The aim of this book is to contribute to understanding risk knowledge and to forecasting components of early flood warning, particularly in the environment of tropical high mountains in developing cities. This research covers a challenge, taking into account the persistent lack of data, limited resources and often complex climatic, hydrologic and hydraulic conditions. In this research, a regional method is proposed for assessing flash flood susceptibility and for identifying debris flow predisposition at the watershed scale. An indication of hazard is obtained from the flash flood susceptibility analysis and continually, the vulnerability and an indication of flood risk at watershed scale was obtained. Based on risk analyses, the research follows the modelling steps for flood forecasting development. Input precipitation is addressed in the environment of complex topography commonly found in mountainous tropical areas. A distributed model, a semi-distributed model and a lumped model were all used to simulate the discharges of a tropical high mountain basin with a paramo upper basin. Performance analysis and diagnostics were carried out in order to identify the most appropriate model for the study area for flood early warning. Finally, the Weather Research and Forecasting (WRF) model was used to explore the added value of numerical weather models for flood early warning in a paramo area.
Maria Carolina Rogelis
Country of Publication:
Series: IHE Delft PhD Thesis Series
27 September 2018
Professional and scholarly
1 Introduction 1.1 Background 1.2 Scope of the thesis 1.3 Outline of the thesis 2 Regional debris flow susceptibility analysis in mountainous peri-urban areas through morphometric and land cover indicators 2.1 Introduction 2.2 Methods and Data 2.2.1 Study Area 2.2.2 Methodology 22.214.171.124 Development of the morphometric indicator 126.96.36.199 Development of the land cover indicator 188.8.131.52 Development of a composite susceptibility index 2.3 Results 2.3.1 Estimation of the morphometric indicator for the study area 184.108.40.206 Morphometric indicator model 220.127.116.11 Assessment of appropriateness of the morphometric indicator 2.3.2 Land cover indicator 2.3.3 Combination of indicators to obtain a final susceptibility index 2.4 Discussion 2.4.1 Morphometric indicator 2.4.2 Debris flow propagation 2.4.3 Land cover indicator, composite susceptibility index and comparison of results 2.5 Conclusions 3 Regional prioritisation of flood risk in mountainous areas 3.1 Introduction 3.2 Conceptualization of Vulnerability 3.3 Methods and Data 3.3.1 Study Area 3.3.2 Methodology 18.104.22.168 Delineation of exposure areas 22.214.171.124 Choice of indicators and principal component analysis for vulnerability assessment 126.96.36.199 Sensitivity of the vulnerability indicator 188.8.131.52 Categories of recorded damage in the study area 184.108.40.206 Prioritization of watersheds 3.4 Results 3.4.1 Exposure Areas 3.4.2 Socio-economic fragility indicators 3.4.3 Lack of Resilience and coping capacity indicators 3.4.4 Physical exposure indicators 3.4.5 Vulnerability indicator 3.4.6 Prioritization of watersheds according to the qualitative risk indicator and comparison with damage records 3.4.7 Sensitivity analysis of the vulnerability indicator 3.5 Discussion 3.5.1 Exposure areas 3.5.2 Representativeness and relative importance of indicators 3.5.3 Sensitivity of the vulnerability indicator 3.5.4 Usefulness of the prioritization indicator 3.6 Conclusions 4 Spatial interpolation for real-time rainfall field estimation in areas with complex topography 4.1 Introduction 4.2 Methods and Data 4.2.1 Study Area 4.2.2 Precipitation data 4.2.3 Geostatistical interpolation procedure 220.127.116.11 Interpolation techniques 18.104.22.168 Topographic parameters as secondary variables 22.214.171.124 Cross validation and statistical criteria of comparison 126.96.36.199 Conditional Simulations 4.3 Results 4.3.1 Exploratory data analysis 4.3.2 Classification of daily datasets 4.3.3 Variogramanalysis 4.3.4 Analysis of performance of the interpolators for the individual storms 4.3.5 Analysis of performance of the interpolators using the climatological variograms and applicability of the climatological variograms for individual event rainfall field generation 4.3.6 Analysis of secondary variables 4.3.7 Analysis of uncertainty in estimates of storm volumes 4.4 Discussion 4.4.1 Characteristics of the rainfall fields 4.4.2 Performance of the climatological variograms and applicability to the generation of individual event rainfall fields 4.4.3 Choice between KED and OK 4.4.4 Volumetric comparison 4.5 Conclusions 5 Hydrological model assessment for flood early warning in a tropical high mountain basin 102 5.1 Introduction 5.2 Study Area 5.3 Methods 5.3.1 Modelling set up and calibration 188.8.131.52 Description of themodels 184.108.40.206 Hydrometeorological forcing 220.127.116.11 Model Configuration and Calibration 5.3.2 Performance analysis and diagnostics 5.3.3 Analysis of precipitation input uncertainty and comparison of models 5.4 Results 5.4.1 Model calibration 18.104.22.168 KGE for HECHMSSMA, TOPMODEL and TETIS 5.4.2 Comparison of water balance fluxes 5.4.3 Signature measures from the flow duration curve (FDC) 5.4.4 Rainfall ensemble analysis, input precipitation uncertainty 5.4.5 Comparison ofmodel ensembles 5.5 Discussion 5.5.1 Model calibration and performance 22.214.171.124 Water balance fluxes and hydrometeorological forcing 126.96.36.199 Pixel size and flux variation for the TOPMODEL and TETIS 188.8.131.52 HECHMSSMA calibration results and fluxes 184.108.40.206 Flow duration curve and signatures 5.5.2 Comparison of discharge ensembles 5.6 Conclusions 6 Streamflow forecasts fromWRF precipitation for flood early warning in tropical mountain areas 6.1 Introduction 6.2 Methods and data 6.2.1 Study Area 6.2.2 WRF model data and observed rainfall fields 6.2.3 Methodology 220.127.116.11 Generation of Precipitation Forecasts 18.104.22.168 Verification of forecasts 6.3 Results 6.3.1 Bias correction of precipitation forecasts through DBS 6.3.2 Quantile regressionmodel 6.3.3 Verification of precipitation forecasts 6.3.4 Verification of deterministic precipitation forecasts and ensemble mean 6.3.5 Verification of deterministic discharge forecasts and ensemble mean 6.3.6 Verification of probabilistic forecasts 6.3.7 Discussion 22.214.171.124 Evaluating precipitation forecasts from the WRF model 126.96.36.199 Evaluating discharge forecast 6.4 Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 158 7 Conclusions and Recommendations 7.1 Conclusions 7.1.1 Regional Flood risk analysis 7.1.2 Hydrometeorological inputs 7.1.3 Hydrological models for flood early warning 7.2 Added value of the numerical weather prediction model WRF in the flood forecasting system 7.3 Recommendations
Mariia Carolina Rogelis was born in Bogota, Colombia in 1977. She obtained a BSc. in Civil Engineering (1999) from The Universidad Nacional de Colombia, a MEng. Water resources Management (2001) from Los Andes University (Bogotai - Colombia) and a MSc. Hydraulic Engineering - River Basin Development (with distinction, 2004) from UNESCO-IHE Delft, the Netherlands. In 2009, she started as a PhD student at UNESCO-IHE. Mrs. Rogelis worked in flood management and flood forecasting systems at the Direccioin de Prevencioin y Atencioin de Emergencias de Bogotai for seven years. Since 2011 she works as a consultant in the field of flood risk management for The World Bank and Colombian companies.