Soil Physics Article Soil Physical processes Soil conservation Climate change effects

1. DEVELOPMENT OF
EARLY WARNING SYSTEM FOR
SOIL QUALITY CHANGES
under TROPICAL CONDITIONS
DOCTORAL RESEARCH PROPOSAL @ UNN
PAUL B. OKON
Department of Soil Science
University of Calabar
CALABAR - NIGERIA
E-mail: pbokon@yahoo.com
INTERNATIONAL WORKSHOP ON SOIL
PHYSICAL PROCESSES FOR WEST AFRICA
20 – 29 June 2011 IAR, ABU, ZARIA, NIGERIA

2. Ideas to tinker on
A PROPOSED METHOD (MODEL) FOR QUANTIFICATION
OF SOIL QUALITY UNDER TROPICAL CONDITIONS.
Can the “minimum” dataset for SQ be
standardized to 20 variables that encompasses
visual, physical, chemical, and biological soil
properties as well as other factors of soil
formation, viz: parent material time, and climatic
variables?
Is building a theory of soil quality for tropical
soils feasible? To further move up from the
current qualifying CONCEPTS?

3. Topical Issues bordering on Soil Quality
 Soil quality is a new chaotic phenomenon that has
recently happened in the young discipline of soil
science worldwide. There are no theories as such
scientists choose whatever comes easy and name it
soil quality. The time to look inward and discard
qualitative ideas, put up "develop quantitative"
theory on soil quality is now. I want to take the bull
by the horn, and I need support by beating the bull
at the buttocks for it to move fast. Not a Pedologist,
Soil Surveyor, Chemist, Microbiologist nor
Mineralogist can do this. The onus lies on the Soil
Physicists, and it’s a task that must be done.

4. Problems of tropical soils
 Because of high variability in climatic conditions in the
tropics, there is rapid decline in SQ of tropical soils leading
to concomitant decline in the soil’s capacity (ability) to
perform the following functions:
 produce biomass
 Filter water
 Cycle elements
 Store plant nutrients, &
 Moderate climate.
 Once this occurs degradation begins, and according to Lal
and Shukla (2004) “soil degradation refers to a decline in
soil quality that it cannot perform one or several of its
principal functions.”

5. Other Soil Related Constraints in the Tropics
 Low AWC in rainfed soils, Poor quality soils
 Depleted nutrients and SOC due to high temperature
 Extractive farming (soil mining)

6. Water &
Nutrient
Holding
Benefits of Soil Carbon
Time
Soil
Quality
Aggregation &
Infiltration Productivity
Air & Water Quality;
Wildlife Habitat
Soil Carbon

7. Efforts & Models so far made in
developing SQ assessment Index
 ∂Q = ƒ[(qi, t –qi, to) …(qn, t–qn, to)]
 Larson and Pierce (1991)
 SQ = ƒ(SOC, CEC, pH, WC, WSA).
 (Lal, 1993)
 QI= qwe(ωt) + qwt (ωt) + qrd(ωt) + qspg(ωt)
 Karlen et al.(1994)
 PI= Σii= 1(Ai x Ci x Di x Fi x Ii x Wfi)
 Modified PI by Anikwe and Obi (1999)
 SQI = ƒ(SP, P, E, H, ER, BD, FQ, MI)
 (Arshad and Martin, 2002)
 SSI = SQI x (100 – CDE). where SSI = Soil sustainabilty Index and
CDE = cumulative degradation effect
 (Toth et al., 2007)

8. Soil quality assessment card (USDA); How many
scientists consulted this in assessment of SQ?

10. Deficiency that still exists
 Is there a world class standard for quantification of Soil
Quality? Answer is NO!
 Are there any models that were developed in sub
Saharan Africa for tropical conditions? NO!
 No model takes into consideration
 - Climatic variables
 - Land use changes
 - The Changes in Soil Physicochemical & Biological
parameters in response to change in climatic variables.
 - None of the existing model is capable of appropriately
describing what is happening to tropical soils.

11. The need for standardization
 Just like soil texture and soil colour, which is
standardized worldwide, irrespective of classification
system adopted, there is need to develop a single,
comprehensive SQ model that will be applicable to all
tropical soils.
 The Theory of SQ need to be developed to suit the
SOIL-PLANT-ATMOSPHERE CONTINUUM.
 A comprehensive model, that combines the USDA
concepts with that of EU, that will consider the soil
forming factors of climatic, time , parent material and
organic matter variables may could be good for the
tropics

12. What & Why Early Warning System
(EWS)?
 Early warning mean the provision of information on an emerging
circumstance where that information can enable action in advance to
reduce the risks involved. EWS helps in mitigating disaster quite ahead
of time. Just like the dashboard of an automobile, EWS should warn
against quality retrogression and lack of resilience. Should the
resilience get depleted, then we face a situation of bare soil syndrome
(BSS) that is likened to HIV/AIDS is AIDS in humans, but a terrible soil
in health condition; [barren, unproductive soils]

13. Components of an EWS
 To be effective and complete, an early warning
system needs to comprise four interacting
elements (ISDR PPEW, 2005), namely:
 (i) risk knowledge,
 (ii ) monitoring and warning service
 (iii) dissemination and communication and,
 (iv) response capability service,

14. Elements of people oriented Early Warning System (EWS)

15. The goals and objectives of the
study are:
 MAIN GOALS: To
 Standardize soil quality assessment in the tropics through a
comprehensive but easy to use system.
 Mitigating the degradation of soil quality and its
concomitant loss of productivity using the early warning
system tool .
 Improve land management and sustainability of soil quality
in tropical ecosystems using the early warning system tool.
 Specific Objective:
 To construct a model to evaluate various soil management
strategies, vegetation, land use change, soil mining and
climate change on soil quality; considering weather, soil
physicochemical and biological properties, ecosystem and
natural vegetation.

16. Justification
 Changes in the capacity of soil to function are reflected in soil
properties that change in response to management, land
cover, land use or climate.
 The five soil forming factors : viz:
 pm, om, veg, climate & T must be integrated
 But most available models do not take into consideration all
these factors, thereby making them incomplete.
 “The focus on local and technical indicators of agro-
ecosystem change is useful for providing farmers with
early warnings about unobservable changes in soil
properties before they lead to more serious and visible
forms of soil degradation.”
 (Barrios et al., 2006)

17. The TSQ Hypothetical Model;
for quantifying Tropical Soil
Quality and its changes
 
, , , , , , , ,
1
. . .
n
t r h s p c b lc a p f i
T
TSQ Ae C S V LU T

 


Where TSQ = Tropical Soil Quality
Ae = Specified Agro-ecosystem (field or region)
C = Climatic variables ; t = soil temp, r = rainfall, h=Relative Humidity,
S = solar radiation. The least period is 10 years record.
S = Soil parameters ; p = physical, c = chemical, b = biological indicators
V = Land cover or native vegetation.
LU = Land Use; a = arable, p =plantation, f = forestry, I = irrigation, e =ENGIN
T= Time period under evaluation, SQ must be time-period dependent.

18. Physical
Indicators
Chemical
Indicators
Biological
Indicators
score score score
TSQI =
f (scored MDS)
score
score
score
Time LAG ?

19. Visual and Climatic Indicators to evaluate
for the proposed TSQ Model
Visual
Indicators
(Land Cover)
1. Exposure of subsoil
2. Plant response
3. Ephemeral gullies
4. Ponding /Runoff
Climatic
indicators
1. Rainfall
2. Temperature
3. Solar radiation
4. Pan Evaporation
Land Use
(Mgt practices)
1. Arable
2. Plantation
3. Irrigation 5. Leisure Park
4. Forestry 6. Engineering (Road or house)

20. Selected Soil Indicators to evaluate to build the
TSQ Model
Physical
Indicators
1. Texture, 2. Structure
3. Bulk density,
4. Porosity (Total & water filled)
5. Aggregate Stability - WSA > 0.25mm
6. Infiltration rate, and
7.Top soil depth.
Chemical
indicators
1. Soil Organic carbon (SOC),
2. Total Nitrogen
3. Extractable Phosphorus
4. EC, 5. CEC, 6. SAR, 7. pH
Biological
Indicators
1. Population of macro arthropods e.g.
Earthworms, termites, ants.
2. Respiration rate (CO2)of microbes

21. Selected ecosystems & Land Use systems to evaluate
Six ecosystems to be evaluated:
 Arable farm agro-ecosystem; continuously cultivated lands
- (Location: Enugu - Nsukka axis on Ultisols)
 Tropical primary/Rainforest ecosystem
 - (Location: Cross River National Park)
 Guinea Savannah ecosystem – (Gashaka –Gumti NP.)
 Sudan Savannah ecosystem (typical grassland) (GGNP)
 Bare soil or barren, degraded lands for comparisons, in each ecosystem
 Wetland; Hydromorphic ecosystem - (Location: Bakassi, Calabar)
 LAND USE SYSTEMS TO FOR SOIL QUALITY STANDARDIZATION
 AGRONOMIC SOIL QUALITY
 ENVIRONMENTAL SOIL QUALITY
 RHEOLOGICAL/ENGINEERING SOIL QUALITY

22. E - W Pit 1
N
S
Pit 2

23. Proposed Methods for Samples Analysis
Indicator Method Ref
Texture International Pipette or hydrometer method Gee & Bauder (1986)
Structure 1. Pore Size Distribution, 2. WSA >0.25mm or
MWD. 3. Bulk density using intact cores
Blake & Hartge (1986)
Bulk density 1. Core method, 2. Clod method USDA (1999)
Water Transmission 1.Infiltration Rate using 6” ring method USDA, 1999;
Sarrantonio (1996).
Topsoil depth Core break method USDA (1999)
Electrical Conduct EC handheld probe (electrometric) method UDSA (1999), IITA 1979
Soil pH pH handheld probe (electrometric) method Sparks(1996), IITA 1979
Earthworms Counting method USDA (1999)
Soil Respiration CO2 in Draeger Tubes method USDA, (1999)

24. Table 1: Critical Levels for Soil physical indicators
Limit Wtg
factor
Rootg
Dept
(cm)
Bulk Density
g/cm3
Soil structure Consiste
ncy
Texture
Light
Textr
Hevy
Textr
WSA
(%)
MWD
(mm)
None 1 >150 <1.3 <1.2 >75 >2.5 Loose Loam
Slight 2 100-
150
1.3 -1.4 1.2 -
1.3
50 – 75 2 – 2.5 V.
Friable
Silt loam
Mod 3 50 –
100
1.4 -1.5 1.3 -
1.4
25 – 50 1.0 -2.0 Friable Clay
Loam
Severe 4 25 – 50 1.5 -1.6 1.4 –
1.5
5 – 25 0.5 –
1.0
Hard Silty clay
Extrem
e
5 <25 >1.6 >1.5 <5 <0.5 Ext
hard
Clay,
Sand

25. Table 2: Critical Levels for Porosity, AWC &
Water Transmission Properties
Limit Weighting
factor
Permeability M. R.
Porosity
AWC Infiltra
Rate
K Sat.
(%) (cm) (cm/hr) (cm/hr)
None 1 Rapid >20 >30 >5 >2
Slight 2 Mod Rapid 18-20 20-30 2-5 0.2-2
Mod 3 Mod slow 15-18 8-20 1-2 0.02 -0.2
Severe 4 Slow 10 – 15 2-8 1-0.5 0.002 -0.2
Extreme 5 Very slow <10 <2 <0.5 <0.002

26. Table 3: Critical levels for Soil Chemical Indicators
Limit
Weighting
factor
pH SAR EC Ex Al SOC Biomass
Carbon
1:1 H2O dS m-1 % of CEC %
None 1 6.0 7.0 <10 <3 <20 5.0-10 >25
Slight 2 5.8-6.0
7.0-7.4
10-12 3-5 20-35 3.0-5.0 20-25
Mod 3 5.4-5.8
7.4-7.8
12-15 5-7 35-40 1.0-3.0 10-20
Severe 4 5.0-5.4
7.8-8.2
15-20 7-10 40-50 0.5-1.0 5-10
Extreme 5 <5.0
>8.2
>20 >10 >50 <0.5 <5

27. The measured data obtained for SQ indicators will be
further processed into an index to assess the level of
SQ in the specified ecosystem. Possible option for
data analysis & synthesis into an operational index
(Nielsen & Wendroth, 2003, Lal, 1994)
APPROACHES
TO
DEV SQ INDEX
PARAMETRIC
METHODS
e.g RUSLE 2
REGRESSION
TECH, e.g
Linear/Stepwise
Autocorrelations
& Kridging
FUNCTIONS

28. Details of the conversion of the ΣSQI to SQ grade
 If 20 critical SQ indicators are selected and
evaluated in the field based on set criteria. The
following matrix will make it clearer what the max
and min limits are:
 Min = 20 ( i.e. No limitation of any form)
 Max = 100 ( i.e. fullest limitations).
 Some conversions must be done by standardizing
the weights to have them blend with the SQ grade
scale. Research on this has just begun.
 The results’ are promising!

29. The Matrix for the TSQ Index Summation
1
2
3
4
5
6
7
8
9
20
SQI
1 2 3 4 5
1 2 3 4 5
1 2 3 4 5
1 2 3 4 5
1 2 3 4 5
1 2 3 4 5
1 2 3 4 5
1 2 3 4 5
1 2 3 4 5
1 2 3 4 5
20 40 60 80 100 %
SQ
SQ
SQ
SQ
SQ
SQ
SQ
SQ
SQ
SQ

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

30. Soil indicator Weighting factor Limitation
Rooting Depth 3 Moderate
Soil pH 5 Extremely low
Al Toxicity 4 Severe
AWC 2 Slight
Texture 1 None
Bulk density 2 Slight
Nutrient Status 5 Extremely low
Soil Org Carbon 3 Moderate
Aggregation/WSA 1 None
Biomass Carbon 3 Moderate
Cumulative SQ Index = 29 %

31. SQGrade
A AB B BC C CD D DE E EF F
SQ
level
0-9 10-19 20-29 30-39 40-49 50-59 60-69 70-79 80-89 90-99 100
Colour
Green Light bright torq Blue DY Yellow LY Red Redder Deepest
Name
Functn OK Ok Ok Mod
Crit SCC
-ve
Fair Poor
V poor
Bad BSS devs
No
soil
Grading of TSQI

32. Some aspects completed & published, Some work in progress

33. Quantification Expts/Field works are in progress
at various sites

34. • Arshad M. A. and G. M. Coen. 1992. Characterization of soil quality:
physical and chemical criteria. American Journal of Alternative
Agriculture 7: 12 – 16.
• Arshad, M. A., & S. Martin. 2002 Identifying critical limits for soil quality
indicators in agro-ecosystems. Agriculture, Ecosystems and
Environment 88: 153–160
• Basher, R. 2006 Global early warning systems for natural hazards:
systematic and people-centred. Phil. Trans. Royal Soc. A (2006) 364,
2167–2182.
• Bauder, Jim. 2007. Soil "Physicals" Give Early Warning of Problems.
Montana State University Communications Services, Bozeman, MT
59717. Online available at www.montana.edu/wwwpb/ag/baudr132.html
• Boussougou, I. N. M et al. 2010. Soil quality and tree growth in
plantation of forest and agricultural origin. Soil Sci Soc Amer J. 74 (3):
993 – 1000.
• IPCC. 2000. Special Report on Land Use, Land-Use Change, and
Forestry: Summary for Policymakers. Intergovernmental Panel on
Climate change. WMO/UNEP. 30 pp.
Nielsen, D. R. and Wendroth, O. 2003. Spatial and temporal Statistics;

35. • Lal R. 1994. Methods and Guidelines for Assessing Sustainable Use of Soil and Water
Resources in the Tropics. SCS Technical Monograph No 21, Soil Management Support
Services, Washington, DC, 78 pp.
• Lal, R. and M. K. Shukla. 2004. Principles of Soil Physics. Marcel Dekker, Inc, Madison Ave,
NY, USA.
• Nortcliff, Stephen (2002) Standardization of soil quality attributes. Agriculture, Ecosystems
and Environment 88: 161–168.
• Okon, Paul B. and O. Babalola. 2005. General and Spatial Variability of Soil under Vetiver
Grass Strips. Journal of Sustainable Agriculture, Vol. 27(3): 93 -116.
• Okon, Paul B., G. O. Adeoye, A. O. Oyebanji, U. C. Amalu. 2004. Validation and use of
conversion factors for organic carbon, soil organic matter and total nitrogen in some tropical
ecosystems. Book of Abstracts, 29th Annual Conf. Soil Science Soc. of Nigeria, December 6 -
10, 2004, University of Agric., Abeokuta. pp 46 - 47.
• Tóth, G., Stolbovoy, V. and Montanarella, L. 2007. Soil Quality and Sustainability Evaluation -
An integrated approach to support soil-related policies of the European Union. EUR 22721
EN. 40 pp. Office for Official Publications of the European Communities, Luxembourg.
ISBN 978-92-79-05250-7
• UN-ISDR (2007) Hyogo Framework for Action 2005-2015: Building the Resilience of Nations
and Communities to Disasters. Extract from the final report of the World Conference on
Disaster Reduction (A/CONF.206/6). I S D R - International Strategy for Disaster Reduction.
Available online at www.unisdr.org (accessed March 2007)
• UN-ISDR-PPEW (2007). Developing Early Warning Systems: A Checklist. EWC III – Third
International Conference on Early Warning, from concept to action. 27 – 29 March 2006. Bonn,
Germany. UN- ISDR www.unisdr-earlywarning.org
• USDA – United States Department of Agriculture. 1999. Soil Quality Test Kit Guide. The Soil
Quality Institute of the USDA Natural Conservation Service. Available online at:
http://soils.suda.gov/sqi

38. • Grateful to ICTP, SSSN and
NPFS, and FAO who Organized
for the opportunity!
&
•THANK YOU FOR YOUR
TIME and ATTENTION!!