{"id":{"repo_id":"tu-berlin","oai_identifier":"oai:depositonce.tu-berlin.de:11303/25675"},"canonical_url":"https://search.dev.ndltd.org/etd/tu-berlin/oai:depositonce.tu-berlin.de:11303/25675","repository":{"repo_id":"tu-berlin","name":"Technische Universität Berlin","base_url":"https://api-depositonce.tu-berlin.de/server/oai/request"},"display":{"title":"A comprehensive modeling approach for urban rainfall - runoff simulation","abstract":"Urban flood modeling is a prevalent research topic worldwide, including surface flow, underground drainage flow and especially the inevitable flow connecting with underground infrastructures in highly urbanized areas. A comprehensive modeling approach and effective mitigation measures are necessary for urban risk assessment and management. Herein in this work, surface flow modeling was first investigated based on an experiment; then, the underground modeling system was included by a coupled model proposed in this work; finally, urban rainfall - runoff simulations were carried out accounting for different spatial and temporal resolutions of rain data and further mitigation effect of rain garden. In pure surface flow modeling, depth-dependent roughness and infiltration methods were numerically investigated based on rainfall - runoff experiments, under two conditions in terms of traditional and LID (Low Impact Development measures) surface conditions, different slopes and rainfall intensities. First, observed runoff data has been used to calibrate the model parameters for the depth - dependent roughness and infiltration approaches for both traditional and LID surfaces. The calibrated parameter values then have been applied to validate other two rainfall events. High NSE Coefficient (Nash-Sutcliffe Efficiency) and low SDR (Standard Deviation R) values were obtained, indicating a satisfied agreement between simulated results and observed data for both calibration and validation cases. Then, further comparison of constant and depth - dependent methods clearly pointed out the superiority of the latter methods, as they led to much better evaluation criteria. In addition, the depth-dependent roughness method ensured stability. We also refer to Mügler et al. (2011a) who compared four roughness methods within one case study also proving that the best results were obtained with a water depth-dependent Manning law. The results demonstrated the superiority of the depth - dependent infiltration method when compared to constant infiltration and the necessity of the depth - dependent roughness approach for accuracy and stability reasons. The methods implemented here might also improve other shallow water models. In coupling between the hydrodynamic surface flow model and the underground drainage system, large underground urban infrastructures were explored especially. While several similar coupled models existed, none of them ever have been used to include large underground urban infrastructures such as transportation tunnels, metro stations or car parks. This, however, is quite important on the one hand to simulate flooding and associated risks within these underground infrastructures; on the other hand, to have a correct representation of the surface flow processes in the surroundings where the underground infrastructures are connected to the surface flow. First, a bidirectional coupling between the open-source surface flow solver hms++ (Hydroinformatics Modeling System) and the SWMM (Storm Water Management Model), which was realized as a plugin, was enabled allowing its capability to be loaded at runtime without changing the hms++ code. Second, the coupled model was verified using an idealized case with separated surface catchments connected via a subsurface link, to establish plausibility and mass conservation. Then, the results of a classic validation case consisting of a system of pipes splitting into parallel paths and reuniting were compared to those obtained with the commercial tool InfoWorks ICM, demonstrating close alignment between the two. Third, the extended hms++ model was applied to two real-world cases, a metro station and a transportation tunnel which both have been idealized as large underground pipes. While the pure surface flow model predicted implausible backwaters at the metro station entrance and the transportation tunnel portals, the coupled model correctly eliminated these backwaters by modeling inflow into the metro station and the transportation tunnel. This further enabled investigating water depths and flow velocities within the metro station and the transportation tunnel and in the latter risks for human stability and recommendations for vehicle speeds were assessed. Overall, the extended coupled hms++ model has demonstrated its capabilities to qualitatively and quantitatively account for large underground urban infrastructures and thus to contribute to representation of urban flooding processes in a more precise way than offering a parameterization of pipe flow capacity and drainage overflow. In the application of the proposed rainfall – runoff model, different spatial and temporal rainfall resolutions, including spatial temporal distribution (TSD), temporal uniform (TU), spatial uniform (SU), spatial uniform reverse (SU_R), and spatial temporal uniform (TSU), and the mitigation effect of green infrastructure were explored. The TSD rainfall data, which accounts for both spatial and temporal variability, provided reference for flood extent and depth in this application. First, the analysis among different rain data resolutions with surface - only model revealed that both spatial and temporal characteristics of rain data affect inundation, spatial resolutions (SU, SU_R and TSU) performed stronger effect than temporal resolution (TU), with respect to the maximum inundation depth in this case. Second, incorporating drainage systems, the comparison between the surface model and the coupled model over different rain data resolutions highlighted the critical role of drainage systems in altering urban flood dynamics, both in inundation time and depth. A larger reduction on final inundated depth than the maximum inundated depth indicated that the drainage system was more efficient in after-peak water removal than in peak attenuation. This further suggests that current drainage systems are more suited for accelerating inundation in recession periods rather than limiting the peak severeness. With regard to the reduction peak inundated depth caused by drainage system, the largest occurred in TU resolution among those five resolutions. Third, the analysis among those rain resolutions with the coupled mode showed that, ignoring spatial variability (SU resolution) led to increased peak inundation volume compared with TSD, while temporal smoothing of rainfall (TU and TSU resolutions) led to substantial reductions in peak inundation volume but advanced the onset of inundation time and delayed the peak arrival. This indicated that neglecting temporal variability would distort the timing of urban flood response even if overall flooding appears reduced. Furthermore, for effect of different rain resolutions on drainage outfalls outflow displayed that, SU, TU, and TSU resolutions delayed outflow peak at both observed outfalls compared to the TSD resolution, only SU_R advances it. These changes highlighted the sensitivity of drainage system response to rainfall structure in spatial and temporal. In the end, the exploration of rain garden as a mitigation measure under three rainfalls was investigated. Optimal placement of rain gardens in areas with higher runoff accumulation significantly reduced flood depths at selected hot spot, indicating that the potential of nature-based solutions in urban flood mitigation. With the simulated rain cases, the effectiveness of rain gardens in reducing surface inundation diminished with increasing storm intensity was demonstrated. And the implementation of a rain garden significantly alters the hydrodynamic response across different storm return periods. These results indicated that while rain gardens effectively mitigate flood depth under moderate storms, their performance becomes weaker under extreme events. These findings provided insights for urban planners and policymakers in designing resilient flood management systems that integrated accurate modeling, high-resolution data and sustainable mitigation practices. Overall, this work proposed a comprehensive modeling approach for simulating urban areas including drainage systems and large underground infrastructures. With the development of depth - dependent roughness and infiltration methods, the investigation of spatial and temporal rainfall resolutions and the application green infrastructures - the rain garden, the model was successfully applied to several test cases and real urban areas. The exploration of rain data resolutions and rain garden cases offered insights into their respective impacts on surface runoff dynamics, drainage performance and the overall effectiveness of mitigation strategies in urban flood scenarios.","abstract_html":"Urban flood modeling is a prevalent research topic worldwide, including surface flow, underground drainage flow and especially the inevitable flow connecting with underground infrastructures in highly urbanized areas. A comprehensive modeling approach and effective mitigation measures are necessary for urban risk assessment and management. Herein in this work, surface flow modeling was first investigated based on an experiment; then, the underground modeling system was included by a coupled model proposed in this work; finally, urban rainfall - runoff simulations were carried out accounting for different spatial and temporal resolutions of rain data and further mitigation effect of rain garden. In pure surface flow modeling, depth-dependent roughness and infiltration methods were numerically investigated based on rainfall - runoff experiments, under two conditions in terms of traditional and LID (Low Impact Development measures) surface conditions, different slopes and rainfall intensities. First, observed runoff data has been used to calibrate the model parameters for the depth - dependent roughness and infiltration approaches for both traditional and LID surfaces. The calibrated parameter values then have been applied to validate other two rainfall events. High NSE Coefficient (Nash-Sutcliffe Efficiency) and low SDR (Standard Deviation R) values were obtained, indicating a satisfied agreement between simulated results and observed data for both calibration and validation cases. Then, further comparison of constant and depth - dependent methods clearly pointed out the superiority of the latter methods, as they led to much better evaluation criteria. In addition, the depth-dependent roughness method ensured stability. We also refer to Mügler et al. (2011a) who compared four roughness methods within one case study also proving that the best results were obtained with a water depth-dependent Manning law. The results demonstrated the superiority of the depth - dependent infiltration method when compared to constant infiltration and the necessity of the depth - dependent roughness approach for accuracy and stability reasons. The methods implemented here might also improve other shallow water models. In coupling between the hydrodynamic surface flow model and the underground drainage system, large underground urban infrastructures were explored especially. While several similar coupled models existed, none of them ever have been used to include large underground urban infrastructures such as transportation tunnels, metro stations or car parks. This, however, is quite important on the one hand to simulate flooding and associated risks within these underground infrastructures; on the other hand, to have a correct representation of the surface flow processes in the surroundings where the underground infrastructures are connected to the surface flow. First, a bidirectional coupling between the open-source surface flow solver hms++ (Hydroinformatics Modeling System) and the SWMM (Storm Water Management Model), which was realized as a plugin, was enabled allowing its capability to be loaded at runtime without changing the hms++ code. Second, the coupled model was verified using an idealized case with separated surface catchments connected via a subsurface link, to establish plausibility and mass conservation. Then, the results of a classic validation case consisting of a system of pipes splitting into parallel paths and reuniting were compared to those obtained with the commercial tool InfoWorks ICM, demonstrating close alignment between the two. Third, the extended hms++ model was applied to two real-world cases, a metro station and a transportation tunnel which both have been idealized as large underground pipes. While the pure surface flow model predicted implausible backwaters at the metro station entrance and the transportation tunnel portals, the coupled model correctly eliminated these backwaters by modeling inflow into the metro station and the transportation tunnel. This further enabled investigating water depths and flow velocities within the metro station and the transportation tunnel and in the latter risks for human stability and recommendations for vehicle speeds were assessed. Overall, the extended coupled hms++ model has demonstrated its capabilities to qualitatively and quantitatively account for large underground urban infrastructures and thus to contribute to representation of urban flooding processes in a more precise way than offering a parameterization of pipe flow capacity and drainage overflow. In the application of the proposed rainfall – runoff model, different spatial and temporal rainfall resolutions, including spatial temporal distribution (TSD), temporal uniform (TU), spatial uniform (SU), spatial uniform reverse (SU_R), and spatial temporal uniform (TSU), and the mitigation effect of green infrastructure were explored. The TSD rainfall data, which accounts for both spatial and temporal variability, provided reference for flood extent and depth in this application. First, the analysis among different rain data resolutions with surface - only model revealed that both spatial and temporal characteristics of rain data affect inundation, spatial resolutions (SU, SU_R and TSU) performed stronger effect than temporal resolution (TU), with respect to the maximum inundation depth in this case. Second, incorporating drainage systems, the comparison between the surface model and the coupled model over different rain data resolutions highlighted the critical role of drainage systems in altering urban flood dynamics, both in inundation time and depth. A larger reduction on final inundated depth than the maximum inundated depth indicated that the drainage system was more efficient in after-peak water removal than in peak attenuation. This further suggests that current drainage systems are more suited for accelerating inundation in recession periods rather than limiting the peak severeness. With regard to the reduction peak inundated depth caused by drainage system, the largest occurred in TU resolution among those five resolutions. Third, the analysis among those rain resolutions with the coupled mode showed that, ignoring spatial variability (SU resolution) led to increased peak inundation volume compared with TSD, while temporal smoothing of rainfall (TU and TSU resolutions) led to substantial reductions in peak inundation volume but advanced the onset of inundation time and delayed the peak arrival. This indicated that neglecting temporal variability would distort the timing of urban flood response even if overall flooding appears reduced. Furthermore, for effect of different rain resolutions on drainage outfalls outflow displayed that, SU, TU, and TSU resolutions delayed outflow peak at both observed outfalls compared to the TSD resolution, only SU_R advances it. These changes highlighted the sensitivity of drainage system response to rainfall structure in spatial and temporal. In the end, the exploration of rain garden as a mitigation measure under three rainfalls was investigated. Optimal placement of rain gardens in areas with higher runoff accumulation significantly reduced flood depths at selected hot spot, indicating that the potential of nature-based solutions in urban flood mitigation. With the simulated rain cases, the effectiveness of rain gardens in reducing surface inundation diminished with increasing storm intensity was demonstrated. And the implementation of a rain garden significantly alters the hydrodynamic response across different storm return periods. These results indicated that while rain gardens effectively mitigate flood depth under moderate storms, their performance becomes weaker under extreme events. These findings provided insights for urban planners and policymakers in designing resilient flood management systems that integrated accurate modeling, high-resolution data and sustainable mitigation practices. Overall, this work proposed a comprehensive modeling approach for simulating urban areas including drainage systems and large underground infrastructures. With the development of depth - dependent roughness and infiltration methods, the investigation of spatial and temporal rainfall resolutions and the application green infrastructures - the rain garden, the model was successfully applied to several test cases and real urban areas. The exploration of rain data resolutions and rain garden cases offered insights into their respective impacts on surface runoff dynamics, drainage performance and the overall effectiveness of mitigation strategies in urban flood scenarios.","abstract_has_math":false,"creators":["Zhang, Yangwei"],"institution":null,"degree_name":null,"degree_level":null,"degree_discipline":null,"degree_department":null,"school":null,"contributors":[],"advisors":["Hinkelmann, Reinhard"],"committee_chairs":[],"committee_members":[],"year":2026,"date_issued":"2026","date_published":"2026","updated_at":"2026-07-27T21:28:52Z","subjects":[],"languages":["en"],"rights":[],"rights_urls":["https://creativecommons.org/licenses/by-nd/4.0/"],"identifier_entries":[{"key":"dc:identifier.uri","label":"Identifier URI","values":["https://doi.org/10.14279/depositonce-24499"],"render_values":[{"text":"https://doi.org/10.14279/depositonce-24499","href":"https://doi.org/10.14279/depositonce-24499","code":true}]}]},"links":{"outbound_url":"https://depositonce.tu-berlin.de/handle/11303/25675","outbound_label":"Repository record","outbound_source":"dc:identifier.uri"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor.advisor","label":"Advisor","values":["Hinkelmann, Reinhard"]},{"key":"dc:creator","label":"Author","values":["Zhang, Yangwei"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.accessioned","label":"Dc Date Accessioned","values":["2026-01-15T16:13:12Z"]},{"key":"dc:date.available","label":"Dc Date Available","values":["2026-01-15T16:13:12Z"]},{"key":"dc:date.issued","label":"Date","values":["2026"]},{"key":"dc:type","label":"Dc Type","values":["Doctoral Thesis"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language.iso","label":"Language (ISO)","values":["en"]},{"key":"dc:rights.uri","label":"Rights URI","values":["https://creativecommons.org/licenses/by-nd/4.0/"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier.uri","label":"Identifier URI","values":["https://depositonce.tu-berlin.de/handle/11303/25675","https://doi.org/10.14279/depositonce-24499"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["Urban flood modeling is a prevalent research topic worldwide, including surface flow, underground drainage flow and especially the inevitable flow connecting with underground infrastructures in highly urbanized areas. A comprehensive modeling approach and effective mitigation measures are necessary for urban risk assessment and management. Herein in this work, surface flow modeling was first investigated based on an experiment; then, the underground modeling system was included by a coupled model proposed in this work; finally, urban rainfall - runoff simulations were carried out accounting for different spatial and temporal resolutions of rain data and further mitigation effect of rain garden. In pure surface flow modeling, depth-dependent roughness and infiltration methods were numerically investigated based on rainfall - runoff experiments, under two conditions in terms of traditional and LID (Low Impact Development measures) surface conditions, different slopes and rainfall intensities. First, observed runoff data has been used to calibrate the model parameters for the depth - dependent roughness and infiltration approaches for both traditional and LID surfaces. The calibrated parameter values then have been applied to validate other two rainfall events. High NSE Coefficient (Nash-Sutcliffe Efficiency) and low SDR (Standard Deviation R) values were obtained, indicating a satisfied agreement between simulated results and observed data for both calibration and validation cases. Then, further comparison of constant and depth - dependent methods clearly pointed out the superiority of the latter methods, as they led to much better evaluation criteria. In addition, the depth-dependent roughness method ensured stability. We also refer to Mügler et al. (2011a) who compared four roughness methods within one case study also proving that the best results were obtained with a water depth-dependent Manning law. The results demonstrated the superiority of the depth - dependent infiltration method when compared to constant infiltration and the necessity of the depth - dependent roughness approach for accuracy and stability reasons. The methods implemented here might also improve other shallow water models. In coupling between the hydrodynamic surface flow model and the underground drainage system, large underground urban infrastructures were explored especially. While several similar coupled models existed, none of them ever have been used to include large underground urban infrastructures such as transportation tunnels, metro stations or car parks. This, however, is quite important on the one hand to simulate flooding and associated risks within these underground infrastructures; on the other hand, to have a correct representation of the surface flow processes in the surroundings where the underground infrastructures are connected to the surface flow. First, a bidirectional coupling between the open-source surface flow solver hms++ (Hydroinformatics Modeling System) and the SWMM (Storm Water Management Model), which was realized as a plugin, was enabled allowing its capability to be loaded at runtime without changing the hms++ code. Second, the coupled model was verified using an idealized case with separated surface catchments connected via a subsurface link, to establish plausibility and mass conservation. Then, the results of a classic validation case consisting of a system of pipes splitting into parallel paths and reuniting were compared to those obtained with the commercial tool InfoWorks ICM, demonstrating close alignment between the two. Third, the extended hms++ model was applied to two real-world cases, a metro station and a transportation tunnel which both have been idealized as large underground pipes. While the pure surface flow model predicted implausible backwaters at the metro station entrance and the transportation tunnel portals, the coupled model correctly eliminated these backwaters by modeling inflow into the metro station and the transportation tunnel. This further enabled investigating water depths and flow velocities within the metro station and the transportation tunnel and in the latter risks for human stability and recommendations for vehicle speeds were assessed. Overall, the extended coupled hms++ model has demonstrated its capabilities to qualitatively and quantitatively account for large underground urban infrastructures and thus to contribute to representation of urban flooding processes in a more precise way than offering a parameterization of pipe flow capacity and drainage overflow. In the application of the proposed rainfall – runoff model, different spatial and temporal rainfall resolutions, including spatial temporal distribution (TSD), temporal uniform (TU), spatial uniform (SU), spatial uniform reverse (SU_R), and spatial temporal uniform (TSU), and the mitigation effect of green infrastructure were explored. The TSD rainfall data, which accounts for both spatial and temporal variability, provided reference for flood extent and depth in this application. First, the analysis among different rain data resolutions with surface - only model revealed that both spatial and temporal characteristics of rain data affect inundation, spatial resolutions (SU, SU_R and TSU) performed stronger effect than temporal resolution (TU), with respect to the maximum inundation depth in this case. Second, incorporating drainage systems, the comparison between the surface model and the coupled model over different rain data resolutions highlighted the critical role of drainage systems in altering urban flood dynamics, both in inundation time and depth. A larger reduction on final inundated depth than the maximum inundated depth indicated that the drainage system was more efficient in after-peak water removal than in peak attenuation. This further suggests that current drainage systems are more suited for accelerating inundation in recession periods rather than limiting the peak severeness. With regard to the reduction peak inundated depth caused by drainage system, the largest occurred in TU resolution among those five resolutions. Third, the analysis among those rain resolutions with the coupled mode showed that, ignoring spatial variability (SU resolution) led to increased peak inundation volume compared with TSD, while temporal smoothing of rainfall (TU and TSU resolutions) led to substantial reductions in peak inundation volume but advanced the onset of inundation time and delayed the peak arrival. This indicated that neglecting temporal variability would distort the timing of urban flood response even if overall flooding appears reduced. Furthermore, for effect of different rain resolutions on drainage outfalls outflow displayed that, SU, TU, and TSU resolutions delayed outflow peak at both observed outfalls compared to the TSD resolution, only SU_R advances it. These changes highlighted the sensitivity of drainage system response to rainfall structure in spatial and temporal. In the end, the exploration of rain garden as a mitigation measure under three rainfalls was investigated. Optimal placement of rain gardens in areas with higher runoff accumulation significantly reduced flood depths at selected hot spot, indicating that the potential of nature-based solutions in urban flood mitigation. With the simulated rain cases, the effectiveness of rain gardens in reducing surface inundation diminished with increasing storm intensity was demonstrated. And the implementation of a rain garden significantly alters the hydrodynamic response across different storm return periods. These results indicated that while rain gardens effectively mitigate flood depth under moderate storms, their performance becomes weaker under extreme events. These findings provided insights for urban planners and policymakers in designing resilient flood management systems that integrated accurate modeling, high-resolution data and sustainable mitigation practices. Overall, this work proposed a comprehensive modeling approach for simulating urban areas including drainage systems and large underground infrastructures. With the development of depth - dependent roughness and infiltration methods, the investigation of spatial and temporal rainfall resolutions and the application green infrastructures - the rain garden, the model was successfully applied to several test cases and real urban areas. The exploration of rain data resolutions and rain garden cases offered insights into their respective impacts on surface runoff dynamics, drainage performance and the overall effectiveness of mitigation strategies in urban flood scenarios.","Die Modellierung urbaner Überflutungen stellt weltweit ein hochaktuelles Forschungsthema dar. Sie umfasst sowohl die Oberflächenabflüsse als auch die unterirdischen Entwässerungssysteme – insbesondere jedoch die unvermeidbaren Fließverbindungen mit unterirdischen Infrastrukturen in stark urbanisierten Gebieten. Für eine fundierte Risikobewertung und ein effektives Management urbaner Überflutungsgefahren ist ein umfassender Modellierungsansatz in Kombination mit geeigneten Minderungsmaßnahmen erforderlich. In der vorliegenden Arbeit wird zunächst die Modellierung von Oberflächenabfluss auf Basis experimenteller Untersuchungen behandelt. Anschließend erfolgt die Einbindung des unterirdischen Systems durch ein in dieser Arbeit entwickeltes gekoppeltes Modell. Schließlich werden Niederschlag-Abfluss-Simulationen durchgeführt, bei denen unterschiedliche räumliche und zeitliche Auflösungen der Niederschlagsdaten auf die Oberflächenabflüsse sowie mögliche Minderungsmaßnahmen untersucht werden. Im ersten Schritt wurden im Rahmen der reinen Oberflächenabflussmodellierung tiefenabhängige Rauigkeits- und Infiltrationsansätze numerisch auf Grundlage von Niederschlag-Abfluss-Experimenten untersucht – unter variierenden Bedingungen in Bezug auf LID- (Low Impact Development) und traditionelle Oberflächen, unterschiedliche Längsgefälle sowie variierende Niederschlagsintensitäten. Beobachtete Abflussdaten wurden zunächst zur Kalibrierung der Modellparameter der tiefenabhängigen Ansätze verwendet. Die kalibrierten Parameter wurden anschließend zur Validierung zweier weiterer Niederschlagsereignisse herangezogen. Hohe Nash-Sutcliffe-Effizienzen (NSE) und niedrige Standardabweichungen (SDR) belegen eine gute Übereinstimmung zwischen Simulation und Messung. Der Vergleich mit konstanten Ansätzen zeigt deutlich die Überlegenheit der tiefenabhängigen Methoden, insbesondere hinsichtlich Stabilität und Modellgenauigkeit. Auch frühere Studien (z. B. Mügler et al., 2011a) belegen die Vorteile einer wasserstandabhängigen Rauigkeitsformulierung nach Manning. Die hier implementierten Ansätze können auch zur Verbesserung anderer Flachwassermodelle beitragen. Im zweiten Schritt wurde ein bidirektional gekoppeltes Modell zwischen dem Open-Source-Oberflächenmodell Hydroinformatics Modeling System (hms++) und dem Storm Water Management Model (SWMM) entwickelt. Dieses wurde als Plugin realisiert und erlaubt die dynamische Kopplung zur Laufzeit ohne Änderung des Quellcodes von hms++. Die Kopplung wurde zunächst in einem idealisierten Szenario mit getrennten Einzugsgebieten über eine unterirdische Verbindung getestet, um Massenerhaltung und Plausibilität sicherzustellen. Anschließend wurde ein klassischer Validierungsfall – ein Leitungssystem mit paralleler Aufspaltung der Abflüsse und Wiedervereinigung – mit den Ergebnissen des kommerziellen Werkzeugs InfoWorks ICM verglichen, wobei eine gute Übereinstimmung erzielt wurde. Schließlich wurde das erweiterte Modell auf zwei reale urbane Fälle angewendet: ein U-Bahnhof und ein Verkehrstunnel, idealisiert als große unterirdische Röhren. Während das reine Oberflächenmodell an den Zugängen zu diesen Infrastrukturen unrealistische Rückstauphänomene prognostizierte, konnte das gekoppelte Modell diese durch die Simulation von Zuflussvorgängen in die Untergrundstrukturen plausibel abbilden. Dies ermöglichte darüber hinaus Analysen zu Wasserständen und Fließgeschwindigkeiten innerhalb der unterirdischen Infrastrukturen sowie Bewertungen hinsichtlich Personensicherheit und Fahrempfehlungen für Autos. Insgesamt zeigt das erweiterte hms++-Modell, dass durch explizite Einbindung großer unterirdischer Infrastrukturen die Prozesse urbaner Überflutung sowohl qualitativ als auch quantitativ besser abgebildet werden können als durch einfache Parametrisierung von Kanalüberlauf und -kapazitäten. Im dritten Schritt wurden mit dem gekoppelten Modell die Auswirkungen unterschiedlicher räumlicher und zeitlicher Auflösungen von Niederschlagsdaten sowie von Maßnahmen der grünen Infrastruktur auf den Oberflächenabfluss untersucht. Der Vergleich zwischen reinem Oberflächenmodell und dem gekoppelten Modell unterstreicht die Bedeutung unterirdischer Entwässerungssysteme für Dynamik und Tiefe urbaner Überflutungen. Dabei zeigt sich, dass die Systeme effektiver in der Ableitung von Nachflutwasser als in der Dämpfung von Spitzenabflüssen sind. Dies weist darauf hin, dass bestehende Entwässerungssysteme vor allem zur Beschleunigung des Rückgangs von Überflutungen ausgelegt sind. Zudem beeinflussen die räumlichen und zeitlichen Merkmale der Niederschlagsverteilung (z. B. TSD, SU, TU, TSU) maßgeblich das Muster und den Zeitpunkt von Überflutungsereignissen. So führt das Vernachlässigen räumlicher Variabilität (SU) zu größeren Überflutungsvolumina, während zeitlich geglättete Niederschläge (TU, TSU) zu einem früheren Beginn und verzögerten Spitzenabflüssen führen. Auch die Abflussdynamik an Auslässen reagiert empfindlich auf die gewählte Niederschlagsstruktur. Darüber hinaus wurde der Einsatz von Rain Gardens als Minderungsmaßnahme unter drei Niederschlagsereignissen analysiert. Dabei zeigte sich, dass eine gezielte Platzierung der Rain Gardens an stark belasteten Stellen die Überflutungstiefen signifikant reduzieren kann. Allerdings nimmt die Wirksamkeit der Rain Gardens mit zunehmender Niederschlagsintensität ab, was die Grenzen naturbasierter Lösungen bei Extremereignissen aufzeigt. Zusammenfassend wurde ein umfassender Modellierungsansatz zur Simulation urbaner Überflutungsprozesse unter Berücksichtigung von Entwässerungssystemen und großräumigen unterirdischen Infrastrukturen entwickelt. Durch die Einführung tiefenabhängiger Parameter, die Untersuchung von Regenauflösungen sowie die Bewertung von grünen und grauen Infrastrukturen konnte das Modell erfolgreich in verschiedenen urbanen Szenarien getestet werden. Es bietet somit ein übertragbares und robustes Werkzeug für zukünftige Anwendungen in der urbanen Überflutungsmodellierung."]},{"key":"dc:title","label":"Title","values":["A comprehensive modeling approach for urban rainfall - runoff simulation"]}]}],"canonical_facts":{"dc:contributor.advisor":["Hinkelmann, Reinhard"],"dc:creator":["Zhang, Yangwei"],"dc:date.accessioned":["2026-01-15T16:13:12Z"],"dc:date.available":["2026-01-15T16:13:12Z"],"dc:date.issued":["2026"],"dc:description.abstract":["Urban flood modeling is a prevalent research topic worldwide, including surface flow, underground drainage flow and especially the inevitable flow connecting with underground infrastructures in highly urbanized areas. A comprehensive modeling approach and effective mitigation measures are necessary for urban risk assessment and management. Herein in this work, surface flow modeling was first investigated based on an experiment; then, the underground modeling system was included by a coupled model proposed in this work; finally, urban rainfall - runoff simulations were carried out accounting for different spatial and temporal resolutions of rain data and further mitigation effect of rain garden. In pure surface flow modeling, depth-dependent roughness and infiltration methods were numerically investigated based on rainfall - runoff experiments, under two conditions in terms of traditional and LID (Low Impact Development measures) surface conditions, different slopes and rainfall intensities. First, observed runoff data has been used to calibrate the model parameters for the depth - dependent roughness and infiltration approaches for both traditional and LID surfaces. The calibrated parameter values then have been applied to validate other two rainfall events. High NSE Coefficient (Nash-Sutcliffe Efficiency) and low SDR (Standard Deviation R) values were obtained, indicating a satisfied agreement between simulated results and observed data for both calibration and validation cases. Then, further comparison of constant and depth - dependent methods clearly pointed out the superiority of the latter methods, as they led to much better evaluation criteria. In addition, the depth-dependent roughness method ensured stability. We also refer to Mügler et al. (2011a) who compared four roughness methods within one case study also proving that the best results were obtained with a water depth-dependent Manning law. The results demonstrated the superiority of the depth - dependent infiltration method when compared to constant infiltration and the necessity of the depth - dependent roughness approach for accuracy and stability reasons. The methods implemented here might also improve other shallow water models. In coupling between the hydrodynamic surface flow model and the underground drainage system, large underground urban infrastructures were explored especially. While several similar coupled models existed, none of them ever have been used to include large underground urban infrastructures such as transportation tunnels, metro stations or car parks. This, however, is quite important on the one hand to simulate flooding and associated risks within these underground infrastructures; on the other hand, to have a correct representation of the surface flow processes in the surroundings where the underground infrastructures are connected to the surface flow. First, a bidirectional coupling between the open-source surface flow solver hms++ (Hydroinformatics Modeling System) and the SWMM (Storm Water Management Model), which was realized as a plugin, was enabled allowing its capability to be loaded at runtime without changing the hms++ code. Second, the coupled model was verified using an idealized case with separated surface catchments connected via a subsurface link, to establish plausibility and mass conservation. Then, the results of a classic validation case consisting of a system of pipes splitting into parallel paths and reuniting were compared to those obtained with the commercial tool InfoWorks ICM, demonstrating close alignment between the two. Third, the extended hms++ model was applied to two real-world cases, a metro station and a transportation tunnel which both have been idealized as large underground pipes. While the pure surface flow model predicted implausible backwaters at the metro station entrance and the transportation tunnel portals, the coupled model correctly eliminated these backwaters by modeling inflow into the metro station and the transportation tunnel. This further enabled investigating water depths and flow velocities within the metro station and the transportation tunnel and in the latter risks for human stability and recommendations for vehicle speeds were assessed. Overall, the extended coupled hms++ model has demonstrated its capabilities to qualitatively and quantitatively account for large underground urban infrastructures and thus to contribute to representation of urban flooding processes in a more precise way than offering a parameterization of pipe flow capacity and drainage overflow. In the application of the proposed rainfall – runoff model, different spatial and temporal rainfall resolutions, including spatial temporal distribution (TSD), temporal uniform (TU), spatial uniform (SU), spatial uniform reverse (SU_R), and spatial temporal uniform (TSU), and the mitigation effect of green infrastructure were explored. The TSD rainfall data, which accounts for both spatial and temporal variability, provided reference for flood extent and depth in this application. First, the analysis among different rain data resolutions with surface - only model revealed that both spatial and temporal characteristics of rain data affect inundation, spatial resolutions (SU, SU_R and TSU) performed stronger effect than temporal resolution (TU), with respect to the maximum inundation depth in this case. Second, incorporating drainage systems, the comparison between the surface model and the coupled model over different rain data resolutions highlighted the critical role of drainage systems in altering urban flood dynamics, both in inundation time and depth. A larger reduction on final inundated depth than the maximum inundated depth indicated that the drainage system was more efficient in after-peak water removal than in peak attenuation. This further suggests that current drainage systems are more suited for accelerating inundation in recession periods rather than limiting the peak severeness. With regard to the reduction peak inundated depth caused by drainage system, the largest occurred in TU resolution among those five resolutions. Third, the analysis among those rain resolutions with the coupled mode showed that, ignoring spatial variability (SU resolution) led to increased peak inundation volume compared with TSD, while temporal smoothing of rainfall (TU and TSU resolutions) led to substantial reductions in peak inundation volume but advanced the onset of inundation time and delayed the peak arrival. This indicated that neglecting temporal variability would distort the timing of urban flood response even if overall flooding appears reduced. Furthermore, for effect of different rain resolutions on drainage outfalls outflow displayed that, SU, TU, and TSU resolutions delayed outflow peak at both observed outfalls compared to the TSD resolution, only SU_R advances it. These changes highlighted the sensitivity of drainage system response to rainfall structure in spatial and temporal. In the end, the exploration of rain garden as a mitigation measure under three rainfalls was investigated. Optimal placement of rain gardens in areas with higher runoff accumulation significantly reduced flood depths at selected hot spot, indicating that the potential of nature-based solutions in urban flood mitigation. With the simulated rain cases, the effectiveness of rain gardens in reducing surface inundation diminished with increasing storm intensity was demonstrated. And the implementation of a rain garden significantly alters the hydrodynamic response across different storm return periods. These results indicated that while rain gardens effectively mitigate flood depth under moderate storms, their performance becomes weaker under extreme events. These findings provided insights for urban planners and policymakers in designing resilient flood management systems that integrated accurate modeling, high-resolution data and sustainable mitigation practices. Overall, this work proposed a comprehensive modeling approach for simulating urban areas including drainage systems and large underground infrastructures. With the development of depth - dependent roughness and infiltration methods, the investigation of spatial and temporal rainfall resolutions and the application green infrastructures - the rain garden, the model was successfully applied to several test cases and real urban areas. The exploration of rain data resolutions and rain garden cases offered insights into their respective impacts on surface runoff dynamics, drainage performance and the overall effectiveness of mitigation strategies in urban flood scenarios.","Die Modellierung urbaner Überflutungen stellt weltweit ein hochaktuelles Forschungsthema dar. Sie umfasst sowohl die Oberflächenabflüsse als auch die unterirdischen Entwässerungssysteme – insbesondere jedoch die unvermeidbaren Fließverbindungen mit unterirdischen Infrastrukturen in stark urbanisierten Gebieten. Für eine fundierte Risikobewertung und ein effektives Management urbaner Überflutungsgefahren ist ein umfassender Modellierungsansatz in Kombination mit geeigneten Minderungsmaßnahmen erforderlich. In der vorliegenden Arbeit wird zunächst die Modellierung von Oberflächenabfluss auf Basis experimenteller Untersuchungen behandelt. Anschließend erfolgt die Einbindung des unterirdischen Systems durch ein in dieser Arbeit entwickeltes gekoppeltes Modell. Schließlich werden Niederschlag-Abfluss-Simulationen durchgeführt, bei denen unterschiedliche räumliche und zeitliche Auflösungen der Niederschlagsdaten auf die Oberflächenabflüsse sowie mögliche Minderungsmaßnahmen untersucht werden. Im ersten Schritt wurden im Rahmen der reinen Oberflächenabflussmodellierung tiefenabhängige Rauigkeits- und Infiltrationsansätze numerisch auf Grundlage von Niederschlag-Abfluss-Experimenten untersucht – unter variierenden Bedingungen in Bezug auf LID- (Low Impact Development) und traditionelle Oberflächen, unterschiedliche Längsgefälle sowie variierende Niederschlagsintensitäten. Beobachtete Abflussdaten wurden zunächst zur Kalibrierung der Modellparameter der tiefenabhängigen Ansätze verwendet. Die kalibrierten Parameter wurden anschließend zur Validierung zweier weiterer Niederschlagsereignisse herangezogen. Hohe Nash-Sutcliffe-Effizienzen (NSE) und niedrige Standardabweichungen (SDR) belegen eine gute Übereinstimmung zwischen Simulation und Messung. Der Vergleich mit konstanten Ansätzen zeigt deutlich die Überlegenheit der tiefenabhängigen Methoden, insbesondere hinsichtlich Stabilität und Modellgenauigkeit. Auch frühere Studien (z. B. Mügler et al., 2011a) belegen die Vorteile einer wasserstandabhängigen Rauigkeitsformulierung nach Manning. Die hier implementierten Ansätze können auch zur Verbesserung anderer Flachwassermodelle beitragen. Im zweiten Schritt wurde ein bidirektional gekoppeltes Modell zwischen dem Open-Source-Oberflächenmodell Hydroinformatics Modeling System (hms++) und dem Storm Water Management Model (SWMM) entwickelt. Dieses wurde als Plugin realisiert und erlaubt die dynamische Kopplung zur Laufzeit ohne Änderung des Quellcodes von hms++. Die Kopplung wurde zunächst in einem idealisierten Szenario mit getrennten Einzugsgebieten über eine unterirdische Verbindung getestet, um Massenerhaltung und Plausibilität sicherzustellen. Anschließend wurde ein klassischer Validierungsfall – ein Leitungssystem mit paralleler Aufspaltung der Abflüsse und Wiedervereinigung – mit den Ergebnissen des kommerziellen Werkzeugs InfoWorks ICM verglichen, wobei eine gute Übereinstimmung erzielt wurde. Schließlich wurde das erweiterte Modell auf zwei reale urbane Fälle angewendet: ein U-Bahnhof und ein Verkehrstunnel, idealisiert als große unterirdische Röhren. Während das reine Oberflächenmodell an den Zugängen zu diesen Infrastrukturen unrealistische Rückstauphänomene prognostizierte, konnte das gekoppelte Modell diese durch die Simulation von Zuflussvorgängen in die Untergrundstrukturen plausibel abbilden. Dies ermöglichte darüber hinaus Analysen zu Wasserständen und Fließgeschwindigkeiten innerhalb der unterirdischen Infrastrukturen sowie Bewertungen hinsichtlich Personensicherheit und Fahrempfehlungen für Autos. Insgesamt zeigt das erweiterte hms++-Modell, dass durch explizite Einbindung großer unterirdischer Infrastrukturen die Prozesse urbaner Überflutung sowohl qualitativ als auch quantitativ besser abgebildet werden können als durch einfache Parametrisierung von Kanalüberlauf und -kapazitäten. Im dritten Schritt wurden mit dem gekoppelten Modell die Auswirkungen unterschiedlicher räumlicher und zeitlicher Auflösungen von Niederschlagsdaten sowie von Maßnahmen der grünen Infrastruktur auf den Oberflächenabfluss untersucht. Der Vergleich zwischen reinem Oberflächenmodell und dem gekoppelten Modell unterstreicht die Bedeutung unterirdischer Entwässerungssysteme für Dynamik und Tiefe urbaner Überflutungen. Dabei zeigt sich, dass die Systeme effektiver in der Ableitung von Nachflutwasser als in der Dämpfung von Spitzenabflüssen sind. Dies weist darauf hin, dass bestehende Entwässerungssysteme vor allem zur Beschleunigung des Rückgangs von Überflutungen ausgelegt sind. Zudem beeinflussen die räumlichen und zeitlichen Merkmale der Niederschlagsverteilung (z. B. TSD, SU, TU, TSU) maßgeblich das Muster und den Zeitpunkt von Überflutungsereignissen. So führt das Vernachlässigen räumlicher Variabilität (SU) zu größeren Überflutungsvolumina, während zeitlich geglättete Niederschläge (TU, TSU) zu einem früheren Beginn und verzögerten Spitzenabflüssen führen. Auch die Abflussdynamik an Auslässen reagiert empfindlich auf die gewählte Niederschlagsstruktur. Darüber hinaus wurde der Einsatz von Rain Gardens als Minderungsmaßnahme unter drei Niederschlagsereignissen analysiert. Dabei zeigte sich, dass eine gezielte Platzierung der Rain Gardens an stark belasteten Stellen die Überflutungstiefen signifikant reduzieren kann. Allerdings nimmt die Wirksamkeit der Rain Gardens mit zunehmender Niederschlagsintensität ab, was die Grenzen naturbasierter Lösungen bei Extremereignissen aufzeigt. Zusammenfassend wurde ein umfassender Modellierungsansatz zur Simulation urbaner Überflutungsprozesse unter Berücksichtigung von Entwässerungssystemen und großräumigen unterirdischen Infrastrukturen entwickelt. Durch die Einführung tiefenabhängiger Parameter, die Untersuchung von Regenauflösungen sowie die Bewertung von grünen und grauen Infrastrukturen konnte das Modell erfolgreich in verschiedenen urbanen Szenarien getestet werden. Es bietet somit ein übertragbares und robustes Werkzeug für zukünftige Anwendungen in der urbanen Überflutungsmodellierung."],"dc:identifier.uri":["https://depositonce.tu-berlin.de/handle/11303/25675","https://doi.org/10.14279/depositonce-24499"],"dc:language.iso":["en"],"dc:rights.uri":["https://creativecommons.org/licenses/by-nd/4.0/"],"dc:title":["A comprehensive modeling approach for urban rainfall - runoff simulation"],"dc:type":["Doctoral Thesis"]},"updated_at":"2026-07-27T21:28:52Z"}