•Backcasting storm runoff response using novel method for generating historical LUC.•Increased peak flow and reduced response time following peri-urban development.•Attribution of flashy response ...using impervious cover plus storm drainage.•Increased impervious cover has greater impact on rural peak flows than urban.•Drainage more important determinant of storm response than land use type.
This paper investigates changes in storm runoff resulting from the transformation of previously rural landscapes into peri-urban areas. Two adjacent catchments (∼5km2) located within the town of Swindon in the United Kingdom were monitored during 2011 and 2012 providing continuous records of rainfall, runoff and actual evaporation. One catchment is highly urbanized and the other is a recently developed peri-urban area containing two distinct areas of drainage: one with mixed natural and storm drainage pathways, the other entirely storm drainage. Comparison of observed storm hydrographs showed that the degree of area serviced by storm drainage was a stronger determinant of storm runoff response than either impervious area or development type and that little distinction in hydrological response exists between urban and peri-urban developments of similar impervious cover when no significant hydraulic alteration is present. Historical levels of urbanization and impervious cover were mapped from the 1960s to the 2010s based on digitized historical topographic maps and were combined with a hydrological model to enable backcasting of the present day storm runoff response to that of the catchments in their earlier states. Results from the peri-urban catchment showed an increase in impervious cover from 11% in the 1960s to 44% in 2010s, and introduction of a large-scale storm drainage system in the early 2000s, was accompanied by a 50% reduction in the Muskingum routing parameter k, reducing the characteristic flood duration by over 50% while increasing peak flow by over 400%. Comparisons with changes in storm runoff response in the more urban area suggest that the relative increase in peak flows and reduction in flood duration and response time of a catchment is greatest at low levels of urbanization and that the introduction of storm water conveyance systems significantly increases the flashiness of storm runoff above that attributed to impervious area alone.
This study demonstrates that careful consideration is required when using impervious cover data within hydrological models and when designing flood mitigation measures, particularly in peri-urban areas where a widespread loss in pervious surfaces and alteration of drainage pathways can significantly alter the storm runoff response. Recommendations include utilizing more refined urban land use typologies that can better represent physical alteration of hydrological pathways.
•A novel ensemble SVM and WoE method was used for flood susceptibility mapping.•Four SVM kernel types: LN, PL, RBF, and SIG were used in the ensemble model.•Cross validation was used to measure the ...most accurate SVM parameters.•The derived ensemble methods were compared with individual WoE and SVM methods.•The proposed ensemble method could improve flood modeling by 29%.
Flood is one of the most devastating natural disasters that occur frequently in Terengganu, Malaysia. Recently, ensemble based techniques are getting extremely popular in flood modeling. In this paper, weights-of-evidence (WoE) model was utilized first, to assess the impact of classes of each conditioning factor on flooding through bivariate statistical analysis (BSA). Then, these factors were reclassified using the acquired weights and entered into the support vector machine (SVM) model to evaluate the correlation between flood occurrence and each conditioning factor. Through this integration, the weak point of WoE can be solved and the performance of the SVM will be enhanced. The spatial database included flood inventory, slope, stream power index (SPI), topographic wetness index (TWI), altitude, curvature, distance from the river, geology, rainfall, land use/cover (LULC), and soil type. Four kernel types of SVM (linear kernel (LN), polynomial kernel (PL), radial basis function kernel (RBF), and sigmoid kernel (SIG)) were used to investigate the performance of each kernel type. The efficiency of the new ensemble WoE and SVM method was tested using area under curve (AUC) which measured the prediction and success rates. The validation results proved the strength and efficiency of the ensemble method over the individual methods. The best results were obtained from RBF kernel when compared with the other kernel types. Success rate and prediction rate for ensemble WoE and RBF-SVM method were 96.48% and 95.67% respectively. The proposed ensemble flood susceptibility mapping method could assist researchers and local governments in flood mitigation strategies.
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► Evaluation of hydrological runoff simulations with 120years of historic data. ► Usage of a large ensemble of regional climate models to address uncertainty in climate projections. ► ...Assessment of range in future runoff conditions until the end of the 21st century.
Runoff conditions are strongly controlled by climate. Therefore, any uncertainties in the projections about future climate directly translate to uncertainties in future runoff. If several climate models are applied with the same emission scenario, there may be large differences in the climate projections due to model related biases and natural climate variability. To address this issue, an ensemble modelling approach – which considers a set of climate models – is applied in this study with a monthly, conceptual hydrological model for assessing future runoff conditions in the upper Danube basin (101,810km2). Observed data of the past 120years of the HISTALP data-set are used to evaluate runoff simulations under historic climate variations as well as to test the delta-change method for bias correction of climate data. Uncertainties caused by the hydrological model or by the method for bias correction appear to be small. Projections about future climate are obtained from 21 regional climate models (RCMs) of the ENSEMBLES project for the A1B emission scenario. Evaluation and ranking of the RCMs reveals that some of the models have considerable biases in simulation of spatio-temporal patterns of historic precipitation and temperature. There is however, no systematic relationship between historic performance and projected future change. Even for the better performing RCMs the differences in the simulation results are large. This is a strong argument for using an ensemble modelling approach, which yields a range of future runoff conditions instead of a deterministic projection. In general, a strong decrease of summer runoff is simulated, whereas there is no clear signal for changes in winter runoff. The spread between different RCMs in future seasonal runoff is larger than for the monthly flow duration curve. Overall, the projected changes in future runoff conditions become more pronounced towards the end of the 21st century.
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