INFLUENCE OF HYDROLOGICAL, GEOMORPHOLOGICAL AND CLIMATOLOGICAL CHARACTERISTICS OF NATURAL CATCHMENTS ON LAG PARAMETERS A THESIS SUBMITTED IN FULFILMENT OF THE REQUIREMENTS FOR THE AWARD OF THE DEGREE OF DOCTOR OF PHILOSOPHY FROM THE UNIVERSITY OF WOLLONGONG BY NANAYAKKARA DAYANANDA BODHINAYAKE BSc (Eng.) - University of Sri-Lanka Post Grad. Dip. Hyd. Eng. - International Institute for Hydraulic Engineering, Delft, The Netherlands Adv. Dip. Tech. Ed. - University of Manchester, United Kingdom Grad. Dip. Ed. - University of Technology Sydney, Australia SCHOOL OF CIVIL, MINING AND ENVIRONMENTAL ENGINEERING 2004 THESIS CERTIFICATION I, Nanayakkara Dayananda Bodhinayake, declare that this thesis, submitted in fulfilment of the requirements for the award of Doctor of Philosophy, in the School of Civil, Mining and Environmental Engineering, University of Wollongong, is wholly my own work unless otherwise referenced or acknowledged. The document has not been submitted for qualifications at any other academic institution. N D Bodhinayake August 2004. iii ABSTRACT Catchment lag time is considered as a key factor in flood hydrograph modelling and design. The extensive literature investigation of this study revealed that most of the lag time equations that have been developed include various hydrological, geomorphological and climatological characteristics of the catchment. However, different studies use different combinations of these variables, and therefore, the appropriate context of the relation is not known with confidence. The intention of this research is to determine to what extent the above mentioned catchment characteristics influence the lag parameter, which is directly related to the catchment’s lag time. In order to assess the influence of catchment characteristics on the lag parameter, reliable and valid rainfall and flow data must be analysed. Therefore, at the outset of this research, the reliability and validity of rainfall data of seventeen rural catchments in Queensland, Australia, were examined. These catchments belong to five river basins and they are, Mary, Haughton, Herbert, Don and Johnstone. A total of 254 storm events on these catchments were analysed. To compute the lag parameters of the catchments, the computer based Watershed Bounded Network Model (WBNM) was selected due to its in-built non-linearity property as well as other capabilities. These include the ability to model spatially varying rainfall, the simplicity of data files and the requirement of a minimum amount of data. The constant- slope method was adopted to separate the base flow from the recorded total hydrograph in order to derive the ordinates of the surface runoff hydrograph, which is one of the essential components for the input file of WBNM. The time variation of the rainfall was examined by means of mass curves of rainfall and the spatial variability of the rainfall was studied with the help of isohyetal plots. Thereafter the rainfall and flow data, as well as the physical features of the catchments, were incorporated into WBNM to generate hydrographs for all iv 254 storm events. The lag parameter was altered until WBNM generated a hydrograph that closely resembled the recorded surface runoff hydrograph. This process was repeated for each storm event to obtain its lag parameter value. From this method, lag parameter values were derived for all 254 storm events on the seventeen catchments. The next stage of the analysis involved testing to determine whether the lag parameter is related to a range of hydrological, geomorphological and climatological variables. To carry out the analysis the necessary hydrological characteristics were extracted from the storm data. Other useful geomorphological and climatological characteristics were obtained from AUSLIG maps and the Bureau of Meteorology. If the lag relations built into WBNM are sufficient to account for those variables, then no significant relation between the lag parameter and those variables should exist when the lag parameter is plotted against each variable. The lag parameter (C) versus a range of hydrological, geomorphological and climatological characteristics of all seventeen catchments were plotted to examine their correlation. Two tailed statistical t-tests were carried out for each plot to find out whether the gradients of best-fit straight lines of those plots are significantly different from zero at 5% level of significance. The results of this research have shown that there are no strong relationships between the lag parameter (C) and the range of catchment characteristics selected for this study. Therefore, the lag parameter can be considered as an independent factor applying to a wide range of catchments. While this research was carried out for the WBNM model, its essential findings, that the non-linearity power is near to 0.23, and that the dominant variable influencing catchment lag time is the catchment area, also apply to other flood hydrograph models. v ACKNOWLEDGEMENT I wish to acknowledge the invaluable support, guidance and assistance contributed by Associate Professor Michael John Boyd during the term of my candidature. I would also like to thank Mr. Terry Malone of the Bureau of Meteorology, Brisbane, Australia, for providing the rainfall and flow data of five river basins to carry out this research study. Last but not least the encouragement and support given by my wife Chandrani and two sons Dinusha and Buddhi as well as my mother (Leelanganee Weraniyagoda Bodhinayake) are greatly appreciated. vi TABLE OF CONTENTS Title page i Thesis Certification ii Abstract iii Acknowledgement v Table of Contents vi List of Figures x List of Tables xxi Papers in preparation xxiii 1. INTRODUCTION 1 2. LITERATURE REVIEW ON RELATIONS BETWEEN LAG TIME AND HYDROLOGICAL, GEOMORPHOLOGICAL AND CLIMATOLOGICAL CHARATERISTICS OF CATCHMENTS 5 2.1 Introduction 5 2.2 Rational Method 7 2.3 Tangent Method 16 2.4 The Time-Area Method 16 2.5 The Unit Hydrograph Theory 17 2.6 Linear and Non-linear Models 30 2.7 Studies with RORB Model 48 2.8 Summary of Lag Relations 64 3. DESCRIPTION OF CATCHMENTS 73 3.1 Gympie, Moy Pocket, Bellbird, Cooran and Kandanga catchments of Mary River 74 3.2 Powerline and Mount Piccaninny catchments of Haughton River 86 3.3 Zattas, Nash’s Crossing, Gleneagle and Silver Valley catchments of Herbert River 88 3.4 Reeves, Mount Dangar, and Ida Creek catchments of Don River 92 3.5 Tung Oil, Nerada and Central Mill catchments of North and South Johnstone Rivers 95 vii 4. SELECTION OF AVAILABLE RAINFALL AND STREAM FLOW DATA 98 4.1 Introduction 98 4.2 Rainfall data of Mary River Basin 4.2.1 Temporal Patterns of Rainfall 98 4.2.2 Spatial variation of Rainfall 104 4.3 Rainfall data of Haughton River Basin 4.3.1 Temporal Patterns of Rainfall 110 4.3.2 Spatial variation of Rainfall 114 4.4 Rainfall data of Herbert River Basin 4.4.1 Temporal Patterns of Rainfall 120 4.4.2 Spatial variation of Rainfall 125 4.5 Rainfall data of Don River Basin 4.5.1 Temporal Patterns of Rainfall 131 4.5.2 Spatial variation of Rainfall 135 4.6 Rainfall data of Johnstone River Basin 4.6.1 Temporal Patterns of Rainfall 142 4.6.2 Spatial variation of Rainfall 147 4.7 STREAMFLOW DATA OF MARY RIVER BASIN 155 4.8 STREAMFLOW DATA OF HAUGHTON RIVER BASIN 159 4.9 STREAMFLOW DATA OF HERBERT RIVER BASIN 161 4.10 STREAMFLOW DATA OF DON RIVER BASIN 163 4.11 STREAMFLOW DATA OF JOHNSTONE RIVER BASIN 165 5. METHOD OF ANALYSIS 167 5.1 Introduction 167 5.2 Mary River Basin 168 5.3 Haughton River Basin 189 5.4 Herbert River Basin 199 5.5 Don River Basin 205 5.6 North Johnstone River Basin 217 viii 6. RELATIONSHIP BETWEEN LAG PARAMETER AND HYDROLOGICAL CHARACTERISTICS 246 6.1. Variation of Lag time with Discharge 246 6.2. Variation of Lag Parameter with Discharge 247 6.3. Relationship between Lag Parameter (C) and Peak Discharge (Qp) 249 6.4. Relationship between Lag Parameter (C) and Surface Runoff Peak Discharge (Qs) 257 6.5. Relationship between Lag Parameter (C) and Total Rainfall Depth (DT) 264 6.6 Relationship between Lag Parameter (C) and Depth of Surface Runoff (DSRO) 271 6.7. Relationship between Lag Parameter (C) and Average Intensity (Iav) 278 6.8. Relationship between Lag Parameter (C) and the Ratio of Time to Peak Intensity and Duration of Excess Rainfall (TpI/DURex) 285 6.9. Relationship between Lag Parameter (C) and Average Peak Intensity (AVPI) 292 6.10 Relationship between Lag Parameter (C) and the Ratio of Excess Depth and Total Depth (Dex/DT) of Rainfall 298 6.11 Relationship between Lag Parameter (C) and the Ratio of Peak Intensity and Average Intensity (Ip/Iav) of Rainfall 305 6.12 Relationship between Lag Parameter (C) and the Ratio of Rainfall Depths at Centroids of Bottom and Top halves (DBC/DTC) of catchment 312 6.13 Summary of the findings of Chapter 6 320 7. RELATIONSHIP BETWEEN LAG PARAMETER AND GEOMORPHOLOGICAL & CLIMATOLOGICAL CHARACTERISTICS 323 7.1 Introduction 323 7.2 Relationship between Lag Parameter (C) and Catchment Area (A) 324 7.3 Relationship between Lag Parameter (C) and Equal Area Slope (Sc) 327 7.4 Relationship between Lag Parameter (C) and the Length of Main Stream (L) 331 7.5 Relationship between Lag Parameter (C) and Catchment Shape Factor (A/L2) 334 7.6 Relationship between Lag Parameter (C) and the Main Stream Length to the Centroid from Catchment’s Outlet (Lc) 337 7.7 Relationship between Lag Parameter (C) and the Ratio of Main Stream Length to the Centroid from Outlet and Main Stream Length (Lc/L) 340 ix 7.8. Relationship between Lag Parameter (C) and the Number of Rain Days per Year (No.RD/year) 345 7.9 Relationship between Lag Parameter (C) and the Mean Annual Rainfall (ARMean) 348 7.10 Relationship between Lag Parameter (C) and the 2-year ARI-72hr Rainfall 2 Intensity Pattern of AR&R ( I72) of catchment 351 7.11 Relationship between Lag Parameter (C) and the Mean Elevation of Catchment (ELMean) 355 7.12 Relationship between Lag Parameter (C) and the Mean Elevation of the Centroid of Catchment (ELCentroid) 358 7.13 Catchments with Large Lag Parameter Values 361 7.14 Summary of the findings of Chapter 7 367 8.