The document discusses developing a Soil Information System (SUSIS) for Sudan using Digital Soil Mapping techniques. It notes that Sudan has highly variable rainfall and drought is common. It lacks an integrated system to manage agricultural land and monitor soil status. SUSIS would provide soil data and maps to support food security, climate adaptation/mitigation, and land management. Developing SUSIS requires digitizing legacy soil data, building staff skills in information management, and mapping key soil properties on pilot areas. Challenges include developing standards, training soil scientists, and ensuring users accept new map and data formats.

1. GloSIS
Sudan Soil Information
System (SUSIS)
Abdelmagid Ali Elmobarak

2. ⮚ Rainfall in Sudan is enormously variable over space and time, ranging from less than
150 mm in the north to more than 700 mm towards the south. Drought spells are
common even during the rainy season. Three agricultural climatic zones (semi-desert,
arid and semiarid) are defined in Sudan (Van der Kevie, 1976) based on the balance of
monthly rainfall and potential evaporation data (Penman, 1965). These zones are
significant for agriculture and also correspond rather well with natural vegetation
zones.
⮚ The main geological formations in Sudan according to Whiteman (1971) comprise
recent Nile deposits (Holocene) overlying the Nubian sandstone (Cretaceous). This
succession is underlain by the old Precambrian basement complex (igneous and
metamorphic ) rocks.
⮚ The main geomorphological features of Sudan comprise the Nile valley, the great
erosional scarp that borders the Red Sea hills and the series of pediplains and
inselbergs.
⮚ The country is traversed by the River Nile and its tributaries which have varying
degrees of effect on irrigated agriculture.
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3. ⮚ Sudan suffers from serious deteriorations in its natural resources during the past three decades partly
due to drought and desertification and partly due to social problems.
⮚ The above mentioned physical and social factors had their impact on Sudan’s economy which was
staggering ever since the mid 80s due to many factors including, natural resources degradation, low
productivity in the government irrigated schemes due to shortage in production inputs, wars and
foreign debts.
⮚ Inexistence of a Soil Information System (SIS) has a negative impact on appropriate integrated land
management of agricultural and forest areas, as well as, design and accurate implementation of
different measures for protection and mitigation of land degradation. The MoAF have no overview
of the quality and spatial distribution of this natural resource, which influence completion of some
politics of the Ministry, e.g. agro-zoning, land suitability overview for different crops, implementation
of agro ecological measures, and recommendations of some good practices towards protection of
soil properties and maintenance of its fertility (green manure, cover crops growing, optimization of
water and fertilizers consumption etc.).
⮚ Considering the importance of soil information for investment and land management under the
current climate change era and taking into account the currently dispersed soil data, developing a
Soil Information System (SIS) with accurate and up-to-date soil information is of high priority for
MoAF. Such system will enable the different applications regarding food security, climate change
mitigation and adaptation, provision of ecosystem services, land suitability analysis, land degradation
assessment, etc.
⮚ The system will also allow the integration of soils with other disciplines and will be
fundamental for monitoring the status of soils as per human interventions though land use
changes and climate change impacts. Once installed on place SUSIS can be continuously
upgraded and supplied with new information from the field and can serve as a reference
centre for storing all valuable soil data from previous and future soil surveying campaigns.

4. ⮚ Establishing a digital national soil information system helps in describing the status
and potential of agricultural soils or individual soil properties such as soil fertility.
The information system should have a defined Web site so that the soil data can
easily be retrieved and used by the broad range of stakeholders (from farmers to
policy makers).
⮚ The huge stock of the legacy soil data (reports, maps, etc.) in the ARC shelves
should be digitized as much as possible and then incorporated in the information
system.
⮚ Lack of skills of the staff in the institution, for using modern techniques of soil
information management had a considerable detrimental effect for effective delivery
of services when requests come from users.
⮚ Mapping certain topsoil properties (on pilot areas) is one of the targets of this
project that will help in developing soil fertility map. These include, EC, pH,
texture, active lime, percentage of saturation, CEC, volume weight, and certain
macro and micro plant nutrients including, tN, aP, aK, OC, OM, soluble C, M, P,K,
Na and Mn. Mapping these properties can provide an important piece of information
that is currently not available for land use planning and research studies. Fertility
surveys should be conducted on pilot areas together in each soil survey area.
⮚ Soil information is fundamental for technically guiding sustainable intensification of
agriculture.
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5. DATA REQUIREMENTS
The data needed for DSM include legacy data and data on environmental
variables (soil forming factors). The legacy data comprise:
• Existing soil maps,
• Soil profile database,
• Laboratory analytical and field observation soil data
• Climate data
• Geology
• Topography and,
• Land use/cover characteristics
• The potential sources of the input data and levels of details are given in
Table 1. The main sources of environmental variables are remote sensing
and digital elevation models.
•
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6. CHALLENGES WITH DIGITAL SOIL MAPPING
• Developing acceptable standards and procedures for the production and quality
control and interpretation of the information.
• Having a sufficient core of soil scientists trained and well versed with DSM
procedures and tools
• Access and generation of relevant and adequate soil data (legacy data) for
application.
• Coordinated activities by different agencies, organizations, and projects
involved in DSM.
• Potential misuse of methods, products and software borrowed from other
fields and incorporated in DSM toolkit
• Complete acceptability by the traditional soil scientists and users.
• The users of soil survey information must be convinced of the relevance and
applicability of maps and data that appear different from the “traditional”
products with which they have become familiar.
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7. PREPARATION OF LEGACY DATA FOR DSM
(i) Legacy data identification and collection
• Availability of the legacy data, data type, data location, and how to access the data. It begins with
definition of area of interest. The sources targeted in the search include documents containing soil
mapping activities, catalogue, data repositories in soil survey departments, online reports and
databases, progress reports from research organizations and NGOs, soil libraries, academic papers
in learning institutions, etc.
(ii) Data selection
• Examined for content and relevance. The examination should consider soil data sources for soil
point data, soil maps, soil profile description and soil reports/documentation. The relevant selected
data are categorized as follows:
• Detailed soil maps with legends and soil point data. These are checked whether or not they fully
cover the area of interest and the geo-reference system
• Soil point data and the geo-reference system
• Detailed soil maps with legends and geo-reference system. Where necessary, any form of
preparation may be included such as need for scanning of paper maps, data entry, data coding, etc.
(iii) Database development
• Create a useful database and enter data into it. The requirements for the database is that it should
be user friendly and can easily be exported or used by any GIS and statistical software.
(iv) Data harmonization and integration
• Legacy soil data may came from different projects and created at different times by different soil
organizations. Consequently, the analysis and measurement units, geo-reference system, and soil
depth observations are also likely to be different. In this step, strategies are put to harmonize the
data. Three types of harmonization need to be taken: geo-reference, information, and soil profile
harmonization.
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8. CAPACITY BUILDING SESSIONS AND DSM TOOLS
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10. SUSIS: DSM OUTPUTS
❖ National
❖Regional Maps
⮚Soil Property Maps
• Soil type, Texture, Total N, Av.P, Ex. K, CaCO3, pH,
CEC, Depth and BD
⮚Soil Threats
• Soil Erosion Type, Class, Salinity, Sodicity.
⮚Soil Condition
• Carbon stock, Soil fertility, H.C., Soil drainage
Other products supporting these outputs:
Geology, landcover, DEM, Temp. max and min.; wind
speed, direction, rainfall,…
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21. Thank You!
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