Evaluating a new LISFLOOD-FP formulation with data from the summer 2007 floods in Tewkesbury, UK

Two-dimensional flood inundation modelling is a widely used tool to aid flood risk management. In urban areas, where asset value and population density are greatest, the model spatial resolution required to represent flows through a typical street network (i.e. < 10m) often results in impractical computational cost at the whole city scale. Explicit diffusive storage cell models become very inefficient at such high resolutions, relative to shallow water models, because the stable time step in such schemes scales as a quadratic of resolution. This paper presents the calibration and evaluation of a recently developed new formulation of the LISFLOOD-FP model, where stability is controlled by the Courant–Freidrichs–Levy condition for the shallow water equations, such that, the stable time step instead scales linearly with resolution. The case study used is based on observations during the summer 2007 floods in Tewkesbury, UK. Aerial photography is available for model evaluation on three separate days from the 24th to the 31st of July. The model covered a 3.6 km by 2 km domain and was calibrated using gauge data from high flows during the previous month. The new formulation was benchmarked against the original version of the model at 20 m and 40 m resolutions, demonstrating equally accurate performance given the available validation data but at 67x faster computation time. The July event was then simulated at the 2 m resolution of the available airborne LiDAR DEM. This resulted in a significantly more accurate simulation of the drying dynamics compared to that simulated by the coarse resolution models, although estimates of peak inundation depth were similar.

Implicit synthesis

In this reply to Neal and Hesketh and to the commentators, we argue that implicit knowledge is partly abstract and can be usefully defined by the criteria of both metaknowledge and intentional control. We suggest that the pattern of dissociations supports a claim of separate implicit and explicit learning modes. According to our characterization, implicit learning leads to knowledge that is not automatically represented as knowledge by the learning process; instead, the presence of knowledge has to be inferred by the subject (partial explicitation) if metaknowledge is gained at all. During explicit learning, knowledge is automatically labeled as knowledge by the learning process, so that metaknowledge comes immediately and to the fullest extent. Finally, we suggest that implicit knowledge may to some degree apply regardless of intention.

Ecological and life-history traits predict bee species responses to environmental disturbances

The ability to predict the responses of ecological communities and individual species to human-induced environmental change remains a key issue for ecologists and conservation managers alike. Responses are often variable among species within groups making general predictions difficult. One option is to include ecological trait information that might help to disentangle patterns of response and also provide greater understanding of how particular traits link whole clades to their environment. Although this ‘‘trait-guild” approach has been used for single disturbances, the importance of particular traits on general responses to multiple disturbances has not been explored. We used a mixed model analysis of 19 data sets from throughout the world to test the effect of ecological and life-history traits on the responses of bee species to different types of anthropogenic environmental change. These changes included habitat loss, fragmentation, agricultural intensification, pesticides and fire. Individual traits significantly affected bee species responses to different disturbances and several traits were broadly predictive among multiple disturbances. The location of nests – above vs. below ground – significantly affected response to habitat loss, agricultural intensification, tillage regime (within agriculture) and fire. Species that nested above ground were on average more negatively affected by isolation from natural habitat and intensive agricultural land use than were species nesting below ground. In contrast below-ground-nesting species were more negatively affected by tilling than were above-ground nesters. The response of different nesting guilds to fire depended on the time since the burn. Social bee species were more strongly affected by isolation from natural habitat and pesticides than were solitary bee species. Surprisingly, body size did not consistently affect species responses, despite its importance in determining many aspects of individuals’ interaction with their environment. Although synergistic interactions among traits remain to be explored, individual traits can be useful in predicting and understanding responses of related species to global change.

Estimating discharge from inundation imagery

Remote sensing from space-borne platforms is often seen as an appealing method of monitoring components of the hydrological cycle, including river discharge, due to its spatial coverage. However, data from these platforms is often less than ideal because the geophysical properties of interest are rarely measured directly and the measurements that are taken can be subject to significant errors. This study assimilated water levels derived from a TerraSAR-X synthetic aperture radar image and digital aerial photography with simulations from a two dimensional hydraulic model to estimate discharge, inundation extent, depths and velocities at the confluence of the rivers Severn and Avon, UK. An ensemble Kalman filter was used to assimilate spot heights water levels derived by intersecting shorelines from the imagery with a digital elevation model. Discharge was estimated from the ensemble of simulations using state augmentation and then compared with gauge data. Assimilating the real data reduced the error between analyzed mean water levels and levels from three gauging stations to less than 0.3 m, which is less than typically found in post event water marks data from the field at these scales. Measurement bias was evident, but the method still provided a means of improving estimates of discharge for high flows where gauge data are unavailable or of poor quality. Posterior estimates of discharge had standard deviations between 63.3 m3s-1 and 52.7 m3s-1, which were below 15% of the gauged flows along the reach. Therefore, assuming a roughness uncertainty of 0.03-0.05 and no model structural errors discharge could be estimated by the EnKF with accuracy similar to that arguably expected from gauging stations during flood events. Quality control prior to assimilation, where measurements were rejected for being in areas of high topographic slope or close to tall vegetation and trees, was found to be essential. The study demonstrates the potential, but also the significant limitations of currently available imagery to reduce discharge uncertainty in un-gauged or poorly gauged basins when combined with model simulations in a data assimilation framework.

Sewage effluent clean-up reduces phosphorus but not phytoplankton in lowland chalk stream (River Kennet, UK) impacted by water mixing from adjacent canal

Information is provided on phosphorus in the River Kennet and the adjacent Kennet and Avon Canal in southern England to assess their interactions and the changes following phosphorus reductions in sewage treatment work (STW) effluent inputs. A step reduction in soluble reactive phosphorus (SRP) concentration within the effluent (5 to 13 fold) was observed from several STWs discharging to the river in the mid-2000s. This translated to over halving of SRP concentrations within the lower Kennet. Lower Kennet SRP concentrations change from being highest under base-flow to highest under storm-flow conditions. This represented a major shift from direct effluent inputs to a within-catchment source dominated system characteristic of the upper part to the catchment. Average SRP concentrations in the lower Kennet reduced over time towards the target for good water quality. Critically, there was no corresponding reduction in chlorophyll-a concentration, the waters remaining eutrophic when set against standards for lakes. Following the up gradient input of the main water and SRP source (Wilton Water), SRP concentrations in the canal reduced down gradient to below detection limits at times near its junction with the Kennet downstream. However, chlorophyll concentrations in the canal were in an order of magnitude higher than in the river. This probably resulted from long water residence times and higher temperatures promoting progressive algal and suspended sediment generations that consumed SRP. The canal acted as a point source for sediment, algae and total phosphorus to the river especially during the summer months when boat traffic disturbed the canal's bottom sediments and the locks were being regularly opened. The short-term dynamics of this transfer was complex. For the canal and the supply source at Wilton Water, conditions remained hypertrophic when set against standards for lakes even when SRP concentrations were extremely low.

Near real-time flood detection in urban and rural areas using high resolution Synthetic Aperture Radar images

A near real-time flood detection algorithm giving a synoptic overview of the extent of flooding in both urban and rural areas, and capable of working during night-time and day-time even if cloud was present, could be a useful tool for operational flood relief management. The paper describes an automatic algorithm using high resolution Synthetic Aperture Radar (SAR) satellite data that builds on existing approaches, including the use of image segmentation techniques prior to object classification to cope with the very large number of pixels in these scenes. Flood detection in urban areas is guided by the flood extent derived in adjacent rural areas. The algorithm assumes that high resolution topographic height data are available for at least the urban areas of the scene, in order that a SAR simulator may be used to estimate areas of radar shadow and layover. The algorithm proved capable of detecting flooding in rural areas using TerraSAR-X with good accuracy, and in urban areas with reasonable accuracy. The accuracy was reduced in urban areas partly because of TerraSAR-X’s restricted visibility of the ground surface due to radar shadow and layover.

A near real-time algorithm for flood detection in urban and rural areas using high resolution Synthetic Aperture Radar images

A near real-time flood detection algorithm giving a synoptic overview of the extent of flooding in both urban and rural areas, and capable of working during night-time and day-time even if cloud was present, could be a useful tool for operational flood relief management and flood forecasting. The paper describes an automatic algorithm using high resolution Synthetic Aperture Radar (SAR) satellite data that assumes that high resolution topographic height data are available for at least the urban areas of the scene, in order that a SAR simulator may be used to estimate areas of radar shadow and layover. The algorithm proved capable of detecting flooding in rural areas using TerraSAR-X with good accuracy, and in urban areas with reasonable accuracy.

Evaluating a new LISFLOOD-FP formulation with data from the summer 2007 floods in Tewkesbury, UK

Two-dimensional flood inundation modelling is a widely used tool to aid flood risk management. In urban areas, the model spatial resolution required to represent flows through a typical street network often results in an impractical computational cost at the city scale. This paper presents the calibration and evaluation of a recently developed formulation of the LISFLOOD-FP model, which is more computationally efficient at these resolutions. Aerial photography was available for model evaluation on 3 days from the 24 to the 31 of July. The new formulation was benchmarked against the original version of the model at 20 and 40 m resolutions, demonstrating equally accurate simulation, given the evaluation data but at a 67 times faster computation time. The July event was then simulated at the 2 m resolution of the available airborne LiDAR DEM. This resulted in more accurate simulation of the floodplain drying dynamics compared with the coarse resolution models, although maximum inundation levels were simulated equally well at all resolutions tested.

Improved predictability of the troposphere using stratospheric final warmings

The final warming of the stratospheric polar vortex at the end of northern hemisphere winter is examined in ECMWF ERA-Interim reanalysis data and an ensemble of chemistry climate models, using 20 years of data from each. In some years the final warming is found to occur first in the mid-stratosphere, and in others to occur first in the upper stratosphere. The strength of the winter stratospheric polar vortex, refraction of planetary waves, and the altitudes at which the planetary waves break in the northern extratropics lead to this difference in the vertical profile of the final warming. Years in which the final warming occurs first in the mid-stratosphere show, on average, a more negative NAO pattern in April mean sea level pressure than years in which the warming occurs first in the upper stratosphere. Thus, in the northern hemisphere, additional predictive skill of tropospheric climate in April can be gained from a knowledge of the vertical profile of the stratospheric final warming.