Can evaporation from urban impervious surfaces be ignored?

Chen, Han; Huang‬‬‬‬, Jinhui Jeanne; Liang, Hong; Wang, Weimin; Li, Han; Wei, Yizhao; Jiang, Albert Z.; Zhang, Pengwei

doi:10.1016/j.jhydrol.2022.128582

Cited by 13 publications

(5 citation statements)

References 90 publications

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“…There is no accurate or uniform setting for H 0 , and its setting range is mainly between 0.5 and 2 mm (Chen et al, 2023; Ramamurthy & Bou‐Zeid, 2014; Willuweit & O'Sullivan, 2013; Zhou et al, 2021). Based on previous experiments and Chinese design specifications, H 0 was set to 2 mm (Zhou et al, 2021).…”

Section: Discussionmentioning

confidence: 99%

“…There is no accurate or uniform setting for H 0 , and its setting range is mainly between 0.5 and 2 mm (Chen et al, 2023;Ramamurthy & Bou-Zeid, 2014;Willuweit & O'Sullivan, 2013;Zhou et al, 2021).…”

Section: Effect Of the Maximum Water Interception Depthmentioning

confidence: 99%

“…However, owing to the highly heterogeneous urban surface, removing the influence of urban vegetation and soil ET and accurately extracting impervious surface evaporation is a technical challenge. EC technology also has spatiotemporal limitations; it lacks data collected during historical periods and cannot be used for large‐scale data analyses (Chen et al, 2023). The second method uses an empirical model.…”

Section: Introductionmentioning

confidence: 99%

“…Geometric registration and classification errors of land‐use pixels (Ackerman & Stein, 2008) have rendered some land‐use data unable to parameterize urban areas correctly (Dams et al, 2013) and meet the needs of mesoscale hydrological models (Montzka et al, 2008). Different area ratios are assigned to the main land cover types, including forests, grasslands, water bodies and impervious surfaces (Wegehenkel et al, 2006), and significantly affect the results of urban hydrological modelling (Chen et al, 2023; Wegehenkel et al, 2006; Zipper et al, 2017). This has further emphasized that accurate land use information is critical for accurate urban evaporation model results (Cheng & Byun, 2008).…”

Section: Introductionmentioning

confidence: 99%

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Spatiotemporal distribution and influencing factors of impervious surface evaporation in the Baiyangdian catchment from 1980 to 2020

Liu,

Mo,

Liu

et al. 2024

Hydrological Processes

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Evaporation from impervious surfaces plays a vital role in the catchment water cycle. Exploring the spatiotemporal variation patterns and influencing mechanisms of impervious surface evaporation at the catchment scale can improve the understanding and evaluation of the evaporation process. This study downloaded 0.5 m resolution images of the Baiyangdian catchment (BYD) from Google Earth and used deep learning to identify impervious surfaces. This was used to revise impervious surfaces of the China land cover dataset in 1985 and 1990–2020. Potential evaporation (PET) from three types of impervious surfaces (roofs, ground affected or not affected by the building height) was calculated by modifying the parameters of the Penman–Monteith equation, and daily precipitation and water‐storage capacity of impervious surfaces were taken into account to estimate impervious surface evaporation (E). The results showed that E values of the three types of impervious surfaces were between 72.1 and 178.2 mm/year and all exhibited the spatial distribution of high in the northwest and low in the southeast of the BYD in 1980–2020. Compared with that in 1980, in 2020, the cumulative evaporation (EAP) increased by 134.4%. The ratio of EAP to cumulative precipitation ranged from 3.0% to 6.9%, increasing significantly in a fluctuating manner. The increments in precipitation days and impervious surface area played a major role in the increase of EAP, and the decrease in precipitation was the fundamental reason for the increase in the proportion of impervious surface evaporation and water resource pressure in the BYD. Excluding the continuous evaporation from the remaining water can likely lead to underestimating the impervious surface evaporation. This study provides an efficient and reasonable novel approach for calculating impervious surface evaporation in long series and large‐scale catchments.

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Section: Discussionmentioning

confidence: 99%

Section: Effect Of the Maximum Water Interception Depthmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Spatiotemporal distribution and influencing factors of impervious surface evaporation in the Baiyangdian catchment from 1980 to 2020

Liu,

Mo,

Liu

et al. 2024

Hydrological Processes

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“…The rapid increase in urban impervious surface area has altered the biogeochemical processes associated with the soil-atmosphere gas exchange within the urban ecosystems and their response to global climate change. An urban impervious surface not only weakens surface transpiration and evaporation but also interferes with the exchange of water and heat between the surface and the atmosphere [4].…”

Section: Introductionmentioning

confidence: 99%

Spatiotemporal Modeling of Carbon Fluxes over Complex Underlying Surfaces along the North Shore of Hangzhou Bay

Zhang,

Zhao,

Zhao

et al. 2024

Atmosphere

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Urban areas contribute to over 80% of carbon dioxide emissions, and considerable efforts are being undertaken to characterize spatiotemporal variations of CO2 (carbon dioxide) at a city, regional, and national level, aiming at providing pipelines for carbon mission reduction. The complex underlying surface composition of urban areas makes process-based and physiology-based models inadequate for simulating carbon flux in this context. In this study, long short-term memory (LSTM), support vector machine (SVM), random forest (RF), and artificial neural network (ANN) were employed to develop and investigate their viability in estimating carbon flux at the ecosystem level. All the data used in our study were derived from the long-term chronosequence observations collected from the flux towers within urban complex underlying surface, along with meteorological reanalysis datasets. To assess the generalization ability of these models, the following statistical metrics were utilized: coefficient of determination (R2), root mean square error (RMSE), and mean absolute error (MAE). Our analysis revealed that the RF model performed the best in simulating carbon flux over long time series, with the highest R2 values reaching up to 0.852, and exhibiting the smallest RMSE and MAE values at 0.293 μmol·m−2·s−1 and 0.157 μmol·m−2·s−1. As a result, the RF model was chosen for simulating carbon flux at spatial scale and assessing the impact of urban impervious surfaces in the simulation. The results showed that the RF model performs well in simulating carbon flux at the spatial scale. The input of impervious surface area index can improve the performance of the RF model in simulating carbon flux, with R2 values of 84.46% (with the impervious surface area index in) and 83.74% (without the impervious surface area index in). Furthermore, the carbon flux in Fengxian District, Shanghai, exhibited significant spatial heterogeneity: the CO2 flux in the western part of Fengxian District was less than in the eastern part, and the CO2 flux gradually increased from the west to the east. In addition, we creatively introduced the diurnal impervious surface area index based on the Kljun model, and clarified the influence of impervious surface on the spatiotemporal simulation of CO2 flux over the complex urban underlying surface. Based on these findings, we conclude that the RF models can be effectively applied for estimating carbon flux on the complex underlying urban surface. The results of our study reduce the uncertainty in modeling carbon cycling in terrestrial ecosystems, and make the variety of models for the carbon cycling of terrestrial ecosystems more diverse.

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Effects of landscape pattern on water quality at multi-spatial scales in Wuding River Basin, China

Zhao,

Li,

Yan

et al. 2024

Environ Sci Pollut Res

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Can evaporation from urban impervious surfaces be ignored?

Cited by 13 publications

References 90 publications

Spatiotemporal distribution and influencing factors of impervious surface evaporation in the Baiyangdian catchment from 1980 to 2020

Spatiotemporal distribution and influencing factors of impervious surface evaporation in the Baiyangdian catchment from 1980 to 2020

Spatiotemporal Modeling of Carbon Fluxes over Complex Underlying Surfaces along the North Shore of Hangzhou Bay

Effects of landscape pattern on water quality at multi-spatial scales in Wuding River Basin, China

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