Predicted models for potential canopy rainfall interception capacity of landscape trees in Shanghai, China

Guo, Jiankang; Yu, Bo; Yuan, Zhang; Che, Shengquan

doi:10.1007/s10342-017-1039-2

Cited by 12 publications

(12 citation statements)

References 28 publications

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“…From this study, we found that the CRIR at the basin scale in Guangdong ranged from 0.33% and 11.67%, which is similar to results in other studies in China that ranged from 0% and 12% [58]. However, this range is lower than that in forest ecosystems [57,59,60]. This is mainly because our study estimated the mean value of the CRIR for all vegetation ecosystems in the basin, which resulted in a lower estimated value when compared with that of a forest ecosystem.…”

Section: Discussionsupporting

confidence: 87%

“…However, this range is lower than that in forest ecosystems [57,59,60]. This is mainly because our study estimated the mean value of the CRIR for all vegetation ecosystems in the basin, which resulted in a lower estimated value when compared with that of a forest ecosystem.…”

Section: Discussionmentioning

confidence: 64%

“…As an interface for atmospheric rainfall in the vegetation ecosystem, vegetation canopy influences the redistribution of rainwater as well as the damping and retention of the water that reaches the soil, affecting runoff dynamics through interception [54,55] . However, previous studies on canopy rainfall interception [55][56][57] have mainly focused on individual plants or groups of plants through in situ observation and are limited by spatiotemporal estimation in larger areas. In this study, we applied a canopy rainfall interception model coupled with MODIS_LAI remote sensing data to understand the spatial and temporal variation patterns of canopy rainfall interception at the basin scale in Guangdong Province, China.…”

Section: Discussionmentioning

confidence: 99%

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Estimating Rainfall Interception of Vegetation Canopy from MODIS Imageries in Southern China

Liu

Sun

et al. 2019

Remote Sensing

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The interception of rainfall by vegetation canopies plays an important role in the hydrologic process of ecosystems. Most estimates of canopy rainfall interception in present studies are mainly through field observations at the plot region. However, it is difficult, yet important, to map the regional rainfall interception by vegetation canopy at a larger scale, especially in the southern rainy areas of China. To obtain a better understanding of the spatiotemporal variation of vegetation canopy rainfall interception with regard to the basin scale in this region, we extended a rainfall interception model by combining the observed rainfall data and moderate resolution imaging spectroradiometer leaf area index (MODIS_LAI) data to quantitatively estimate the vegetation canopy rainfall interception rate (CRIR) at small/medium basin scales in Guangdong Province, which is undergoing large changes in vegetation cover due to rapid urban expansion in the area. The results showed that the CRIR in Guangdong declined continuously during 2004-2012, but increased slightly in 2016, and the spatial variability of CRIR showed a diminishing yearly trend. The CRIR also exhibited a distinctive spatial pattern, with a higher rate to the east and west of the mountainous areas and a lower rate in the central mountainous and coastal areas. This pattern was more closely related to the spatial variation of the LAI than that of rainfall due to frequent extreme rainfall events saturating vegetation leaves. Further analysis demonstrated that forest coverage, instead of background climate, has a certain impact on the canopy rainfall interception, especially the proportion of broad-leaved forests in the basin, but more in-depth study is warranted in the future. In conclusion, the results of this study provide insights into the spatiotemporal variation of canopy rainfall interception at the basin scale of the Guangdong Province, and suggest that forest cover should be increased by adjusting the species composition to increase the proportion of native broad-leaved species based on the local condition within the basin. In addition, these results would be helpful in accurately assessing the impacts of forest ecosystems on regional water cycling, and provide scientific and practical implications for water resources management.

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Section: Discussionsupporting

confidence: 87%

Section: Discussionmentioning

confidence: 64%

Section: Discussionmentioning

confidence: 99%

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Estimating Rainfall Interception of Vegetation Canopy from MODIS Imageries in Southern China

Liu

Sun

et al. 2019

Remote Sensing

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“…As an important part of the urban ecosystem, most of the urban green space does not meet its design expectations. Attention is only paid to the aesthetics, causing poor performance regarding reduction of peak flow and pollutant load [21]. Therefore, the transformation of green space into a roadside bioretention system is necessary to resolve this problem.…”

Section: Introductionmentioning

confidence: 99%

Design and Performance Characterization of Roadside Bioretention Systems

et al. 2019

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In the current study, three roadside bioretention systems with different configurations were constructed to investigate their pollutant removal efficiency in different rainfall recurrence intervals. The bioretention systems (referred as units) (unit A: 700 mm height material without submerged zone; unit B: 400 mm height material with 300 mm submerged zone; unit C: 400 mm height material without submerged zone) were used to conduct the rainfall events with uniform 120 min rainfall duration for 2-, 5-, 10-, 15-, and 30-year recurrence intervals. Results reveal that the gradual increase of rainfall return period would have negative effects on TN and NH 4 + -N removal. The higher filler layer may increase pollutant removal efficiency. Setting a submerged zone could improve the COD Mn and TN removal compared to TP and NH 4 + -N removal. The values for comprehensive reduction rate of pollutant load in the three bioretention systems were recorded as follows: 64% in SS, 50%~80% in TP, 69% in NH 4 + -N, and 28%~53% in NO 3 -N separately. These results provide greater understanding of the design and treatment performance of bioretention systems.

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“…Green spaces include two parts: the overground part, with limbs and canopy; and the underground part, with roots and soil. Studies have suggested that limbs, canopy, and roots are related to rainwater regulation and storage capacity of green spaces [1]. Physical soil properties, especially soil porous characteristics, also have a great impact on rainfall infiltration [2].…”

Section: Introductionmentioning

confidence: 99%

Effects of Tree Root Density on Soil Total Porosity and Non-Capillary Porosity Using a Ground-Penetrating Tree Radar Unit in Shanghai, China

Xie

Cai³

et al. 2018

Sustainability

Self Cite

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To explore the relationship between arbor root density and corresponding physical soil properties (total porosity, non-capillary porosity, specific weight, bulk density, moisture content, and permeability), noninvasive methods such as Tree Radar Unit (TRU) were utilized to detect the root systems of 10 species of tree that are commonly used in Shanghai green spaces with more than 70% frequency of occurrence. Using TRU and soil investigation, root density and soil porous features were determined for different tree species, depth slices, and distances. The relationships among root density, soil porosity, and non-capillary porosity were identified using variance analysis and regression analysis. The results indicated that root density decreased with increasing distance from the trunk and soil depth. Soil porosity and non-capillary porosity had significantly positive and linear correlations with root density. Compared with lawns, trees such as Zelkova serrata, Koelreuteria paniculata, Cinnamomum camphora, and Metasequoia glyptostroboides had the greatest effects on soil improvement through soil porosity and non-capillary porosity. Due to the spatial distribution of root systems, trees could be divided into three types based on their influence at various soil depths.

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Predicted models for potential canopy rainfall interception capacity of landscape trees in Shanghai, China

Cited by 12 publications

References 28 publications

Estimating Rainfall Interception of Vegetation Canopy from MODIS Imageries in Southern China

Estimating Rainfall Interception of Vegetation Canopy from MODIS Imageries in Southern China

Design and Performance Characterization of Roadside Bioretention Systems

Effects of Tree Root Density on Soil Total Porosity and Non-Capillary Porosity Using a Ground-Penetrating Tree Radar Unit in Shanghai, China

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