Impervious Area Research Articles

Evaluating Factors Affecting Flood Susceptibility in the Yangtze River Delta Using Machine Learning Methods

AbstractFloods are widespread and dangerous natural hazards worldwide. It is essential to grasp the causes of floods to mitigate their severe effects on people and society. The key drivers of flood susceptibility in rapidly urbanizing areas can vary depending on the specific context and require further investigation. This research developed an index system comprising 10 indicators associated with factors and environments that lead to disasters, and used machine learning methods to assess flood susceptibility. The core urban area of the Yangtze River Delta served as a case study. Four scenarios depicting separate and combined effects of climate change and human activity were evaluated using data from various periods, to measure the spatial variability in flood susceptibility. The findings demonstrate that the extreme gradient boosting model outperformed the decision tree, support vector machine, and stacked models in evaluating flood susceptibility. Both climate change and human activity were found to act as catalysts for flooding in the region. Areas with increasing susceptibility were mainly distributed to the northwest and southeast of Taihu Lake. Areas with increased flood susceptibility caused by climate change were significantly larger than those caused by human activity, indicating that climate change was the dominant factor influencing flood susceptibility in the region. By comparing the relationship between the indicators and flood susceptibility, the rising intensity and frequency of extreme precipitation as well as an increase in impervious surface areas were identified as important reasons of heightened flood susceptibility in the Yangtze River Delta region. This study emphasized the significance of formulating adaptive strategies to enhance flood control capabilities to cope with the changing environment.

Pattern-based assessment of the influence of catchment characteristics on urban stormwater quality

ABSTRACT Use of traditional catchment characteristics and lack of effective separation of catchment characteristics from rainfall characteristics limits the adequate understanding of the actual influences of catchment characteristics on stormwater quality. In this context, this study adopted a pattern-based separation approach to identifying common events from three rainfall clusters of study catchments, where rainfall characteristics for identified common 8, 9 and 36 events are similar, but catchment characteristics are different. This study identified that the locations of pervious surfaces and urban forms are also important catchment characteristics. The contribution of the pervious area to runoff is significant for long durational (cluster 1) and high-intensity (cluster 3) rainfall events associated with low antecedent dry days and initiated at around 35 mm rainfall depth. A catchment having a large impervious area and pervious area located at far distances from the drainage system can contribute more pollutant load at first 10% runoff volume. High socio-economic developed urban form can contribute a high fraction wash-off corresponding to 10–70% runoff volume due to traffic-related behaviour and various anthropogenic activities. The developed knowledge will overcome the shortcomings of lumped characteristics-based treatment design and improve the efficiency of current stormwater treatment system design practices.

Combined effects of urbanization and climate variability on water and carbon balances in a rice paddy-dominated basin in Southern China

Abstract Urbanization is known to elevate storm runoff, but how it influences carbon cycle and ecosystem productivity through altering the evapotranspiration (ET) process is less clear. We examined the combined effects of urbanization including change in impervious surface area (ISA) and climate variability on the water and carbon balances of the Qinhuai River Basin (QRB) over 2001-2018. QRB represents a typical rice paddy-dominated region that experienced rapid urbanization in southern China. We improved a monthly scale Water Supply Stress Index (WaSSI) ecosystem service model by integrating local eddy flux measurements and high-resolution remote sensing data. We found a significant downward trend in both ET (−4.6 mm yr-1, p<0.05) and gross primary productivity (GPP) (−10.4 gC m-2 yr-1, p<0.05) but a significant upward trend in water yield (Q) (+28.6 mm yr-1, p<0.05). These ecosystem function changes coincided with a 96% increase in urban areas, 23.2% increase in ISA, and a 37% reduction in rice paddy fields. The mean annual watershed GPP decreased from 1048 gC m-2 to 998 gC m-2 while the annual Q increased from 284 mm to 669 mm from 2001 to 2018. Scenario modelling experiments suggested that the negative impacts of loss of rice paddy fields and increase in ISA on ET and GPP overwhelmed the positive impacts of climate warming. The reduction in GPP and increase in Q were largely attributed to the increases in ISA, not necessarily due to changes in land use types (e.g., urban area). The expansion of urban area, increase in ISA and reduction in leaf area index, and increase in precipitation explained the increase in Q. Our research offers insight about the interactions of carbon and water cycles through the critical ET processes under a changing climate and land surface characteristics at a watershed level. Our modelling tool and analysis provides land managers and policy makers information for designing effective ‘Urban Nature-based Solutions’ to mitigate the negative environmental effects of urbanization on carbon and water.

Floods modeling and analysis for Dubai using HEC-HMS model and remote sensing using GIS

Floods accompanied by thunderstorms in developed cities are hazardous, causing damage to infrastructure. To secure infrastructure, it is important to employ an integrated approach, combining remote sensing, GIS and precipitation data. The model was developed based on the estimation of event-based runoff and investigated the relationship between runoff and impervious surfaces. The novel approach of combining Hydrologic Engineering Center’s River Analysis System (HEC-GeoRAS) along with satellite imagery was utilized, where spatial data was combined with real-time values to run the model. As a first step, the Hydrologic Engineering Center-Hydrologic Modeling System (HEC-HMS) model was fed with information about precipitation, slope, soil type, as well as land use and land cover. The results reveal that the subbasins of Deira, Nief and Jumeirah have the largest impervious area and, thus, a higher probability of flood occurrence. The model was calibrated and validated using previous runoff events and by comparing observed and simulated streak flow and peak discharge against those reported in previous studies. It was found that the model is efficient and can be used in similar regions.

Assessment of Fine-Scale Urban Heat Health Risk and Its Potential Driving Factors Based on Local Climate Zones in Shenzhen, China

Cities are facing increased heat-related health risks (HHRs) due to the combined effects of global warming and rapid urbanization. However, few studies have focused on HHR assessment based on fine-scale information. Moreover, most studies only analyze spatial HHR patterns and do not explore the potential driving factors. In this study, we estimated the potential HHRs based on the “hazard–exposure–vulnerability” framework by using multisource data, including the modified thermal–humidity index (MTHI), population density, and land cover. Then, the variations in the HHRs among different local climate zones (LCZs) at the fine spatial scale were analyzed in detail. Finally, we compared the different contributions of the LCZs and types of land cover to the HHRs and their three components by using multiple linear regression models. The results indicate that the spatial pattern of the HHRs was different from those of the individual components, and high-hazard regions do not mean high HHRs. There were huge variations in the HHRs among the different LCZs. The built-up LCZs typically had much higher HHRs than the natural ones, with compact LCZs facing the most severe risk. LCZ 6 (open low-rise buildings) had a relatively low HHR and should be paid more attention in future urban planning. Compared to the LCZs, the land covers better explained the variations in the HHR. In contrast, the LCZs better predicted the land surface temperatures. However, both the LCZs and land covers made only slight contributions to the heat exposure and vulnerability. Furthermore, the manmade buildings and impervious surface areas contributed much more to the HHR than the natural land covers. Therefore, the arrangement of the warming LCZs and land cover types is worthy of further investigation from the perspective of HHR mitigation.

Water quality benefits of implementing Green and Blue Infrastructure in a peri-urban catchment – Case study of a Brazilian metropolis

This paper investigates the effectiveness of Green and Blue Infrastructure (GBI) in managing non-point source pollution in the 120 km2 catchment of the Vargem das Flores reservoir, which supplies water to 600,000 inhabitants in the Belo Horizonte metropolitan area, Brazil's third-largest metropolis. A calibrated water quality model within the Storm Water Management Model (SWMM) was used to simulate total suspended solids (TSS) and nutrients loads under different future land use scenarios. The first scenario reflects maximum urban development according to current legislation. An alternative scenario was proposed considering the protection of forest remnants and the adoption of the most cost-effective GBI techniques in newly developed areas. Results indicated a substantial contribution of diffuse pollution to the reservoir's water quality degradation, mainly due to TSS loads transported from the most urbanized subcatchments. The application of bioretention cells to treat 12.6 km2 new impervious areas effectively mitigated diffuse pollution, removing 52.1% of TSS, 19.5% of total phosphorus (TP), and 17.1% of chemical oxygen demand (COD) loads flowing into the reservoir. The GBI implementation would maintain pollutant loads similar to current levels despite the increased urbanization.

Remote Sensing Mapping and Analysis of Spatiotemporal Patterns of Land Use and Cover Change in the Helong Region of the Loess Plateau Region (1986–2020)

Land use and cover change (LUCC) is directly linked to the sustainability of ecosystems and the long-term well-being of human society. The Helong Region in the Loess Plateau has become one of the areas most severely affected by soil and water erosion in China due to its unique geographical location and ecological environment. The long-term construction of terraces and orchards is one of the important measures for this region to combat soil erosion. Despite the important role that terraces and orchards play in this region, current studies on their extraction and understanding remain limited. For this reason, this study designed a land use classification system, including terraces and orchards, to reveal the patterns of LUCC and the effectiveness of ecological restoration projects in the area. Based on this system, this study utilized the Random Forest classification algorithm to create an annual land use and cover (LUC) dataset for the Helong Region that covers eight periods from 1986 to 2020, with a spatial resolution of 30 m. The validation results showed that the maps achieved an average overall accuracy of 87.54% and an average Kappa coefficient of 76.94%. This demonstrates the feasibility of the proposed design and land coverage mapping method in the study area. This study found that, from 1986 to 2020, there was a continuous increase in forest and grassland areas, a significant reduction in cropland and bare land areas, and a notable rise in impervious surface areas. We emphasized that the continuous growth of terraces and orchards was an important LUCC trend in the region. This growth was primarily attributed to the conversion of grasslands, croplands, and forests. This transformation not only reduced soil erosion but also enhanced economic efficiency. The products and insights provided in this study help us better understand the complexities of ecological recovery and land management.

Spatio-temporal Evolution of Land Use in Guangdong-Hong Kong-Macao Greater Bay Economic Area, 1985-2022 and Analysis of Influencing Factors

This research employs GIS and remote sensing technology, along with time-series Land cover data, to examine the evolving patterns of various land use categories (such as forest land, cultivated land, and impervious surfaces) within the Guangdong-Hong Kong-Macao Greater Bay Area. The results indicate that the predominant spatial configuration of land use in this region follows a sequence of "forest land-cultivated land-impervious land." Notably, the key transformation observed involves the conversion of cultivated land to impervious surfaces, resulting in a cumulative expansion of impervious areas by 3,346,985 hectares between 1985 and 2022. Moreover, the level of spatial integration among land use types in the Greater Bay Area is progressively standardizing, with notable advancements in scientific, technological, economic, and transportation sectors leading to a high degree of synergy. The system as a whole demonstrates effective coordination and operational efficiency. The methodology section outlines the data sources and analytical techniques employed, encompassing the utilization of the land use transfer matrix, individual land use degree assessment, and spatial coupling function model. Through these methodologies, the study identifies urban economic development as the primary driver behind the proliferation of impervious surfaces, offering valuable insights to inform regional development strategies and environmental governance policies.

Sensitivity Analysis and Parameterization of Gridded and Lumped Models Representation for Heterogeneous Land Use and Land Cover

Hydrological processes can be highly influenced by changes in land use land cover (LULC), which can make hydrological modelling also very sensitive to land cover characterization. Therefore, obtaining up-to-date LULC data is a crucial process in hydrological modelling, and as such, different sources of LULC data raises questions on their quality and applicability. This is especially true with new data sources, such as citizen science-based land cover maps. Therefore, this research aims to explore the influence of LULC data sources on hydrological models via their parameterization and by performing sensitivity analyses. Kiffissos catchment, in Greece, a poorly gauged and highly urbanized basin including the city of Athens, is the case study area. In total, 12 continuous hydrological models were developed by mainly varying their structure and parametrization (lumped and gridded) and using three LULC datasets: coordination of information on the environment (CORINE), Urban Atlas and Scent (citizen-based). It was found that excess precipitation is negligibly contributed to by soil saturation and is dominated by the runoff over impervious areas. Therefore, imperviousness was the main parameter influencing both sensitivity to land cover and parameterization. Lastly, although the parametrization as lumped and gridded models affected the representation of hydrological processes in pervious areas, it was not relevant in terms of excess precipitation.

Exploring Stormwater Best Management Practices for Urban Flood Reduction in Khulna City of Bangladesh Using PCSWMM

Khulna City Corporation (KCC), located in a low-lying area in southwestern Bangladesh, has been suffering from frequent water logging in the rainy season almost every year. This situation is intensified due to rapid urbanization and the impact of climate change, which have consequently created numerous problems in KCC related to stormwater management issues that require immediate consideration. Therefore, the current study aims to explore stormwater management problems in KCC and find possible countermeasures through different best management practices. Stormwater management must be incorporated into urban design and development, particularly in densely populated urban areas like KCC. In Ward No. 30 of KCC, controlling stormwater is a vital concern due to heavy rainfall, a lack of proper drainage infrastructure, unplanned growth, extensive land cover areas, etc. In the current study, the most widely used Personnel Computer Storm Water Management Model (PCSWMM) software was adopted to evaluate the city's current stormwater management practices and develop a long-term stormwater management strategy. A reconnaissance investigation of the existing states of the soil, drainage, and outlet infrastructures was conducted. The study area (KCC Ward No. 30) was then divided into many small catchments in the ArcGIS platform, and areas of each sub-catchment were identified. To determine the percentage of impervious area and the elevation of the study area, the land use and land cover (LULC) map and the digital elevation model (DEM) were generated using the ArcGIS software. All the aforementioned parameters were then entered into the PCSWMM software, and simulations were performed for various rainfall durations using different best management practices. The PCSWMM simulation provided the results of runoff, infiltration, peak runoff, floods, or surcharges at every drainage node or discharge point in the existing and altered drainage system of the study area due to the occurrence of extreme rainfall. The results indicate that various best management practices, increasing the slope, reducing the roughness of the drainage systems, reducing imperviousness, permitting more infiltrations, and promoting green infrastructure, are highly effective in controlling urban flooding or surcharges in the study area caused by the occurrence of extreme rainfall in the future. The findings of this study are expected to be supportive to policymakers, urban planners, and water managers in implementing and promoting sustainable and climate-resilient urban drainage infrastructures to tackle stormwater management problems in the KCC area. Journal of Engineering Science 15(1), 2024, 107-118

Thermal Environments of Residential Areas: Sunlight and Building Shadow in a Chinese City with Hot and Humid Summers

With a primary focus on sunlight and building shadows, we studied the impact of residential building orientation angles, building heights, and area combinations, as well as the underlying surface materials, on the outdoor thermal environment in Changsha, a city located north of the Tropic of Cancer. On the basis of Changsha’s regulations, the research results indicate that building orientation angles of 15–45° and 315–345° can generate more building-shadow areas and have a better effect on improving the outdoor thermal environment. Based on the study of many common residential block building layouts in Changsha, we believe that, for point-pattern residential blocks, an increase in building lengths can be very effective for increasing building-shadow areas and thermal comfort. For row-pattern residential blocks, an increase in building heights can be regarded as more effective for increasing building-shadow areas and reducing air temperatures. Shadow areas formed on impervious surface material areas, such as concrete pavements, reduce the air temperature more than shadow areas formed on natural surfaces, such as grasslands. For the planning and regeneration of residential areas, urban planners should focus on placing more green spaces in areas which are seldom or never covered by building shadows; they should also focus on installing more impervious surfaces in areas covered by building shadows. These strategies are beneficial for making full use of building shadows to reduce air temperatures in residential areas.

Exploring the influence of urban agglomeration on extreme precipitation: Evidence from the middle reaches of the Yangtze River, China

Study regionThe urban agglomeration in the middle reaches of the Yangtze River (MRUA) consisting of 31 cities is a pillar of the Yangtze River Economic Belt and the largest urban agglomeration in China, densely populated, and rapidly urbanizing. Study focusExtreme precipitation events are affected by rapidly urbanized regions with uneven levels of urbanization. Hence, it is important to explore the spatiotemporal evolution of extreme precipitation in urban agglomerations and the influence of the spatially uneven development of urban areas under rapid large-scale urbanization. New hydrological insights for the regionExtreme precipitation indices (Pmax1d, R20, and PF95) exhibited significant positive trends during 1979–2018 in the MRUA, increasing by 0.43 mm/year, 0.11 day/year, and 2.46 mm/year, respectively. Regression models based on raster urbanization data were constructed, and the impervious area ratio (IA) and landscape shape index (SI) were shown to be the dominant urbanization factors affecting regional extreme precipitation, with a particularly positive spatial correlation with PF95 and Pmax1d at all stages of urbanization. Moreover, the urban-rural comparison results revealed that the difference in SI of each city was positively correlated with the urban heat island intensity. In the three provincial capitals, Pmax1d and R50 were greater in urban centres than in rural areas. This study contributes to a comprehensive understanding in the variability of extreme precipitation events under the influence of large-scale urbanization.

Land Surface Temperature Anomalies as Indicators of Urban Land Cover Change—A Study of Two Indian Cities

Rapid urbanisation over the years has led to the loss of natural land cover, thereby affecting Land Surface Temperature (LST) distribution in urban areas. This study aims to analyse LST anomalies (calculated as the deviation from the normal) over selected Indian cities and check if critical land cover changes can be identified. LST from Landsat Thermal Infrared (TIR) images acquired in March, April and May from 1988 to 2020 were used to estimate LST anomalies. Positive LST anomalies were observed mainly over barren and impervious areas; however, some areas showed a negative anomaly where the barren lands were converted to vegetated areas. The study has demonstrated that while some developed areas exhibit a positive anomaly indicative of significant changes or development, there are instances where the conversion of barren land to developed (i.e. built up) areas has resulted in a negative anomaly. Developed areas that are closer to the water creek or mangroves were associated with lower anomaly values indicating the cooling effect of the water body and vegetation. Conversely, the core urban areas generally exhibited higher LST values with positive anomalies indicating a warming effect. These findings can be used by city planners to identify hotspot areas and develop more effective strategies and policies to address the challenges of urban heat. They also highlight the regions that require infrastructural resources and policy changes to reduce the temperature.

How does urban form explain water cooling effect heterogeneity: A case study in Wuhan, China

Water bodies in urban areas are considered to be natural and effective cooling factors that can help mitigate the urban heat island (UHI) effect. Previous studies highlighted the cooling effect is determined by the size and landscape of the water bodies. However, it is unclear how the urban form surrounding water bodies influences the water cooling effect received by human activity space. Using high resolution data and a multiple linear regression model, the effect of various 2D/3D urban form factors on the average water cooling intensity (AWCI) and water cooling intensity (WCI) at the fine scale were examined in Wuhan City on hot days. We further verified the spatial heterogeneity of the relationship between urban form factors and WCI according to the distance to and size of adjacent water bodies. The AWCI of the entire surrounding area were correlated with building morphology indicators. Urban form indicators effectively explained the variations of WCI at the fine scale, indicating that a mixture of large building volume density (BVD) with small building density (BD), and an aggregated impervious surface area (ISA) with a complex shape were conducive to WCI. Additionally, building morphology had a larger impact on the cooling effect around small water bodies and in the outer buffer area of water bodies. In comparison, the cooling effect of the area surrounding large water bodies was more affected by the landscape of the ISA. We therefore propose a differentiated urban planning strategy to take full use of the limited water cooling effect.

Analyzing Thermal Environment Contributions and Driving Factors of LST Heterogeneity in Different Urban Development Zones

Analyzing the impacts of urban landscape patterns on the thermal environment has become one of the key research areas in addressing urban heat islands (UHIs) and improving the living environment. A case study was carried out in Fuzhou, Fujian Province of China, and bi-temporal Landsat imagery was selected to calculate land surface temperature (LST), percent impervious surface area (ISA), and fractional vegetation cover (FVC). The urban area was further divided into three concentric urban zones, ranging from the city center to the urban periphery, based on urban development densities. The spatial pattern of LST and its variance were analyzed and compared between different zones and different dates. The thermal environment contribution of different zones was also quantified to indicate the change in urban landscape patterns resulting from urban expansion in different zones. Furthermore, Geodetector was used to explore the single factors and interaction factors controlling the spatial patterns of LST in each zone. The results showed that (i) urban expansion primarily increased in Zone 2 and Zone 3, and the areal proportion of high and sub-high LST areas increased from 56.11% and 21.08% to 62.03% and 32.49% in Zone 2 and Zone 3, respectively, from 2004 to 2021; (ii) the heat effect contribution of Zones 2 and 3 reached from 75.16% in 2004 to 89.40% in 2021, indicating that the increase in ISA with >LSTmean was more pronounced in Zone 3 and Zone 2 during the period; (iii) the driving factors of LST spatial distribution were regionally different because of the different landscape patterns, and the explanatory power for the heterogeneity of LST in Zone 1 was weaker than in Zone 2 and Zone 3 in the study area; (iv) the interaction of different factors had a higher explanatory power in the spatial distribution of LST than a single factor in each zone because the distributions of land cover types are heterogeneous in urban areas. The results of this study can be used to improve urban planning for urban ecology and UHI mitigation.

Drivers of long-term changes in summer compound hot extremes in China: Climate change, urbanization, and vegetation greening

Induced by numerous environmental and anthropogenic factors, the frequency of compound hot extremes (CoHot) is increasing globally. However, there is a lack of a comprehensive understanding of the relative importance of different factors in the change of CoHot, as most studies focused solely on individual factors. We systematically attribute the long-term trends of summertime CoHot in China to 24 factors including climate background, climate change, urbanization (including impervious area expansion and three-dimensional urban morphology), and vegetation change, using partial least square regression (PLSR) and variable importance projections for analysis. Cross-evaluation results based on 2259 meteorological stations indicate that the PLSR model accurately simulates the trends of CoHot frequency, duration, and intensity, with a relative error of 4–20% from national to individual station scales. A warm and humid climate background, rising average summertime temperatures, impervious area expansions, high building volume densities, low building heights, and vegetation wilting are the main factors that favoring the increasing and intensifying trends of CoHot. Although summertime warming contributes the most, the significance of urbanization and vegetation greening has been growing in recent years. Urbanization's contribution increases from 9.3% on a national scale to over 40% in urban centers, mainly due to increased building volume density rather than expansions of impervious area. In northern China, vegetation greening has reduced the local increasing trends in frequency/duration of CoHot by 20% to 40%, and such mitigation effects are primarily induced by increased vegetation cover. Our results suggest that, reducing building volume density and promoting vegetation greening can mitigate the increasing risk of CoHot under global warming.

Simulasi Jaringan Drainase Kawasan Desa Lubuk Suli Kec. Depati VII Kabupaten Kerinci Menggunakan Program EPA SWMM Versi 5.1

One of the areas in Kerinci Regency that is often hit by floods is Lubuk Suli Village. Flooding was caused by overflowing water from the Batang Marao river. The main objective of this research is to provide information to the relevant government about good drainage for the Lubuk Suli Village Area using existing data and planning data by simulating the capability of the Drainage Network for the Lubuk Suli Village Area using the EPA SWMM 5.1 program. The data used in this research are land use maps to determine the percentage of impervious area, rainfall data and drainage channel dimension data in the area. The rain data series used is hourly rain data. Due to the absence of hourly rainfall data at the rain station at the research location, hourly rainfall distribution was determined by changing the Intensity-Duration-Frequency (IDF) curve for a 5 year return period into a planned rainfall hyetograph using the Alternating Block Method (ABM). After all parameters have been input into EPA SWMM 5.1. Simulation can be done. The simulation quality is quite good if the continuity error for surface runoff and flow tracing is > 10%. The simulation carried out in this research is divided into 2 scenarios, namely with existing data and additional storage. From the simulation results, it was found that in the 2 scenarios, the number of flood points in the simulation for scenario 1 was 6 points and in scenario 2 there were 5 points. This shows that the drainage planning design for the Lubuk Suli Village area has not been able to overcome the existing drainage load in the area.

Identifying factors influencing reservoir eutrophication using interpretable machine learning combined with shoreline morphology and landscape hydrological features: A case study of Danjiangkou Reservoir, China

Reservoir nearshore areas are influenced by both terrestrial and aquatic ecosystems, making them sensitive regions to water quality changes. The analysis of basin landscape hydrological features provides limited insight into the spatial heterogeneity of eutrophication in these areas. The complex characteristics of shoreline morphology and their impact on eutrophication are often overlooked. To comprehensively analyze the complex relationships between shoreline morphology and landscape hydrological features, with eutrophication, this study uses Danjiangkou Reservoir as a case study. Utilizing Landsat 8 OLI remote sensing data from 2013 to 2022, combined with a semi-analytical approach, the spatial distribution of the Trophic State Index (TSI) during flood discharge periods (FDPs) and water storage periods (WSPs) was obtained. Using Extreme Gradient Boosting (XGBoost) and SHapley Additive exPlanations (SHAP), explained the relationships between landscape composition, landscape configuration, hydrological topography, shoreline morphology, and TSI, identified key factors at different spatial scales and validated their reliability. The results showed that: (1) There is significant spatial heterogeneity in the TSI distribution of Danjiangkou Reservoir. The eutrophication levels are significant in the shoreline and bay areas, with a tendency to extend inward only during the WSPs. (2) The importance of landscape composition, landscape configuration, hydrological topography, and shoreline morphology to TSI variations during the FDPs are 25.12 %, 29.6 %, 23.09 %, and 22.19 % respectively. Besides shoreline distance, the Landscape Shape Index (LSI) and Hypsometric Integral (HI) are the two most significant environmental variables overall during the FDPs. Forest and grassland areas become the most influential factors during the WSPs. The influence of landscape patterns and hydrological topography on TSI varies at different spatial scales. At the 200 m riparian buffer zone, the increase in cropland and impervious areas significantly elevates eutrophication levels. (3) Morphology complexity, shows a noticeable threshold effect on TSI, with complex shoreline morphology increasing the risk of eutrophication.

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.

Substantial terrestrial carbon emissions from global expansion of impervious surface area

Global impervious surface area (ISA) has more than doubled over the last three decades, but the associated carbon emissions resulting from the depletion of pre-existing land carbon stores remain unknown. Here, we report that the carbon losses from biomass and top soil (0–30 cm) due to global ISA expansion reached 46–75 Tg C per year over 1993–2018, accounting for 3.7–6.0% of the concurrent human land-use change emissions. For the Annex I countries of UNFCCC, our estimated emissions are comparable to the carbon emissions arising from settlement expansion as reported by the national greenhouse gas inventories, providing independent validation of this kind. The contrast between growing emissions in non-Annex I countries and declining ones in Annex I countries over the study period can be explained by an observed emerging pattern of emissions evolution dependent on the economic development stage. Our study has implications for international carbon accounting and climate mitigation as it reveals previously ignored but substantial contributions of ISA expansion to anthropogenic carbon emissions through land-use effects.