New Methods for Quantifying Effective Impervious Area in Urban Watersheds (original) (raw)
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Impervious surfaces are useful indicators of the urbanization impacts on water resources. Effective impervious area (EIA), which is the portion of total impervious area (TIA) that is hydraulically connected to the drainage system, is a better catchment parameter in the determination of actual urban runoff. Development of reliable methods for quantifying EIA rather than TIA is currently one of the knowledge gaps in the rainfall-runoff modeling context. The objective of this study is to improve the rainfall-runoff data analysis method for estimating EIA fraction in urban catchments by eliminating the subjective part of the existing method and by reducing the uncertainty of EIA estimates. First, the theoretical framework is generalized using a general linear least square model and using a general criterion for categorizing runoff events. Issues with the existing method that reduce the precision of the EIA fraction estimates are then identified and discussed. Two improved methods, based on ordinary least square (OLS) and weighted least square (WLS) estimates, are proposed to address these issues. The proposed weighted least square method is then applied to eleven urban catchments in Europe, Canada, and Australia. The results are compared to map measured directly connected impervious area (DCIA) and are shown to be consistent with DCIA values. In addition, both of the improved methods are applied to nine urban catchments in Minnesota, USA. Both methods were successful in removing the subjective component inherent in the analysis of rainfall-runoff data of the current method. The WLS method is more robust than the OLS method and generates results that are different and more precise than the OLS method in the presence of heteroscedastic residuals in our rainfall-runoff data.
GENERALIZED METHOD FOR ESTIMATING VARIABILITY IN DIRECTLY CONNECTED IMPERVIOUS AREAS
Determining impervious areas is a key factor regarding the expected amount of runoff in an urbanized watershed. Imperviousness occurs from land alterations that change the predevelopment hydrology, especially as relates to land cover and its effects on surface infiltration. An urbanized watershed can be divided into three general types: Directly Connected Impervious Area (DCIA), Non-Directly Connected Impervious Area (NDCIA), and Pervious Area (PA). Runoff from DCIAs is conveyed directly to storm water sewers while runoff from NDCIA may pass through a PA before it reaches the drainage system. The amount of DCIA is highly unknown, yet it is often the dominant factor in most urban environments. Total Impervious Area (TIA) is defined as the sum of DCIA and NDCIA. In the past, several methods have been applied in the estimation of TIA. Among these methods are direct field measurements, empirical equations, and interpretation of satellite images. While empirical relationships have been developed for different land cover, generalized methods still need to be developed. In this study, DCIA as a function of rainfall depth was estimated. DCIA reaches its maximum value when enough rainfall has occurred to connect runoff from all impervious surfaces (TIA). The new approach was tested with rainfall runoff data on a small, but highly urbanized catchment in Temple Terrace, FL. The result of this research indicated that impervious surfaces become increasingly effective in generating storm water runoff with increased rainfall depth and decreased infiltration. The results of this research can be used to study the impact of urbanization on storm water runoff and improve hydrologic modeling.
Effective Impervious Area for Runoff in Urban Watersheds
Effective impervious area (EIA), or the portion of total impervious area (TIA) that is hydraulically connected to the storm sewer system, is an important parameter in determining actual urban runoff. EIA has implications in watershed hydrology, water quality, environment, and ecosystem services. The overall goal of this study is to evaluate the application of successive weighted least square (WLS) method to urban catchments with different sizes and various hydrologic conditions to determine EIA fraction. Other objectives are to develop insights on the data selection issues, EIA fraction, EIA/TIA ratio, and runoff source area patterns in urban catchments. The successive WLS method is applied to 50 urban catchments with different sizes from less than 1 ha to more than 2000 ha in Minnesota, Wisconsin, Texas, USA as well as Europe, Canada and Australia. The average, median, and standard deviation of EIA fractions for the 42 catchments with residential land uses are found to be 0.222, 0.200, and 0.113, respectively. These values for the EIA/TIA ratio in the same 42 catchments are 0.50, 0.48, and 0.21, respectively. While the EIA/TIA results indicate the importance of EIA, 95% prediction interval of the mean EIA/TIA is found to be 0.07 to 0.93, which shows that using an average value for this ratio in each land use to determine EIA from TIA in ungauged urban watersheds can be misleading. The successive WLS method was robust and is recommended for determining EIA in gauged urban catchments.
Journal of The American Water Resources Association, 2008
Abstract: Impervious cover is a commonly used metric to help explain or predict anthropogenic impacts on aquatic resources; often it is used as a surrogate for intensity of human impacts when evaluating effects on aquatic resources. The most common way to estimate imperviousness is based on relationships with land use. Few studies have evaluated how the relationship between impervious surface and land use varies among geographies with different levels of development and between types of imagery used to assign land use type. In this study, we assess variability in estimates of imperviousness based on two locally available land use datasets: one based on aerial imagery (2-m resolution) and another based on satellite imagery (30-m resolution). The ranges and variability in imperviousness within land use categories were assessed at several spatial scales, including within counties, between counties, and between watersheds. Results indicate that there was considerable variability for all developed land use types. Estimated impervious cover often varied over a range of 20-40% points within a land use category. Furthermore, there were clear spatial patterns both between and within counties, with impervious cover for a given land use type being higher near the urban centers and lower at the margins of development. Estimates of imperviousness for 12 study watersheds indicated that variability increased with increasing watershed development, making it difficult to confidently set management or regulatory targets based on impervious cover. This study suggests that locally derived, high resolution satellite or aerial imagery should be used to estimate imperviousness when a high level of accuracy and precision is required for regulatory or management decisions. Furthermore, the error associated with impervious land use relationships should be accounted for when using impervious cover in runoff or water quality models, or when making management decisions regarding stream health.
Error analysis for the evaluation of model performance: rainfall–runoff event summary variables
Hydrological Processes, 2007
This paper provides a procedure for the evaluation of model performance for rainfall-runoff event summary variables, such as total discharge or peak runoff. The procedure is based on the analysis of model errors, defined as the differences between observed values and values predicted by a simulation model. Model errors can (i) indicate whether and where the model can be improved, (ii) be used to measure the performance of a model, and (iii) be used to compare model simulations. In this paper, both statistical and graphical methods are used to characterize model errors. We explore model recalibration by relating model errors to the model predictions, and to external, independent variables. The R-5 catchment data sets that we used in this study include summary variables for 72 rainfall-runoff events. The simulations used in this study were previously conducted with the quasi-physically based rainfall-runoff model QPBRRM for 11 different characterizations of the R-5 catchment, each with increasing information or a refined spatial discretization of the overland flow planes. This paper is about proposing model diagnostics and not about procedures for using diagnostics for model modification.
Calibration of a Simple Rainfall-runoff Model for Long-term Hydrological Impact Evaluation
2006
Continued land development and land-use changes within cities and at the urban fringe present considerable challenges for environmental management. Hydrologic changes including increased impervious area, soil compaction, and increased drainage efficiency generally lead to increased direct runoff, decreased groundwater recharge, and increased flooding, among other problems (Booth 1991). Hydrologic models, especially simple rainfall-runoff models, are widely used in understanding and quantifying the impacts of land-use changes, and to provide information that can be used in land-use decision making. Many hydrologic models are available, varying in nature, complexity, and purpose (Shoemaker et al. 1997). One such model, Long-Term Hydrological Impact Assessment (L-THIA), a simple rainfall-runoff model based on the U.S. Department of Agriculture's Curve Number (CN) method (USDA 1986), was developed to help land-use planners and watershed managers obtain initial insight into the hydrologic impacts of different land-use scenarios, including historic, current, and future alternatives (Harbor 1994). Like other models, L-THIA is based on empirical relationships that capture the main processes and controls on runoff, but do not account for all the conditions and controls specific to particular study sites, and do not predict the baseflow component of stream flow. Where close correspondence between predicted and observed runoff values is required, rather than simply a relative measure of change, it is necessary to produce a modified (calibrated) model. Calibration of rainfall-runoff models with respect to local observational data is used to improve model predictability. When model results match observed values from stream-flow measurement, users have greater confidence in the reliability of the model. In the present study, a simple method based on univariate linear regression has been used to calibrate L-THIA, using land-use change data, model predicted direct runoff, and direct runoff derived from stream-flow data using hydrograph separation.
The rational method for peak discharge (Q p ) estimation was introduced in the 1880s. Although the rational method is considered simplistic, it remains an effective method for estimating peak discharge for small watersheds. The runoff coefficient (C) is a key parameter for the rational method and can be estimated in various ways. Literature-based C values (C lit ) are listed for different land-use/land cover (two words, no hyphen) (LULC) conditions in various design manuals and textbooks; however, these C lit values were developed with little basis on observed rainfall and runoff data. In this paper, C lit values were derived for 90 watersheds in Texas by using LULC data for 1992 and 2001; the C lit values derived from the two data sets were essentially the same. Also for this study, volumetric runoff coefficients (C v ) were estimated by using observed rainfall and runoff depths from more than 1,600 events observed in the watersheds. Watershed-median and watershedaverage C v values were computed, and both are consistent with data from the National Urban Runoff Program. In addition, C v values were estimated by using rank-ordered pairs of rainfall and runoff depths (i.e., frequency matching). As anticipated, C values derived by all three methods (literature based, event totals, and frequency matching) consistently had larger values for developed watersheds than for undeveloped watersheds. Two regression equations of C v versus percent impervious area were developed and combined into a single equation that can be used to rapidly estimate C v values for similar Texas watersheds.
Uncertainty in watershed response predictions induced by spatial variability of precipitation
Environmental Monitoring and Assessment, 2007
Negligence to consider the spatial variability of rainfall could result in serious errors in model outputs. The objective of this study was to examine the uncertainty of both runoff and pollutant transport predictions due to the input errors of rainfall. This study used synthetic data to represent the "true" rainfall pattern, instead of interpolated precipitation. It was conducted on a synthetic case area having a total area of 20 km 2 with ten subbasins. Each subbasin has one rainfall gauge with synthetic precipitation records. Six rainfall storms with varied spatial distribution were generated. The average rainfall was obtained from all of the ten gauges by the arithmetic average method. The input errors of rainfall were induced by the difference between the actual rainfall pattern and estimated average rainfall. The results show that spatial variability of rainfall can cause uncertainty in modeling outputs of hydrologic, which would be transport to pollutant export predictions, when uniformity of rainfall is assumed. Since rainfall is essential information for predicting watershed responses, it is important to consider the properties of rainfall, particularly spatial rainfall variability, in the application of hydrologic and water quality models.
Sensitivity of imperviousness determination methodology on runoff prediction
ISH Journal of Hydraulic Engineering, 2017
Imperviousness in urban catchment is defined by Total Impervious Area (TIA) or Effective Impervious Area (EIA). The methodology of imperviousness determination considers its significance in terms of its connectivity and can affect the runoff determination. This paper evaluates the sensitivity of various impervious estimation methodologies on runoff prediction. Four types of imperviousness were used for distributed hydrological modeling. Green-Ampt parameters were determined through field experiments by Tension Infiltrometer. The runoff was simulated by using two indirect methods of EIA estimation and the results were compared. It was observed that the predicted runoff was 205% more if EIA estimated by indirect method was used in the model in place of EIA estimated by direct method. Also the peak runoff was found to be maximum at TIA value of 64.3%. Further TIA was found to increase the peak runoff by 398% than the runoff predicted by directly estimated EIA.
Quantitative assessment of the runoff index in an urbanized watershed
Environmental Geosciences, 2018
Urbanization modifies the natural water cycle. In this study, a weighted-rating multicriteria analysis was adopted to quantify the runoff index and to assess the impact of urbanization on the water cycle. The considered parameters are (1) slope, (2) permeability of soil, and (3) rainfall. Using the land use map, a runoff risk map was established. The approach was applied to Manouba catchment. The main results revealed that between 2004 and 2014, the area with a high runoff index increased from 32% to 39%. The runoff risk increased; in 2004, the high class covered 18% of the watershed area. This value became 30% in 2014. Results demonstrate that urbanization affects hydrological processes. This method is appropriate in other similar watersheds to estimate the runoff index.