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Uncertainty Models for Estimates of Physical Characteristics of River Segments Over Large Areas
Authors:Nicolas Lamouroux  Hervé Pella  Ton H Snelder  Eric Sauquet  Jérome Lejot  Ude Shankar
Institution:1. Irstea, , Villeurbanne, F‐69626 France;2. Aqualinc Research, , Christchurch, New Zealand;3. Université Lyon 2, , Lyon, France;4. National Institute for Water and Atmospheric Research, , Christchurch, New Zealand
Abstract:Spatially comprehensive estimates of the physical characteristics of river segments over large areas are required in many large‐scale analyses of river systems and for the management of multiple basins. Remote sensing and modeling are often used to estimate river characteristics over large areas, but the uncertainties associated with these estimates and their dependence on the physical characteristics of the segments and their catchments are seldom quantified. Using test data with varying degrees of independence, we derived analytical models of the uncertainty associated with estimates of upstream catchment area (CA), segment slope, and mean annual discharge for all river segments of a digital representation of the hydrographic network of France. Although there were strong relationships between our test data and estimates at the scale of France, there were also large relative local uncertainties, which varied with the physical characteristics of the segments and their catchments. Discharge and CA were relatively uncertain where discharge was low and catchments were small. Discharge uncertainty also increased in catchments with large rainfall events and low minimum temperature. The uncertainty of segment slope was strongly related to segment length. Our uncertainty models were consistent across large regions of France, suggesting some degree of generality. Their analytical formulation should facilitate their use in large‐scale ecological studies and simulation models.
Keywords:watersheds  surface water hydrology  river networks     DEM        GIS     error modeling  regionalization
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