The world's population living on low-lying deltas is increasingly vulnerable to flooding, whether from intense rainfall, rivers or from hurricane-induced storm surges. High-resolution SRTM and MODIS satellite data along with geo-referenced historical map analysis allows quantification of the extent of low-lying delta areas and the role of humans in contributing to their vulnerability. Thirty-three major deltas collectively include ~26,000 km 2 of area below local mean sea level and ~96,000 km 2 of vulnerable area below 2 m a.s.l. The vulnerable areas may increase by 50% under projected 21st Century eustatic sea level rise, a conservative estimate given the current trends in the reduction in sedimentary deposits forming on the surface of these deltas. Analysis of river sediment load and delta topographical data show that these densely populated, intensively farmed landforms, that often host key economic structures, have been destabilized by human-induced accelerated sediment compaction from water, oil and gas mining, by reduction of incoming sediment from upstream dams and reservoirs, and from floodplain engineering. IntroductionClose to 0.5 billion people live on, or near, world deltas, inclusively in many mega-cities (1, 2). Ten countries (China, India, Bangladesh, Vietnam, Indonesia, Japan, Egypt, USA, Thailand, and the Philippines) account for 73% of the people that live in the world's coastal zone, defined as within 10 m a.s.l. (3). 20 th -century catchment developments and population and economic growth within subsiding deltas have placed these environments and their populations under a growing risk of coastal flooding, wetland loss, shoreline retreat, and loss of infrastructure (4, 5). It is estimated that more than 10 million people per year experience flooding due to storm surges, and most of these people are living on Asian deltas (6). Using new, globally-consistent and highresolution topographic data, three hypotheses are tested: 1) deltas are rapidly sinking, often to below local sea level, 2) the lack of sediment getting to delta floodplains is the main reason so many deltas are sinking, and 3) human activities are largely responsible for the present vulnerability of deltas. For a representative suite of deltas, Shuttle Radar Topography Mission (SRTM) data are applied to evaluate delta topography, in relation to mean sea level. Historical maps are geo-referenced against detailed topographic data to map morphodynamic patterns and quantify how rivers once flowed through deltas. Visible and near-infrared Moderate Resolution Imaging Spectroradiometer (MODIS) satellite images are used to assess flooding in modern deltas and investigate whether such flooding is mainly from river runoff or instead from coastal storm surges, and whether present river suspended load is sufficient to maintain delta plain aggradation and stability.

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A holistic perspective on changing rainfall-driven flood risk is provided for the late 20th and early 21st centuries. Economic losses from floods have greatly increased, principally driven by the expanding exposure of assets at risk. It has not been possible to attribute rain-generated peak streamflow trends to anthropogenic climate change over the past several decades. Projected increases in the frequency and intensity of heavy rainfall, based on climate models, should contribute to increases in precipitation-generated local flooding (e.g. flash flooding and urban flooding). This article assesses the literature included in the IPCC SREX report and new literature published since, and includes an assessment of changes in flood risk in seven of the regions considered in the recent IPCC SREX report-Africa, Asia, Central and South America, Europe, North America, Oceania and Polar regions. Also considering newer publications, this article is consistent with the recent IPCC SREX assessment finding that the impacts of climate change on flood characteristics are highly sensitive to the detailed nature of Le risque d'inondation et les perspectives de changement climatique mondial et régionalRésumé Cet article trace une perspective globale de l'évolution des risques d'inondation d'origine pluviale pour la fin du 20ème et le début du 21ème siècle. Les pertes économiques dues aux inondations ont fortement augmenté, principalement en raison de l'exposition croissante des actifs à risque. Il n'a pas été possible d'attribuer les tendances de débits de pointe au changement climatique d'origine anthropique au cours des dernières décennies. Les augmentations prévues de la fréquence et de l'intensité des précipitations extrêmes, basées sur des modèles climatiques, devraient contribuer à une augmentation des inondations locales (par exemple, des crues éclairs et des inondations en milieu urbain) provoquées par les pluies. Nous avons évalué la littérature incluse dans le rapport SREX du GIEC et celle qui a été publiée depuis, afin d'estimer l'évolution des risques d'inondation dans les sept régions considérées dans le rapport récent du SREX du GIEC, à savoir l'Afrique, l'Asie, l'Amérique centrale et du Sud, l'Europe, l'Amérique du Nord, l'Océanie et les régions polaires. Tenant compte des publications les plus récentes, le présent article rejoint la récente évaluation SREX du GIEC selon laquelle les impacts du changement climatique sur les caractéristiques des crues sont très sensibles aux détails de ces changements, et qu'à l'heure actuelle nous ne pouvons avoir qu'une confiance limitée dans les projections numériques de l'évolution de l'amplitude ou de la fréquence des inondations résultant du changement climatique.

[1] Satellite passive microwave sensors provide global coverage of the Earth's land surface on a near-daily basis without severe interference from cloud cover. Using a strategy first developed for wide-area optical sensors, and in conjunction with even limited ground-based discharge information, such microwave data can be used to estimate river discharge changes, river ice status, and watershed runoff. Water surface area in a river reach increases as flow widens, and any temporally calibrated observation sensitive to changing water area monitors discharge. The sensor spatial resolution is less important than the scene-to-scene calibration and the contrast in upwelling radiance between water and land. We use the Advanced Microwave Scanning Radiometer (AMSR-E) band at 36.5 GHz, descending orbit, horizontal polarization, and the resampled Level-3 daily global data product. The discharge estimator HR is a ratio of calibration-target radiance (expressed as brightness temperature), for a local land parcel unaffected by the river, to measurement-target brightness temperature, for a pixel centered over the river. At midlatitudes, pixel dimensions are approximately 25 km. Because of low emission from water surfaces, HR increases with discharge as in-pixel water area expands. It increases sharply once overbank flow conditions occur. River ice-cover is also detectable. The sensitivity and accuracy of the orbital measurements is tested along U.S. rivers monitored by in situ gaging stations, with favorable results. Other tests demonstrate that for seasonally variable rivers, AMSR-E can provide useful international measurements of daily river discharge even if only fragmentary monthly mean discharge data are available for calibration.Citation: Brakenridge, G. R., S. V. Nghiem, E. Anderson, and R. Mic (2007), Orbital microwave measurement of river discharge and ice status, Water Resour. Res., 43, W04405,

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Floods are among the most catastrophic natural disasters around the globe impacting human lives and infrastructure. Implementation of a flood prediction system can potentially help mitigate flood-induced hazards. Such a system typically requires implementation and calibration of a hydrologic model using in situ observations (i.e., rain and stream gauges). Recently, satellite remote sensing data have emerged as a viable alternative or supplement to in situ observations due to their availability over vast ungauged regions. The focus of this study is to integrate the best available satellite products within a distributed hydrologic model to characterize the spatial extent of flooding and associated hazards over sparsely gauged or ungauged basins. We present a methodology based entirely on satellite remote sensing data to set up and calibrate a hydrologic model, simulate the spatial extent of flooding, and evaluate the probability of detecting inundated areas. A raster-based distributed hydrologic model, Coupled Routing and Excess STorage (CREST), was implemented for the Nzoia basin, a subbasin of Lake Victoria in Africa. Moderate Resolution Imaging Spectroradiometer Terra-based and Advanced Spaceborne Thermal Emission and Reflection Radiometer-based flood inundation maps were produced over the region and used to benchmark the distributed hydrologic model simulations of inundation areas. The analysis showed the value of integrating satellite data such as precipitation, land cover type, topography, and other products along with space-based flood inundation extents as inputs to the distributed hydrologic model. We conclude that the quantification of flooding spatial extent through optical sensors can help to calibrate and evaluate hydrologic models and, hence, potentially improve hydrologic prediction and flood management strategies in ungauged catchments.

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