” in accordance with Universiti Pertanian Malaysia (higher Degree) Act

1980 and Universiti Pertanian Malaysia (Higher Degree) Regulations 1981. The

Committee recommends that the candidate be awarded the relevant degree. Members

of the Examination committee are as follows:

Name of Chairperson, PhD Title (e.g. Professor/Associate Professor/Ir)

Name of Faculty

Universiti Putra Malaysia

(Chairman)

Name of Examiner 1, PhD

Title (e.g. Professor/Associate Professor/Ir)

Name of Faculty


(Internal Examiner)



Name of Faculty


(Internal Examiner)



Name of Department and/or Faculty

Name of Organization (university and/or Institute)

Country

(External Examiner)

_______________________________________

BUJANG KIM HUAT, Ph.D

Professor and Deputy Dean School of Graduate Studies


Date:

This thesis was submitted to the Senate of Universiti Putra Malaysia and has been

accepted as fulfilment of the requirements for the degree of Doctor of Philosophy.

The members of the Supervisory Committee were as follows:

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Lee Teang Shui, PhD, Ir

Professor

Faculty of Engineering

University Putra Malaysia

(Chairman)

Abdul Halim Ghazali, Ph.D

Associate Professor


University Putra Malaysia

(Member)

Badronnisa bt.Yusuf, PhD

Senior Lecturer



(Member)

Teymour Sohrabi, PhD

Professor

Faculty of Agricultural Engineering & Technology

College of Agriculture & Natural Resources,

University of Tehran, Karaj, Iran.

(Member)

_______________________________________

BUJANG BIN KIM HUAT, PhD

Professor and Dean

School of Graduate Studies


Date :

DECLARATION


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I declare that the thesis is my original work except for equations and citations, which

have been duly acknowledged. I also declare that it has not been previously and is not

currently submitted for any other degree at Universiti Putra Malaysia or other

institutions.

MAJID MIRZAEI

Date: 28 May 2012

TABLE OF CONTENTS

Page

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ABSRACT III

ABSTRAK VI

ACKNOWLEDGEMENTS IX

APPROVAL X

DECLARATION XII

LIST OF TABLES XVII

LIST OF FIGURES XIX

LIST OF ABBREVIATION XXV

CHAPTER

1 INTRODUCTION

1.1 Introduction............................................................................... 1

1.2 Statement of problem ................................................................ 2

1.3 Objectives of the Research ....................................................... 3

1.4 Thesis Outline ........................................................................... 4

2 LITERATURES REVIEW

2.1 Introduction............................................................................... 5

2.2 Rainfall-Runoff Modelling ....................................................... 5

2.2.1 Modelling Types and Procedures .................................. 6

2.2.1.1 Classification of Rainfall-Runoff Models .. 6

2.2.1.2 Model Type Selection ................................ 9

2.2.2 GIS-Based Hydrologic Modeling ................................ 10

2.2.2.1 The Automated Geospatial Watershed

Assessment (AGWA) ............................... 12

2.3 Uncertainty ............................................................................. 16

2.3.1 Introduction .................................................................... 16

2.3.2 Types of Uncertainty ..................................................... 17

2.3.2.1 Intrinsic Uncertainty ................................ 17

2.3.3 Uncertainty in Hydrology ............................................. 18

2.3.3.1 Introduction .............................................. 18

2.3.3.2 Classifications of Uncertainty in Hydrology

.................................................................. 19

2.3.4 Uncertainty Analysis Methods in Hydrology ............ 24

2.3.4.1 Historical Developments .......................... 24

2.3.4.2 Understanding, Quantification and

Reducing Uncertainty .............................. 27

2.3.4.3 Classification of Uncertainty Analysis

Methods .................................................... 30

2.3.4.4 Selection of Uncertainty Analysis Methods

.................................................................. 31

2.3.4.5 Generalize Likelihood Uncertainty

Estimation (GLUE) .................................. 32

2.3.5 Depth-Duration-Frequency (DDF) Curves ................ 34

2.3.5.1 The Probability Distribution for Extreme

Rainfall ..................................................... 35

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2.3.4.6 Uncertainty in DDF Curves ..................... 36

2.4 Summary ................................................................................. 38

3 METHODOLOGY

3.1 Introduction............................................................................. 40

3.1.1 Framework of Study ........................................................... 41

3.2 Case Study .............................................................................. 43

3.2.1 Zayanderood Basin ........................................................ 43

3.2.2 Study Area ...................................................................... 45

3.2.2.1 Surface Elevation ..................................... 45

3.2.2.2 Land Cover ................................................... 47

3.2.2.3 Soil ................................................................ 48

3.3 Rainfall ................................................................................... 50

3.3.1 Rainfall Stations ............................................................ 50

3.3.2 Annual Maximum Daily Rainfall ................................ 53

3.3.3 Depths Duration Frequency Curves (DDF) ............... 55

3.3.3.1 Design Using DDF Curves ...................... 57

3.3.3.2 Creating a DDF Curve ............................. 57

3.3.3.3 Confidence Intervals on a Frequency

Curves ...................................................... 58

3.3.4 Time Distributions of Storm Rainfall ......................... 59

3.3.4.1 Huff Design Storm Method ..................... 60

3.4 Rainfall Runoff Modeling....................................................... 64

3.4.1 Introduction .................................................................... 64

3.4.2 KINEROS2 (Kinematic Runoff and Erosion Model)64

3.4.3 The Automated Geospatial Watershed Assessment

Tool (AGWA2) .............................................................. 66

3.4.3.1 Watershed Delineation and Discretization 68

3.4.3.1 Parameter Estimation ............................... 70

3.4.3.2 Rainfall Input ........................................... 72

3.4.3.3 Modeling .................................................. 73

3.5 Uncertainty Analysis Methods ............................................... 74

3.5.1 Introduction .................................................................... 74

3.5.2 The Generalized Likelihood Uncertainty Estimation

methodology (GLUE) ................................................... 74

3.5.2.1 Likelihood Measures ................................ 78

3.6 Monte Carlo Simulation........................................................... 82

4 RESULTS AND DISCUSSION

4.1 Introduction............................................................................. 84

4.2 Rainfall .................................................................................... 84

4.2.1 Rainfall Depth-Duration-Frequency (DDF) .............. 84

4.2.1.1 Regional Variability in Extreme Rainfall

Statistics ................................................... 84

4.2.1.2 Fitting a GEV Distribution ...................... 85

4.2.1.3 Regional Estimation and Modeling of GEV

Parameters ................................................ 89

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4.2.2 Depth Duration Frequency (DDF) Analysis for

Chelgerd Station ............................................................ 90

4.2.2.1 GEV Parameters as a Function of Duration

for Chelgerd Station ................................. 91

4.2.2.2 Derivation of DDF Curves for Chelgerd

Station ...................................................... 94

4.2.2.3 Modelling Uncertainty in Chelgerd Station

DDF Curves ............................................. 96


Damaneh Station ........................................................... 98


for Damaneh Station ................................ 99

4.2.3.2 Derivation of DDF Curves for Damaneh

Station .................................................... 101

4.2.3.3 Modelling Uncertainty in Damaneh Station

DDF Curves ........................................... 102


Shahrukh Palace Station ............................................. 104


for Shahrukh Palace Station ................... 105

4.2.4.2 Derivation of DDF Curves for Shahrukh

Palace Station ......................................... 107

4.2.4.3 Modelling Uncertainty in Shahrukh Palace

Station DDF Curves ............................... 108

4.2.5 Depth Duration Frequency (DDF) Analysis for Sade

Zayanderood Station ................................................... 110


for Sade Zayanderood Station ................ 111

4.2.5.2 Derivation of DDF Curves for Sade

Zayanderood Station .............................. 113

4.2.5.3 Modelling Uncertainty in Sade

Zayanderood Station DDF Curves ......... 114

4.2.6 Time Distributions of Storm Rainfall ........................ 116

4.3 Rainfall-Runoff Modeling .................................................... 121

4.3.1 Application of KINEROS2 ......................................... 121

4.3.2 Evaluation Procedure .................................................. 125

4.3.2.1 Parameters Sensitivity ............................ 125

4.3.3 Calibration of Rainfall-Runoff Model Using GLUE 126

4.3.3.1 The GLUE Framework ........................... 126

4.3.3.2 Storm Events Selection for Calibration and

Validation ............................................... 129

4.3.3.3 GLUE Analysis ..................................... 131

4.4 Uncertainty Analysis in Modeling of Hydrological Extreme

Event ..................................................................................... 136

4.4.1 Uncertainty Analysis for 24 Hour Rainfall Event ... 138




4.4.5 Uncertainty Analysis for 120 Hour Rainfall Event . 159

4.4.6 Uncertainty Analysis for Different Return Periods 164

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4.4.6.1 Peak Discharge Analysis ....................... 164

4.4.6.2 Stream volume Analysis ........................ 167

5 SUMMARY AND CONCLUSIONS

5. 1 Summery ...................................................................................... 169

5.2 Conclusions ................................................................................... 170

5.2 Recommendations for Future Work ............................................. 171

REFERENCES .................................................................................. 173

BIODATA OF STUDENT ............................................................... 190

LIST OF PUBLICATIONS ............................................................. 191

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