Modelling and managing critical zone relationships between soil, water and ecosystem processes across the Loess Plateau

Lead Research Organisation: Rothamsted Research
Department Name: Sustainable Agriculture Sciences-NW


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.

Planned Impact

The primary impact will be the coupled benefits of environmental sustainability and the promotion of economic development and social welfare in the Loess region. This will be achieved through better understanding the relationships between the soil and water processes and agro-ecosystem services, including grain production, net primary production, carbon sequestration, water retention and soil erosion control. This research will provide guidance on practices and managements for sustainable ecosystem services in the fragile region, which will secure food production and save water resources in the arid Loess Plateau. Farmers in the area will receive guidance, enabling them to make informed decisions to adopt optimal agricultural and water management practises, thus increasing income by maintaining or increasing agricultural production. Likewise, environmental agencies and other organisations will have the tools to enable more accurate estimation of water balance, enabling stable management of ecosystems services.

To achieve the benefits, a series of workshops will be run during the project period to transfer our understanding to local people, mainly targeted at low income farmers. Workshops with main stakeholders including local government and environmental agency in year 3 and 4 will be held to introduce our research findings and recommendations.
Description In the Chinese Loess Plateau (CLP), loess samples were collected at five sites through a 50 to 200 m loess profile. The estimated storage of mineral N varied significantly among the five sites, ranging from 0.46 to 2.43 × 104 kg N ha-1. Ammonium exhibited fluctuations and dominated mineral N stocks within the whole profile at the sites, except for the upper 20-30 m at Yangling and Changwu. Measured nitrate content in the entire profile at Fuxian, An'sai and Shenmu is low, but significant accumulations were observed to 30-50 m depth at the other two sites. Analysis of d15N and d18O of nitrate indicates different causes for accumulated nitrate at these two sites. Mineralization and nitrification of manure and organic N respectively contribute nitrate to the 0-12 and 12-30 m profile at Changwu; while nitrification of NH4+ fertilizer, NO3- fertilizer and nitrification of organic N control the nitrate distribution in the 0-3, 3-7 and 7-10 m layer at Yangling, respectively. Furthermore, our analysis illustrates the low denitrification potential in the lower part of the vadose zone. The accumulated nitrate introduced by human activities is thus mainly distributed in the upper vadose zone (above 30 m), indicating, currently, a low nitrate leaching risk to groundwater due to a high storage capacity of the thick vadose zone in the region.
We proposed that classification of regional critical zone (CZ) by quantifying the geographical differentiation of CZs in the CLP using a comprehensive clustering approach is fundamental for further advancing CZ observatories and key scientific issues such as CZ interactions at regional scale. We optimally classified the CLP into 8 CZ types. There are large variations on area percentage of different CZs in the CLP with the smallest urbanizing CZ (category V) and the largest Loess hilly- gully agriculture and grassland CZ (category III) accounting for 0.78% and 22.51% of the CLP, respectively. The classified CZs also show complex spatial configurations such as the urbanizing CZs are surrounding by all the other CZs while the mountainous forest CZ (category I) intersect mainly with the flood plain agricultural CZ and the loess hilly-gully agriculture-grassland-woodland transition CZ (category IV). A practical approach establishing CZ observatories in the CLP is to fill the gaps between those existed observatories and the observational requirements revealed by the CZs identified here.
Exploitation Route An app could be further developed for fertiliser application guidance. A recommendation could be reported to the local and central government for optimised land uses.
Sectors Agriculture, Food and Drink,Environment

Description BBSRC China Partnering Award
Amount £30,000 (GBP)
Funding ID BB/P025595/1 
Organisation Biotechnology and Biological Sciences Research Council (BBSRC) 
Sector Public
Country United Kingdom
Start 04/2017 
End 03/2020
Description Using the Critical Zone as a framework to understand sustaining the ecosystem services of soil and water (CZO) A UK China Collaboration: adding value and increasing impact
Amount £157,333 (GBP)
Funding ID NE/S009094/1 
Organisation Natural Environment Research Council 
Sector Public
Country United Kingdom
Start 01/2019 
End 03/2021
Title GWmodel R package 
Description GWmodel R package is a collection spatial statistical tools for exploring spatial heterogeneity. Continually developed since its release in 2013. 
Type Of Material Data analysis technique 
Year Produced 2017 
Provided To Others? Yes  
Impact "GWmodel" produced 66,200 Google hits. 
Title GWmodel R package 
Description A suite of spatial statistical modelling tools See 
Type Of Technology Software 
Year Produced 2019 
Open Source License? Yes  
Impact 66200 Google hits 
Description GW models, CAS, Research Centre for Eco-Environmental Sciences, Beijing, China (two-day workshop with A Comber) 
Form Of Engagement Activity Participation in an activity, workshop or similar
Part Of Official Scheme? No
Geographic Reach International
Primary Audience Postgraduate students
Results and Impact GW models, CAS, Research Centre for Eco-Environmental Sciences, Beijing, China (two-day workshop with A Comber)
Year(s) Of Engagement Activity 2017
Description Geographically Weighted PCA: Introductions and Uses. Spatial Accuracy Conference, Beijing, China (one-day workshop with A Comber) 
Form Of Engagement Activity Participation in an activity, workshop or similar
Part Of Official Scheme? No
Geographic Reach International
Primary Audience Postgraduate students
Results and Impact Geographically Weighted PCA: Introductions and Uses. Spatial Accuracy Conference, Beijing, China (one-day workshop with A Comber)
Year(s) Of Engagement Activity 2018