Percent Impervious Cover Research Articles

Integrative Review of Riparian Buffers Benefits in Urbanized Watersheds

Riparian buffers or riparian corridors are areas of vegetation in the floodplains and areas surrounding a stream. By the early 2000s, numerous national reports and studies of riparian buffer benefits established that vegetation near streams is helpful in protecting the stream from increasing urban runoff, minimizing bank erosion, reducing flooding, and improving overall water quality. However, influential studies concluded that buffer benefits dwindle as urbanization increases, eventually becoming ineffective. This study evaluates more recent research that suggests riparian buffers are more effective at countering urbanization impacts than previously understood, and considers the extent to which we can quantify these benefits and identify the factors that maximize their effectiveness (i.e. greater efficiency based on buffer distance from the stream, extent of stream setbacks, and percentage of impervious cover in the area). Much of the research has been conducted in the Kansas City area in the Blue River Watershed, which begins in Kansas and flows into Missouri River east of downtown Kansas City, Missouri. About 800,000 residents live in the watershed, which includes some of the region’s fastest growing areas. It is critical to protect this major resource, and other regional rivers and streams, for residents of the Kansas City Metropolitan area and the ecosystems that depend on them. It is also critical to provide the latest and best information to the community-of-practice currently updating regional stormwater management planning and design guidance.

The Role of Stream Restoration in Mitigating Sediment and Phosphorous Loads in Urbanizing Watersheds

Stream corridor erosion can majorly contribute to the overall sediment and phosphorus load in urbanizing watersheds. However, the relative contribution of stream bed and bank erosion, compared with upland watershed sources and the potential for stream restoration to mitigate total contaminant loads, is poorly understood. In this study, a new method was developed, using the percent impervious cover (PIC) indicator of urbanization to evaluate the relative contribution of the stream corridor versus upland watershed contributions to observed total sediment and phosphorus loads in the receiving watercourse. This method was used to develop a cost-optimized mitigation plan, including implementing low-impact development (LID) stormwater infrastructure for urban areas and agricultural best management practices (BMPs) for rural areas in the watershed and stream restoration for the degraded stream reaches. A new cost–benefit analysis methodology is developed and used to assess the relative benefits of the mitigation measures for the case study of the Tannery Creek sub-watershed of the East Holland River in Ontario, Canada. The novel contributions of this study include the development of three relationships to estimate sediment and associated phosphorus loading based on contributing catchment area and land use, as well as a method to optimize the costs and benefits of planned mitigation measures. The results support stream restoration as an essential and cost-effective part of a comprehensive water quality watershed management plan to help maintain healthy streams in urbanized watersheds.

An Assessment of Southeast United States Headwater Tidal Creek Sediment Contamination Over a Twenty-Year Period in Relation to Coastal Development.

Headwater tidal creeks are a primary link between estuarine and upland habitats, serving as conduits for runoff. They are sentinel habitats, providing early warning of potential harm, thus ideal systems to evaluate the effects of coastal suburban and urban development on environmental quality. Estuarine sediments have concentrations of metals, polycyclic aromatic hydrocarbons (PAHs), pesticides, polychlorinated biphenyls (PCBs), and polybrominated diphenyl ethers (PBDEs) that are associated with human activity. High concentrations of contaminants can impair faunal communities, habitat quality, and ecosystem function. Forty-three headwater creeks were sampled between 1994 and 2006 to assess contaminants, and 18 of these were sampled again in 2014/2015. Watersheds were classified as forested, forested to suburban, suburban, or urban land. These values are based on their percent impervious cover (IC) levels and change in IC from 1994-2014. Analyses of temporal data resulted in significant relationships between IC and select metals, PAHs, pesticides, PCBs, and PBDEs. In addition, 11 of the creeks sampled in 2014/2015 have paired data from 1994/1995, allowing for change analysis over the 20 years. Results indicated increasing chemical contamination occurring with increasing levels of development, although only PAHs and total dichloro-diphenyl-trichloroethane (DDT) exhibited a statistically significant increase over time; PAHs also exhibited significantly higher concentrations in developed creeks. Additionally, several metals were deemed enriched in developed creeks based on reference conditions. These results expand our knowledge of how these systems respond to urban development and can inform managers about how human population growth along coastlines may predict altered tidal creek health.

A machine learning approach to evaluate the spatial variability of New York City's 311 street flooding complaints

Urbanization, accompanied by the creation of roads, pavements, and sidewalks creates an environment where there is limited infiltration capacity, leaving metropolitan areas especially vulnerable during intense rain events. Furthermore, within an urban setting, there is spatial variability, as certain areas, owing to location, topography, land feature conditions, population and physical attributes or precipitation patterns, are more prone to flood damages. To detect neighborhoods with increased flood risk, crowdsourced data, which is the consolidation of eyewitness accounts, affords particular value. With an intent to understand how factors affect the spatial variability of street flooding, the Random Forest regression machine learning algorithm is employed, where the 311 street flooding reports of New York City (NYC) serve as the response, while the explanatory variables include topographic and land feature, physical and population dynamics, locational, infrastructural, and climatic influences. This study also analyzes socio-economic variables as predictors, as to allow for better insight into potential biases within the NYC 311 crowdsourced platform. It is found that catch basin complaints have overwhelmingly the greatest predictor importance, at 41%, almost sixfold higher than that of the second highest ranked predictor, slope, at 6.7%. Thus, NYC has an apparent issue with debris blocking the basins, and this may be remediated by increased cleaning efforts or public awareness to maintain clear streets, particularly during forecasted rain events. Furthermore, more than a third of the top predictors are land feature and topographical conditions, with building characteristics dominating the category. Often excluded in urban flood models, building effects, with a combined total importance of 11.7%, have greater significance than commonly considered flooding factors, such as percent impervious cover or elevation. Another major finding is the significance of the ‘commuters who drive alone’ variable, which alerts to the prospect of more reports being filed by those more affected by street flooding, as opposed to reflecting the actual occurrence of flooding (more reports being filed by those who drive on flooded roads versus those who do not). Overall, the leading contribution of this study is the identification of the top flooding factors in NYC, along with the presentation of their specific impacts towards street flooding variability among zip codes.

A Case Study Evaluating Water Quality and Reach-, Buffer-, and Watershed-Scale Explanatory Variables of an Urban Coastal Watershed

Land use land cover within a watershed influences stream water quality, habitat quality, and biological community structure. As development and associated impervious surface increases in a watershed, changes in storm water and nutrient inputs generally cause declines in habitat conditions and biodiversity. The first goal of our study was to evaluate the water quality in the Charles River watershed, in which our objective (G1O1) was to establish ten 100-meter reach-scale sampling stations and conduct physical, chemical, and biological assessments. The second goal of this study was to better understand the direct and indirect effects of hierarchical variables on water quality in the Charles River watershed. Our first objective of our second goal (G2O1) was to calculate land use land cover percentages at the pour-point subwatershed and local 100-meter buffer scale for each of our ten 100-meter reach sampling stations. Our second objective of our second goal (G2O2) was to use path analysis to determine the direct and indirect effects of land use land cover and impervious surface on water quality in the Charles River watershed. The results of G1O1 were that habitat quality assessments ranged from “marginal” to “optimal” and biological quality assessments ranged from “fair” to “good“, indicating overall “fair” or better water quality conditions in the watershed. The results of G2O2 were that our path analysis resulted in differences in effects of development between the buffer and sub-watershed scale. At the buffer scale, water quality was influenced more negatively by the percentage of developed land area versus the percentage of impervious cover. While both buffer development and habitat quality had a direct effect on Streamside Biosurvey Macroinvertebrates, buffer development also directly hindered habitat quality, thus having an indirect effect on Streamside Biosurvey Macroinvertebrates through habitat. Streamside Biosurvey Macroinvertebrate scores were shown to be more sensitive to development within the buffer versus at the sub-watershed scale, where impervious cover was a more important indicator of stream water quality. Through this small case study of 10 stations within the Charles River watershed, we illustrated how citizen-science level water quality assessments can be combined with water chemistry and hierarchical LULC data to provide insights into potential direct and indirect effects on water quality. As the fields of landscape ecology and conservation continue to grow, so does our ability to determine changes in land development and devise management strategies aimed at improving water quality.

The disparity in tree cover and ecosystem service values among redlining classes in the United States

In the 1930’s the Federal Home Loan Bank Board established a program to appraise real estate risk levels in several cities. Four classes indicating level of security for real estate investments were developed: A (green) – best, B (blue) – still desirable, C (yellow) – declining, and D (red) – hazardous. Recent studies have shown that heat island effects are greater, imperviousness is higher, and tree cover lower in areas that were formerly redlined (class D). This paper analyzed all redlined areas in U.S. cities and confirms that redlined areas (class D) have lower tree cover, greater impervious cover and lower forest ecosystem service values than other classes, with tree cover declining and impervious cover increasing as security risk class increased. Nationally, tree cover averaged 40.1 percent in class A and 20.8 percent in Class D; impervious cover averaged 30.6 in Class A and 53.0 percent in Class D. Loss of annual ecosystem services in riskier redlined areas (classes B-D) compared to the highest rated zone (class A) conservatively equates to $308 million nationally if classes B-D had the percent tree cover exhibited in Class A. At the city scale, these losses in foregone services can reach up to $100 million per year (New York, NY). As percent tree cover and percent tree cover stocking declines as percent impervious cover increases, differences in the physical impervious structure of the redlined areas at the time of designation influence tree cover differences. As redlined areas were often delimited in areas with higher population density and impervious cover, these areas tend have lower tree cover today. Even if stocking levels were increased to levels exhibited in Class A (57.8%) among all classes, tree cover would still decrease as class risk increases due to less available greenspace in lower graded classes. These patterns illustrate the importance of impervious cover on the distribution of ecosystem services and understanding the impacts of redlining practices. City policies could be directed to help offset these disparities by enhancing tree cover and reducing impervious cover in these under-resourced areas.

Assessing urban rainfall‐runoff response to stormwater management extent

AbstractWe report an empirical analysis of the hydrologic response of three small, highly impervious urban watersheds to pulse rainfall events, to assess how traditional stormwater management (SWM) alters urban hydrographs. The watersheds vary in SWM coverage from 3% to 61% and in impervious cover from 45% to 67%. By selecting a set of storm events that involved a single rainfall pulse with >96% of total precipitation delivered in 60 min, we reduced the effect of differences between storms on hydrograph response to isolate characteristic responses attributable to watershed properties. Watershed‐average radar rainfall data were used to generate local storm hyetographs for each event in each watershed, thus compensating for the extreme spatial and temporal heterogeneity of short‐duration, intense rainfall events. By normalizing discharge values to the discharge peak and centring each hydrograph on the time of peak we were able to visualize the envelope of hydrographs for each group and to generate representative composite hydrographs for comparison across the three watersheds. Despite dramatic differences in the fraction of watershed area draining to SWM features across these three headwater tributaries, we did not find strong evidence that SWM causes significant attenuation of the hydrograph peak. Hydrograph response for the three watersheds is remarkably uniform despite contrasts in SWM, impervious cover and spatial patterns of land cover type. The primary difference in hydrograph response is observed on the recession limb of the hydrograph, and that change appears to be associated with higher storm‐total runoff in the watersheds with more area draining to SWM. Our findings contribute more evidence to the work of previous authors suggesting that SWM is less effective at attenuating urban hydrographs than is commonly assumed. Our findings also are consistent with previous work concluding that percent impervious cover may have greater influence on runoff volume than percent SWM coverage.

Satellites to Sprinklers: Assessing the Role of Climate and Land Cover Change on Patterns of Urban Outdoor Water Use

AbstractOutdoor water use represents over 50% of total water demand in semiarid and arid cities and presents both challenges to and opportunities for improved efficiency and water resilience. The current work adapts a remote sensing‐based methodology to estimate growing season irrigation rates at the census block group scale in Denver, Colorado. Results show that city‐wide outdoor water use does not change significantly from 1995 to 2018, while per capita water use and total water use significantly decrease from 2000 to 2018. Because total water use, but not outdoor use, is decreasing, the percent of water used outdoors significantly increases across the city from 2000 to 2018. Climate variables account for one‐quarter of interannual variation in mean irrigation rates due primarily to changes in temperature, not precipitation. Percent impervious land cover exhibits a significant inverse nonlinear relationship with irrigation rates at the census block group scale. Finally, 38% of Denver census block groups show significantly increasing irrigation rates between 1995 and 2018 driven primarily by increasing temperatures. The increasing proportion of water used for irrigation highlights the importance of outdoor demand management for urban water systems as indoor efficiencies improve. We advocate that resilient water systems necessitate integrated land use, infrastructure, and water planning in the face of urban growth and climate change. While minimizing irrigated urban areas may reduce demand, remaining green spaces should be designed to maximize multiple benefits including reductions in water demand and urban heat islands, stormwater management, and recreation to improve the sustainability of growing cities.

Environmental Vulnerability Assessment and Stormwater Management to Enhance Watershed Performance

The declination of environmental quality triggers several harmful impacts on society, such as the increasing of water-borne diseases, low quality of health, and lousy habitat ecosystem. The research aims to conduct a vulnerability assessment method of a watershed and to perform stormwater management to increase the catchment performance due to dynamic changes. The observation focused on Sugutamu sub-catchment, Depok, West Java. The evaluation includes sub-watershed map compilation, impervious cover calculation, river assessment, and restoration capacity evaluation. The result indicates that the sub-catchment describes as restorable non-supporting sub-watershed. There are three main regions in the sub-catchment. These areas have a percentage of impervious cover 95.6%, 72.5%, and 38.5%, respectively. Also, according to the future impervious cover prediction, these areas will have 97.8%, 95.3%, and 97.5%, respectively. The paper used the National Stormwater Calculator and EPA SWMM 5.1 software to visualize and to predict the future condition of sub-watershed with the various scenario. The application of low impact development (LID) in the research area declines the level of runoff, enhances the level of infiltration, and reduces the peak discharge. The research concludes that watershed vulnerability assessment, along with stormwater management, could control flooding in urban areas.

Accuracy assessment of NLCD 2011 percent impervious cover for selected USA metropolitan areas

The emergence of high-resolution land cover data has created the opportunity to assess the accuracy of impervious cover (IC) provided by the National Land Cover Database (NLCD). We assessed the accuracy of the 900 m2 NLCD2011 %IC for 18 metropolitan areas throughout the conterminous United States using reference data from 1 m2 land cover data developed as part of the United States Environmental Protection Agency’s EnviroAtlas project. Agreement was assessed from two perspectives: 1) sensitivity to the size of the assessment unit used for the comparison, and 2) utility of NLCD %IC to serve as a proxy for high-resolution IC. The former perspective was considered because statistical relationships can be sensitive to assessment unit size and shape, and the latter perspective was considered because high resolution (reference) %IC data are not available nationwide. The utility of NLCD %IC as a proxy for the high resolution data was assessed for seven lattice (square) cell sizes ranging from 1 ha to 200 ha using four EnviroAtlas IC indicators: 1) %IC per 100 ha (1 km2); 2) %IC by Census block group; 3) %IC within a 15 m (radius) of the riparian zone, and; 4) %IC within a 50 m (radius) of the riparian zone. Agreement was quantified as per assessment unit deviation (NLCD %IC – reference %IC) and summarized as Mean Absolute Deviation (MAD) and Mean Deviation (MD) both within and across the 18 metropolitan areas. Ordinary least squares (OLS) regression (y = reference %IC and x = NLCD %IC) was also used to evaluate the quality of the NLCD %IC data. MAD was ≤ 5% for six of the seven lattice cell sizes. MAD was also ≤ 5% for Census block groups > 100 ha and for both riparian units. These results suggest that uncertainty attributable to the measurement of %IC was no greater than the uncertainty related to the effect of IC on aquatic resources that have been derived from studies of aquatic condition (e.g., benthic fauna) over a range of %IC. Overall, agreement was variable from one metropolitan area to the next. Agreement improved as assessment unit size increased and declined as the level of urbanization (NLCD %IC) increased. NLCD %IC tended to underestimate reference %IC overall, but NLCD %IC was sometimes greater than reference %IC in urbanized settings.

Urbanization induces bird color homogenization

Urbanization acts as an environmental filter that allows bird species with certain ecological traits, such as a generalist diet and nesting on buildings, to occur in urban centers. However, its effect on other bird traits, such as plumage color, has still not been studied. The aim of this study was to analyze changes in plumage diversity and composition along urbanization gradients of three cities in central Argentina: Mar del Plata, Balcarce and Miramar. Bird surveys were made in urban, suburban and rural areas using transects during two breeding seasons. Color description and bird size were obtained from the literature. Color diversity was calculated using functional diversity indices: FD and FDis. Null models that control for species richness were used to estimate standardized effect sizes. Color composition was analyzed using Non-metric multidimensional scaling. FD and FDis decreased with percentage of impervious cover and increased with habitat diversity, whereas FDis also showed an interaction between city type and impervious cover. After both indices were controlled for species richness, they showed decreases with impervious cover and effects of city type. Highly urbanized areas were dominated by grey color, plumage dimorphism, polymorphism and small and medium sizes. Sites with high habitat diversity were inhabited by species of yellow and green coloration, whereas rural areas were occupied by large species with combinations of black, brown and white. More urbanized areas show not only fewer species, but also species that look more similar than expected by chance. These results suggest that urbanization acts as an environmental filter for bird colors, allowing the presence of birds with similar colors.

Optimising statistical models to predict faecal pollution in coastal areas based on geographic and meteorological parameters

This article describes a methodology for optimising predictive models for concentrations of faecal indicator organisms (FIOs) in coastal areas based on geographic and meteorological characteristics of upstream catchments. Concentrations of FIOs in mussels and water sampled from 50 sites in the south of Brazil from 2012 to 2013 were used to develop models to separately predict the spatial and temporal variations of FIOs. The geographical parameters used in predictive models for the spatial variation of FIOs were human population, urban area, percentage of impervious cover and total catchment area. The R2 of models representing catchments located within 3.1 km from the monitoring points was up to 150% higher than that for the nearest catchment. The temporal variation of FIOs was modelled considering the combined effect of meteorological parameters and different time windows. The explained variance in models based on rainfall and solar radiation increased up to 155% and 160%, respectively.

Estimating percent impervious cover from Landsat-based land cover with a simple and transferable regression model

ABSTRACTPercent impervious cover (PIC) is a widely used metric in ecological and hydrological analyses because it is highly correlated with pollutant and storm water run-off. The moderate-resolution satellite data (e.g. Landsat), that are typically used to calculate PIC, tend to overestimate PIC for all but very rural and very urban landscapes. Existing models for calibrating PIC estimates (e.g. ISAT, ETIS) are limited in that they are applicable only for specific land cover datasets and may also require population data; furthermore, these models have not been tested for performance outside of the geographic locations in which they were developed. The goal of this study was to explore simple but widely applicable regression models as tools for calibrating PIC estimates based on moderate resolution satellite data. The regression models used impervious land cover, from Landsat-based datasets, as the sole predictor of actual PIC. PIC was calculated for analysis units, ranging in size from 2.25 ha to ≥100 ha, for locations in Connecticut, Massachusetts, and Ohio in the United States. Regression models were fit for each size class of analysis unit at each study location; generalized versions of the models were created by fitting a regression to all size classes of analysis units at a given study location. Calibrated PIC estimates had root mean square error (RMSE) values that ranged from 1.5–10.7%; these values were considerably better than RMSE values for uncalibrated PIC estimates which ranged from 10.1–23.3%. For both calibrated and uncalibrated PIC, the accuracy of the estimates improved with the increasing size of the analysis units. Model regression coefficients were similar regardless of the analysis unit size, geographic location, or land cover dataset; model performance declined only slightly when applied outside the area in which it was developed. The simple regression models developed in this study had similar performance to previous calibration models (i.e. ISAT, ETIS) but are easier to apply and more widely applicable.

Development of correlation-regression model between land use change and water quality indices in Ciliwung watershed

Urbanization and industrialization lead to the change of land cover from pervious into impervious. This can impact environmental problems such as water quality degradation that affects human health and water ecosystems. The study aimed to develop a regression-correlation model between impervious cover in Ciliwung watershed and water quality indices in Ciliwung river. The correlation-regression model can be used to predict changes in the status of Ciliwung river water quality due to impervious cover changes. Methods of assessing the indices of water quality are CCME-WQI, NSF-WQI, and STORET within the period of 2005-2016. Monitoring locations from the most upstream to downstream are Atta’awun, Katulampa, Kedung Halang, Pondok Rajeg, Panus Bridge, Kelapa Dua, Condet, Kalibata, MT Haryono and Manggarai. Impervious cover data for each water quality monitoring location is processed using ArcGIS Software. Test of correlation significance between percentage of impervious cover and water quality indices using Pearson Correlation test method. The result of correlation test is significantly a strong inverse relationship between impervious cover and water quality indices. The result of regression test is trend line between impervious cover change and water quality indices that can be used to predict the change of water quality status in Ciliwung River.

Temporal Trends in the Spatial Distribution of Impervious Cover Relative to Stream Location

AbstractUse of impervious cover is transitioning from an indicator of surface water condition to one that also guides and informs watershed planning and management, including Clean Water Act (33 U.S.C. §1251 et seq.) reporting. Whether it is for understanding surface water condition or planning and management, impervious cover is most commonly expressed as summary measurement (e.g., percentage watershed in impervious cover). We use the National Land Cover Database to estimate impervious cover in the vicinity of surface waters for three time periods (2001, 2006, 2011). We also compare impervious cover in the vicinity of surface waters to watershed summary estimates of impervious cover for classifying the spatial pattern of impervious cover. Between 2001 and 2011, surface water shorelines (streams and water bodies) in the vicinity of impervious cover increased nearly 10,000 km. Across all time periods, approximately 27% of the watersheds in the continental United States had proximally distributed impervious cover, i.e., the percentage of impervious cover in the vicinity of surface waters was higher than its watershed summary expression. We discuss how impervious cover spatial pattern can be used to inform watershed planning and management, including reporting under the Clean Water Act.

Effect of urbanization on the long-term persistence of streamflow records

We investigate here the effect of urbanization on the temporal behavior of streamflow records. To this end, we analyzed daily streamflow records from 22 urban basins using the scaling exponents for long-term correlated records and the multifractality strength. Additionally, we separated the streamflow into fast and slow components and performed the analysis separately on each of these time series. Overall, results indicate that in the most urbanized basins, with percent impervious cover greater than 25, the long-term correlation exponents for streamflow are generally lower than in the least urbanized basins (percent impervious cover less than 10), while the multifractality strength does not seem to be appreciably affected by the urbanization process. Based on the correlation exponents, we also found that in the most urbanized basins streamflow records tend to be more similar to quickflow and precipitation than in the least urbanized basins. Thus, the loss of long-term persistence in the most urbanized basins may be explained by their lesser ability, due to the combined presence of impervious surfaces and conventional stormwater infrastructure, to filter the precipitation forcing. We conclude that the correlation exponents can be useful for assessing the temporal alteration of streamflow in urban basins.

Quantifying Urban Watershed Stressor Gradients and Evaluating How Different Land Cover Datasets Affect Stream Management.

Watershed management and policies affecting downstream ecosystems benefit from identifying relationships between land cover and water quality. However, different data sources can create dissimilarities in land cover estimates and models that characterize ecosystem responses. We used a spatially balanced stream study (1) to effectively sample development and urban stressor gradients while representing the extent of a large coastal watershed (>4400km(2)), (2) to document differences between estimates of watershed land cover using 30-m resolution national land cover database (NLCD) and <1-m resolution land cover data, and (3) to determine if predictive models and relationships between water quality and land cover differed when using these two land cover datasets. Increased concentrations of nutrients, anions, and cations had similarly significant correlations with increased watershed percent impervious cover (IC), regardless of data resolution. The NLCD underestimated percent forest for 71/76 sites by a mean of 11% and overestimated percent wetlands for 71/76 sites by a mean of 8%. The NLCD almost always underestimated IC at low development intensities and overestimated IC at high development intensities. As a result of underestimated IC, regression models using NLCD data predicted mean background concentrations of NO3 (-) and Cl(-) that were 475 and 177%, respectively, of those predicted when using finer resolution land cover data. Our sampling design could help states and other agencies seeking to create monitoring programs and indicators responsive to anthropogenic impacts. Differences between land cover datasets could affect resource protection due to misguided management targets, watershed development and conservation practices, or water quality criteria.

Regional impacts of urbanization on stream channel geometry: A case study in semiarid southern California

Urbanization often increases storm runoff, peak discharges and rates of stream channel erosion. Coastal California has experienced rapid urbanization over the past several decades and has the potential for stream channel degradation. Several counties in California have implemented Hydromodification Management Plans (HMPs) to protect channels from erosion, but few studies have quantified the impact of urbanization on channel geometry in diverse geological settings at the county scale. A synoptic survey of field sites (N=56) by the California Environmental Data Exchange Network (CEDEN) and additional field surveys (N=24) were used to develop regional hydraulic geometry curves relating bankfull cross-sectional area (Axs), width (w), mean depth (d), and discharge (Qbf) to watershed area (Aw) in San Diego County. Regional curves were compared for urban and reference sites and to other regional curves developed for southern California. Multiple regression models were used to identify dominant watershed and channel controls on geometry, including Aw, percent impervious cover (I%), mean annual precipitation, underlying geology, longitudinal slope, hydrologic soil group, and channel particle size. For the reference streams, regional curves were statistically significant for w and Axs (p<0.05). The regional curves for urban channels (I%>20%) had significantly larger w, d, Axs, and Qbf for a given watershed size. A majority (68%) of the urban channels and 78% of the small urban channels (Aw<10km2) were enlarged. Enlargement of channels in small watersheds disrupted the correlation between Aw and bankfull dimensions, and I% was the only significant predictor of channel geometry in urban watersheds. Channel response differed by channel substrate: sand-bedded channels incised and experienced extreme enlargement of up to 115× the Axs of reference sites, while gravel-bedded channels widened and showed less enlargement (<7× reference Axs). Diverse channel responses to urbanization were observed at the county scales with significant scatter about the regional curves and regression equations. Urban channels have a high probability of enlargement, with greater risk for sand-bedded streams, but the magnitude of enlargement was not predictable from watershed or channel characteristics.

Spatio-temporal variation in stream water chemistry in a tropical urban watershed

Urban activities and related infrastructure alter the natural patterns of stream physical and chemical conditions. According to the Urban Stream Syndrome, streams draining urban landscapes are characterized by high concentrations of nutrients and ions, and might have elevated water temperatures and variable oxygen concentrations. Here, we report temporal and spatial variability in stream physicochemistry in a highly urbanized watershed in Puerto Rico. The main objective of the study was to describe stream physicochemical characteristics and relate them to urban intensity, e.g., percent impervious surface cover, and watershed infrastructure, e.g., road and pipe densities. The Rio Piedras Watershed in the San Juan Metropolitan Area, Puerto Rico, is one of the most urbanized regions on the island. The Rio Piedras presented high solute concentrations that were related to watershed factors, such as percent impervious cover. Temporal variability in ion concentrations lacked seasonality, as did all other parameters measured except water temperature, which was lower during winter and highest during summer, as expected based on latitude. Spatially, stream physicochemistry was strongly related to watershed percent impervious cover and also to the density of urban infrastructure, e.g., roads, pipe, and building densities. Although the watershed is serviced by a sewage collection system, illegal discharges and leaky infrastructure are probably responsible for the elevated ion concentration found. Overall, the Rio Piedras is an example of the response of a tropical urban watershed after major sewage inputs are removed, thus highlighting the importance of proper infrastructure maintenance and management of runoff to control ion concentrations in tropical streams.

Impervious surfaces and sewer pipe effects on stormwater runoff temperature

Summary The warming effect of the impervious surfaces in urban catchment areas and the cooling effect of underground storm sewer pipes on stormwater runoff temperature are assessed. Four urban residential catchment areas in the Cities of Guelph and Kitchener, Ontario, Canada were evaluated using a combination of runoff monitoring and modelling. The stormwater level and water temperature were monitored at 10 min interval at the inlet of the stormwater management ponds for three summers 2009, 2010 and 2011. The warming effect of the ponds is also studied, however discussed in detail in a separate paper. An artificial neural network (ANN) model for stormwater temperature was trained and validated using monitoring data. Stormwater runoff temperature was most sensitive to event mean temperature of the rainfall (EMTR) with a normalized sensitivity coefficient (Sn) of 1.257. Subsequent levels of sensitivity corresponded to the longest sewer pipe length (LPL), maximum rainfall intensity (MI), percent impervious cover (IMP), rainfall depth (R), initial asphalt temperature (AspT), pipe network density (PND), and rainfall duration (D), respectively. Percent impervious cover of the catchment area (IMP) was the key parameter that represented the warming effect of the paved surfaces; sensitivity analysis showed IMP increase from 20% to 50% resulted in runoff temperature increase by 3 °C. The longest storm sewer pipe length (LPL) and the storm sewer pipe network density (PND) are the two key parameters that control the cooling effect of the underground sewer system; sensitivity analysis showed LPL increase from 345 to 966 m, resulted in runoff temperature drop by 2.5 °C.