Gj-P Schumann

An intercomparison of remote sensing river discharge estimation algorithms from measurements of river height, width, and slope

The Surface Water and Ocean Topography (SWOT) satellite mission planned for launch in 2020 will map river elevations and inundated area globally for rivers >100 m wide. In advance of this launch, we here evaluated the possibility of estimating discharge in ungauged rivers using synthetic, daily ‘‘remote sensing’’ measurements derived from hydraulic models corrupted with minimal observational errors. Five discharge algorithms were evaluated, as well as the median of the five, for 19 rivers spanning a range of hydraulic and geomorphic conditions. Reliance upon a priori information, and thus applicability to truly ungauged reaches, varied among algorithms: one algorithm employed only global limits on velocity and depth, while the other algorithms relied on globally available prior estimates of discharge. We found at least one algorithm able to estimate instantaneous discharge to within 35% relative root-mean-squared error (RRMSE) on 14/16 nonbraided rivers despite out-of-bank flows, multichannel planforms, and backwater effects. Moreover, we found RRMSE was often dominated by bias; the median standard deviation of relative residuals across the 16 nonbraided rivers was only 12.5%. SWOT discharge algorithm progress is therefore encouraging, yet future efforts should consider incorporating ancillary data or multialgorithm synergy to improve results.

The direct use of radar satellites for event-specific flood risk mapping

A near-simultaneous satellite acquisition of a flood event on 12 December 2006 on the Dee River in Wales (UK) is used to illustrate the potential to develop standalone space-borne flood risk mapping techniques. Both the ERS-2 and ENVISAT satellites recorded the event close to flood peak and only 28 min apart. This unique opportunity enables the creation of a very rare but extremely useful observed data set for flood inundation studies. This letter illustrates how this unique set of space-borne radar images can be used for rapid flood risk mapping. An event-specific weighted hazard map was generated based on plausible flood area observations from an aggregation of widely applied image-processing techniques. This map can be further augmented to an event-specific fuzzy flood risk map by fusing the multi-algorithm ensemble map with vulnerability-weighted land cover vector data in a geographic information system (GIS) environment. The technique presented is fairly flexible and leads to a potentially useful data set for direct use in flood management.

Flood risk and uncertainty

Introduction Extreme floods are among the most destructive forces of nature. Flooding accounts for a significant proportion of the total number of reported natural disasters occurring in the world (Figure 7.1a) and over the last 30 years this proportion has been increasing (Figure 7.1b). Reasons for this trend may not be clear; for each hazard there is a need to quantify whether this is an increase in the hazard itself, an increase in exposure to the hazard internationally or a change in the reporting of what constitutes a natural disaster. Internationally, the costs and scale of flooding are enormous but differ depending on the types of impact that are analysed and the databases used. Globally in 2007 it was estimated that annually 520 million people are affected by floods and that the death toll is approximately 25000 people in any one year. Jonkman (2005) found for a study using data from 1974 to 2003 (from data maintained by the Centre for Research on the Epidemiology of Disasters in Brussels) that floods are the most significant natural disaster type in terms of the number of people affected – some 51% of the total of that period of approximately five billion people affected by natural disaster (droughts are second with 36%, and earthquakes third at 2%). However, in terms of overall estimated deaths flooding accounts for 10% of the approximately two million reported deaths associated with natural disasters over the 1974–2003 period (droughts 44% and earthquakes 27%). In monetary terms an assessment by Munich RE for the period 1980–2010 determined that at 2010 prices the losses totalled US

Near real-time flood wave approximation on large rivers from space: Application to the River Po, Italy

3000 billion from ~19400 events with 2.275 million fatalities. Of these, hydrological catastrophes (flooding and mass movement, i.e. landslips and debris flow in this case) accounted for 24% of these monetary losses, from 35% of the total events, and 11% of the fatalities. Other categories of natural disasters included in these totals were geophysical, meteorological and climatological (NatCatSERVICE, 2011).