1. 1
a case study ofa case study of Nakhon Ratchasima, Thailand
Spatial Modeling and Timely Prediction of SalinizationSpatial Modeling and Timely Prediction of Salinization
usingusing SAHYSMODSAHYSMOD in GIS environmentin GIS environment
Thesis Assessment Board
Prof. Dr.V. G.Jetten Chairman
Dr.T.W.J. Van Asch External Examiner
Dr.A. (Abbas) Farshad First Supervisor
Dr.D. B. (Dhruba) Pikha Shrestha Second Supervisor
Tsegay Fithanegest Desta
Applied Earth Sciences: GEOHAZARDS
2. 2
Presentation outlinePresentation outline
1.1. IntroductionIntroduction
Research ObjectiveResearch Objective
Research questionsResearch questions
1.1. The Study AreaThe Study Area
Salient featuresSalient features
1.1. Materials and MethodsMaterials and Methods
MaterialsMaterials
MethodsMethods
4.4. Result discussionResult discussion
Model calibrationModel calibration
Model validationModel validation
Salinity predictionSalinity prediction
4.4. Conclusion and RecommendationConclusion and Recommendation
Applied Earth Sciences: GEOHAZARDS
3. 3
1.0 IntroductionIntroduction
1. Salt and Salinization
def. 1.salt is presences of excessive soluble salts in the root zone, while
2. salinization is process of its accumulation in root zone area,
Together threaten
Biophysical ecology
Crop physiological processes
Biogeochemical processes of agricultural soils
National socio-economy
2. General objective
To detect soil salinity change both in time and spaces dimension and to model
salinization as a process.
3. General research questions
Could soil salinity change be detected in spaces & time dimension? and
salinization be modelled as a process? Applied Earth Sciences: GEOHAZARDS
4. 4
2.0 The Study Area
Study area salient features
Name: Nong sung
1. Geographical
• 795858 – 821786 E
• 1659635 –1688797 N
• Elevation: 114 – 209 Meter amsl.
2. Administrative
• Province: Nakhon Ratchasima
• Region: Northeast
• Country: Thailand
3. Area size:816 km2
4. Climatic features
• Aver. Rainfall=1030mm/yr
• Aver. Temperature = 27o
c
5. Dominant soil and Rocks
• Sandy loam
• Mahasarakham formation
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5. 2.0 Layout of the study Area
5
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6. 6
3.0 Literature review
The millstone literature reviews of the study:-
1. Greiner (1997) Saline soils are identified by their:-
• EC, SAR, ESP, and degree of acidity (pH) soil extract @ 250
C
• ECe > 4 mS/m, threshold for deleterious effects to occur
2. The findings of Slavich and Petterson (1993),
• EC1:X soil-water solutions, is > 2 to 3*higher than the FC H2
O
content
3. Oosterbaan (2005) SAHYSMOD model works based on electrical
conductive at filed capacity (ECfc) so needs conversions.
f = texture dependant conversion factor
ECe = standardized electrical conductivity(EC of saturation extract)
EC1:5 = Electrical conductivity of 1gm soil to 5 ml of distilled water.
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ECe = f * EC1:5 ECFc = ECe*2
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4.0 Materials and Methods
1. Materials
Hardware
Gramin GPS 12X, pH meter, EC meter, Topographic map,
Geopedological map, DEM map and Aerial photo, lab
chemicals and buffer solutions and user manuals.
Software
ArcInfo Map, Erdas, ILWIS, ENVI,
SPSS, MS-Excel, MS-Word, and
SAHYSMOD
2. Breakdown of methods followed
Pre field work
At field work
Post field work
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8.3 Prediction spatial salinity distribution based on three aspects
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16. Applied Earth Sciences: GEOHAZARDS16
8.4 DSS for extrapolation model prediction results
Table 6 Designed decision supporting system for extrapolation of model predicted attributes
DEM
< 192m
Slope
< 0.5%
LUS
2
VSS
Expert decision
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8.5 Interim Conclusion
With successful model
• Calibration, sensitivity analysis,
• validation and evaluation works
Able to predicate soil salinity perfectly and identify/model
1. Saline geopedologic units
2. Salinity rate per geopedologic unit per year.
3. Change of salinization in space and in time.
4. Main factor of salinization, Rise of saline GWT.
5. Biophysical factors that aggravate salinization :-
I. Hot climate condition, high ETO
II. Deforestation.
III. Uncontrolled irrigation practise
IV. Traditional salt making remnants
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8.6 Prediction spatial salinity distribution map for the three profiles
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9.0 Recommendation
1. salinity related
Reafforestation indigenous trees.
Agronomic packages:
Adding organic matter
Using resistance Varity
Crop rotation
Installation of drainage network => 4 to 5 times
1. Model related
Area selection should be done with care.
Grid alignment limitation should be noted before use.
Output data reduction should be noted before use.
Integrating different factors of salinization is advisable.
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20. I recommend a change detection research to be carried
1. The study area is large enough for bigger grid size
creation and alignment.
2. There are enough resources references materials
3. Salinization rate of the area is fast & destructive
so it needs monitoring
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10.0 Concluding remark
Applied Earth Sciences: GEOHAZARDS