Modelling and managing critical zone relationships between soil, water and ecosystem processes across the Loess Plateau
Modelling and managing critical zone relationships between soil, water and ecosystem processes across the Loess Plateau
批准号:
NE/N007433/1
负责人:
Lianhai Wu
金额:
$51.22万
依托单位:
依托单位国家:
英国
项目类别:
Research Grant
财政年份:
2016
资助国家:
英国
项目状态:
已结题
起止时间:
2016 至 --
中文摘要
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英文摘要
The Loess Plateau of China covers an area 2.5x the size of the UK (some 640,000 square km) in the upper and middle reaches of China's Yellow River and is renowned for having the most severe soil erosion in the world; deforestation, over-grazing and poor agricultural practice have resulted in degenerated ecosystems, desertification and unproductive agriculture in the region. To control severe soil erosion on the Loess Plateau, the Chinese government imposed a series of policies for fragile ecosystems, such as the 1999 state-funded "Grain-for-Green" project, which has resulted in significant land use changes. Related programmes have produced beneficial effects on soil erosion and water cycles. However, the impact of these changes in soil and water processes on related ecosystem services is unknown and demands further study. The proposed research will focus on three spatial scales: slope, watershed, and region. It uses a combination of A) experiments to collect environmental, biological and agronomic data; B) remote sensing data and C) modelling approaches. A) Data collection: Four experimental stations located in four main topographical regions of the Plateau are chosen as case studies: 1) Ansai Comprehensive Experimental Station of Soil and Water Conservation; 2) Changwu Agro-ecology Experiment Station; 3) Guyuan Ecological Station; 4) Shenmu Erosion and Environment Station. At each station, treatments of different vegetative covers, slopes, and the practices of soil and water conservation at the plot scale were set up in the 1980s and data collections include: soil water, canopy size, runoff, soil losses and meteorological records. Most of the Chinese members of this project have been involved in prior studies at the stations.At the slope scale, additional environmental, biological and agronomic data will be monitored in a sub-set of the plots. At watershed scale, four watersheds where the stations are located will be monitored. The spatial distribution of the following variables will be measured: precipitation, soil properties, vegetative types, canopy size, runoff and soil loss.B) Remote sensing data collection: At the regional scale, remote sensing combined with ground-truthing data will be used to investigate the spatial variability of vegetation type, land cover, productivity, the components of water balance, soil losses, soil type, etc.C) Modelling approaches: a cascade approach will be used to build an improved model framework applied to different spatial scales. Mechanistic soil-water-plant models will be applied to the slope scale. Their outputs will then be used as inputs for models at watershed level. Spatial empirical/statistical models will be used at the regional level. Observed and collected data from A) and B) will be used to further develop, calibrate and validate our models.Model simulations at the slope level will be used to reveal the dynamic mechanisms in soil and water in different regions and analyse the effects of vegetation type, soil type, slope degree, climatic factors and management practice. Watershed models will estimate soil and water carrying capacity for different vegetation types, predict the effect of land use/cover changes on soil losses, water cycle and ecosystem services and evaluate management scenarios in the practices of soil and water conservation, vegetative changes, and ecosystem services. The soil and water carrying capacity for different vegetation types and the optimal ecosystem services will be addressed at the regional scale. Outreach workshops and demonstrations will disseminate knowledge to farmers and policy makers.The proposed research will elucidate the coupled relationships between soil and water processes and agro-ecosystem services at various scales, and evaluate the effects of vegetation cover and changes in land use on water cycle, soil erosion, and ecosystem services across the Loess Plateau.
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Spatial prediction with categorical response variables
使用分类响应变量进行空间预测
DOI:
--
发表时间:
2018
期刊:
影响因子:
--
作者:
[Charlton M]
通讯作者:
Charlton M
Sociatal Geo-Innovation, 20th AGILE Conference Proceedings
社会地理创新,第 20 届 AGILE 会议论文集
DOI:
--
发表时间:
2017
期刊:
影响因子:
--
作者:
[Comber A]
通讯作者:
Comber A
DOI:
10.3390/land11030399
发表时间:
2022-03
期刊:
Land
影响因子:
3.9
作者:
[A. Comber;P. Harris]
通讯作者:
A. Comber;P. Harris
Semantic considerations of local statistical modelling: what does it all mean?
本地统计建模的语义考虑:这一切意味着什么?
DOI:
--
发表时间:
2017
期刊:
影响因子:
--
作者:
[Comber A]
通讯作者:
Comber A
DOI:
10.1111/gean.12337
发表时间:
2021-09
期刊:
Geographical Analysis
影响因子:
3.6
作者:
[A. Comber;M. Callaghan;P. Harris;Binbin Lu;N. Malleson;C. Brunsdon]
通讯作者:
A. Comber;M. Callaghan;P. Harris;Binbin Lu;N. Malleson;C. Brunsdon
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MIDST-CZ: Maximising Impact by Decision Support Tools for sustainable soil and water through UK-China Critical Zone science
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批准号:NE/S009094/1
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项目类别:Research Grant
-
资助金额:$20.05万
-
财政年份:2019
-
负责人:Lianhai Wu
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依托单位:
Soil processes and ecological services in the karst critical zone of Southwest China
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批准号:NE/N007557/1
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项目类别:Research Grant
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资助金额:$9.39万
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财政年份:2016
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负责人:Lianhai Wu
-
依托单位:
海外基金