Land degradation: Difference between revisions
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{{ComponentTemplate2 | {{ComponentTemplate2 | ||
| | |Application=Roads from Rio+20 (2012) project;Global Land Outlook 1;Global Land Outlook 2 | ||
|IMAGEComponent=Atmospheric composition and climate;Land cover and land use | |||
|Model-Database=GlobCover database;WorldClim database;HWSD database;S-World database;WISE database | |||
|KeyReference=Hootsmans et al., 2001;Stoorvogel et al., 2017;Stoorvogel, 2014;Van Beek, 2012 | |||
|Reference=FAO, 2011a;Wischmeier and Smith, 1978;Nkonya et al., 2011;Bindraban et al., 2012;UNCCD, 2012;Rozanov et al., 1990 | |||
|InputVar=Precipitation - grid;Number of wet days - grid;Land cover, land use - grid;Temperature - grid | |||
|Parameter=Slope - grid;Land management;Initial land cover, land use;Initial temperature, precipitation;Soil types and profiles (S-World);Weighting factors for temperature, precipitation, land use and slope | |||
|OutputVar=Erosion risk - grid;Change in soil properties - grid | |||
|ComponentCode=LD | |||
|AggregatedComponent=Impacts | |||
|FrameworkElementType=impact component | |||
}} | }} | ||
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Land degradation is human-induced damage to ecosystems leading to a sustained loss of capacity. This is a serious and widespread problem leading ultimately to loss of arable land, and to demand for new arable land to compensate for decline in production on existing land. A key symptom of land degradation is loss of organic carbon from soils and vegetation, also contributing to global greenhouse gas emissions. The key mechanisms in land degradation are soil erosion (by water and wind), compaction, salinization, nutrient depletion, structural decay and contamination. The main causes are deforestation, land conversion, inadequate agricultural land use and management, and construction (urbanisation, road construction). | |||
In 2012, the UN Convention to Combat Desertification ({{abbrTemplate|UNCCD}}) formulated the goal to achieve zero net land degradation as a Sustainable Development Goal for [[Roads from Rio+20 (2012) project|Rio+20]] ''‘to secure the contribution of our planet’s land and soil to sustainable development, including food security and poverty eradication’'' ([[UNCCD, 2012]]). Land degradation is also relevant to the other Rio Conventions, with one of the Aichi targets of the Convention on Biological Diversity ({{abbrTemplate|CBD}}) aiming to restore at least 15% of degraded ecosystems. | |||
While recognized as a global threat, the impacts of land degradation are poorly understood, and studies report differing results. For instance, productive soil loss equals 15 million km<sup>2</sup> according to [[Rozanov et al., 1990]], while FAO reports about 43 million km<sup>2</sup> moderately to severely degraded land because of soil quality loss, water resource depletion and biodiversity loss ([[FAO, 2011a]]). As a result, the impacts on productivity and economic losses with consequences for food security are also very uncertain. In the same way, the costs and benefits of investments to prevent land degradation and to restore degraded areas are also largely unknown ([[Nkonya et al., 2011]]). Many reasons for these discrepancies and knowledge gaps are identified ([[Bindraban et al., 2012]]), including uncertainty about data, ambiguous definitions of land degradation, and methodology weaknesses in attributing changes in ecosystems to land degradation or to other causes. | |||
Although a comprehensive model to capture the complex system interactions is not readily available, IMAGE 3.0 offers the following approaches to address soil degradation: | |||
A. Water Erosion Risk: Risk assessment of soil erosion caused by water based on the Universal Soil Loss Equation ({{abbrTemplate|USLE}}; Wischmeier and Smith[[Wischmeier and Smith, 1978|(1978)]]). | |||
B. Change in soil properties: Quantitative assessment of changes in soil properties, from a hypothetically undisturbed (pristine) situation to a new situation, accounting for changes in land cover and other changes caused by human activity. The effect of changes in soil properties on crop production, hydrology and water can be assessed in other components of IMAGE. | |||
C. Including historically observed degradation trends derived from satellite-observed NDVI trends in land-use projections. Observed degradation is assumed to correlate with crop yield loss. By reducing or restoring yields the role of land degradation in the agricultural economy is assessed. | |||
{{InputOutputParameterTemplate}} | |||
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Latest revision as of 12:57, 21 November 2022
Parts of Land degradation
Component is implemented in: |
|
Related IMAGE components |
Projects/Applications |
Models/Databases |
Key publications |
References |
Key policy issues
- In what parts of the world have human-induced changes in land and soil conditions occurred?
- What are the future risks of soil degradation?
- To what extent are ecosystem functions lost by soil degradation, adding to local and global concerns about food security, biodiversity loss and climate change?
Introduction
Land degradation is human-induced damage to ecosystems leading to a sustained loss of capacity. This is a serious and widespread problem leading ultimately to loss of arable land, and to demand for new arable land to compensate for decline in production on existing land. A key symptom of land degradation is loss of organic carbon from soils and vegetation, also contributing to global greenhouse gas emissions. The key mechanisms in land degradation are soil erosion (by water and wind), compaction, salinization, nutrient depletion, structural decay and contamination. The main causes are deforestation, land conversion, inadequate agricultural land use and management, and construction (urbanisation, road construction).
In 2012, the UN Convention to Combat Desertification (UNCCD) formulated the goal to achieve zero net land degradation as a Sustainable Development Goal for Rio+20 ‘to secure the contribution of our planet’s land and soil to sustainable development, including food security and poverty eradication’ (UNCCD, 2012). Land degradation is also relevant to the other Rio Conventions, with one of the Aichi targets of the Convention on Biological Diversity (CBD) aiming to restore at least 15% of degraded ecosystems.
While recognized as a global threat, the impacts of land degradation are poorly understood, and studies report differing results. For instance, productive soil loss equals 15 million km2 according to Rozanov et al., 1990, while FAO reports about 43 million km2 moderately to severely degraded land because of soil quality loss, water resource depletion and biodiversity loss (FAO, 2011a). As a result, the impacts on productivity and economic losses with consequences for food security are also very uncertain. In the same way, the costs and benefits of investments to prevent land degradation and to restore degraded areas are also largely unknown (Nkonya et al., 2011). Many reasons for these discrepancies and knowledge gaps are identified (Bindraban et al., 2012), including uncertainty about data, ambiguous definitions of land degradation, and methodology weaknesses in attributing changes in ecosystems to land degradation or to other causes.
Although a comprehensive model to capture the complex system interactions is not readily available, IMAGE 3.0 offers the following approaches to address soil degradation:
A. Water Erosion Risk: Risk assessment of soil erosion caused by water based on the Universal Soil Loss Equation (USLE; Wischmeier and Smith(1978)).
B. Change in soil properties: Quantitative assessment of changes in soil properties, from a hypothetically undisturbed (pristine) situation to a new situation, accounting for changes in land cover and other changes caused by human activity. The effect of changes in soil properties on crop production, hydrology and water can be assessed in other components of IMAGE.
C. Including historically observed degradation trends derived from satellite-observed NDVI trends in land-use projections. Observed degradation is assumed to correlate with crop yield loss. By reducing or restoring yields the role of land degradation in the agricultural economy is assessed.
Input/Output Table
Input Land degradation component
IMAGE model drivers and variables | Description | Source |
---|---|---|
Number of wet days - grid (historical data) | Number of days with a rain event, per month; assumed constant after the historical period | CRU database |
Temperature - grid | Monthly average temperature. | Atmospheric composition and climate |
Precipitation - grid | Monthly total precipitation. | Atmospheric composition and climate |
Land cover, land use - grid | Multi-dimensional map describing all aspects of land cover and land use per grid cell, such as type of natural vegetation, crop and grass fraction, crop management, fertiliser and manure input, livestock density. | Land cover and land use |
External datasets | Description | Source |
---|---|---|
Slope - grid | Terrain slope index. | IIASA |
Soil types and profiles (S-World) | Soil profiles based on the HWSD (Harmonised World Soil Database) and on the ISRIC-WISE international soil profile dataset | HWSD database, S-World database |
Weighting factors for temperature, precipitation, land use and slope | Weighting factors for the contribution of temperature, precipitation, land use and slope on distribution of soil properties. | expert judgement |
Output Land degradation component
IMAGE model variables | Description | Use |
---|---|---|
Erosion risk - grid | Risk of soil erosion caused by water. | |
Change in soil properties - grid | Change in soil properties, such as clay/sand content, organic carbon content, soil depth (topsoil/subsoil). |