Mapping Water Levels across a Region of the Cuvette Centrale Peatland Complex

Inundation dynamics are the primary control on greenhouse gas emissions from peatlands. Situated in the central Congo Basin, the Cuvette Centrale is the largest tropical peatland complex. However, our knowledge of the spatial and temporal variations in its water levels is limited. By addressing this gap, we can quantify the relationship between the Cuvette Centrale’s water levels and greenhouse gas emissions, and further provide a baseline from which deviations caused by climate or land-use change can be observed, and their impacts understood. We present here a novel approach that combines satellite-derived rainfall, evapotranspiration and L-band Synthetic Aperture Radar (SAR) data to estimate spatial and temporal changes in water level across a sub-region of the Cuvette Centrale. Our key outputs are a map showing the spatial distribution of rainfed and flood-prone locations and a daily, 100 m resolution map of peatland water levels. This map is validated using satellite altimetry data and in situ water table data from water loggers. We determine that 50% of peatlands within our study area are largely rainfed, and a further 22.5% are somewhat rainfed, receiving hydrological input mostly from rainfall (directly and via surface/sub-surface inputs in sloped areas). The remaining 27.5% of peatlands are mainly situated in riverine floodplain areas to the east of the Congo River and between the Ubangui and Congo rivers. The mean amplitude of the water level across our study area and over a 20-month period is 22.8 ± 10.1 cm to 1 standard deviation. Maximum temporal variations in water levels occur in the riverine floodplain areas and in the inter-fluvial region between the Ubangui and Congo rivers. Our results show that spatial and temporal changes in water levels can be successfully mapped over tropical peatlands using the pattern of net water input (rainfall minus evapotranspiration, not accounting for run-off) and L-band SAR data

Amazon hydrology from space : scientific advances and future challenges

As the largest river basin on Earth, the Amazon is of major importance to the world's climate and water resources. Over the past decades, advances in satellite-based remote sensing (RS) have brought our understanding of its terrestrial water cycle and the associated hydrological processes to a new era. Here, we review major studies and the various techniques using satellite RS in the Amazon. We show how RS played a major role in supporting new research and key findings regarding the Amazon water cycle, and how the region became a laboratory for groundbreaking investigations of new satellite retrievals and analyses. At the basin-scale, the understanding of several hydrological processes was only possible with the advent of RS observations, such as the characterization of "rainfall hotspots" in the Andes-Amazon transition, evapotranspiration rates, and variations of surface waters and groundwater storage. These results strongly contribute to the recent advances of hydrological models and to our new understanding of the Amazon water budget and aquatic environments. In the context of upcoming hydrology-oriented satellite missions, which will offer the opportunity for new synergies and new observations with finer space-time resolution, this review aims to guide future research agenda toward integrated monitoring and understanding of the Amazon water from space. Integrated multidisciplinary studies, fostered by international collaborations, set up future directions to tackle the great challenges the Amazon is currently facing, from climate change to increased anthropogenic pressure

Expressive fluxes over Amazon floodplain revealed by 2D hydrodynamic modelling

Water fluxes in the Amazon River floodplain affect hydrodynamic and ecological processes from local to global scales, but they remain poorly understood due to difficult accessibility and limited data. We characterized the hydrodynamics of eight floodplain units of the central Amazon River (40000 km2) using the 2D hydraulic model HEC-RAS. High resolution modelling (∼400 m) improved the representation of river and floodplain discharge, water surface elevation (77 cm accuracy) and flood extent (∼80% - high water period, ∼52% - low water period) compared to past modelling studies. Our results show that floodplain flows during floods are very intense with upstream inflow and downstream outflow of the floodplain units. These gross flows are much larger than the net flows, with values of up to 20% of the Amazon River discharge and residence time around 6 days during floods (several months during low water period). Water extent did not show strong interannual variability during floods as the volume stored in the floodplain did, possibly due to topographic constraints. Significant hysteresis in flood extent and volume, and active and storage zones on the floodplain highlight the complexity of floodplain hydrodynamics. Extreme floods strongly impacted the onset and duration of the flood by up to one month and, consequently on duration of high water renewal period with the river. Our characterization is important to assess the effects of extreme floods on riverine communities, understand nutrient and sediment variations in the floodplain, and characterize the export of water, sediment, and carbon flux to the ocean from the world's largest hydrological system

Inundações em múltiplas escalas na América do Sul : de áreas úmidas a áreas de risco

South America hosts some of the major river systems on Earth, often associated with large floodplains that are inundated every year, such as the Pantanal and many Amazon wetlands. Interfluvial wetland complexes are also found across the continent, with particular geomorphic settings and unique savanna or grassland vegetation. South American wetlands can provide distinctive ecosystem services such as biodiversity supporting, food provision and flood attenuation. On the other hand, humans have settled around wetlands for millennia, benefiting from all resources they provide, and have adapted to its flood regime as well adapted its landscape, defining what has been called human-water systems. Yet, an increasing number of South American people have been negatively affected by extreme floods. Moving from continental to local scales, this thesis invites the readers to a journey across major South American wetland systems and their unique hydrological dynamics, under the light of the satellite era and the breakthrough advances on hydrologic-hydrodynamic modeling in the last decades. This work is founded on the proposition of a continental wetland research agenda, and based on a comparative hydrology approach. Floods are studied through both natural wetland processes and hazard dimensions. The first part presents a set of studies on the Amazon basin wetlands, from the development of 1D and 2D models to simulate hydrological processes in contrasting wetland types in the Negro river basin to the basin-wide intercomparison of 29 inundation products and assessment of long-term inundation trends. While most wetland studies have been conducted over the central Amazon floodplains, major knowledge gaps remain for understanding the hydrological dynamics of interfluvial areas such as the Llanos de Moxos and Negro savannas, where the inundation is less predictable and shallower. The second part of the thesis leverages satellite-based datasets of multiple hydrological variables (water levels, total water storage, inundation extent, precipitation and evapotranspiration) to address the hydrology of 12 large wetland systems in the continent. It shows the major differences among river floodplains and interfluvial wetlands on the water level annual amplitude, time lag between precipitation and inundation, and evapotranspiration dynamics. Finally, the third part addresses the flood hazard component of human-wetland interactions through large-scale assessments of flood hazard dynamics and effects of built infrastructure (dams) on flood attenuation. The dynamics of the great 1983 floods, one of the most extreme years ever recorded in the continent, is assessed with a continental hydrological model. Then, the capabilities of continental models to simulate the river-floodplain-reservoir continuum that exists across large river basins are assessed with case studies for major river basins affected by human intervention (Itajaí-Açu and upper Paraná river basins in Brazil). While this thesis enlightens some relevant hydrological processes regarding South American floods and their positive and negative effects to human societies and ecosystems in general, major knowledge gaps persist and provide great research opportunities for the near future. The launching of many hydrology-oriented satellite missions, and an ever-growing computational capacity, make the continental hydrology agenda related to wetlands and floods a great research topic for the upcoming years.A América do Sul abriga alguns dos maiores sistemas hídricos do planeta, frequentemente associados a grandes planícies de inundação, como o Pantanal e várias áreas da Amazônia. Áreas úmidas (AU’s) interfluviais são também encontrados no continente, com características geomorfológicas particulares, e vegetações de savana e gramíneas únicas. As AU’s da América do Sul provêm diversos serviços ecossistêmicos, como suporte à biodiversidade, provisão de alimento e atenuação de cheias. Humanos têm se estabelecido ao redor de AU’s por milênios, se beneficiando dos recursos providos por elas. Eles se adaptaram ao seu regime de inundação, e adaptaram sua paisagem, definindo o que tem sido chamado de sistemas sociedade-água. Por outro lado, um número crescente de pessoas têm sido negativamente afetado por cheias extremas. Da escala continental à local, esta tese convida o leitor a uma jornada através de importantes AU’s da América do Sul e suas particulares dinâmicas de inundação, sob a luz da era dos satélites e dos grandes avanços em modelagem hidrológica-hidrodinâmica das últimas décadas. Este trabalho é baseado na proposta de uma escala continental de pesquisa sobre AU’s, e é baseado em uma abordagem de hidrologia comparativa. Inundações são estudadas em múltiplas dimensões, de processos de AU’s naturais à questão do perigo para humanos. A primeira parte apresenta uma série de estudos sobre as AU’s da bacia amazônica, desde o desenvolvimento de modelos 1D e 2D para simular processos hidrológicos em tipos contrastantes de AU’s na bacia do Rio Negro, até a intercomparação de 29 produtos de inundação e avaliação de tendências de inundações de longo prazo para a escala da bacia amazônica. Enquanto a maioria dos estudos de AU’s foi conduzida nas várzeas do rio Amazonas, importantes lacunas do conhecimento permanecem para a compreensão da dinâmica hidrológica de áreas interfluviais como Llanos de Moxos e as savanas do rio Negro, onde a inundação é menos previsível e mais rasa. A segunda parte da tese utiliza dados oriundos de satélites relacionados a múltiplas variáveis hidrológicas (níveis d’água, armazenamento total de água, extensão de áreas inundadas, precipitação e evapotranspiração) para estudar a hidrologia de 12 grandes sistemas de AU’s do continente. São destacadas as grandes diferenças entre planícies de inundação e AU’s interfluviais em termos de amplitude anual de níveis d’água, defasagem entre precipitação e inundação, e dinâmica de evapotranspiração. Por fim, a última parte da tese aborda o componente de perigo de inundação das interações sociedade-água através de avaliações em grande escala da dinâmica de inundação e dos efeitos de infraestruturas construídas (como barragens) na atenuação de cheias. A dinâmica das grandes cheias de 1983, um dos anos mais extremos já registrados no continente, é avaliada com um modelo hidrológico continental. Depois, a capacidade de modelos continentais para simular o continuum entre rios, planícies de inundação e reservatórios que existe em grandes bacias hidrográficas é avaliada com estudos de casos para importantes bacias afetadas pela intervenção humana (bacia dos rios Paraná e Itajaí-Açu). Enquanto esta tese avança a compreensão de relevantes processos hidrológicos relacionados a inundações na América do Sul em múltiplas escalas, bem como seus efeitos positivos e negativos nas sociedades humanas e ecossistemas em geral, importantes lacunas do conhecimento persistem e fomentam importantes oportunidades de pesquisa futuras. O lançamento de várias missões satelitais orientadas a hidrologia, e uma cada vez mais crescente capacidade computacional, faz da agenda continental de hidrologia relacionada a AU’s e inundações um grande tópico de pesquisa para os próximos anos

Tributary impacts, hydrological connectivity and distribution of sediment sinks along the middle-lower Amazon River

By integrating hydro-geomorphic data collected from the field with remote sensing data, this dissertation investigates the roles of the tributaries and vast floodplain on suspended sediment distribution patterns in the Amazon River system. To assess the tributary impacts, I focused on the Solimões and Negro Rivers, and found the significant seasonal variations in surface water mixing and distribution patterns; however inter-annual variations between flooded (2009) and drought years (2005) were not notable. It is also observed that the anabranching channel patterns were observed to prevent fast mixing of different water types. Channel-floodplain hydro-sedimentary interactions were investigated over water-saturated floodplain in the lower Amazon by mapping geomorphic mosaic, and characterizing the seasonal flooding and storage patterns. Hydrological connectivity processes over floodplain varied significantly between geomorphic units, which were not correlated with their distance from the river, implying that application of the traditional “flood pulse” model is not applicable in the Amazon. The channel-floodplain connectivity also resulted in failure of the rating curve around Obidos due to the seasonal water storage in floodplain. Using a series of ADCP data, both the threshold of hydrological connectivity and geomorphic factors influencing the rating curve were assessed, and then the rating curve at Obidos was revised. Floodplain suspended sediment storage along the lower Amazon in between Manacapuru and Obidos was estimated as 79 million tons annually. However sedimentation rates which are determined by the connectivity processes and geomorphologic characteristics of floodplain significantly varied between different reaches, showing downstream increase in the magnitude of sediment sinks. This indicates a nonlinear geomorphic evolution of the Amazon floodplain at least since the Holocene through the river’s longitudinal profile. Through sequences of interrelated chapters, I arrived to the conclusion that the influences of the tributaries and channel-floodplain interactions on the Amazon River system’s suspended sediment distribution are significant and their patterns are more complex than expected. The major factor contributing to this complexity is the geomorphologic styles of the river, which are related both to the long-term evolution processes and to the current anabranching channel dynamics. These geomorphologic styles along the Amazon River are different reach-by-reach due to the varying interactive processes with regional tectonics, hydroclimatology and human activities.Geography and the Environmen

Radar satellite imagery for humanitarian response. Bridging the gap between technology and application

This work deals with radar satellite imagery and its potential to assist of humanitarian operations. As the number of displaced people annually increases, both hosting countries and relief organizations face new challenges which are often related to unclear situations and lack of information on the number and location of people in need, as well as their environments. It was demonstrated in numerous studies that methods of earth observation can deliver this important information for the management of crises, the organization of refugee camps, and the mapping of environmental resources and natural hazards. However, most of these studies make use of -high-resolution optical imagery, while the role of radar satellites is widely neglected. At the same time, radar sensors have characteristics which make them highly suitable for humanitarian response, their potential to capture images through cloud cover and at night in the first place. Consequently, they potentially allow quicker response in cases of emergencies than optical imagery. This work demonstrates the currently unused potential of radar imagery for the assistance of humanitarian operations by case studies which cover the information needs of specific emergency situations. They are thematically grouped into topics related to population, natural hazards and the environment. Furthermore, the case studies address different levels of scientific objectives: The main intention is the development of innovative techniques of digital image processing and geospatial analysis as an answer on the identified existing research gaps. For this reason, novel approaches are presented on the mapping of refugee camps and urban areas, the allocation of biomass and environmental impact assessment. Secondly, existing methods developed for radar imagery are applied, refined, or adapted to specifically demonstrate their benefit in a humanitarian context. This is done for the monitoring of camp growth, the assessment of damages in cities affected by civil war, and the derivation of areas vulnerable to flooding or sea-surface changes. Lastly, to foster the integration of radar images into existing operational workflows of humanitarian data analysis, technically simple and easily-adaptable approaches are suggested for the mapping of rural areas for vaccination campaigns, the identification of changes within and around refugee camps, and the assessment of suitable locations for groundwater drillings. While the studies provide different levels of technical complexity and novelty, they all show that radar imagery can largely contribute to the provision of a variety of information which is required to make solid decisions and to effectively provide help in humanitarian operations. This work furthermore demonstrates that radar images are more than just an alternative image source for areas heavily affected by cloud cover. In fact, what makes them valuable is their information content regarding the characteristics of surfaces, such as shape, orientation, roughness, size, height, moisture, or conductivity. All these give decisive insights about man-made and natural environments in emergency situations and cannot be provided by optical images Finally, the findings of the case studies are put into a larger context, discussing the observed potential and limitations of the presented approaches. The major challenges are summarized which need be addressed to make radar imagery more useful in humanitarian operations in the context of upcoming technical developments. New radar satellites and technological progress in the fields of machine learning and cloud computing will bring new opportunities. At the same time, this work demonstrated the large need for further research, as well as for the collaboration and transfer of knowledge and experiences between scientists, users and relief workers in the field. It is the first extensive scientific compilation of this topic and the first step for a sustainable integration of radar imagery into operational frameworks to assist humanitarian work and to contribute to a more efficient provision of help to those in need.Die vorliegende Arbeit beschäftigt sich mit bildgebenden Radarsatelliten und ihrem potenziellen Beitrag zur Unterstützung humanitärer Einsätze. Die jährlich zunehmende Zahl an vertriebenen oder geflüchteten Menschen stellt sowohl Aufnahmeländer als auch humanitäre Organisationen vor große Herausforderungen, da sie oft mit unübersichtlichen Verhältnissen konfrontiert sind. Effektives Krisenmanagement, die Planung und Versorgung von Flüchtlingslagern, sowie der Schutz der betroffenen Menschen erfordern jedoch verlässliche Angaben über Anzahl und Aufenthaltsort der Geflüchteten und ihrer natürlichen Umwelt. Die Bereitstellung dieser Informationen durch Satellitenbilder wurde bereits in zahlreichen Studien aufgezeigt. Sie beruhen in der Regel auf hochaufgelösten optischen Aufnahmen, während bildgebende Radarsatelliten bisher kaum Anwendung finden. Dabei verfügen gerade Radarsatelliten über Eigenschaften, die hilfreich für humanitäre Einsätze sein können, allen voran ihre Unabhängigkeit von Bewölkung oder Tageslicht. Dadurch ermöglichen sie in Krisenfällen verglichen mit optischen Satelliten eine schnellere Reaktion. Diese Arbeit zeigt das derzeit noch ungenutzte Potenzial von Radardaten zur Unterstützung humanitärer Arbeit anhand von Fallstudien auf, in denen konkrete Informationen für ausgewählte Krisensituationen bereitgestellt werden. Sie sind in die Themenbereiche Bevölkerung, Naturgefahren und Ressourcen aufgeteilt, adressieren jedoch unterschiedliche wissenschaftliche Ansprüche: Der Hauptfokus der Arbeit liegt auf der Entwicklung von innovativen Methoden zur Verarbeitung von Radarbildern und räumlichen Daten als Antwort auf den identifizierten Forschungsbedarf in diesem Gebiet. Dies wird anhand der Kartierung von Flüchtlingslagern zur Abschätzung ihrer Bevölkerung, zur Bestimmung von Biomasse, sowie zur Ermittlung des Umwelteinflusses von Flüchtlingslagern aufgezeigt. Darüber hinaus werden existierende oder erprobte Ansätze für die Anwendung im humanitären Kontext angepasst oder weiterentwickelt. Dies erfolgt im Rahmen von Fallstudien zur Dynamik von Flüchtlingslagern, zur Ermittlung von Schäden an Gebäuden in Kriegsgebieten, sowie zur Erkennung von Risiken durch Überflutung. Zuletzt soll die Integration von Radardaten in bereits existierende Abläufe oder Arbeitsroutinen in der humanitären Hilfe anhand technisch vergleichsweise einfacher Ansätze vorgestellt und angeregt werden. Als Beispiele dienen hier die radargestützte Kartierung von entlegenen Gebieten zur Unterstützung von Impfkampagnen, die Identifizierung von Veränderungen in Flüchtlingslagern, sowie die Auswahl geeigneter Standorte zur Grundwasserentnahme. Obwohl sich die Fallstudien hinsichtlich ihres Innovations- und Komplexitätsgrads unterscheiden, zeigen sie alle den Mehrwert von Radardaten für die Bereitstellung von Informationen, um schnelle und fundierte Planungsentscheidungen zu unterstützen. Darüber hinaus wird in dieser Arbeit deutlich, dass Radardaten für humanitäre Zwecke mehr als nur eine Alternative in stark bewölkten Gebieten sind. Durch ihren Informationsgehalt zur Beschaffenheit von Oberflächen, beispielsweise hinsichtlich ihrer Rauigkeit, Feuchte, Form, Größe oder Höhe, sind sie optischen Daten überlegen und daher für viele Anwendungsbereiche im Kontext humanitärer Arbeit besonders. Die in den Fallstudien gewonnenen Erkenntnisse werden abschließend vor dem Hintergrund von Vor- und Nachteilen von Radardaten, sowie hinsichtlich zukünftiger Entwicklungen und Herausforderungen diskutiert. So versprechen neue Radarsatelliten und technologische Fortschritte im Bereich der Datenverarbeitung großes Potenzial. Gleichzeitig unterstreicht die Arbeit einen großen Bedarf an weiterer Forschung, sowie an Austausch und Zusammenarbeit zwischen Wissenschaftlern, Anwendern und Einsatzkräften vor Ort. Die vorliegende Arbeit ist die erste umfassende Darstellung und wissenschaftliche Aufarbeitung dieses Themenkomplexes. Sie soll als Grundstein für eine langfristige Integration von Radardaten in operationelle Abläufe dienen, um humanitäre Arbeit zu unterstützen und eine wirksame Hilfe für Menschen in Not ermöglichen

Monitoring River Basin Development and Variation in Water Resources in Transboundary Imjin River in North and South Korea Using Remote Sensing

This paper presents methods of monitoring river basin development and water variability for the transboundary river in North and South Korea. River basin development, such as dams and water infrastructure in transboundary rivers, can be a potential factor of tensions between upstream and downstream countries since dams constructed upstream can adversely affect downstream riparians. However, because most of the information related to North Korea has been limited to the public, the information about dams constructed and their locations were inaccurate in many previous studies. In addition, water resources in transboundary rivers can be exploited as a political tool. Specifically, due to the unexpected water release from the Hwanggang Dam, upstream of the transboundary Imjin River in North and South Korea, six South Koreans died on 6 September 2009. The Imjin River can be used as a political tool by North Korea, and seven events were reported as water conflicts in the Imjin River from 2001 to 2016. In this paper, firstly, we have updated the information about the dams constructed over the Imjin River in North Korea using multi-temporal images with a high spatial resolution (15-30 cm) obtained from Google Earth. Secondly, we analyzed inter- and intra-water variability over the Hwanggang Reservoir using open-source images obtained from the Global Surface Water Explorer. We found a considerable change in water surface variability before and after 2008, which might result from the construction of the Hwanggang Dam. Thirdly, in order to further investigate intra-annual water variability, we present a method monitoring water storage changes of the Hwanggang Reservoir using the area-elevation curve (AEC), which was derived from multi-sensor Synthetic Aperture Radar (SAR) images (Sentinel-1A and -1B) and the Shuttle Radar Topography Mission (SRTM) Digital Elevation Model (DEM). Since many previous studies for estimating water storage change have depended on satellite altimetry dataset and optical images for deriving AEC, the method adopted in this study is the only application for such inaccessible areas since no altimetry ground track exists for the Hwanggang Reservoir and because clouds can block the study area for wet seasons. Moreover, this study has newly proven that unexpected water release can occur in dry seasons because the water storage in the Hwanggang Reservoir can be high enough to conduct a release that can be used as a geopolitical tool. Using our method, potential risks can be mitigated, not in response to a water release, but based on pre-event water storage changes in the Hwanggang Reservoir

Delimitation of flooded areas based on Sentinel-1 SAR data processed through machine learning

Delimitation of areas subject to flooding is crucial to understand water dynamics and fluvial changes. This study analyzed the potential of C-band Synthetic Aperture Radar (SAR) images acquired by the Sentinel-1 satellite in 2017, 2018, and 2019 to delineate flooded areas in the Central Amazon. The images were processed by the Artificial Neural Network Multi-Layer Perceptron (ANN-MLP) and two K-Nearest Neighbor (KNN-7 and KNN-11) machine learning (ML) classifiers. Pre-processing of Single Look Complex (SLC) SAR images involved the following methodological steps: orbit-file application; radiometric calibration (σ0); Range-Doppler terrain correction; speckle noise filtering; and conversion of linear data to backscattering coefficients (units in dB). We applied the Lee filter, with a window size of 3x3, for speckle filtering. A set of 6000 randomly distributed samples for training (70%), validation (20%), and test (10%) was obtained based on visual interpretation of Sentinel-2 optical satellite image acquired in the same years of SAR images. We found the largest flooded areas in 2019 in the study area (municipality of Parintins and Urucará, Amazonas River, Brazil): 6244km2 by the ANN-MLP classifier; 6268km2 by KNN-7; and 6290km2 by KNN-11, while the smallest flooded areas were found in 2018: 5364km2 by ANN-MLP; 5412km2 by KNN-7; and 5535km2 by KNN-11. The three classifiers presented Kappa coefficients between 0.77 and 0.91. ANN-MLP showed the best accuracy. The presence of shadow effects in the SAR images increased the commission errors

Detection of temporarily flooded vegetation using time series of dual polarised C-band synthetic aperture radar data

The intense research of the last decades in the field of flood monitoring has shown that microwave sensors provide valuable information about the spatial and temporal flood extent. The new generation of satellites, such as the Sentinel-1 (S-1) constellation, provide a unique, temporally high-resolution detection of the earth's surface and its environmental changes. This opens up new possibilities for accurate and rapid flood monitoring that can support operational applications. Due to the observation of the earth's surface from space, large-scale flood events and their spatiotemporal changes can be monitored. This requires the adaptation of existing or the development of new algorithms, which on the one hand enable precise and computationally efficient flood detection and on the other hand can process a large amounts of data. In order to capture the entire extent of the flood area, it is essential to detect temporary flooded vegetation (TFV) areas in addition to the open water areas. The disregard of temporary flooded vegetation areas can lead to severe underestimation of the extent and volume of the flood. Under certain system and environmental conditions, Synthetic Aperture Radar (SAR) can be utilized to extract information from under the vegetation cover. Due to multiple backscattering of the SAR signal between the water surface and the vegetation, the flooded vegetation areas are mostly characterized by increased backscatter values. Using this information in combination with a continuous monitoring of the earth's surface by the S-1 satellites, characteristic time series-based patterns for temporary flooded vegetation can be identified. This combination of information provides the foundation for the time series approach presented here. This work provides a comprehensive overview of the relevant sensor and environmental parameters and their impact on the SAR signal regarding temporary open water (TOW) and TFV areas. In addition, existing methods for the derivation of flooded vegetation are reviewed and their benefits, limitations, methodological trends and potential research needs for this area are identified and assessed. The focus of the work lies in the development of a SAR and time series-based approach for the improved extraction of flooded areas by the supplementation of TFV and on the provision of a precise and rapid method for the detection of the entire flood extent. The approach developed in this thesis allows for the precise extraction of large-scale flood areas using dual-polarized C-band time series data and additional information such as topography and urban areas. The time series features include the characteristic variations (decrease and/or increase of backscatter values) on the flood date for the flood-related classes compared to the whole time series. These features are generated individually for each available polarization (VV, VH) and their ratios (VV/VH, VV-VH, VV+VV). The generation of the time series features was performed by Z-transform for each image element, taking into account the backscatter values on the flood date and the mean value and standard deviation of the backscatter values from the nonflood dates. This allowed the comparison of backscatter intensity changes between the image elements. The time series features constitute the foundation for the hierarchical threshold method for deriving flood-related classes. Using the Random Forest algorithm, the importance of the time series data for the individual flood-related classes was analyzed and evaluated. The results showed that the dual-polarized time series features are particularly relevant for the derivation of TFV. However, this may differ depending on the vegetation type and other environmental conditions. The analyses based on S-1 data in Namibia, Greece/Turkey and China during large-scale floods show the effectiveness of the method presented here in terms of classification accuracy. Theiv supplementary integration of temporary flooded vegetation areas and the use of additional information resulted in a significant improvement in the detection of the entire flood extent. It could be shown that a comparably high classification accuracy (~ 80%) was achieved for the flood extent in each of study areas. The transferability of the approach due to the application of a single time series feature regarding the derivation of open water areas could be confirmed for all study areas. Considering the seasonal component by using time series data, the seasonal variability of the backscatter signal for vegetation can be detected. This allows for an improved differentiation between flooded and non-flooded vegetation areas. Simultaneously, changes in the backscatter signal can be assigned to changes in the environmental conditions, since on the one hand a time series of the same image element is considered and on the other hand the sensor parameters do not change due to the same acquisition geometry. Overall, the proposed time series approach allows for a considerable improvement in the derivation of the entire flood extent by supplementing the TOW areas with the TFV areas