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Student Number 90342004
Author Dong-Sin Shih(¥Û´ÉøÊ)
Author's Email Address No Public.
Statistics This thesis had been viewed 2083 times. Download 844 times.
Department Civil Engineering
Year 2005
Semester 1
Degree Ph.D.
Type of Document Doctoral Dissertation
Language zh-TW.Big5 Chinese
Title Rainfall-Runoff Simulations Using Distributed Watershed Models with High-Resolution Precipitation
Date of Defense 2006-01-11
Page Count 140
Keyword
  • distributed-parameter model
  • groundwater flow
  • High-resolution precipitation
  • radar-rainfall estimates
  • surface flow
  • Abstract Hydrological hazards often occur in conjunction with extreme precipitation events in Taiwan. The exceptional volume and intensity of the precipitation cause frequent torrential floods, sometimes with devastating effects on life and property. To improve our understanding of extreme events, the study modeled the rainfall-runoff processes using distributed watershed models with high-resolution precipitation input.
    Precipitation data is generally collected from rain gauge stations. However, each measurement represents only the amount of rainfall at that particular spot, not precipitation in the surrounding area. Radar approaches are considered to offer a good spatial description of precipitation, but hardly predict precipitation quantities with acceptable accuracy. High resolution radar-rainfall estimates are compared with ground observations for an extreme precipitation event. The Taipei City area and the Shihmen reservoir watershed were chosen as the study sites, and the passage of Typhoon Nari (2001) through these areas was taken as the case study event. It was concluded that radar reflectivity from the Wufenshan radar station can be helpful for identifying precipitation variations during the passage of a land falling tropical cyclone. Spots with extreme rainfall can be identified when radar approaches are performed, but not based on gauge approaches. However, compared to the gauge approaches to the radar-rainfall estimates over the investigated domain tended to be overestimated. The divergence between radar-rainfall and gauge-rainfall can be identified via sub watershed investigations.
    The watershed model with high resolution precipitation data was tested on a complex mountainous reservoir region, the Shihmen reservoir watershed. Radar-rainfall estimates were examined on this study. Numerical results generally revealed acceptable agreement between the observed and simulated reservoir stage hydrographs. The model calibration processes verified that the proposed model was effective for flood routing in the Shihmen reservoir watershed. Moreover, simulated results obtained using a grid size equal to 160m by 160m had the strongest agreement between simulated and measured data, and resulted in an execution time reduction of 40% than that of the case with 120m by 120m. Case study showed that inverse-distance weighting method carried the smallest error in estimation compared to all other spatial precipitation interpretations. The ratio approach produced the smallest residual error in simulation results among all other radar approaches. Precipitation is identified to be the main factor forcing model result.
    A physical based distributed-parameter model combining surface runoff and groundwater flow is developed for investigating hydrological processes. Surface runoff is composed of both overland flow and river flow components, and the groundwater module considers the unsaturated zone and saturated zone in an unconfined aquifer system. An investigation of hydrological processes, including precipitation, infiltration, evaporation, percolation, surface runoff and groundwater flow are all considered in the proposed simulation model. Comparative analysis shows that the gradient method is superior to the GIS approach for describing the flow above riverbed. This study suggests using the Thiessen polygon method for precipitation interpolation. The best calibrations are obtained at a spatial resolution of 160m by 160m, when the simulated time step is less than five seconds. The proposed model shows good potential for storm based simulations, recession period description and long-term modeling. Therefore, the proposed model is confirmed to be suitable for mountainous watershed, such as Shihmen reservoir watershed.
    Table of Content TABLE OF CONTENTS
    pages
    ¤¤¤åºK­n I
    ABSTRACT III
    ­PÁÂ V
    TABLE OF CONTENTS VI
    LIST OF FIGURES XI
    LISTS OF TABLES XIV
    NOTATION XVII
    CHAPTER 1. INTRODUCTION 1-1
    1.1. Motivation 1-1
    1.2. Literature reviews 1-3
    1.2.1. Radar-rainfall estimates 1-3
    1.2.2. Distributed-parameter models 1-5
    1.2.3. Watershed models 1-7
    1.3. Objectives and overall structure 1-8
    CHAPTER 2. RELATED WORKS 2-1
    2.1. Study areas 2-1
    2.2. Selected land falling typhoons 2-2
    2.3. Digital terrain model and land use 2-2
    2.4. Error Evaluation 2-3
    CHAPTER 3. A COMPARISON OF GAUGE AND RADAR-RAINFALL ESTIMATES IN A LAND FALLING TYPHOON IN TAIWAN 3-1
    3.1. Precipitation inputs 3-1
    3.1.1. Interpolation using rain gauges 3-2
    3.1.2. Radar-rainfall estimates 3-3
    3.1.3. Radar-gauge combinations 3-5
    3.2. Discussion 3-6
    3.2.1. Tracing spatial precipitation movements by the radar approach 3-6
    3.2.2. Temporal variations of radar-rainfall estimates 3-7
    3.2.3. Radar-rainfall spatial variations 3-8
    3.2.4. Radar-rainfall amounts 3-10
    3.3. Summary 3-13
    CHAPTER 4. DISTRIBUTED FLOOD SIMULATIONS FOR THE SHIHMEN RESERVOIR WATERSHED WITH GAUGE OBSERVATIONS AND RADAR-RAINFALL ESTIMATES 4-1
    4.1. Two-dimensional diffusive overland flow model. 4-1
    4.1.1. Governing Equations. 4-2
    4.1.2. Numerical approach 4-3
    4.1.3. Infiltration model 4-4
    4.2. Model calibrations 4-5
    4.3. Sensitivity analysis 4-6
    4.4. Case study 4-9
    4.5. Summary 4-10
    CHAPTER 5. COUPLED SURFACE AND GROUNDWATER MODELS FOR INVESTIGATING HYDROLOGICAL PROCESSES 5-1
    5.1. Model development 5-1
    5.1.1. Surface flow 5-2
    5.1.1.1. Channel flow 5-2
    5.1.1.2. Overland flow 5-4
    5.1.2. Groundwater model 5-6
    5.1.2.1. Unsaturated groundwater module 5-6
    5.1.2.2. Saturated groundwater module 5-7
    5.1.3. Model linkage 5-8
    5.1.3.1. Simulation procedure for the surface flow 5-8
    5.1.3.2. Simulation procedure for the groundwater module 5-9
    5.1.3.3. Module combination 5-9
    5.2. Model configurations setup 5-10
    5.2.1. Study area 5-10
    5.2.2. Reservoir boundary determination 5-11
    5.2.3. Precipitation input 5-11
    5.2.4. Channel flow setup 5-13
    5.2.5. Temporal resolution 5-14
    5.2.6. Spatial resolution 5-15
    5.3. Model calibrations 5-16
    5.3.1. Calibration of the Manning¡¦s roughness coefficient for the channel (nc) 5-16
    5.3.2. Calibration of the Manning¡¦s roughness coefficient for surface land (n(j,k)) 5-17
    5.3.3. Calibration of the wetting front soil suction head ( ) 5-18
    5.3.4. Calibration of the equilibrium capacity (fc) 5-19
    5.3.5. Calibration of the constant decay rate (k) 5-19
    5.3.6. Calibration of the thickness of the riverbed mud (mt) 5-20
    5.4. Case study 5-20
    5.4.1. Storm based simulation 5-21
    5.4.2. Recession period simulations 5-22
    5.4.3. Long-term simulations 5-23
    5.5. Summary 5-24
    CHAPTER 6. CONCLUSIONS 6-1
    BIBLIOGRAPHY R-1
    APPENDIX A-1

    LIST OF FIGURES
    Pages
    Fig. 2-1.Study site (Shihmen reservoir watershed and Taipei City).2-7
    Fig. 3-1.Rain gauge locations in the study site (Shihmen reservoir watershed and Taipei City). 3-16
    Fig. 3-2.Radar reflectivity in north Taiwan from 09/16/2000 to 09/17/0130. 3-17
    Fig. 3-3.Radar reflectivity in North Taiwan from 09/17/1300 to 09/17/1830. 3-18
    Fig. 3-4.Hourly radar-rainfall estimates and gauge observations for the Taipei City from 09/16/2000 to 09/17/1200. 3-19
    Fig. 3-5.Hourly radar-rainfall estimates and gauge observations for the Shihmen reservoir watershed from 09/16/2000 to 09/17/2000. 3-20
    Fig. 3-6.Regional precipitation estimated from gauge-rainfall between 09/17/0000 to 09/17/0100: (a) Thiessen polygon method, (b) Inverse-distance weighting method (first-order), (c) Inverse-distance weighting method (second-order), (d) Kriging method. 3-21
    Fig. 3-7.Regional radar-rainfall between 09/17/0000 to 09/17/0100: (a) Linear regression, (b) Quadratic regression, (c) Ratio, (d) Objective analysis. 3-22
    Fig. 3-8.Subwatersheds in the Shihmen reservoir watershed and the gauge measured flow. 3-23
    Fig. 3-9.Accumulation of precipitation and discharge in sub watersheds of the Shihmen reservoir watershed in 2001. 3-24
    Fig. 4-1Simulated results for model calibration. 4-19
    Fig. 4-2Simulated reservoir stage for the case study (gauge interpolation approaches). 4-20
    Fig. 4-3Simulated reservoir stage for the case study (radar-rainfall estimates). 4-21
    Fig. 5-1.Model construction. 5-36
    Fig. 5-2.River basin in the Shihmen reservoir watershed. 5-37
    Fig. 5-3.Computational results for rating curve and simulations. 5-37
    Fig. 5-4.Simulated inflows for the various precipitation methods. 5-38
    Fig. 5-5.Simulated inflows for the various riverbed methods. 5-38
    Fig. 5-6.Simulated inflows for the various computational time steps. 5-39
    Fig. 5-7.Simulated inflows for the various spatial resolutions. 5-39
    Fig. 5-8.Simulated inflows for the various Manning¡¦s N (rivers). 5-40
    Fig. 5-9.Simulated inflows for the various Manning¡¦s N (forests). 5-40
    Fig. 5-10.Simulated inflows for the various wetting front suction heads ( ).
    5-41
    Fig. 5-11.Simulated inflows for the various equilibrium infiltration capacities ( ).
    5-41
    Fig. 5-12.Simulated inflows for the various infiltration decay parameters ( ).
    5-42
    Fig. 5-13.Simulated inflows for the various mud thicknesses ( ).
    5-42
    Fig. 5-14.Storm based simulation (Typhoon Wayne). 5-43
    Fig. 5-15.Storm based simulation (Typhoon Nari). 5-43
    Fig. 5-16.Recession simulation (Typhoon Wayne). 5-44
    Fig. 5-17.Recession simulation (Typhoon Nari). 5-44
    Fig. 5-18.Long-term simulation (1994/07/09~1994/08/09). 5-45

    LISTS OF TABLES
    pages
    Table 2-1.Precipitation events. 2-5
    Table 2-2.Shihmen reservoir watershed (763km2) land use. 2-6
    Table 3-1.Precipitation accumulations in the Shihmen reservoir watershed estimated with the various approaches from 09/16/2000 to 09/17/2000. 3-14
    Table 3-2.Precipitation and discharge accumulations in the sub watersheds of the Shihmen reservoir watershed in 2001. 3-14
    Table 3-3.Precipitation accumulations based on various approaches for the sub watersheds of the Shihmen reservoir watershed from 09/16/2000 to 09/17/2000. 3-15
    Table 4-1.List of simulated typhoon events. 4-12
    Table 4-2.Shihmen reservoir watershed (763km2) land use. 4-13
    Table 4-3.Residual statistics for model calibrations. 4-14
    Table 4-4.Simulated results obtained by a 120m by 120m resolution with variable Manning¡¦s roughness coefficient for the forested land use and initial infiltration capacity. 4-15
    Table 4-5.Simulated results obtained with a 120m by 120m resolution with variable infiltration decay parameter. 4-15
    Table 4-6.Simulated results obtained with a 160m by 160m resolution with variable Manning¡¦s roughness coefficient for the forested land use and initial infiltration capacity. 4-16
    Table 4-7.Simulated results obtained with a 160m by 160m resolution with variable constant infiltration decay parameter. 4-16
    Table 4-8.Simulated results obtained with a 240m by 240m resolution with variable Manning¡¦s roughness coefficient for the forested land use and initial infiltration capacity. 4-17
    Table 4-9.Simulated results obtained with a 240m by 240m resolution with variable constant infiltration decay parameter. 4-17
    Table 4-10.Comparative simulated results for various spatial resolutions. 4-18
    Table 4-11.Residual errors obtained with variable precipitation algorithms. 4-18
    Table 5-1.Precipitation events. 5-27
    Table 5-2.Shihmen reservoir watershed (763km2) land use. 5-27
    Table 5-3.Errors in peak flow obtained with variable precipitation algorithms. 5-28
    Table 5-4.Stream length and average gradient. 5-28
    Table 5-5.Errors in peak obtained with various riverbed generations. 5-29
    Table 5-6.Errors in peak flow obtained with a variable computational time step. 5-29
    Table 5-7.Residual errors obtained with a variable spatial resolution. 5-30
    Table 5-8.Residual errors obtained with variable Manning¡¦s roughness (rivers). 5-30
    Table 5-9.Residual errors obtained with variable Manning¡¦s roughness (forest). 5-31
    Table 5-10.Wetting front soil suction head. 5-31
    Table 5-11.Residual errors obtained with variable wetting front soil suction head. 5-32
    Table 5-12.Equilibrium infiltration rate. 5-32
    Table 5-13.Residual errors obtained with variable equilibrium infiltration capacity. 5-33
    Table 5-14.Residual errors obtained with variable infiltration decay parameters. 5-33
    Table 5-15.Simulation of thickness of riverbed mud. 5-34
    Table 5-16.Case study (Typhoon Wayne). 5-34
    Table 5-17.Case study (Typhoon Nari). 5-35
    Table 5-18.Recession and long-term simulations. 5-35
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    74.http://www.cwb.gov.tw/
    75.http://www.usace.army.mil/
    Advisor
  • Ray-Shyan Wu(§d·ç½å)
  • Files
  • 90342004.pdf
  • approve immediately
    Date of Submission 2006-01-24

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