Examining the impact of land use/land cover characteristics on flood losses
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Characteristics of the built environment and overall local-level land use patterns are increasingly being attributed to greater surface runoff, flooding and resulting economic losses from flood events. Specific configurations of impervious surfaces and land cover may be as important to determining a community's flood risk as baseline environmental conditions. This study addresses this issue by statistically examining the impacts of adjacent land use and land cover (LULC) on flood damage recorded on parcels within a coastal watershed in southeast Texas. We analyse empirical models to identify the influence of different LULCs surrounding over 7900 properties claiming insured flood losses from 1999–2009. Results indicate that specific types of surrounding LULCs impact observed flood losses and provide guidance on how neighbourhoods can be developed more resiliently over the long term.Keywords:
Impervious surface
Land Cover
Abstract Runoff on impervious surfaces (roads, roofs, etc.) raises a number of environmental and road safety‐related problems. The primary objective of this research effort is to improve our knowledge of the hydrological behaviour of impervious urban surfaces in order to better assess runoff on these surfaces and its subsequent consequences. This article will focus on two street stretches studied over a 38‐month period. Measurements of rainfall and runoff discharge on these stretches have made it possible to estimate runoff losses as well as to constitute a database for modelling purposes. On the basis of these data, two models have been used, one simple the other more detailed and physically based. For both models, runoff discharges at a 3‐min time step are well reproduced, although runoff coefficients and runoff losses are still poorly estimated. Detailed analyses of experimental data and model output, however, indicate that runoff losses could be quite high on such ‘impervious surfaces’ (between 30 and 40% of total rainfall, depending on the street stretch) and that these losses are mainly because of evaporation and infiltration inside the road structure. Copyright © 2011 John Wiley & Sons, Ltd.
Impervious surface
Infiltration (HVAC)
Low-impact development
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A method is presented by which the proportions of a watershed that contribute surface runoff in different storms and at different times during the same storm can be determined by analysis of rainfall and runoff records. The method is a modification of a method described in an earlier paper, which eliminates the need for subjective selection of particular runoff events for analysis. The method is illustrated using data from a 16.8‐ha watershed in Queensland, Australia, and the estimates of runoff from the different source areas are compared with actual records of runoff from the whole watershed. Runoff occurred from the entire watershed area on only three occasions in the 15‐yr study period, about 10% of runoff events. In about two‐thirds of runoff events, runoff came only from the 15% of the watershed that has the smallest surface storage capacity.
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As a watershed is urbanized, characteristics of runoff from new upslope impervious surfaces may differ from runoff generated on the predevelopment soil surface in quantity, time of concentration, and sediment load. This may cause changes to the erosion regime on downslope soil surfaces. We simulated rainfall at three rates (20, 30, 40 mm/h) to generate runoff from 0.6 m2 boxes. Boxes were either treated with an impervious surface or filled with soil 0.2 m deep and were connected together in series of four boxes along the 4-m slope to produce different arrangements of impervious and pervious soil surfaces (0, 25, 50% impervious) and under different antecedent soil moisture conditions. Results indicate that previously established numerical models predicting runoff characteristics as a function of run-on characteristics generate good correlations at 0% imperviousness, but these correlations become insignificant as imperviousness increases. Imperviousness significantly influenced sediment regime, suggesting that some previously established equations relating soil erosion to run-on characteristics cannot be simply applied to areas where runoff production occurs on surfaces having an impervious component.
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Antecedent moisture
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In this study, runoff responses of typical urban surfaces were investigated by scale models under artificial rainfall simulation, and the Soil Conservation Service (SCS) model was used to assess the impacts of land use changes and green infrastructures implementation on surface runoff of Beijing urban areas. The results showed that: Runoff coefficient of the impervious surface was about 2.1 times than that of the grassland. Time to runoff of the grassland was about 22.0 times that of the impervious surface. The concaved grassland, compared with the impervious surface, can significantly delay by 6.2 minutes the time to runoff, while the porous pavement significantly reduces 28.1% of the runoff coefficient. The runoff coefficient of Beijing urban areas increased from 0.68 in 2002 to 0.72 in 2012, due to the substantially increased impervious surfaces. The runoff coefficient decreased by 2.7%, 15.3% and 22.2% respectively under three green infrastructure scenarios.
Impervious surface
Urban runoff
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Abstract: The summertime heating of runoff in urban areas is recognized as a common and consistent urban climatological phenomenon. In this study, a simple thermal urban runoff model (TURM) is presented for the net energy flux at the impervious surfaces of urban areas to account for the heat transferred to runoff. The first step in developing TURM consists of calculating the various factors that control how urban impervious areas absorb heat and transfer it to moving water on the surface. The runoff temperature is determined based on the interactions of the physical characteristics of the impervious areas, the weather, and the heat transfer between the moving film of runoff and the impervious surface common in urban areas. Key surface and weather factors that affect runoff temperature predictions are type of impervious surface, air temperature, humidity, solar radiation before and during rain, rainfall intensity, and rainfall temperature. Runoff from pervious areas is considered separately and estimated using the Green‐Ampt Mein‐Larson rainfall excess method. Pervious runoff temperature is estimated as the rainfall temperature. Field measurements indicate that wet bulb temperature can be used as a surrogate for rainfall temperature and that runoff temperatures from sod average just 2°C higher than rainfall temperatures. Differences between measured and predicted impervious runoff temperature average approximately 2°C, indicating that TURM is a useful tool for determining runoff temperatures for typical urban areas.
Impervious surface
Urban Heat Island
First flush
Urban runoff
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