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

Application of open-access and 3rd party geospatial technology for integrated flood risk management in data sparse regions of developing countries

Floods are one of the most devastating disasters known to man, caused by both natural and anthropogenic factors. The trend of flood events is continuously rising, increasing the exposure of the vulnerable populace in both developed and especially developing regions. Floods occur unexpectedly in some circumstances with little or no warning, and in other cases, aggravate rapidly, thereby leaving little time to plan, respond and recover. As such, hydrological data is needed before, during and after the flooding to ensure effective and integrated flood management. Though hydrological data collection in developed countries has been somewhat well established over long periods, the situation is different in the developing world. Developing regions are plagued with challenges that include inadequate ground monitoring networks attributed to deteriorating infrastructure, organizational deficiencies, lack of technical capacity, location inaccessibility and the huge financial implication of data collection at local and transboundary scales. These limitations, therefore, result in flawed flood management decisions and aggravate exposure of the most vulnerable people. Nigeria, the case study for this thesis, experienced unprecedented flooding in 2012 that led to the displacement of 3,871,53 persons, destruction of infrastructure, disruption of socio-economic activities valued at 16.9 billion US Dollars (1.4% GDP) and sadly the loss of 363 lives. This flood event revealed the weakness in the nation’s flood management system, which has been linked to poor data availability. This flood event motivated this study, which aims to assess these data gaps and explore alternative data sources and approaches, with the hope of improving flood management and decision making upon recurrence. This study adopts an integrated approach that applies open-access geospatial technology to curb data and financial limitations that hinder effective flood management in developing regions, to enhance disaster preparedness, response and recovery where resources are limited. To estimate flood magnitudes and return periods needed for planning purposes, the gaps in hydrological data that contribute to poor estimates and consequently ineffective flood management decisions for the Niger-South River Basin of Nigeria were filled using Radar Altimetry (RA) and Multiple Imputation (MI) approaches. This reduced uncertainty associated with missing data, especially at locations where virtual altimetry stations exist. This study revealed that the size and consistency of the gap within hydrological time series significantly influences the imputation approach to be adopted. Flood estimates derived from data filled using both RA and MI approaches were similar for consecutive gaps (1-3 years) in the time series, while wide (inconsecutive) gaps (> 3 years) caused by gauging station discontinuity and damage benefited the most from the RA infilling approach. The 2012 flood event was also quantified as a 1-in-100year flood, suggesting that if flood management measures had been implemented based on this information, the impact of that event would have been considerably mitigated. Other than gaps within hydrological time series, in other cases hydrological data could be totally unavailable or limited in duration to enable satisfactory estimation of flood magnitudes and return periods, due to finance and logistical limitations in several developing and remote regions. In such cases, Regional Flood Frequency Analysis (RFFA) is recommended, to collate and leverage data from gauging stations in proximity to the area of interest. In this study, RFFA was implemented using the open-access International Centre for Integrated Water Resources Management–Regional Analysis of Frequency Tool (ICI-RAFT), which enables the inclusion of climate variability effect into flood frequency estimation at locations where the assumption of hydrological stationarity is not viable. The Madden-Julian Oscillation was identified as the dominant flood influencing climate mechanism, with its effect increasing with return period. Similar to other studies, climate variability inclusive regional flood estimates were less than those derived from direct techniques at various locations, and higher in others. Also, the maximum historical flood experienced in the region was less than the 1-in-100-year flood event recommended for flood management. The 2012 flood in the Niger-South river basin of Nigeria was recreated in the CAESAR-LISFLOOD hydrodynamic model, combining open-access and third-party Digital Elevation Model (DEM), altimetry, bathymetry, aerial photo and hydrological data. The model was calibrated/validated in three sub-domains against in situ water level, overflight photos, Synthetic Aperture Radar (SAR) (TerraSAR-X, Radarsat2, CosmoSkyMed) and optical (MODIS) satellite images where available, to access model performance for a range of geomorphological and data variability. Improved data availability within constricted river channel areas resulted in better inundation extent and water level reconstruction, with the F-statistic reducing from 0.808 to 0.187 downstream into the vegetation dominating delta where data unavailability is pronounced. Overflight photos helped improve the model to reality capture ratio in the vegetation dominated delta and highlighted the deficiencies in SAR data for delineating flooding in the delta. Furthermore, the 2012 flood was within the confine of a 1-in-100-year flood for the sub-domain with maximum data availability, suggesting that in retrospect the 2012 flood event could have been managed effectively if flood management plans were implemented based on a 1-in-100-year flood. During flooding, fast-paced response is required. However, logistical challenges can hinder access to remote areas to collect the necessary data needed to inform real-time decisions. Thus, this adopts an integrated approach that combines crowd-sourcing and MODIS flood maps for near-real-time monitoring during the peak flood season of 2015. The results highlighted the merits and demerits of both approaches, and demonstrate the need for an integrated approach that leverages the strength of both methods to enhance flood capture at macro and micro scales. Crowd-sourcing also provided an option for demographic and risk perception data collection, which was evaluated against a government risk perception map and revealed the weaknesses in the government flood models caused by sparse/coarse data application and model uncertainty. The C4.5 decision tree algorithm was applied to integrate multiple open-access geospatial data to improve SAR image flood detection efficiency and the outputs were further applied in flood model validation. This approach resulted in F-Statistic improvement from 0.187 to 0.365 and reduced the CAESAR-LISFLOOD model overall bias from 3.432 to 0.699. Coarse data resolution, vegetation density, obsolete/non-existent river bathymetry, wetlands, ponds, uncontrolled dredging and illegal sand mining, were identified as the factors that contribute to flood model and map uncertainties in the delta region, hence the low accuracy depicted, despite the improvements that were achieved. Managing floods requires the coordination of efforts before, during and after flooding to ensure optimal mitigation in the event of an occurrence. In this study, and integrated flood modelling and mapping approach is undertaken, combining multiple open-access data using freely available tools to curb the effects of data and resources deficiency on hydrological, hydrodynamic and inundation mapping processes and outcomes in developing countries. This approach if adopted and implemented on a large-scale would improve flood preparedness, response and recovery in data sparse regions and ensure floods are managed sustainably with limited resources

Spatiotemporal flood hazard and flood risk assessment using remote sensing techniques. Case study: Khartoum State, Sudan

Dissertation submitted in partial fulfilment of the requirements for the degree of Master of Science in Geospatial TechnologiesThe state of Khartoum being the most populated state in Sudan, faces the consequences of floods recurrence almost annually during rainy season. Policy makers and on ground NGOs need to tackle the hazard of floods in an effective and efficient manner. Recent research demonstrated the capabilities and potentials of remote sensing in flood hazard and risk mapping. This study aims to map flood hazard and assess the risk of floods in state of Khartoum, Sudan. In order to identify the flood hazard in state counties, an inundation indicator is used, namely the relative frequency of inundation (RFI). Flood events that occurred from 1988 to 2018 were mapped using Landsat satellite images, and maximum flood extent was then delineated. RFI was obtained using maximum flood extent maps and served as the flood hazard map. We developed a Land Cover Land Use (LCLU) map using Landsat 8 to identify affected urban and croplands areas in the state of Khartoum. RFI values was used along with LCLU map to assess state counties, and to assess the vulnerability of public facilities (health and educational facilities) using zonal statistics. It was demonstrated that, in terms of average RFI values for LCLU classes per county, croplands had the highest flood hazard, and Urban areas carried a relatively moderate flood hazard. The results of this study indicate that croplands on the riverbanks are the most inundated areas in the state of Khartoum, and the most urbanized counties have the highest flood hazard

Flood Prediction and Mitigation in Data-Sparse Environments

In the last three decades many sophisticated tools have been developed that can accurately predict the dynamics of flooding. However, due to the paucity of adequate infrastructure, this technological advancement did not benefit ungauged flood-prone regions in the developing countries in a major way. The overall research theme of this dissertation is to explore the improvement in methodology that is essential for utilising recently developed flood prediction and management tools in the developing world, where ideal model inputs and validation datasets do not exist. This research addresses important issues related to undertaking inundation modelling at different scales, particularly in data-sparse environments. The results indicate that in order to predict dynamics of high magnitude stream flow in data-sparse regions, special attention is required on the choice of the model in relation to the available data and hydraulic characteristics of the event. Adaptations are necessary to create inputs for the models that have been primarily designed for areas with better availability of data. Freely available geospatial information of moderate resolution can often meet the minimum data requirements of hydrological and hydrodynamic models if they are supplemented carefully with limited surveyed/measured information. This thesis also explores the issue of flood mitigation through rainfall-runoff modelling. The purpose of this investigation is to assess the impact of land-use changes at the sub-catchment scale on the overall downstream flood risk. A key component of this study is also quantifying predictive uncertainty in hydrodynamic models based on the Generalised Likelihood Uncertainty Estimation (GLUE) framework. Detailed uncertainty assessment of the model outputs indicates that, in spite of using sparse inputs, the model outputs perform at reasonably low levels of uncertainty both spatially and temporally. These findings have the potential to encourage the flood managers and hydrologists in the developing world to use similar data sets for flood management

Impacts of DEM Type and Resolution on Deep Learning-Based Flood Inundation Mapping

This paper presents a comprehensive study focusing on the influence of DEM type and spatial resolution on the accuracy of flood inundation prediction. The research employs a state-of-the-art deep learning method using a 1D convolutional neural network (CNN). The CNN-based method employs training input data in the form of synthetic hydrographs, along with target data represented by water depth obtained utilizing a 2D hydrodynamic model, LISFLOOD-FP. The performance of the trained CNN models is then evaluated and compared with the observed flood event. This study examines the use of digital surface models (DSMs) and digital terrain models (DTMs) derived from a LIDAR-based 1m DTM, with resolutions ranging from 15 to 30 meters. The proposed methodology is implemented and evaluated in a well-established benchmark location in Carlisle, UK. The paper also discusses the applicability of the methodology to address the challenges encountered in a data-scarce flood-prone region, exemplified by Pakistan. The study found that DTM performs better than DSM at lower resolutions. Using a 30m DTM improved flood depth prediction accuracy by about 21% during the peak stage. Increasing the resolution to 15m increased RMSE and overlap index by at least 50% and 20% across all flood phases. The study demonstrates that while coarser resolution may impact the accuracy of the CNN model, it remains a viable option for rapid flood prediction compared to hydrodynamic modeling approaches

Dynamique des inondations dans le continuum rivière-estuaire-océan littoral du delta du Bengale : synergie de la modélisation hydrodynamique et de la télédétection spatiale

Le delta du Bengale est le plus vaste au monde. Il est formé par la confluence des trois rivières transfrontalières que sont le Gange, le Brahmapoutre et la Meghna. Des inondations massives frappent régulièrement cette région côtière très densément peuplée, située à seulement quelques mètres au-dessus du niveau moyen de la mer. Elles résultent du puissant cycle saisonnier des débits fluviaux, de la marée océanique très ample, et des cyclones tropicaux fréquents. Au cours des cinquante dernières années, les inondations de la partie littorale du delta ont fait plus de 500'000 victimes. La montée du niveau moyen de la mer ne va faire qu'aggraver la vulnérabilité de cette région où le taux de pauvreté est très élevé. Le long du littoral, les estrans sont les zones alternativement inondées à marée haute et découvertes à marée basse. Leur topographie joue un rôle important dans l'hydrodynamique littorale et dans les submersions qui surviennent lors des évènements extrêmes. En mettant en œuvre une synergie entre l'imagerie par télédétection spatiale de la constellation Sentinel-2 et la modélisation numérique de la marée, nous avons cartographié la topographie de l'estran du delta du Bengale sur une superficie de 1134 km2, avec une résolution de 10 m. Les marées, qui sont le facteur dominant de la variabilité du niveau de la mer côtier, sont apparues comme sensibles à la montée du niveau de la mer. Dans une hiérarchie de scénarios de montée du niveau de la mer représentatifs de l'évolution attendue au 21ème siècle, nous avons conclu que l'amplitude de marée devrait augmenter significativement avec la montée du niveau de la mer, à la fois dans le Sud-Ouest et dans le Sud-Est du delta. Au contraire, l'extension graduelle et massive de la superficie des estrans dans la partie centrale du delta devrait induire une nette atténuation de la marée, dans ces scénarios futurs. La marée joue par ailleurs un rôle central dans l'évolution des surcotes cyloniques. Un exercice de prévision du dernier super-cyclone ayant frappé le delta du Bengale avec notre plate-forme de modélisation hydrodynamique couplée marée-surcote-vagues a révélé la nécessité du couplage dynamique entre ces trois composantes de la submersion, et nous avons pu confirmer le rôle-clé de la topographie côtière dans le succès des prévisions numériques. Grâce à une approche ensembliste basée sur la simulation numérique hydrodynamique de plusieurs milliers de cyclones synthétiques, cohérents tant du point de vue de la physique que de la statistique, nous avons pu conclure qu'il y a à l'heure actuelle de l'ordre de 10% de la population côtière du delta, soit trois millions de personnes, résidant dans la zone exposée à la submersion cinquentennale. La compréhension et la quantification des mécanismes de l'inondation exposés dans cette thèse constituent une information pertinente pour contribuer à l'ingénierie des infrastructures côtières, à la gestion du risque, ainsi qu'à l'élaboration de l'agenda de la recherche en hydrodynamique côtière sur le delta du Bengale.The Bengal delta is the largest in the world. It is formed by the confluence of three transboundary rivers - Ganges, Brahmaputra, and Meghna. Flooding induced by large seasonal continental discharge, strong tide, and frequent deadly storm surges, regularly strikes this densely populated (density > 1000 person/km2), low-lying coastal region (<5 m above mean sea level). In the last five decades, coastal flooding took more than half a million lives. Ongoing global sea level rise (SLR) will only further aggravate the vulnerability of this impoverished region. Along the shoreline, intertidal zones are the first landmass that gets flooded, periodically between each high- and low-tide. Their topography plays an important role in the coastal hydrodynamics and associated flooding during extremes. A synergy between remote sensing from Sentinel-2 constellation and tidal numerical modelling allowed us to map an intertidal area of 1134 km2 and its topography at 10 m resolution. Tides, that prominently drive the variability of coastal sea level, are shown to be sensitive to SLR. In future SLR scenarios in line with the 21st century forecasts, we found that the tidal amplitude will significantly increase with SLR over both the south-western and south-eastern parts of the delta. In contrast, the central part of the delta will potentially experience massive free-flooding of river banks, hereby inducing a decay of the tidal amplitude. Tide plays a vital role in the evolution of storm surges also. Hindcast simulation of a recent super cyclone with our coupled tide-surge-wave model reveals the necessity of the coupling between tide, surge and wave modelling, and confirmed the crucial role played by the coastal topography for effective inundation modelling and forecast. With an ensemble forecast of thousands of physically and statistically consistent synthetic cyclones, we could conclude that about 10% of the coastal population of the Bengal delta, amounting to 3 million people, currently lives exposed to the 50-year return period flooding. The understanding and quantification of the inundation mechanisms extended in this study is expected to help with coastal infrastructure engineering, risk zoning, resource allocation and future adaptation to coastal flood across the Bengal delta

Facing the storm:Assessing global storm tide hazards in a changing climate

Coastal flooding is one of the most frequent natural hazards around the globe and can have devastating societal impacts. It is caused by extreme storm tides, which are composed of storm surges and tides, on top of mean sea levels. Due to socio-economic developments in the world’s coastal zones, the impacts of coastal floods have increased in recent decades. In addition, projected changes in the frequency and intensity of storms, as well as sea level rise due to climate change are expected to increase the coastal flood hazard. These trends show that it is crucial to further improve coastal flood hazard assessments to support coastal flood management. A lack of understanding of the influence of tropical cyclones (TCs) on storm tide level return periods (RPs) currently prevails. Available meteorological data does not adequately capture the structure of TCs, and the temporal length of this data is too short to accurately compute RPs because TCs are low-probability events. Existing large scale coastal flood hazard assessments assume an infinite flood duration and do not capture the physical hydrodynamic processes that drive coastal flooding. Furthermore, future changes in the frequency and intensity of TCs and extratropical cyclones (ETCs) are often neglected in coastal flood hazard assessments. As such, the goal of this thesis is to improve global storm tide modelling through the better representation of TC-related extremes and enable dynamic flood mapping in both current and future climates. The research in this thesis contributes to ongoing efforts in the coastal risk community to better understand coastal flood hazards and risks on a global scale. The COAST-RP dataset can help identify hotspot regions most prone to coastal flooding. Such information can then be used to determine where more detailed local-scale coastal flood hazard assessments are most needed. Combining data from COAST-RP with the HGRAPHER method allows us to move away from planar towards more advanced dynamic inundation methods. This will improve the accuracy of the coastal flood hazard maps. Lastly, the developed TC intensity Δ method that is applicable to different kinds of future climate TC datasets opens the door to studying the future intensity of TCs and corresponding storm surges by placing them in a future climate