Percent Impervious Surface Research Articles

Exploring the Relationships between Impervious Surface Percentage and Frequency of Urban Waterlogging: A Case Study in Hanoi, Vietnam

In developing countries, rapid urbanization reduces the natural land area and increases the impervious surface. At the same time, urban rainstorm waterlogging is also becoming more frequent and serious. Therefore, one of the important works to be done is to elucidate the relationship between impervious surface expansion and waterlogging frequency (WF) causes of urban waterlogging. To move forward, we used ENVI to classify land cover types and applied the spatial analysis methods integrated in ArcGIS with internet open data to explore these relationships in Hanoi, Vietnam in 2018. The results show that waterlogging frequency was positively related to impervious surface percentage (ISP), indicating that if the median values of ISP increased then the waterlogging frequency would increase as well with a confidence level of 63.2%. This study demonstrates the importance for controlling the impervious surface expansion in urban waterlogging risk management and urban planning.

Urban flood hazard mapping using a hydraulic–GIS combined model

Urban flooding is a reoccurring disaster, and its frequency and intensity are likely to increase in the future due to the increasing frequency of storm events. Up-to-date monitoring on the distribution of flood hazards in cities is necessary and valuable for urban planning. This research combines two common urban flooding approaches, namely hydraulic and GIS models, in a case study of London, Ontario, Canada. The hydraulic–GIS combined model employs the hydraulic concept in a simplified GIS frame, hence avoiding heavy computation in the hydraulic model and arbitrary coefficients in a GIS model. We used a binary logistic regression model to integrate the hydraulic concept in a GIS model. The multi-criteria GIS model built by binary logistic regression was able to simulate the results from the hydraulic model with good consistency. Such a strategy serves as a promising prototype for addressing similar geographical modelling issues, where the time-consuming physical model can be potentially replaced by a simplified GIS model. Furthermore, the impervious surface percentage is an important input in the hydraulic model. This research experimented different impervious surface percentages as input to the hydraulic model and found that a spatially variable impervious surface percentage achieves better agreement with hydraulic modelling than that of uniform (25% and 42%) impervious surface percentages.

Precipitation spatial patterns in cities with different urbanisation types: Case study of Novi Sad (Serbia) as a medium-sized city

A direct outcome of the global climate change is the modification of seasonal precipitation patterns, apparent on a monthly temporal scale. In Central Europe, it includes more frequent high-intensity rainfalls, occurring mostly during spring and summer. These heavy rainfalls induce pluvial floods in urban areas due to a high percentage of impervious surfaces and limited drainage systems. This hazard affects Central European cities and impacts many receptors, including lives, infrastructures, private properties or the functioning of cities. This study focuses on the monitoring of precipitation events with the aim of revealing precipitation patterns across two different types of land cover: urban and suburban/rural areas of Novi Sad (Serbia). Measurements from seven rain gauge stations were used as input data, covering the 2015-2018 period. The precipitation data were analysed using 12 precipitation indices, nine of which were defined by the Expert Team on Climate Change Detection and Indices (ETCCDI), while three additional were designed specifically for this study. Based on their locations, the stations were classified into the 'urbanized' and 'non-urbanised' group. The concept of the Local Climate Zone (LCZ) was used to classify urbanised areas LCZ1-8, non-urbanised areas LCZ9 and the land cover zones (LCZ A-G). A statistical analysis based on the ANOVA F-test was conducted, defining the significance threshold at 90% for a = 0.01 and at 95% for a = 0.05. The obtained results revealed one relation for the CDD index at 95% and two relations at 90% for CDD and Rp95 indices, showing a relation between heavy rainfall and the type of land cover. Statistical results underline the need for a denser station network and longer monitoring periods in order to proceed to stronger statistical tests and make it possible to establish other relations with the climate indices.

Estimation of large-scale impervious surface percentage by fusion of multi-source time series remote sensing data

Estimation of large-scale impervious surface percentage by fusion of multi-source time series remote sensing data

Identification of environmental drivers in urban greenway communities

Urban trails and greenspaces have become ubiquitous features in cities, in part due to their ability to provide ecological benefits to the built-up environment. A major factor in their popularity is their potential to enhance habitat connectivity by bridging the gaps between remnant patches across urbanized areas, however, information on the structure and function of greenways themselves is limited. In this study we examined how greenways serve as distinct habitats in their own right by characterizing the vegetative structure of the Capital Area Greenway (CAG) in Raleigh, NC. We conducted a systematic vegetation survey of woody vegetation along 39 km of trails (354 random plots) in 2016 and identified environmental variables related to site conditions (percent canopy cover, stream proximity, flood zones), management efforts (designated conservation areas), and local anthropogenic activities (percent impervious surface, street proximity). We preformed three types of multivariate analyses (non-metric multidimensional scaling (NMS), multi-response permutation procedures (MRPP), and indicator species analysis (ISA)) to distinguish potential influences on species distribution and community structure. We observed highly diverse riparian, upland mesic, and xeric forest communities within the CAG. Results from NMS and MRPP suggested that vegetation patterns can be differentiated based on local environmental variables. Sites located in conservation areas and floodplains, for instance, were typically found at further distances from streets and were characterized by greater basal area, canopy cover, and higher non-native species richness. Individual study sites were highly diverse and varied even within similar local environments. Our findings indicate that the CAG serves as established natural habitat for native vegetation, supporting the idea that greenways can be used to enhance environmental quality in cities as ecological corridors.

Ecosystem functioning in urban grasslands: The role of biodiversity, plant invasions and urbanization.

Urbanization is driving the transformation of natural and rural ecosystems worldwide by affecting both the abiotic environment and the biota. This raises the question whether urban ecosystems are able to provide services in a comparable way to their non-urban counterparts. In urban grasslands, the effects of urbanization-driven ecological novelty and the role of plant diversity in modulating ecosystem functioning have received little attention. In this study, we assessed the influence of biodiversity, abiotic and biotic novelty on ecosystem functioning based on in situ measurements in non-manipulated grasslands along an urbanization gradient in Berlin (Germany). We focused on plant aboveground biomass (AGB), intrinsic water-use efficiency (iWUE) and 15N enrichment factor (Δδ15N) as proxies for biomass production, water and N cycling, respectively, within grassland communities, and tested how they change with plant biogeographic status (native vs alien), functional group and species identity. Approximately one third of the forb species were alien to Berlin and they were responsible for 13.1% of community AGB. Community AGB was positively correlated with plant-species richness. In contrast, iWUE and Δδ15N were mostly determined by light availability (depicted by sky view factor) and urban parameters like the percentage of impervious surface or human population density. We found that abiotic novelty potentially favors aliens in Berlin, mainly by enhancing their dispersal and fitness under drought. Mainly urban parameters indicating abiotic novelty were significantly correlated to both alien and native Δδ15N, but to AGB and iWUE of alien plants only, pointing to a stronger impact of abiotic novelty on N cycling compared to C and water cycling. At the species level, sky view factor appeared to be the prevailing driver of photosynthetic performance and resource-use efficiency. Although we identified a significant impact of abiotic novelty on AGB, iWUE and Δδ15N at different levels, the relationship between species richness and community AGB found in the urban grasslands studied in Berlin was comparable to that described in non-urban experimental grasslands in Europe. Hence, our results indicate that conserving and enhancing biodiversity in urban ecosystems is essential to preserve ecosystem services related to AGB production. For ensuring the provision of ecosystem services associated to water and N use, however, changes in urban abiotic parameters seem necessary.

New Perspectives for Mapping Global Population Distribution Using World Settlement Footprint Products

In the production of gridded population maps, remotely sensed, human settlement datasets rank among the most important geographical factors to estimate population densities and distributions at regional and global scales. Within this context, the German Aerospace Centre (DLR) has developed a new suite of global layers, which accurately describe the built-up environment and its characteristics at high spatial resolution: (i) the World Settlement Footprint 2015 layer (WSF-2015), a binary settlement mask; and (ii) the experimental World Settlement Footprint Density 2015 layer (WSF-2015-Density), representing the percentage of impervious surface. This research systematically compares the effectiveness of both layers for producing population distribution maps through a dasymetric mapping approach in nine low-, middle-, and highly urbanised countries. Results indicate that the WSF-2015-Density layer can produce population distribution maps with higher qualitative and quantitative accuracies in comparison to the already established binary approach, especially in those countries where a good percentage of building structures have been identified within the rural areas. Moreover, our results suggest that population distribution accuracies could substantially improve through the dynamic preselection of the input layers and the correct parameterisation of the Settlement Size Complexity (SSC) index.

Estimating 2009–2017 Impervious Surface Change in Gwadar, Pakistan Using the HJ-1A/B Constellation, GF-1/2 Data, and the Random Forest Algorithm

The China–Pakistan Economic Corridor (CPEC) is the flagship project of the Belt and Road Initiative. At the end of the CPEC, the Gwadar port on the Arabian Sea is being built quickly, providing an important economical route for the flow of Central Asia’s natural resources to the world. Gwadar city is in a rapid urbanization process and will be developed as a modern, world-class port city in the near future. Therefore, monitoring the urbanization process of Gwadar at both high spatial and temporal resolution is vital for its urban planning, city ecosystem management, and the sustainable development of CPEC. The impervious surface percentage (ISP) is an essential quantitative indicator for the assessment of urban development. Through the integration of remote sensing images and ISP estimation models, ISP can be routinely and periodically estimated. However, due to clouds’ influence and spatial–temporal resolution trade-offs in sensor design, it is difficult to estimate the ISP with both high spatial resolution and dense temporal frequency from only one satellite sensor. In recent years, China has launched a series of Earth resource satellites, such as the HJ (Huangjing, which means environment in Chinese)-1A/B constellation, showing great application potential for rapid Earth surface mapping. This study employs the Random Forest (RF) method for a long-term and fine-scale ISP estimation and analysis of the city of Gwadar, based on the density in temporal and multi-source Chinese satellite images. In the method, high spatial resolution ISP reference data partially covering Gwadar city was first extracted from the 1–2 meter (m) GF (GaoFen, which means high spatial resolution in Chinese)-1/2 fused images. An RF retrieval model was then built based on the training samples extracted from ISP reference data and multi-temporal 30-m HJ-1A/B satellite images. Lastly, the model was used to generate the 30-m time series ISP from 2009 to 2017 for the whole city area based on the HJ-1A/B images. Results showed that the mean absolute error of the estimated ISP was 6.1–8.1% and that the root mean square error (RMSE) of the estimation results was 12.82–15.03%, indicating the consistently high performance of the model. This study highlights the feasibility and potential of using multi-source Chinese satellite images and an RF model to generate long-term ISP estimations for monitoring the urbanization process of the key node city in the CPEC.

A review of research on remote sensing for ground impervious surface percentage retrieval

A review of research on remote sensing for ground impervious surface percentage retrieval

Urbanization and elevated cholesterol in American Crows

Abstract Although urban areas can be sources of abundant food for wildlife, anthropogenic foods may be lower in quality than natural food sources, with possible consequences for birds. We examined how urbanization and anthropogenic food were linked to cholesterol levels, condition, and survival of American Crows (Corvus brachyrhynchos). We collected cholesterol and landscape data from 140 crow nestlings along an urban-to-rural gradient in Davis, California, USA. We also ran a supplementation experiment with high-cholesterol fast food (McDonald’s cheeseburgers) on 86 nestlings in a rural population in Clinton, New York, USA. Plasma cholesterol increased with percentage of impervious surface along the urban-to-rural gradient. Cholesterol levels were sensitive to anthropogenic foods: crows supplemented with fast food cheeseburgers had higher cholesterol levels than unsupplemented crows. Elevated cholesterol levels had no detectable effects on survival and were associated with higher indices of body condition, although urbanization itself was linked to lower survival. Elevated cholesterol levels could indicate access to high-calorie, high-fat anthropogenic foods, which might, in some contexts, improve body condition, potentially offsetting other negative effects of urbanization. Observations over a longer time scale, assessing additional indices of health and fitness, are needed to evaluate long-term costs or benefits of elevated cholesterol for urban crows.

Downsizing for downtown: Limb lengths, toe lengths, and scale counts decrease with urbanization in western fence lizards (Sceloporus occidentalis).

Urbanization induced habitat loss and alteration causes significant challenges for the survival of many species. Identifying how species respond to urbanization can yield insights for the conservation of wildlife, but research on reptiles has been narrowly-focused. We compared morphology among four populations of western fence lizards (Sceloporus occidentalis) to determine whether a common native species affected by urbanization exhibits morphological differences consistent with habitat use. We quantified habitat differences across four sites in Los Angeles County, California, USA that varied in level of urbanization, measured how lizards used microhabitats, and assessed variation in body size, limb length, toe length, and scalation of lizards collected from each site. Urban and suburban populations of fence lizards mostly used human-made substrates while lizards from more natural areas mostly used natural woody substrates. Lizards from the most urban site also exhibited the widest breadth of substrates used, indicating that urban sites might offer more variable microhabitats. Urban lizards had reduced limb lengths and toe lengths consistent with how they used microhabitats and other habitat characteristics (e.g., percent impervious surface cover). Urban lizards also had fewer dorsal scales, which might be associated with changes in ambient temperature (e.g., urban heat island effect), given that lizards with fewer and larger scales typically have reduced evaporative water loss. Our results uniquely differ from past studies on lizard responses to urbanization, indicating that work on diverse taxa is necessary to assess the potential varied pathways of morphological adaptations to urban environments.

Leaf litter decomposition and macroinvertebrate assemblages along an urban stream gradient in Puerto Rico

AbstractUrbanization is a major land use form that has large impacts on ecosystems. Urban development in the watershed impacts stream ecosystems by increasing nutrient and organic matter loads, altering hydrology, and reducing biodiversity. Puerto Rico is an ideal location to assess and monitor the effects of urbanization on streams, because it is increasingly urbanized and streams do not receive inputs of untreated sewage, characteristic of many other tropical urban areas. The objective of this study was to determine how leaf litter decomposition and aquatic macroinvertebrate assemblages varied along a tropical urban gradient. We conducted the study in the Río Piedras watershed, San Juan Metropolitan Area, in six low‐order streams that formed an urban gradient ranging from 10% to 70% urban land cover. At each stream, we placed six 5 g leaf bags of Ficus longifolia in three different pools and collected one bag on each sampling date. Decomposition rates were fast in forested streams (range 0.021–0.039/day) and decreased with increasing urbanization (range 0.007–0.008/day). Rates were strongly and negatively correlated with percent impervious surface cover (R = 0.81, p = 0.01). Functional feeding group diversity was higher in forested streams, with the presence of shredders. Decomposition rates were significantly and positively correlated with functional feeding group diversity and abundance (R = 0.66, p = 0.04). Overall, our results show that urbanization affected the environment and macroinvertebrate diversity resulting in large negative effects on stream ecosystem function.Abstract in Spanish is available with online material.

Performances of WorldView 3, Sentinel 2, and Landsat 8 data in mapping impervious surface

Many efforts have been made to map developed impervious surface from remotely sensed information in the last two decades. The U.S. Geological Survey (USGS) developed the National Land Cover Database (NLCD) to provide consistent land cover and change products for the Nation since 2001. Percent impervious surface area (ISA), one of the products in NLCD as a continuous field and estimated with Landsat imagery, represents the fraction of human-made impervious area in a 30 m resolution grid. ISA is used to map urban land cover types and extents for the United States. However, it is still a challenge to quantify highly heterogeneous features in many urban areas using remotely sensed data with spatial and spectral resolutions similar to Landsat and to determine the impacts of remotely sensed data characteristics on ISA mapping.

Interactive effects of urbanization and local habitat characteristics influence bee communities and flower visitation rates.

Current declines in the abundance and diversity of bees and other pollinators has created uncertainty in their ability to reliably deliver pollination services. Recent studies examining urban bee diversity have provided conflicting results, with some studies identifying parts of cities with high bee diversity and others documenting reduced diversity with high levels of urbanization, with potential effects on surrounding agricultural areas. However, these studies have not specifically investigated pollination services, or examined the influence of local habitat conditions on these services. We surveyed urban gardens and city parks across the metropolitan region of Toledo, Ohio (USA) to understand how urbanization (impervious surface) and local habitat characteristics (herbaceous cover, floral abundance and color, tree abundance, canopy cover, soil moisture, garden size) impact bee communities (abundance, diversity, composition) and pollination services (visitation frequency). We collected 729 bees representing 19 genera and 57 species. We found that bee community composition was strongly associated with percent impervious surface. Bee abundance declined with increased canopy cover and impervious surface, while declines in bee diversity with increasing impervious surface were greatly reduced by increases in floral resources. Visitation rates were positively correlated with bee abundance and diversity, declining with increased impervious surface, but increasing with floral resource availability. These results suggest that increasing floral resources at high impervious sites may counteract the negative effects of impervious surface on bee diversity and pollination services in cities similar to Toledo, OH.

Using biased sampling data to model the distribution of invasive shot-hole borers in California

The invasive shot-hole borers (ISHB), Coleoptera: Curculionidae: Scolytinae: Euwallacea spp. and their ambrosial fusaria symbionts were first detected in Southern California in 2003 and have since caused dieback and tree mortality in urban, agricultural, and natural environments. This research assesses the relative predictive ability of distribution models for ISHB. A series of 100-m resolution models were developed using the Maxent modeling tool to test the effects of three main parameters: length of sampling period, spatial extent, and spatial filtering. Five chronologically cumulative sampling periods, simulating stages of invasion, were used to train the models. To evaluate model predictions, we used independent test records from the 2012–2016 sampling period, as well as presence and absence data collected via 2018 field surveys. Testing the models against both datasets demonstrated that as length of sampling period increased, prediction errors decreased, and overall accuracy improved for predictions of ISHB host occurrence. All models achieved high presence-only, area under the receiver operating characteristic curve (AUCPO) values > 0.93 and correctly classified 87.7 ± 18.8% of independent test records, indicating high model performance regardless of the degree of temporal bias. Spatial filtering produced more discriminating results without compromising model sensitivity to test records. Sensitivity was consistently higher for models that used the larger spatial extent (state of California), which suggests that for an emerging species, larger backgrounds may produce less discriminating predictions. The relative contribution of the top environmental predictor variables, including minimum temperature of the coldest month, percent impervious surface, isothermality, and dry-season normalized difference vegetation index, differed according to the modeled spatial extent. Regardless of the parameters used, the study finds that ISHB distribution models reliably identified areas vulnerable to infestation. Such predictions, particularly those early in the study period, may have aided early containment and detection efforts.

Use of national-scale data to examine human-mediated additions of heavy metals to wetland soils of the US

Soil concentrations of 12 heavy metals that have been linked to various anthropogenic activities were measured in samples collected from the uppermost horizon in approximately 1000 wetlands across the conterminous US as part of the 2011 National Wetland Condition Assessment (NWCA). The heavy metals were silver (Ag), cadmium (Cd), cobalt (Co), chromium (Cr), copper (Cu), nickel (Ni), lead (Pb), antimony (Sb), tin (Sn), vanadium (V), tungsten (W), and zinc (Zn). Using thresholds to distinguish natural background concentrations from human-mediated additions, we evaluated wetland soil heavy metal concentrations in the conterminous US and four regions using a Heavy Metal Index (HMI) that reflects human-mediated heavy metal loads based on the number of elements above expected background concentration. We also examined the individual elements to detect concentrations of heavy metals above expected background that frequently occur in wetland soils. Our data show that wetland soils of the conterminous US typically have low heavy metal loads, and that most of the measured elements occur nationally in concentrations below thresholds that relate to anthropogenic activities. However, we found that soil lead is more common in wetland soils than other measured elements, occurring nationally in 11.3% of the wetland area in concentrations above expected natural background (> 35 ppm). Our data show positive relationships between soil lead concentration and four individual landscape metrics: road density, percent impervious surface, housing unit density, and population density in a 1-km radius buffer area surrounding a site. These relationships, while evident on a national level, are strongest in the eastern US, where the highest road densities and greatest population densities occur. Because lead can be strongly bound to wetland soils in particular, maintenance of the good condition of our nation’s wetlands is likely to minimize risk of lead mobilization.

Hybrid land use regression modeling for estimating spatio-temporal exposures to PM2.5, BC, and metal components across a metropolitan area of complex terrain and industrial sources

Land use regression (LUR) modeling has become a common method for predicting pollutant concentrations and assigning exposure estimates in epidemiological studies. However, few LUR models have been developed for metal constituents of fine particulate matter (PM2.5) or have incorporated source-specific dispersion covariates in locations with major point sources. We developed hybrid AERMOD LUR models for PM2.5, black carbon (BC), and steel-related PM2.5 constituents lead, manganese, iron, and zinc, using fine-scale air pollution data from 37 sites across the Pittsburgh area. These models were designed with the aim of developing exposure estimates for time periods of interest in epidemiology studies. We found that the hybrid LUR models explained greater variability in PM2.5 (R2 = 0.79) compared to BC (R2 = 0.59) and metal constituents (R2 = 0.34–0.55). Approximately 70% of variation in PM2.5 was attributable to temporal variance, compared to 36% for BC, and 17–26% for metals. An AERMOD dispersion covariate developed using PM2.5 industrial emissions data for 207 sources was significant in PM2.5 and BC models; all metals models contained a steel mill-specific PM2.5 emissions AERMOD term. Other significant covariates included industrial land use, commercial and industrial land use, percent impervious surface, and summed railroad length.

An evaluation of energy balance parameters, and the relations between topographical and biophysical characteristics using the mountainous surface energy balance algorithm for land (SEBAL)

ABSTRACTEnergy balance parameters are very important in various applications such as energy global cycle, environment, climatic change monitoring, weather forecast, agriculture. The present study evaluates the influence of topographical conditions on the amount of downward shortwave radiation (SWD) of the surface, as well as the relation between surface Net radiation with biophysical characteristics and region’s land use’s. For this purpose, Landsat images, Digital Elevation Model (DEM), and a set of sample points have been used. To calculate the downward shortwave radiation and Net radiation fluxes, it has employed the mountainous SEBAL algorithm. Greenness, Brightness, Wetness, Normalization Difference Built-up Index (NDBI), Normalization Difference Vegetation Index (NDVI) and Albedo parameters considered as surface biophysical characteristics. Brightness, NDBI and Albedo information shows the percentage of impervious‏ surfaces while Greenness and NDVI information is related to vegetation percentage and Wetness information concerns water-related rates as well as the wetness of the soil, plant, and built-up lands. Statistical analysis has been used to study the relationship between different parameters. Results show that the slope is the most influential topographical parameters on the amount of SWD of the surface. There is a reverse relation between the variants of SWD of the surface, and the slope of the surface, in second-degree polynomial form with a Pearson’s correlation coefficient (r) of 0.82. North aspect receive the minimum SWD average with a 681 W m–2 while flat lands receive the maximum SWD average with a 783 W m–2. Areas with the highest elevation, lowest slope, and flatlands, receive the highest SWD. Built-up lands have the lowest Net radiation flux average with a 595 W m–2 while water has the highest Net radiation flux average with a 761 W m–2. Net radiation flux is directly related with NDVI, Greenness and Wetness parameters, while it is reversely related to NDBI, Albebo and Brightness with a high r.

Characterizing the spatial pattern of annual urban growth by using time series Landsat imagery

Previous studies of urbanization have largely focused on the irreversible urban growth process and the conversion of non-urban lands into impervious surfaces, but less on the conversion from impervious surfaces to green space, also referred to as deurbanization. However, urbanization and deurbanization are both typical urban renewal process, which may happen simultaneously during the urban renewal. In this study, we proposed a new method to retrieve and map annual impervious surface percentage (ISP) and to characterize urban growth patterns using time series medium- resolution images. The method is implemented by employing the Cubist tree model for annual ISP inversion (AoCubist), optimizing multi-temporal Landsat composite images to minimize the impact of phenology and inter-year climate variation, and developing the C5.0 decision tree algorithm with temporal-spatial filtering rules to improve the space-time continuity and separability of patterns derived by unsupervised K-means classification. The method was applied to investigate the urban renewal in Guangzhou, China, between 2000 and 2010. The results demonstrate that the use of ISP slope series can capture the spatial variations and temporal trends of urban growth. Validation by fieldwork and comparing with Google Earth imagery indicates that our classification yielded a reasonable overall accuracy, ranging from 88.32% to 90.85%. Annual urban expansion rate remained between 4% and 10%, while annual deurbanization rate varied from 1% to 5%. In addition, the total pixels of rapid deurbanization surpassed that of rapid urban expansion. This finding suggests that various change directions occurred in the urban renewal process and that deurbanization was a way to counter-balance the rapid urbanization. This study provides a solid methodology for ISP change detection and fresh insight into the characteristics of urban growth in terms of timing, duration, and magnitude.

Runoff quantity response of three urban mountain parks-hilltop subtype in humid subtropical climate based on SWMM

With the development of sustainable stormwater management, urban parks have the advantages and necessities in constructing low impact development system to reduce and reuse stormwater. This study aims to understand the hydrological processes in small scale mountain watersheds based on three typical hilltop parks in Chongqing, China. Sub-catchment areas were divided into paved square type (PST), vegetation cover type (VCT) and mixed cover type (MCT). Native stromwater models by SWMM were created under 25 mm, 50 mm, 4 years and 20 years precipitation events to simulate the runoff quantity. The runoff quantity per unit area in different sub-catchments was provided as : PST > MCT >VCT. Runoff quantity affected by impervious surface percentage was the most significant compared to other parameters. Positive correlation between slop and runoff quantity was showed visibly when slop was above 42 degrees. Peak runoff could be affected by characteristic width of sub-catchment.