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Precipitation events cause disruption around the world and will be altered by climate change. However, different climate modeling approaches can result in different future precipitation projections. The corresponding ''method uncertainty'' is rarely explicitly calculated in climate impact studies and major reports but can substantially change estimated precipitation changes. A comparison across five commonly used modeling activities shows that, for changes in mean precipitation, less than half of the regions analyzed had significant changes between the present climate and 1.58C global warming for the majority of modeling activities. This increases to just over half of the regions for changes between present climate and 28C global warming. There is much higher confidence in changes in maximum 1-day precipitation than in mean precipitation, indicating the robust influence of thermodynamics in the climate change effect on extremes. We also find that none of the modeling activities captures the full range of estimates from the other methods in all regions. Our results serve as an uncertainty map to help interpret which regions require a multimethod approach. Our analysis highlights the risk of overreliance on any single modeling activity and the need for confidence statements in major synthesis reports to reflect this method uncertainty. Considering multiple sources of climate projections should reduce the risks of policymakers being unprepared for impacts of warmer climates relative to using single-method projections to make decisions.

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 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.

Choosing a suitable set of cross sections for the representation of the natural geometry of a river is important for the efficiency of one-dimensional (1D) hydraulic models, but only few guidelines are available for the selection of the most suitable distance between cross sections, depending on the hydraulic problem at hand. This issue is investigated by examining models of a ∼55km reach of the River Po, Italy, and a ∼16km reach of the River Severn, United Kingdom, for both of which high quality laser scanning altimetry are available. The high-resolution digital terrain models of the two river reaches enabled the construction of a series of hypothetical topographical ground surveys with different spacing between cross sections, which could be used as input to a standard 1D model (UNET). Both historical and synthetic flood events for the two river reaches were simulated, and the results were then analyzed to quantify the accuracy associated with each resolution and to assess how survey resolution impacts the performance of standard 1D models. The study results agree with the available suggestions in the literature and provide useful guidelines for 1D hydrodynamic modeling.

This paper presents a methodology to calibrate hydraulic models using possibility of inundation maps derived from satellite imagery. The study was performed on a river reach of the Lower Dee, UK, where a coarse resolution image (ENVISAT ASAR) and high resolution satellite image (ERS-2 SAR) were acquired at the same time during the December 2006 flood event. Ten different flood extent maps were derived from the two flood images by using five different procedures to process these data. These flood extent maps were used to perform a sensitivity analysis of a simple raster-based inundation model (LISFLOOD-FP). The sensitivity analysis enabled us to investigate the capability of the two different resolution images to calibrate the friction parameters of the flood inundation model. The analysis showed that the optimal parameters of the model depend on the type of satellite image used to evaluate the model as well as on the particular procedure used to derive the flood extent map. Finally, the study developed a novel methodology to calibrate flood inundation models by comparing the model results to a possibility of inundation map obtained by combining the ten different flood extent maps.