Effective Impervious Area Research Articles

Urban impervious cover characterization for rainfall-runoff analysis: Impacts of data availability and resolution

Urban watershed hydrologic and water quality models, and stormwater control measure (SCM) designs, rely on accurate determination of stormwater runoff volume and impervious areas contributing to runoff. This research assesses the impacts of data availability and spatial resolution on two of the main indicators of urban impervious cover: total impervious area (TIA) and directly connected impervious area (DCIA). The research also explores the relationship between TIA, DCIA, and the effective impervious area (EIA), another important indicator of urban impervious cover. Using spatial programming, surface runoff was tracked, from originated to discharged locations, in nine urban catchments (ranging from 16 to 2035 ha) in Minnesota, USA, under various scenarios combining geospatial data types and resolutions. TIA fractions derived from low-resolution, nationally available imperviousness data were not statistically different than those from high-resolution land cover (LC) data modified by “unshading” to remove tree canopies overlaying impervious surfaces. Comparison of DCIA and EIA values indicated that modified LC is preferable for accurate DCIA delineation in ungauged catchments. EIA was 65 % of DCIA under the assumption that all rooftops were connected to sewer systems, while it exceeded DCIA by 34 % assuming all rooftops were unconnected, underscoring the importance of rooftop connectivity information in urban areas. The assumption of 0 % to 40 % rooftop connectivity resulted in comparable DCIA and EIA values in the study catchments. Using roads as the runoff collection system (instead of sewer inlets) did not significantly alter DCIA values at 5 % level, when unshaded LC was used. Given the absence of observed runoff data in most urban areas, DCIA serves as an appropriate imperviousness indicator for determining runoff in ungauged urban watersheds. However, achieving accurate DCIA delineation necessitates high-resolution LC data, emphasizing the need for relevant urban management organizations to develop such data.

Estimation of EIA by Semi-Automated Direct Method for Western Indian Urban Catchment Area

Urbanization impacts water resources, with impervious surfaces indicating the degree of disturbance. Effective impervious area (EIA) is a better measure than total impervious area (TIA) for urban runoff. EIA is the portion of TIA connected to the storm sewer system. Remote sensing data alone is insufficient for EIA determination. An alternative approach integrates remote sensing data with drainage networks to ensure connectivity of impervious surfaces. This approach uses GIS data including multi-sensor data. The modified literature algorithm was used in python to analyze the study area. It is observed that for western Indian urban catchment area, some empirical equation such as Sutherland’s and Alley-Veenhuis showed under-estimation and over-estimation at some watershed parts which were obtained using DEM delineation. Based on the results obtained from proposed method, a quadratic relationship was established between easily measured TIA and hydraulically relevant EIA for an urban catchment in western India. These outcomes should result in more effective and properly designed SCMs, with potential improvements in water quality and cost savings.

An automated approach to establish relationship between total and effective impervious area for urban Indian catchments

ABSTRACT Determination of total impervious area (TIA) or effective impervious area (EIA) is mandatory for hydrological modelling of water quantity and quality in urban areas. In this study, a multilayer deep learning model Convolutional Neural Network (CNN) is implemented for estimating TIA. A more realistic automated method is suggested to determine EIA by integrating the remote sensing data, the digital format of the drainage network, and a digital elevation model (DEM). A graphical user interface (GUI) called EIA estimator is developed for automatic creation of EIA maps. An effort is made to derive a relationship between TIA and EIA. Several power relationships are obtained for easily measurable TIA and hydraulically relevant EIA in urban catchments of India. These relationships would aid planners and decision-makers with quick initial estimates for surface water quantity and quality problems.

Long-term effects of land-use change on water resources in urbanizing watersheds

The changes in energy balance resulting from land-use change may significantly affect the amount and timing of water loss to the atmosphere as evapotranspiration (ET). Also, these will impact water fluxes in the watershed system, influencing runoff rate, flow volume, intensity, and frequency of floods. During the past century, land-use change in the SuAsCo (Sudbury-Assabet and Concord) watershed has altered basin hydrology, sediment, and nutrient load that is detrimental to water resources in SuAsCo. This study uses an integrated physically-based model Hydrological Simulation Program-FORTRAN (HSPF), along with Land Transformation Model (LTM), to assess predicted temporal and spatial changes in water, nutrient, and sediment yields for future land-use scenarios of 2035, 2065, and 2100. Results showed that a 75% increase in effective impervious area and a 50% decrease in forest area in 2100 (from 2005 baseline levels) are projected to cause a 3% increase in annual streamflow and a 69% increase in total yearly mean surface runoff. The average annual total suspended solid (TSS) yield at the watershed outlet is estimated to increase by 54% in 2100. An increase of 12% and 13% concentrations of average annual total phosphorus (TP) and total nitrogen (TN) are predicted by 2100 due to urban expansion and increased runoff volume. This integrated modeling approach will inform watershed managers and landowners about critical areas of the SuAsCo watershed to apply best management practices (BMPs) to mitigate the effects of land-use land cover (LULC) change.

Water Sensitive Urban Design (WSUD) Spatial Prioritisation through Global Sensitivity Analysis for Effective Urban Pluvial Flood Mitigation

Water Sensitive Urban Design (WSUD) has attracted growing attention as a sustainable approach for mitigating pluvial flooding (also known as flash flooding), which is expected to increase in frequency and intensity under the impacts of climate change and urbanisation. However, spatial planning of WSUD is not an easy task, not only due to the complex urban environment, but also the fact that not all locations in the catchment are equally effective for flood mitigation. In this study, we developed a new WSUD spatial prioritisation framework that applies global sensitivity analysis (GSA) to identify priority subcatchments where WSUD implementation will be most effective for flood mitigation. For the first time, the complex impact of WSUD locations on catchment flood volume can be assessed, and the GSA in hydrological modelling is adopted for applications in WSUD spatial planning. The framework uses a spatial WSUD planning model, the Urban Biophysical Environments and Technologies Simulator (UrbanBEATS), to generate a grid-based spatial representation of catchment, and an urban drainage model, the U.S. EPA Storm Water Management Model (SWMM), to simulate catchment flooding. The effective imperviousness of all subcatchments was varied simultaneously in the GSA to mimic the effect of WSUD implementation and future developments. Priority subcatchments were identified based on their influence on catchment flooding computed through the GSA. The method was tested for an urbanised catchment in Sydney, Australia. We found that high priority subcatchments were clustering in the upstream and midstream of the main drainage network, with a few distributed close to the catchment outlets. Rainfall frequency, subcatchment characteristics, and pipe network configuration were found to be important factors determining the influence of changes in different subcatchments on catchment flooding. The effectiveness of the framework in identifying influential subcatchments was validated by comparing the effect of removing 6% of the Sydney catchment's effective impervious area under four WSUD spatial distribution scenarios. Our results showed that WSUD implementation in high priority subcatchments consistently achieved the largest flood volume reduction (3.5-31.3% for 1% AEP to 50% AEP storms), followed by medium priority subcatchments (3.1-21.3%) and catchment-wide implementation (2.9-22.1%) under most design storms. Overall, we have demonstrated that the proposed method can be useful for maximising WSUD flood mitigation potential through identifying and targeting the most effective locations.

Challenges in Quantifying Losses in a Partly Urbanised Catchment: A South Australian Case Study

Quantifying hydrological losses in a catchment is crucial for developing an effective flood forecasting system and estimating design floods. This can be a complicated and challenging task when the catchment is urbanised as the interaction of pervious and impervious (both directly connected and indirectly connected) areas makes responses to rainfall hard to predict. This paper presents the challenges faced in estimating initial losses (IL) and proportional losses (PL) of the partly urbanised Brownhill Creek catchment in South Australia. The loss components were calculated for 57 runoff generating rainfall events using the non-parametric IL-PL method and parametric method based on two runoff routing models, Runoff Routing Burroughs (RORB) and Rainfall-Runoff Routing (RRR). The analysis showed that the RORB model provided the most representative median IL and PL for the rural portion of the study area as 9 mm and 0.81, respectively. However, none of the methods can provide a reliable loss value for the urban portion because there is no runoff contribution from unconnected areas for each event. However, the estimated non-parametric IL of 1.37 mm can be considered as IL of EIA of the urban portion. Several challenges were identified in the loss estimation process, mainly when selecting appropriate storm events, collecting data with the available temporal resolution, extracting baseflow, and determining the main-stream transmission losses, which reduced the urban flow by 5.7%. The effect of hydrograph shape in non-parametric loss estimation and how combined runoff from the effective impervious area and unconnected (combined indirectly connected impervious and pervious) areas affects the loss estimation process using the RORB and RRR models are further discussed. We also demonstrate the importance of identifying the catchment specific conditions appropriately when quantifying baseflow and runoff of selected events for loss estimation.

The Effectiveness of Centralized versus Decentralized Green Infrastructure in Improving Water Quality and Reducing Flooding at the Catchment Scale

Green infrastructure (GI), such as green roofs, rain gardens, and porous pavement, is a stormwater management strategy designed to capture rain where it falls and allow it to soak into the ground rather than running off into a stream channel, thus reducing flooding and improving water quality. While there has been a lot of research into the performance of individual GI projects, much less is known about its performance at the catchment scale. This study uses a US EPA SWMM model to examine the effectiveness of GI in improving water quality and reducing flooding at the catchment scale. Results show that in the study catchment, a large centralized wetland was the most effective at reducing and slowing peak discharge. Infiltration based decentralized GI best reduced flood volumes. In addition to changes in effective impervious area, flood volumes were also reduced due to differences in drainage network structure and modifications to the pervious portions of the catchment. Reductions in flood volumes resulted in lower pollutant loads, except for pollutants that are particularly efficiently removed by wetlands. Routing runoff through a large, centralized wetland removed more nitrate load than letting rain infiltrate where it falls.

Inter-Event Water Quality Variability and Intra-Event Pollutant Dynamics in Context of Effective Impervious Area

AbstractWater quality modeling has been studied extensively to better manage urban runoff impacts on stream health and effectively address stormwater permitting requirements. Recent studies have in...

Continuous Simulation of Highly Urbanized Watershed to Quantify Nutrients’ Loadings

The United States has witnessed various extreme land use changes over the years. These changes led to alterations in watersheds’ characteristics, impacting their water quality and quantity. To quantify this impact in highly urbanized watersheds such as the Chicago Metropolitan Area, it is crucial to examine the characteristics and imperviousness distribution of urban land uses and available point and non-point sources. In this paper, the effect of urban runoff and nutrient loadings to water bodies in the Chicago River Watershed resulting from level (III) detailed urban land uses is investigated. A watershed scale hydrologic and water quality simulation using BASINS/HSPF model was developed for the highly urbanized watershed. Appropriate considerations were given to the effective impervious area (EIA). The results from the five-year calibrated water quality simulation were reasonably reflected with observed data in the study area and nutrient loadings of both point and non-point sources for 44 different land uses were found. The export coefficients (EC) values obtained are site-specific depending on conditions and variables at the watershed level such as physical characteristics, land use management practices, hydro-meteorological and topographical data, while using a continuous simulation approach and watershed perspective analysis. This is the first attempt to measure and model nutrients’ loadings using detailed land use types in the Chicago River Watershed. The proposed continuous calibrated and validated model can be used in the investigation and analysis of different scenarios and possible future conditions and land utilization.

The Effect of Urban Land-Use Change on Runoff Water Quality: A Case Study in Hangzhou City.

The main functions of this research are to guide the proportion of urban land that is used and the layout of the facilities on it, help understand the changes to surface runoff that are caused by land being used in urban development, and thus solve surface runoff pollution. Hangzhou City, China has been selected for the experiment, and the way in which its land is utilized as well as the grading of urban construction projects in the demonstration area are specifically analyzed. This study systematically distinguishes the definitions of impervious area based on the Sutherland equation and analyzes the impact of different impervious area subtypes on surface runoff water quality. Then, we compare the impact of impervious area subtypes with the impact of other land-use patterns on surface runoff water quality. This study shows the relationship between different land-use types and runoff water bodies: Land-use index can affect runoff water quality; Greening activities, impervious surface, and the water quality index are negatively correlated; the effective impervious area rate is positively correlated with the water quality index. The paper suggests that increasing the proportion of green spaces and permeable roads in build-up land reduces the effective impervious area (EIA) and thus controls land runoff pollution and improves runoff water quality.

A Bayesian approach to model the trends and variability in urban stormwater quality associated with catchment and hydrologic parameters

Stormwater runoff pollution has become a key environmental issue in urban areas. Reliable estimation of stormwater pollutant discharge is important for implementing robust water quality management strategies. Even though significant attempts have been undertaken to develop water quality models, deterministic approaches have proven inappropriate as they do not address the variability in stormwater quality. Due to the random nature of rainfall characteristics and the differences in catchment characteristics, it is difficult to generate the runoff pollutographs to a desired level of certainty. Bayesian hierarchical modelling is an effective tool for developing complex models with a large number of sources of variability. A Bayesian model does not look for a single value of the model parameters, but rather determines a distribution of the model parameters from which all inference is drawn. This study introduces a Bayesian hierarchical linear regression model to describe a catchment specific runoff pollutograph incorporating the associated uncertainties in the model parameters. The model incorporates catchment and rainfall characteristics including the effective impervious area, time of concentration, rain duration, average rainfall intensity and the antecedent dry period as the contributors to random effects.

Assessing the effects of four SUDS scenarios on combined sewer overflows in Oslo, Norway: evaluating the low-impact development module of the Mike Urban model

Abstract Paved surfaces, increased precipitation intensities in addition to limited capacity in the sewer systems, cause a higher risk of combined sewer overflows (CSOs). Sustainable drainage systems (SUDS) offer an alternative approach to mitigate CSO by managing the stormwater locally. Seven SUDS scenarios, developed based on the concept of effective impervious area reduction, have been implemented in the Grefsen catchment using the Mike Urban model. This study evaluated the hydrological performance of two SUDS controls (i.e. green roof (GR) and rain garden (RG)) modules of the model and the effect of the SUDS scenarios on the CSOs using event-based and continuous simulations. The Nash–Sutcliffe efficiency (NSE) along with flow duration curves (FDCs) has been used for evaluating the model performance. Event-based evaluations revealed the superior performance of the RG in reducing CSOs for larger precipitation events, while GRs were proven to have beneficial outcomes during smaller events. The study illustrated another way of assessing the continuous simulations by employing the FDCs. The FDCs were assessed against a discharge threshold at the outlet (which authorities can set as design criteria) of the catchment in terms of the extent, each scenario reduced occurrence and duration of outflow that invokes flow in the overflow pipe.

Effectivity analysis of the application of TIA (total impervious area) and EIA (effective impevious area) in a micro scale watershed (case study on Sugutamu sub-watershed)

There are two methods that can be used to calculate the area of impervious cover on a watershed, Total Impervious Area (TIA) and Effective Impervious Area (EIA). Calculation of impervious cover generally uses the TIA method. Recently, based on several researches, EIA is the better indicator for identifying surface runoff discharge. This study aims to analyze the difference of surface runoff discharge using both TIA and EIA methods in different scales of an urban watershed area, specifically the Sugutamu sub-watershed and Sugutamu catchment area. Land cover identification with the TIA method uses the Rupa Bumi Indonesia map of 2017. While for the EIA method, the land cover identification uses the 2017 visual interpretation of high-resolution satellite imagery from the software GIS. FTUI and Cibinong stations have been selected as the daily rainfall data for the surface runoff simulation of the watershed and the catchment area using the software HEC-HMS. The result of the simulation shows that the EIA method in the urban catchment area has a more significant impact. In conclusion, the use of EIA should be considered more in micro-scaled modelling of an urban watershed’s surface runoff.

Improving Effective Impervious Estimates to Inform Stormwater Management

Sizing stormwater runoff control facilities and their performance relies on the amount of runoff generated from impervious cover in the watershed. Total impervious area (TIA) often overestimates unit runoff values because it fails to account for intervening pervious surfaces which can reduce effective impervious area (EIA) below the TIA. While EIA is a better estimator for designing stormwater control facilities, direct measurement of EIA can be limited to small catchments as the process is rigorous and time intensive. This paper develops an EIA-TIA regression relationship with a single parameter TIA for semi-arid Southern California. TIA of seven watersheds of the region is calculated from 30 m resolution National Land Cover Dataset and EIA is indirectly measured from observed rainfall and runoff data from 2005 to 2007 in study watersheds using three methods – (1) Ordinary Least Square (OLS), (2) Modified Ordinary Least Square (MOLS) and (3) Weighted Least Square (WLS) methods. Results show that a linear relationship between EIA derived from WLS method and estimated watershed TIA meet the sensitivity test requirement and have highest R2 value. This empirical EIA-TIA relationship is valid for watersheds with TIA greater than 2.56% and estimated EIAs for the study watersheds are between 20 and 50% lower than the TIAs. Using EIA instead of TIA can results in reduced runoff volume and the associated design size of stormwater control devices. This empirical relationship can be applied to other semi-arid watersheds with similar size, land use and other geomorphic characteristics.

Urban Spatial Configuration and Functional Runoff Connectivity: Influence of Drainage Grid Density and Landscape Metrics

Due to changing precipitation patterns induced by climate change, urban planners are confronted with new challenges to effectively mitigate rainfall runoff. An important knowledge gap that needs to be addressed before tackling these challenges is how and to which extent street/drainage grid density and spatial land use configuration influence the amount of runoff. Therefore, a virtual experiment was conducted to assess the influence of grid density and spatial land use configuration on the functional runoff connectivity (Fc), which is a measure of the easiness by which water flows through the landscape. Through the use of a design of experiments approach in combination with the SCS—Curve Number runoff model, a wide variety of neutral landscape models with a fixed percentage of pervious- and impervious cover were generated that maximized the variance of Fc. Correlations between landscape metrics and neutral landscape models were calculated. Our results indicated that, out of the 17 landscape metrics tested, the average impervious cluster area, the number of impervious clusters, the standard deviation of the cluster size, two proximity indexes and the effective impervious area were strongly correlated with Fc throughout all grid scenarios. The relationship between Fc on the one hand and the average impervious cluster area and the effective impervious area on the other hand, was modelled. The average impervious cluster area models showed a relationship with Fc that closely approximated a logarithmic function (R2: 0.49–0.73), while the effective impervious area models were found to have a linear relationship with Fc (R2: 0.63–0.99). A dense grid was shown to cause a strong increase in Fc, demonstrating the effectiveness of an urban grid in channeling and removing runoff. Our results further indicate that fine-grained landscapes with a lot of small impervious clusters are preferred over course-grained landscapes when the goal is to reduce Fc. In highly urbanized landscapes, where the percentage of impervious area is high, small changes in landscape pattern could significantly reduce Fc. By using a downward hydrological modeling approach this research aims to bring more clarity to the underlying variables influencing Fc, rather than trying to generate realistic prediction values.

Taxonomy of influential factors for predicting pollutant first flush in urban stormwater runoff

Pollutant first flush in urban stormwater runoff is an important phenomenon influenced by a range of rainfall and catchment related variables. Even though numerous studies have been undertaken to mathematically define the first flush and the influential variables of first flush, limited research have been carried out to rank such variables in terms of their level of importance in generating first flush. Identifying the degree of importance of the variables is critical for accurate predictions of first flush occurrence and understanding the main drivers of first flush. This research study undertook a comprehensive analysis of the variables influencing the predictions of first flush occurrence and their relative importance. The study results are expected to contribute to more accurate predictions of first flush by affording greater importance to the highly ranked factors and their impacts. The study outcomes confirmed that total rainfall depth was the most important variable influencing the prediction of first flush events while the maximum intensity was the second. Rain duration, runoff depth, runoff peak and average intensity were the next four most important variables. Antecedent dry period and effective impervious area fraction had relatively low ranking while the time of concentration and the event mean concentration were found to be the least important variables. Furthermore, the study outcomes highlight that the use of a combination of variables and due consideration of their interactions can yield better results than considering their individual roles.

The effects of spatial discretization on performances and parameters of urban hydrological model.

Selecting a proper spatial resolution for urban rainfall runoff modeling was not a trivial issue because it could affect the model outputs. Recently, the development of remote sensing technology and increasingly available data source had enabled rainfall runoff process to be modeled at detailed and microscales. However, the models with less complexity might have equally good performance with less model establishment and computation time. This study attempted to explore the impact of model spatial resolution on model performance and parameters. Models with different discretization degree were built up on the basis of actual drainage networks, urban parcels and specific land use. The results showed that there was very little difference in the total runoff volumes while peak flows showed obvious scale effects which could be up to 30%. Generally, model calibration could compensate the scale effect. The calibrated models with different resolution showed similar performances. The consideration of effective impervious area (EIA) as a calibration parameter marginally increased performance of the calibration period but also slightly decreased performance in the validation period which indicated the importance of detailed EIA identification.

Using spatially-identified effective impervious area to target green infrastructure retrofits: A modeling study in Knoxville, TN

There is a need for enhanced guidance in siting distributed, infiltrative green infrastructure (GI) practices, especially in densely developed urban watersheds where retrofits come at a high cost. To maximize the hydrologic benefit of GI practices on urban streams, the disconnection of effective impervious areas (EIA), or those impervious areas hydraulically connected to the stormwater network, has been identified as a strategic management approach that is expected to have the greatest impact. The overall effect of full disconnection of spatially-identified EIA on watershed hydrology is uncertain because this type of full disconnection is rarely brought to full-scale implementation. In this study, spatial EIA identification is used to parametrize an urban runoff model using the United States Environmental Protection Agency’s Storm Water Management Model (SWMM). The calibrated model is used to assess runoff reductions resulting from GI practices distributed through the watershed via different placement strategies, both spatially-informed and not. Full treatment of the spatially-identified EIA using bioretention cells was compared to two scenarios treating the same area of impervious surfaces, but with random placement either among all impervious areas or placement focused in areas of higher imperviousness. Model results indicate that substantially higher runoff reduction could be realized by targeting EIA, with a median runoff reduction of nearly 30% more than other treatment scenarios across storm events ranging from 1.27 to 20.7 mm using this strategic siting. Further improvements in optimizing distributed infiltrative GI practice placement are needed and targeting of spatially-identified EIA appears to be a viable method for increasing the hydrologic improvements realized through watershed scale implementations.

Impact of urbanization on effective impervious area of Ahmedabad city in India

ABSTRACT With increasing urbanization and population pressure, the barren ground is altered from undisturbed soils to disturbed soils, which multiplies fast growth of impervious areas in cities. An impervious area is a modified surface that prevents water from infiltrating into the soil. Hydraulically connected impervious areas are denoted as effective impervious area (EIA) and hydraulically disconnected are denoted as non-effective impervious area (NEIA). The summation of above two impervious covers amounts to the total impervious area (TIA). Impervious surface data is important for urban planning and environmental and resources management. Therefore, remote sensing of impervious surfaces in the urban areas has recently attracted unprecedented attention. The estimation of TIA is comparatively simple as compared to the estimation of EIA, despite the fact that later is viewed as more proper for hydrologic studies. In this paper, emphasis was given on the estimation of impervious area (TIA) for the year 2000 and 2014 to scrutinize urbanization growth of Ahmedabad city in India using medium resolution satellite imageries by using geospatial techniques under the ArcGIS 10.1 platform. The more hydraulically relevant EIA is estimated using two indirect methods, i.e. empirical equations derived from the whole basin or sub-basin parameters from the estimated TIA and using an annual hydrograph methodology. A graphical demonstration of the estimated EIA and TIA for different years is illustrated to analyze the rate of urban expansion.

Effects of the spatial resolution of urban drainage data on nonpoint source pollution prediction.

Detailed urban drainage data are important for urban nonpoint source (NPS) pollution prediction. However, the difficulties in collecting complete pipeline data usually interfere with urban NPS pollution studies, especially in large-scale study areas. In this study, NPS pollution models were constructed for a typical urban catchment using the SWMM, based on five drainage datasets with different resolution levels. The influence of the data resolution on the simulation results was examined. The calibration and validation results of the higher-resolution (HR) model indicated a satisfactory model performance with relatively detailed drainage data. However, the performances of the parameter-regionalized lower-resolution (LR) models were still affected by the drainage data scale. This scale effect was due not only to the pipe routing process but also to changes in the effective impervious area, which could be limited by a scale threshold. The runoff flow and NPS pollution responded differently to changes in scale, primarily because of the difference between buildup and washoff and the more significant decrease in pollutant infiltration loss and the much greater increase of pollutant flooding loss while scaling up. Additionally, scale effects were also affected by the rainfall type. Sub-area routing between impervious and pervious areas could improve the LR model performances to an extent, and this approach is recommended to offset the influence of spatial resolution deterioration.