scholarly journals Impacts of impervious surface expansion on soil organic carbon – a spatially explicit study

2015 ◽  
Vol 5 (1) ◽  
Author(s):  
Yan Yan ◽  
Wenhui Kuang ◽  
Chi Zhang ◽  
Chunbo Chen
2021 ◽  
Vol 13 (14) ◽  
pp. 7901
Author(s):  
Jifeng Du ◽  
Mengxiao Yu ◽  
Junhua Yan

Empirical evidence shows that the expansion of impervious surface threatens soil organic carbon (SOC) sequestration in urbanized areas. However, the understanding of deep soil excavation due to the vertical expansion of impervious surface remains limited. According to the average soil excavation depth, we divided impervious surface into pavement (IS20), low-rise building (IS100) and high-rise building (IS300). Based on remote-sensing images and published SOC density data, we estimated the SOC storage and its response to the impervious surface expansion in the 0–300 cm soil depth in Guangzhou city, China. The results showed that the total SOC storage of the study area was 8.31 Tg, of which the top 100 cm layer contributed 44%. The impervious surface expansion to date (539.87 km2) resulted in 4.16 Tg SOC loss, of which the IS20, IS100 and IS300 contributed 26%, 58% and 16%, respectively. The excavation-induced SOC loss (kg/m2) of IS300 was 1.8 times that of IS100. However, at the residential scale, renovating an IS100 plot into an IS300 plot can substantially reduce SOC loss compared with farmland urbanization. The gains of organic carbon accumulation in more greenspace coverage may be offset by the loss in deep soil excavation for the construction of underground parking lots, suggesting a need to control the exploitation intensity of underground space and promote residential greening.


2021 ◽  
Vol 7 (9) ◽  
pp. eaaz5236 ◽  
Author(s):  
Umakant Mishra ◽  
Gustaf Hugelius ◽  
Eitan Shelef ◽  
Yuanhe Yang ◽  
Jens Strauss ◽  
...  

Large stocks of soil organic carbon (SOC) have accumulated in the Northern Hemisphere permafrost region, but their current amounts and future fate remain uncertain. By analyzing dataset combining >2700 soil profiles with environmental variables in a geospatial framework, we generated spatially explicit estimates of permafrost-region SOC stocks, quantified spatial heterogeneity, and identified key environmental predictors. We estimated that 1014−175+194 Pg C are stored in the top 3 m of permafrost region soils. The greatest uncertainties occurred in circumpolar toe-slope positions and in flat areas of the Tibetan region. We found that soil wetness index and elevation are the dominant topographic controllers and surface air temperature (circumpolar region) and precipitation (Tibetan region) are significant climatic controllers of SOC stocks. Our results provide first high-resolution geospatial assessment of permafrost region SOC stocks and their relationships with environmental factors, which are crucial for modeling the response of permafrost affected soils to changing climate.


CATENA ◽  
2012 ◽  
Vol 92 ◽  
pp. 113-121 ◽  
Author(s):  
Shengxiang Xu ◽  
Xuezheng Shi ◽  
Yongcun Zhao ◽  
Dongsheng Yu ◽  
Shihang Wang ◽  
...  

2013 ◽  
Vol 10 (11) ◽  
pp. 18359-18406 ◽  
Author(s):  
Y. Yagasaki ◽  
Y. Shirato

Abstract. In order to develop a system to estimate a country-scale soil organic carbon stock change (SCSC) in agricultural lands in Japan that enables to take account effect of land-use changes, climate, different agricultural activity and nature of soils, a spatially-explicit model simulation system using Rothamsted Carbon Model (RothC) integrated with spatial and temporal inventories was developed. Future scenarios on agricultural activity and land-use change were prepared, in addition to future climate projections by global climate models, with purposely selecting rather exaggerated and contrasting set of scenarios to assess system's sensitivity as well as to better factor out direct human influence in the SCSC accounting. Simulation was run from year 1970 to 2008, and to year 2020, with historical inventories and future scenarios involving target set in agricultural policy, respectively, and subsequently until year 2100 with no temporal changes in land-use and agricultural activity but with varying climate to investigate course of SCSC. Results of the country-scale SCSC simulation have indicated that conversion of paddy fields to croplands occurred during past decades, as well as a large conversion of agricultural fields to settlements or other lands that have occurred in historical period and would continue in future, could act as main factors causing greater loss of soil organic carbon (SOC) at country-scale, with reduction organic carbon input to soils and enhancement of SOC decomposition by transition of soil environment to aerobic conditions, respectively. Scenario analysis indicated that an option to increase organic carbon input to soils with intensified rotation with suppressing conversion of agricultural lands to other land-use types could achieve reduction of CO2 emission due to SCSC in the same level as that of another option to let agricultural fields be abandoned. These results emphasize that land-use changes, especially conversion of the agricultural lands to other land-use types by abandoning or urbanization accompanied by substantial changes in the rate of organic carbon input to soils, could cause a greater or comparable influence on country-scale SCSC compared with changes in management of agricultural lands. A net-net based accounting on SCSC showed potential influence of variations in future climate on SCSC, that highlighted importance of application of process-based model for estimation of this quantity. Whereas a baseline-based accounting on SCSC was shown to have robustness over variations in future climate and effectiveness to factor out direct human-induced influence on SCSC. Validation of the system's function to estimate SCSC in agricultural lands, by comparing simulation output with data from nation-wide stationary monitoring conducted during year 1979–1998, suggested that the system has an acceptable levels of validity, though only for limited range of conditions at current stage. In addition to uncertainties in estimation of the rate of organic carbon input to soils in different land-use types at large-scale, time course of SOC sequestration, supposition on land-use change pattern in future, as well as feasibility of agricultural policy planning are considered as important factors that need to be taken account in estimation on a potential of country-scale SCSC.


2021 ◽  
Author(s):  
Yan Yan ◽  
Weige Zhang ◽  
Yunfeng Hu ◽  
Huaipeng Liu ◽  
Xiaoping Zhang ◽  
...  

Abstract Precise spatiotemporal datasets of artificial impervious surfaces (AISs) are essential for evaluating urbanization processes and associated soil organic carbon (SOC) dynamics. However, spatially explicit studies on SOC stocks based on high-quality AIS data remain deficient, which affects the accuracy of urban SOC budgets. In this study, we used 30-m Landsat images and a subpixel-based model to accurately evaluate and quantify the annual AIS of Kaifeng, an ancient city in China that experienced intensive urbanization from 2000 to 2020. Soil organic carbon (SOC) dynamics were further estimated and spatially exhibited based on the SOC densities (SOCD) of different land covers observed in the field. Our results demonstrate that Kaifeng experienced drastic AIS expansion from 2000–2020, both in total area (an increase of ~154.35%) and density (described by mean AIS abundance, 0.56 vs. 0.72). Spatially, AIS mainly sprawled to the west, and infilling was observed in the old town. Moreover, the expansion of AIS in Kaifeng has resulted in a total of 0.08 Tg of SOC loss over the past 20 years, and the study area has acted as a clear carbon source. The greatest SOC losses occurred during 2010 — 2015, mainly in the west — with >30% (~0.024 Tg) of the total loss occurring between 2010 and 2015. This study provides new insights into urban growth through the mapping of growth patterns in terms of both outward sprawl and infill. We also provide a novel means of presenting the spatial patterns of urbanization-induced SOC dynamics using subpixel AIS maps.


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