Abstract
River deltas belong to the most densely settled places on earth. Although they only account for 5% of the global land surface, over 550 million people live in deltas. These preferred livelihood locations, which feature flat terrain, fertile alluvial soils, access to fluvial and marine resources, a rich wetland biodiversity and other advantages are, however, threatened by numerous internal and external processes. Socio-economic development, urbanization, climate change induced sea level rise, as well as flood pulse changes due to upstream water diversion all lead to changes in these highly dynamic systems. A thorough understanding of a river delta’s general setting and intra-annual as well as long-term dynamic is therefore crucial for an informed management of natural resources. Here, remote sensing can play a key role in analyzing and monitoring these vast areas at a global scale. The goal of this study is to demonstrate the potential of intra-annual time series analyses at dense temporal, but coarse spatial resolution for inundation characterization in five river deltas located in four different countries. Based on 250 m MODIS reflectance data we analyze inundation dynamics in four densely populated Asian river deltas—namely the Yellow River Delta (China), the Mekong Delta (Vietnam), the Irrawaddy Delta (Myanmar), and the Ganges-Brahmaputra (Bangladesh, India)—as well as one very contrasting delta: the nearly uninhabited polar Mackenzie Delta Region in northwestern Canada for the complete time span of one year (2013). A complex processing chain of water surface derivation on a daily basis allows the generation of intra-annual time series, which indicate inundation duration in each of the deltas. Our analyses depict distinct inundation patterns within each of the deltas, which can be attributed to processes such as overland flooding, irrigation agriculture, aquaculture, or snowmelt and thermokarst processes. Clear differences between mid-latitude, subtropical, and polar deltas are illustrated, and the advantages and limitations of the approach for inundation derivation are discussed.
Highlights
Background and Scope of This PaperIn recent decades numerous studies have dealt with the derivation of inland water surfaces from remote sensing data [1]
The information product depicting intra-annual inundation patterns is a product ranging from 0 to 365 days, overlain on the gap-filled shaded digital elevation model, DEM, derived based on data of the Shuttle Radar Topography Mission, SRTM, and auxiliary DEM data
Whereas synthetic aperture radar (SAR) data of higher spatial resolution is and will remain the preferred choice for most studies focusing on flood and inundation detection at high accuracy [15,16], coarse spatial resolution but temporally dense time series of inundation information derived from optical sensors allow for the revelation of intra-annual dynamics and overall inundation patterns for very large areas
Summary
In recent decades numerous studies have dealt with the derivation of inland water surfaces from remote sensing data [1]. Whereas the wording “water body” derivation is usually used when dealing with inland lakes or ponds, or any permanent water body ( reservoirs, etc.), the term “flood” mapping or monitoring is usually used when natural hazard events are being observed. Earth observation based flood mapping aims at the delineation of affected areas that are not usually water covered under average conditions [10], and at damage assessment during flood situations along major rivers, after storm surges and catastrophic events such as tsunamis [11]. The term “inundation analysis” or “inundation mapping” is usually used in regions where water surfaces exhibit high spatio-temporal dynamics without a catastrophic or destructive character. Inundation analyses are performed for the world’s untamed river ecosystems, major wetlands, and inland as well as coastal river deltas [12,13,14,15,16]
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