Estimation of peak flood discharge using satellite-based precipitation data and hydrological modeling with Google Earth Engine : case studies in Ecuador and Korea|RISS 상세보기

다국어 초록 (Multilingual Abstract)

This study aims to estimate peak river discharges using IMERG satellite-based precipitation data via Google Earth Engine (GEE) combined with hydrological modeling in HEC-HMS, focusing on two case studies: the Blanco River Basin in Ecuador and the Yeongsan River Basin in Korea. High-resolution remote sensing products were integrated with a physically based hydrological model to assess extreme flood flows in data-scarce tropical and temperate, monsoonal catchments. Digital Elevation Models from USGS SRTM 1 Arc-Second Global data were processed to delineate subbasins and extract drainage networks, while virtual rainfall stations were established within each subbasin to ensure consistent precipitation inputs. The selected extreme rainfall events, a 10-day flood in Blanco River on March 18, 2023, and the July 17-18, 2025, flood in Yeongsan, were simulated to estimate peak discharges. The Blanco River Basin reached a peak discharge of approximately 12,814.3 m³/s at the basin outlet, while the Yeongsan River Basin reached approximately 4,170.1 m³/s. These results demonstrate that satellite-derived precipitation, when properly preprocessed and incorporated into HEC-HMS, can provide reliable estimates of extreme flows in basins with limited ground data. The study underscores the potential of GEE-based IMERG data for flood risk assessment, infrastructure planning, and early-warning systems in regions prone to rapid-onset flooding. Keywords: Peak discharge analysis, Extreme rainfall events, Hydrological modeling, Satellite precipitation

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목차 (Table of Contents)

CHAPTER 1 1
INTRODUCTION 1
1.1. Global context of flood risk 1
1.2. Riverine floods 2
1.3. Overflow of the Blanco Basin flood 2023 and bridge collapse 3

CHAPTER 1 1
INTRODUCTION 1
1.1. Global context of flood risk 1
1.2. Riverine floods 2
1.3. Overflow of the Blanco Basin flood 2023 and bridge collapse 3
1.4. Overflow of the Yeongsan Basin 2025 and Inundation of the Cities 5
1.5. Importance of peak discharge 6
1.6. Advantages of satellite-based precipitation products 8
1.7. Purpose of this study 12
1.7.1. General Objective. 12
1.7.2. Specific objectives 12
CHAPTER 2 14
2. LITERATURE REVIEW 14
2.1. Peak discharge 14
2.1.1. Definition of Peak Discharge. 14
2.1.2. Factors Controlling Peak Flow 14
2.1.3. Runoff Generation Mechanisms 15
2.1.4. Hydrograph 15
2.1.5. Temporal Dynamics of Peak Discharge 16
2.1.6. Spatial Variability and Hydrograph Modulation 16
2.2. Traditional methods for estimating peak discharge 16
2.2.1. Introduction to Traditional Methods 16
2.2.2. Empirical Methods Overview 17
2.2.3. Rational Method 17
2.2.4. SCS Curve Number Method 17
2.2.5. Unit Hydrograph Method 18
2.2.6. Hydraulic Methods 18
2.2.7. River Gauging Overview 18
2.2.8. Streamflow Measurement Methods 19
2.2.9. Rating Curve 19
2.2.10. Limitations and Need for Spatial Data 19
2.3. Satellite-based precipitation data for discharge estimation 20
2.3.1. Overview of Satellite Precipitation Products 20
2.3.2. Temporal and Spatial Resolution 20
2.3.3. Advantages of Satellite Precipitation Data 21
2.3.6. Integration with Hydrological Models 22
2.3.7. Limitations in Extreme Event Simulation 22
2.3.8. Applications in Ungauged Basins 23
2.4. Hydrological modeling for peak discharge using HEC-HMS 24
2.4.1. Overview of HEC-HMS 24
2.4.2. Watershed Representation and Basin Model Structure 24
2.4.3. Precipitation Input and Data Integration 25
2.4.4. Loss Modeling (Infiltration and Abstraction) 25
2.4.5. Transforming Precipitation to Runoff 26
2.4.6. Baseflow Modeling 26
2.4.7. Channel Routing 27
2.4.8. Model Calibration 27
2.4.10. Event-Based vs. Continuous Simulation 28
2.4.12. Preprocessing in HEC-HMS 29
2.4.14. Uncertainty Analysis 29
2.4.15. Output Analysis and Peak Discharge Extraction 30
2.4.16. Integration with Ungauged Basins 30
2.4.17. Automation and Batch Processing 30
2.5. HEC-HMS and Google Earth Engine workflow for peak discharge estimation 31
2.5.1. Satellite Data Extraction Using Google Earth Engine 31
2.5.2. Preprocessing of IMERG Data 31
2.5.3. Watershed Delineation and Sub-Basin Definition 32
2.5.4. Integration into HEC-HMS 32
2.5.5. Initial Model Calibration 33
2.5.6. Temporal Synchronization and Event Selection 33
2.5.7. Spatial Distribution and Heterogeneity Consideration 33
2.5.8. Quality Control and Preprocessing Checks 34
2.5.9. Model Validation Using Historical Events 34
2.5.10. Peak Discharge Extraction and Hydrograph Analysis 34
2.5.11. Sensitivity Analysis and Parameter Optimization 35
2.5.13. Event-Based Batch Processing 35
2.5.14. Integration with Hydraulic Models for Flood Mapping 36
2.5.15. Adaptation for Real-Time or Forecasting Applications 36
2.5.16. Documentation and Reproducibility 36
2.5.17. Consolidation of Workflow Components 37
2.6. Virtual Stations Selection criteria 37
2.6.1. Station Location 37
2.6.2. Selection Criteria 37
2.6.3. Comparison with Real Stations 38
2.6.4. Preliminary Data Validation 38
2.6.5. IMERG Data Download 38
2.6.6. Comparison with Real Stations 38
2.6.7. Preliminary Data Validation 39
2.7. Curve Number (CN) Data Acquisition and Processing 39
2.7.1. Land Use Data 39
2.7.2. Soil Data 39
2.7.3. Hydrologic Soil Group Classification 39
2.7.4. CN Lookup Table 40
2.8. Knowledge gaps 40
CHAPTER 3 43
3. METHODS 43
3.1. Study Area delimitation Blanco River Basin (Ecuador) 43
3.1.1. Location and Basin Delimitation 43
3.1.2. Topography and Geomorphology 44
3.1.3. Climate 44
3.1.4. Land Use and Land Cover 47
3.1.5. Historical Data 48
3.1.6. DEM Obtention for Blanco River Basin 48
3.1.7. Station Location 50
3.1.8. Virtual station selected 51
3.2. Study Area – Yeongsan River Basin (Korea) 52
3.2.1. Location and Basin Delimitation 52
3.2.2. Topography and Geomorphology 53
3.2.3. Climate 54
3.2.4. Land Use and Land Cover 56
3.2.5. Historical Data 56
3.2.6. DEM Obtention for Yeongsan Rive Basin 57
3.2.7. Station Location 59
3.2.8. Selection Criteria 59
3.3. Code Using for extract Precipitation Data in GEE 60
3.4. Acquisition of Curve Number 66
3.4.1. Code Using for extract CN Data in GEE 66
3.4.2. CN-II Computation 73
3.5. Calculation of concentration time 74
3.5.1. Blanco River concentration time 75
3.5.2. Yeongsan River concentration time 76
3.6. Data Acquisition and Pre-processing Workflow 77
3.6.1. Satellite Precipitation Data 77
3.6.2. Data Extraction by Subbasin 77
3.6.3. Resampling and Reprojection 77
3.6.4. Temporal Aggregation and Quality Control 78
3.6.5. Bias Validation 78
3.6.6. Integration with Historical Data 78
3.6.7. Preparation for HEC-HMS 78
3.7. Pre-processing in HEC-HMS Blanco River Basin Case 79
3.7.1. Definition of Design and Historical Events 79
3.7.2. Model Configuration: Loss Method 80
3.7.3. Model Configuration: Transform Method 80
3.7.4. Baseflow and Routing 81
3.7.5. Hietogram Generation 81
3.7.6. Preliminary Simulation and Verification 81
3.8. Pre-processing in HEC-HMS Yeongsan Basin Case 82
3.8.1. Definition of Design and Historical Events 82
3.8.2. Model Configuration: Loss Method 83
3.8.3. Model Configuration: Transform Method 83
3.8.4. Baseflow and Routing 84
3.8.5. Hietogram Generation 84
3.8.6. Preliminary Simulation and Verification 84
3.9. Data Analysis and Integration 85
3.9.1. Integration of Spatial and Temporal Data 85
3.9.2. Subbasin Input Preparation 85
3.8.3 Visualization and Preliminary Analysis 87
3.8.4 Documentation of Data Processing Workflow 87
3.9 Quality Assurance and Limitations 87
viii
3.9.1 Comparison with Gauging Station Data 87
3.9.2 Hydraulic Capacity of the Channel 88
3.9.3 Statistical Validation 88
CHAPTER 4 89
4. RESULTS 89
4.1. Case Study: Ecuador (Blanco River Basin) 89
4.1.1. Rainfall Input and Temporal Distribution 89
4.1.2. Peak Discharge and Hydrograph Analysis 92
4.1.3. Summary of Hydrological Response 98
4.1.4. Channel Capacity vs. Simulated Flow 102
4.1.5. Validation and Comparison with Observed Data 104
4.2. Case Study: Korea (Yeongsan Basin, Naju) 108
4.2.1. Rainfall Input and Temporal Distribution 108
4.2.2. Peak Discharge and Hydrograph Analysis 111
4.2.3. Summary of Hydrological Response 115
4.2.4. Channel Capacity vs. Simulated Flow 118
4.2.5. Validation and Comparison with Observed Data 120
CHAPTER 5 123
5. DISCUSSION 123
5.1. Hydrological Response of Blanco River Basin in Valle Hermoso 123
5.2. Hydrological Response of Yeongsan Basin in Naju 124
5.3. Sensitivity and Uncertainty Location and Basin Delimitation 125
5.4. Applicability to Data-Limited Basins 126
5.5. Implications for Flood Risk Management 127
5.6. Conclusions 128
5.7. Limitations 133
5.8. Recommendations 135
REFERENCES 139
APPENDICES 145

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