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Assessing land degradation and quantifying its drivers in the Amudarya River delta

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Abstract
The shrinking of the Aral Sea is one of the most shocking environmental disasters in the world. The Amudarya River delta (AD) is highly vulnerable to land degradation. In this research, NDVI and albedo, which represent vegetation and soil conditions, were applied in change vector analysis (CVA) to monitor land degradation. The vegetation degradation and soil exposure characteristics of land degradation were considered. Furthermore, based on boosted regression trees (BRTs), eight potential driving factors (precipitation, temperature, drought, water withdrawal, canal, livestock, salt discharge and population) were chosen to explore their relative importance to land degradation. The results revealed that some land areas have gradually degraded and fell into high land degradation in the AD, especially in the downstream areas near the Aral Sea. Soil salinization is a major consequence of high land degradation in this region. Subsequently, 920.75 km(2) and 183.10 km(2) of abandoned croplands were converted to sparse vegetation and grasslands, respectively. The BRT model indicated that water withdrawal availability and decreased precipitation were the most influential factors explaining the land degradation of croplands and natural vegetation from 1990 to 2000, respectively. In contrast, the salt discharge to the field plot was a major force causing land degradation of different vegetation types in the subsequent time interval (2000-2015). Because an increase in the groundwater level resulted in secondary soil salinization, a large proportion (45%) of the increased salinization occurred during this time period. Notably, due to the accelerated shrinking of the Aral Sea, some land areas surrounding the sea have fallen into high land degradation. Our findings can contribute to the implementation of the land degradation neutrality initiative to deploy restoration plans in the AD.
Keywords
CLIMATIC WATER-BALANCE, CHANGE-VECTOR ANALYSIS, QUANTITATIVE ASSESSMENT, SOIL-SALINITY, DESERTIFICATION, REGION, IRRIGATION, DYNAMICS, ROMANIA, REHABILITATION, Land degradation, Climate change, Anthropogenic disturbances, Amudarya, River delta

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Citation

Please use this url to cite or link to this publication:

MLA
Jiang, Liangliang, et al. “Assessing Land Degradation and Quantifying Its Drivers in the Amudarya River Delta.” ECOLOGICAL INDICATORS, vol. 107, 2019.
APA
Jiang, L., Jiapaer, G., Bao, A., Li, Y., Guo, H., Zheng, G., … De Maeyer, P. (2019). Assessing land degradation and quantifying its drivers in the Amudarya River delta. ECOLOGICAL INDICATORS, 107.
Chicago author-date
Jiang, Liangliang, Guli Jiapaer, Anming Bao, Yaoming Li, Hao Guo, Guoxiong Zheng, Tao Chen, and Philippe De Maeyer. 2019. “Assessing Land Degradation and Quantifying Its Drivers in the Amudarya River Delta.” ECOLOGICAL INDICATORS 107.
Chicago author-date (all authors)
Jiang, Liangliang, Guli Jiapaer, Anming Bao, Yaoming Li, Hao Guo, Guoxiong Zheng, Tao Chen, and Philippe De Maeyer. 2019. “Assessing Land Degradation and Quantifying Its Drivers in the Amudarya River Delta.” ECOLOGICAL INDICATORS 107.
Vancouver
1.
Jiang L, Jiapaer G, Bao A, Li Y, Guo H, Zheng G, et al. Assessing land degradation and quantifying its drivers in the Amudarya River delta. ECOLOGICAL INDICATORS. 2019;107.
IEEE
[1]
L. Jiang et al., “Assessing land degradation and quantifying its drivers in the Amudarya River delta,” ECOLOGICAL INDICATORS, vol. 107, 2019.
@article{8650021,
  abstract     = {The shrinking of the Aral Sea is one of the most shocking environmental disasters in the world. The Amudarya River delta (AD) is highly vulnerable to land degradation. In this research, NDVI and albedo, which represent vegetation and soil conditions, were applied in change vector analysis (CVA) to monitor land degradation. The vegetation degradation and soil exposure characteristics of land degradation were considered. Furthermore, based on boosted regression trees (BRTs), eight potential driving factors (precipitation, temperature, drought, water withdrawal, canal, livestock, salt discharge and population) were chosen to explore their relative importance to land degradation. The results revealed that some land areas have gradually degraded and fell into high land degradation in the AD, especially in the downstream areas near the Aral Sea. Soil salinization is a major consequence of high land degradation in this region. Subsequently, 920.75 km(2) and 183.10 km(2) of abandoned croplands were converted to sparse vegetation and grasslands, respectively. The BRT model indicated that water withdrawal availability and decreased precipitation were the most influential factors explaining the land degradation of croplands and natural vegetation from 1990 to 2000, respectively. In contrast, the salt discharge to the field plot was a major force causing land degradation of different vegetation types in the subsequent time interval (2000-2015). Because an increase in the groundwater level resulted in secondary soil salinization, a large proportion (45%) of the increased salinization occurred during this time period. Notably, due to the accelerated shrinking of the Aral Sea, some land areas surrounding the sea have fallen into high land degradation. Our findings can contribute to the implementation of the land degradation neutrality initiative to deploy restoration plans in the AD.},
  articleno    = {105595},
  author       = {Jiang, Liangliang and Jiapaer, Guli and Bao, Anming and Li, Yaoming and Guo, Hao and Zheng, Guoxiong and Chen, Tao and De Maeyer, Philippe},
  issn         = {1470-160X},
  journal      = {ECOLOGICAL INDICATORS},
  keywords     = {CLIMATIC WATER-BALANCE,CHANGE-VECTOR ANALYSIS,QUANTITATIVE ASSESSMENT,SOIL-SALINITY,DESERTIFICATION,REGION,IRRIGATION,DYNAMICS,ROMANIA,REHABILITATION,Land degradation,Climate change,Anthropogenic disturbances,Amudarya,River delta},
  language     = {eng},
  pages        = {14},
  title        = {Assessing land degradation and quantifying its drivers in the Amudarya River delta},
  url          = {http://dx.doi.org/10.1016/j.ecolind.2019.105595},
  volume       = {107},
  year         = {2019},
}

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