Notaro, V., C.M. Fontanazza, G. Freni, and V. Puleo, 2013: “Impact of rainfall data resolution in time and space on the urban flooding evaluation.” Water Science and Technology, v. 68, pp. 1984-1993, doi: 10.2166/wst.2013.435.
Climate change and modification of the urban environment increase the frequency and the negative effects of flooding, increasing the interest of researchers and practitioners in this topic. Usually, flood frequency analysis in urban areas is indirectly carried out by adopting advanced hydraulic models to simulate long historical rainfall series or design storms. However, their results are affected by a level of uncertainty which has been extensively investigated in recent years. A major source of uncertainty inherent to hydraulic model results is linked to the imperfect knowledge of the rainfall input data both in time and space. Several studies show that hydrological modelling in urban areas requires rainfall data with fine resolution in time and space. The present paper analyses the effect of rainfall knowledge on urban flood modelling results. A mathematical model of urban flooding propagation was applied to a real case study and the maximum efficiency conditions for the model and the uncertainty affecting the results were evaluated by means of generalised likelihood uncertainty estimation (GLUE) analysis. The added value provided by the adoption of finer temporal and spatial resolution of the rainfall was assessed.
Dankers, R., N.W. Arnell, D.B. Clark, P.D. Falloon, B.M. Fekete, S.N. Gosling, J. Heinke, H. Kim, Y. Masaki, Y. Satoh, T. Stacke, Y. Wada, and D. Wisser, 2013: “First look at changes in flood hazard in the Inter-Sectoral Impact Model Intercomparison Project ensemble.” Proceedings of the National Academy of Sciences, doi: 10.1073/pnas.1302078110.
Climate change due to anthropogenic greenhouse gas emissions is expected to increase the frequency and intensity of precipitation events, which is likely to affect the probability of flooding into the future. In this paper we use river flow simulations from nine global hydrology and land surface models to explore uncertainties in the potential impacts of climate change on flood hazard at global scale. As an indicator of flood hazard we looked at changes in the 30-y return level of 5-d average peak flows under representative concentration pathway RCP8.5 at the end of this century. Not everywhere does climate change result in an increase in flood hazard: decreases in the magnitude and frequency of the 30-y return level of river flow occur at roughly one-third (20–45%) of the global land grid points, particularly in areas where the hydrograph is dominated by the snowmelt flood peak in spring. In most model experiments, however, an increase in flooding frequency was found in more than half of the grid points. The current 30-y flood peak is projected to occur in more than 1 in 5 y across 5–30% of land grid points. The large-scale patterns of change are remarkably consistent among impact models and even the driving climate models, but at local scale and in individual river basins there can be disagreement even on the sign of change, indicating large modeling uncertainty which needs to be taken into account in local adaptation studies.
Ward, P.J., B. Jongman, F.S. Weiland, A. Bouwman, R. van Beek, M.F.P. Bierkens, W. Ligtvoet, and H.C. Winsemius, 2013: “Assessing flood risk at the global scale: Model setup, results, and sensitivity.” Environmental Research Letters, v. 8, paper no. 044019, doi: 10.1088/1748-9326/8/4/044019.
Globally, economic losses from flooding exceeded $19 billion in 2012, and are rising rapidly. Hence, there is an increasing need for global-scale flood risk assessments, also within the context of integrated global assessments. We have developed and validated a model cascade for producing global flood risk maps, based on numerous flood return-periods. Validation results indicate that the model simulates interannual fluctuations in flood impacts well. The cascade involves: hydrological and hydraulic modelling; extreme value statistics; inundation modelling; flood impact modelling; and estimating annual expected impacts. The initial results estimate global impacts for several indicators, for example annual expected exposed population (169 million); and annual expected exposed GDP ($1383 billion). These results are relatively insensitive to the extreme value distribution employed to estimate low frequency flood volumes. However, they are extremely sensitive to the assumed flood protection standard; developing a database of such standards should be a research priority. Also, results are sensitive to the use of two different climate forcing datasets. The impact model can easily accommodate new, user-defined, impact indicators. We envisage several applications, for example: identifying risk hotspots; calculating macro-scale risk for the insurance industry and large companies; and assessing potential benefits (and costs) of adaptation measures.
Hally, A., E. Richard, S. Fresnay, and D. Lambert, 2013: “Ensemble simulations with perturbed physical parameterizations: Pre-HyMeX case studies.” Quarterly Journal of the Royal Meteorological Society, doi: 10.1002/qj.2257.
Heavy precipitation events (HPEs) affect the southeastern area of France frequently during the months of September–November. Very high amounts of rain can fall during these events, with the ensuing flash floods causing widespread damage. The cases of 6 September 2010 and 1–4 November 2011 represent the different large-scale conditions under which these episodes can occur. These HPEs are forecast with differing levels of skill by the Méso-NH model at 2.5 km resolution. The case of 6 September 2010 is used to test different methods of addressing cloud physics parameterization uncertainties. Three ensembles are constructed, where the warm-process microphysical time tendencies are perturbed by different methods. Results are compared by examining the spatio-temporal distribution of the precipitation field as well as looking at ensemble statistics. The ensemble methodology that induces the most dispersion in the rainfall field is deemed the most suitable. This method is then used to examine the sensitivity of four cases from November 2011 to errors in the microphysical and turbulent parameterizations. It appears that the sensitivity to microphysical perturbations varies according to the model skill for the HPE. Events where the model skill is high (low) show low (moderate) sensitivity. These cases show a stronger sensitivity to perturbations performed upon the turbulent tendencies, while perturbing the microphysical and turbulent tendencies together produces even greater dispersion. The results show the importance and usefulness of ensembles with perturbed physical parameterizations in the forecasting of HPEs.
Dettinger, M.D., 2013: “Atmospheric rivers as drought busters on the U.S. west coast.” Journal of Hydrometeorology, v. 14, pp. 1721–1732, doi: 10.1175/JHM-D-13-02.1.
Atmospheric rivers (ARs) have, in recent years, been recognized as the cause of the large majority of major floods in rivers all along the U.S. West Coast and as the source of 30%–50% of all precipitation in the same region. The present study surveys the frequency with which ARs have played a critical role as a common cause of the end of droughts on the West Coast. This question was based on the observation that, in most cases, droughts end abruptly as a result of the arrival of an especially wet month or, more exactly, a few very large storms. This observation is documented using both Palmer Drought Severity Index and 6-month Standardized Precipitation Index measures of drought occurrence for climate divisions across the conterminous United States from 1895 to 2010. When the individual storm sequences that contributed most to the wet months that broke historical West Coast droughts from 1950 to 2010 were evaluated, 33%–74% of droughts were broken by the arrival of landfalling AR storms. In the Pacific Northwest, 60%–74% of all persistent drought endings have been brought about by the arrival of AR storms. In California, about 33%–40% of all persistent drought endings have been brought about by landfalling AR storms, with more localized low pressure systems responsible for many of the remaining drought breaks.
Tani, M., 2013: “A paradigm shift in stormflow predictions for active tectonic regions with large-magnitude storms: generalisation of catchment observations by hydraulic sensitivity analysis and insight into soil-layer evolution.” Hydrology and Earth System Sciences, v. 17, pp. 4453-4470, doi: 10.5194/hess-17-4453-2013.
In active tectonic regions with large-magnitude storms, it is still difficult to predict stormflow responses by distributed runoff models from the catchment properties without a parameter calibration using observational data. This paper represents an attempt to address the problem. A review of observational studies showed that the stormflow generation mechanism was heterogeneous and complex, but stormflow responses there were simply simulated by a single tank with a drainage hole when the stormflow-contribution area was spatially invariable due to the sufficient amount of rainfall supply. These results suggested such a quick inflow/outflow waveform transmission was derived from the creation of a hydraulic continuum under a quasi-steady state. General conditions necessary for the continuum creation were theoretically examined by a sensitivity analysis for a sloping soil layer. A new similarity framework using the Richards equation was developed for specifying the sensitivities of waveform transmission to topographic and soil properties. The sensitivity analysis showed that saturation-excess overland flow was generally produced from a soil layer without any macropore effect, whereas the transmission was derived mainly from the vertical unsaturated flow instead of the downslope flow in a soil layer with a large drainage capacity originated from the macropore effect. Both were possible for the quick transmission, but a discussion on the soil-layer evolution process suggested that an inhibition of the overland flow due to a large drainage capacity played a key role, because a confinement of the water flow within the soil layer might be needed for the evolution against strong erosional forces in the geographical regions. The long history of its evolution may mediate a relationship between simple stormflow responses and complex catchment properties. As a result, an insight into this evolution process and an inductive evaluation of the dependences on catchment properties by comparative hydrology are highly encouraged to predict stormflow responses by distributed runoff models.
Villarini, G., and J.A. Smith, 2013: “Flooding in Texas: Examination of temporal changes and impacts of tropical cyclones.” Journal of the American Water Resources Association, v. 49, pp. 825-837, doi: 10.1111/jawr.12042.
Annual maximum peak discharge measurements from 62 stations with a record of at least 70 years are used to assess extreme flooding in Texas at the regional scale. This work focuses on examination of the validity of the stationarity assumption and on the impact of tropical cyclones (TCs) on the upper tail of the flood peak distribution. We assess the validity of the stationarity assumption by testing the records for abrupt and gradual changes. The presence of abrupt changes in the first two moments of the flood peak distribution is assessed using the Lombard test. We use the Mann-Kendall test to examine the presence of monotonic trends. Results indicate that violations of the stationarity assumption are most commonly caused by abrupt changes, which are often associated with river regulation. We fit the time series of stationary flood records with the generalized extreme value distribution to investigate whether TCs control the upper tail of the flood peak distribution. Our results indicate that TCs play a diminished role in shaping the upper tail of the flood peak distribution compared with areas of the eastern United States subject to frequent TCs.
Ilorme, F., and V.W. Griffis, 2013: “A novel procedure for delineation of hydrologically homogeneous regions and the classification of ungauged sites for design flood estimation.” Journal of Hydrology, v. 492, pp. 151-162, doi: 10.1016/j.jhydrol.2013.03.045.
Regional flood frequency techniques are widely used to estimate flood quantiles when flow data is unavailable for the basin under study or the record length is insufficient for reliable analyses. Data from nearby gauged sites are pooled to compensate for the lack of at-site data. This requires the delineation of hydrologically homogeneous regions in which the flood regime is sufficiently similar to allow the spatial transfer of information. It is generally accepted that hydrologic similarity results from similarity among basins’ physiographic characteristics, and thus these characteristics can be used to delineate regions and classify ungauged sites. However, as currently practiced, the delineation is highly subjective and dependent on the similarity measures and classification techniques employed. Herein, a novel procedure for region delineation is proposed and evaluated using data for sites across the Southeastern United States. Key components of this procedure are a new statistical metric to identify physically discordant sites and a new methodology to identify the physical attributes that are the most indicative of extreme hydrologic response. The novel approach for region delineation is shown to produce regions which are more homogeneous and more efficient for quantile estimation at ungauged sites than those delineated using alternative physically-based procedures typically employed in practice. In addition, the identified physical attributes can be used to infer the flood regime and estimate quantiles at sites outside the extent of the area used for model development.
Schumann, G.J.-P., J.C. Neal, N. Voisin, K.M. Andreadis, F. Pappenberger, N. Phanthuwongpakdee, A.C. Hall, and P.D. Bates, 2013: “A first large scale flood inundation forecasting model.” Water Resources Research, v. 49, doi: 10.1002/wrcr.20521.
At present continental to global scale flood forecasting predicts at a point discharge, with little attention to detail and accuracy of local scale inundation predictions. Yet, inundation variables are of interest and all flood impacts are inherently local in nature. This paper proposes a large-scale flood inundation ensemble forecasting model that uses best available data and modeling approaches in data scarce areas. The model was built for the Lower Zambezi River to demonstrate current flood inundation forecasting capabilities in large data-scarce regions. ECMWF ensemble forecast (ENS) data were used to force the VIC (Variable Infiltration Capacity) hydrologic model, which simulated and routed daily flows to the input boundary locations of a 2-D hydrodynamic model. Efficient hydrodynamic modeling over large areas still requires model grid resolutions that are typically larger than the width of channels that play a key role in flood wave propagation. We therefore employed a novel subgrid channel scheme to describe the river network in detail while representing the floodplain at an appropriate scale. The modeling system was calibrated using channel water levels from satellite laser altimetry and then applied to predict the February 2007 Mozambique floods. Model evaluation showed that simulated flood edge cells were within a distance of between one and two model resolutions compared to an observed flood edge and inundation area agreement was on average 86%. Our study highlights that physically plausible parameter values and satisfactory performance can be achieved at spatial scales ranging from tens to several hundreds of thousands of km2 and at model grid resolutions up to several km2.
Trigg, M.A., K. Michaelides, J.C. Neal, and P.D. Bates, 2013: “Surface water connectivity dynamics of a large scale extreme flood.” Journal of Hydrology, doi: 10.1016/j.jhydrol.2013.09.035.
During flood inundation, river water passes from the main channel into the floodplain through floodplain channels and diffusive overbank flow. This flood water is then distributed within the floodplain depending upon internal connections, barriers and storage, and finally returns back to the river through drainage connections. This surface water connectivity can be complex and is important to many aspects of floodplain functioning, including ecology, sediment movement and flood risk. However, there is currently no accepted way of quantifying this connectivity objectively. We quantify surface water connectivity geostatistically as an objectively measurable characteristic of an observed flood event using a time series of MODIS (Moderate Resolution Imaging Spectroradiometer) surface water product for an extreme large scale flood event (11,000 km2 flooded area and 6 month duration) during 2011 in Bangkok, Thailand. We develop and apply a new gap filling method that better preserves the dynamic information of the event than simple aggregation methods. Comparison of MODIS results with the higher resolution Earth Observer 1 shows fundamental differences in the resolved connectivity with scale despite similar flooded area. The effect of the passage of the flood wave is directly observable in the river reach, as out-of-bank flooding progresses and increases connectivity along the river during rising water. Around peak flow, there is an increase in connectivity of the floodplain adjacent to the river as low lying areas fill. A step increase in connectivity is correlated with a major levee breach. During recession there is a rapid reduction in along river connectivity in the first week after the peak. This rapid reduction contrasted with a slow decrease in the floodplain connectivity as flooded depressions gradually drained reducing depth, while flood extent remained static for long periods. The connectivity analysis of the threshold in floodplain draining indicates that although spatial flood extent changes are small at this time, there is a reorganisation of the internal surface water connectivity within the flooded area. Thus through this measure of connectivity, we can see a clear structure to the event progression with new insights into flood dynamics that were not anticipated a priori.