The primary objectives of this study are to characterize the spatial structure of soil properties under a tropical climate in terms of semivariogram parameters, to map the variation in soil properties in Universiti Teknologi Petronas, and to evaluate the effect of land use changes on the variability of soil properties. . All soil properties in the study area have moderate spatial dependence, as the ratio is between 25% and 75%, but the fine content has the lowest ratio, which is 3.48%. A large spatial variability of moisture content was found in the study area and the degree of variability was heterogeneous among different soil properties.
The variation in soil properties in the study area is produced in the form of maps, and the effect of land use changes on the variability of soil properties is evaluated. Soil disturbances, forest clearance and topographic conditions all contributed to the variability of soil properties. Variability in moisture content Variability in mass density • Variability in organic content 4.5 Variation of soil properties on land.
Soil properties vary spatially, even within homogeneous layers, as a result of depositional and post-depositional processes that cause variation in properties (Lacasse and Nadim, 1996). One of the main problems in hydrological modeling of distributed parameters is how to estimate attributes of spatially varying soil properties.
PROBLEM STATEMENT .1 Problem Identification
Significance
For example, the spatial distribution of soil moisture content affects infiltration of water into the soil, lateral redistribution of soil moisture, and determines rainfall-runoff responses in many catchments (Anctil et at., 2002). Soil properties under tropical climates exhibit more spatial variability due to their greater exposure to harsh climatic conditions (Mapa and Kumaragamage, 1996). Characterization of spatial structure of soil engineering properties is important for several types of analyses: (i) to determine the optimal size of spatial grids for distributed parameter hydrological models (Anctil et al., 2002), (ii) estimation of point or spatial averages values of soil properties using the kriging technique (e.g. Bardossy and Lehmann, 1998), (iii) in designing sampling networks and improving their efficiency (e.g. Prakash and Singh, 2000).
It also appears that no geostatistical study has been reported for the assessment of the spatial variability of small-scale and regional soil engineering properties. The proposed project will allow the understanding and characterization of the nature of small-scale spatial variability of tropical soil physical properties in the Tronoh area of Perak State, Malaysia.
OBJECTIVES
SCOPE OF STUDY
FINDINGS
CHAPTER2
LITERATURE REVIEW
THE STUDY AREA
CHAPTER3
MEmODOLOGY
- SAMPLE POINT I COORDINATE
- STUDY AREA TOPOGRAPIDC MAP
- SAMPLE COLLECTION
- LABORATORY ANALYSIS
- Bulk Density
- Moisture Content
- Specific Gravity
- Particle Size Distribution
- At the instant the cylinder with the soil suspension is replaced upright in the bath, the timer is started. The rubber bung is carefully removed from
- The hydrometer is immersed in the suspension to a depth slightly below its floating position and it is allowed to float freely
- The hydrometer is slowly removed, rinsed in distilled water and placed in a cylinder of distilled water with dispersion at the same temperature
- The hydrometer is reinserted in the soil suspension and readings after periods of 8 min, 30 min, 2 hours, 8 hours and 24 hours from the start of
- The particle size, percentage finer is calculated using the following formula
- STATISTICAL AND GEOSTATISTICAL ANALYSIS
- ANALYSIS OF SPATIAL VARIABILITY OF SOIL ENGINEERING PROPERTIES IN TERMS OF CONTOUR MAP
- JOB SAFETY ANALYSIS
- Burn Student Medium • Hand gloves must be worn during handling
Soil moisture content was determined from the difference between the wet weight (field sample) and the dry weight (subjected to oven drying at 11 0°C for 24 h) of the sample and expressed as a percentage of the dry weight of the sample . Changes in sample weight are the weight of water or moisture content in the sample. The results of the two analyzes will be combined to produce the complete particle size distribution of the soil samples.
The hydrometer readings are taken at the upper edge of the meniscus after periods of 1, 2 and 4 minutes. Where W, = sample weight retained on specific sieve Wtw = total weight of the soil sample. The results of the laboratory tests of soil engineering properties were subjected to two types of analysis: normal statistical and geostatistical analysis.
Geostatistical characterization of the data is performed using GS+ (Gamma Design Software, Plainwell, MI, USA). The results of the interpolation provided maps on variation of soil engineering properties (bulk density, moisture content, particle size analysis and organic content) over the study area.
CBAPTER4
RESULTS AND DISCUSSION
- RESULTS FROM LABORATORY ANALYSIS
- EVALUATION OF STATISTICAL CHARACTERISTICS OF SOIL PROPERTIES
- SPATIAL DEPENDENCE OF SOIL PROPERTIES
- KRIGING SPATIAL SOIL PROPERTIES
- Variability in Moisture Content
- VARIATION OF SOIL PROPERTIES ON LAND USE CONDITIONS
The range of CVs obtained indicates different degrees of heterogeneity among the different soil properties examined in the study area. The lower CV for soil bulk density is expected because the range over which soil density could fluctuate is narrow compared to other soil properties. Large differences in soil properties over a large area could be the result of heterogeneity in soil formation, land use pattern and erosion processes (Sun eta!., 2003).
Therefore, the difference in bulk density is smaller compared to other soil properties in the study. The semivariograms of different soil properties and the best-fitting semivariogram models are presented in Figures 5, 6, 7 and 8 below. Having established semivariogram models and parameters for soil properties, it is now possible to examine the spatial structure and dependencies of soil properties in terms of semivariogram parameters, range, threshold, clump, and clump-to-threshold ratio.
The relatively smaller clumps for soil vme content, organic content, and bulk density indicate that less variation existed for these three soil properties at distances shorter than the smallest lag. The strong spatial dependence of the soil properties indicates the influence of intrinsic or extrinsic factors. All these soil properties have a moderate spatial dependence as the ratio is between 25 and 75%, but fines content is the lowest.
From Table 4, moisture content and bulk density have almost similar (71.37% and 75% respectively) but strong spatial auto-correlation, while soil organic content exhibited spatial auto-correlation to a lesser extent ( 50%) than other soil properties. The relatively larger range and threshold for moisture content (Table 3) implies that the water content is spatially dependent over long distances (indicated by the large range) and the variability is very high (indicated by the large threshold) compared to the properties others of the earth. The spatial distribution of soil properties for the unsampled locations in the study area was obtained by interpolation between the sampled locations using the kriging method, based on the semivariograms of the soil properties in the sampled locations.
These maps of the spatial distribution of soil properties relative to the location map now allow examination. From the map of the spatial distribution of moisture content in Figure 8, the table of soil properties can be observed. Comparison of Figure 11 and Figure 12 shows the existence of a relationship between soil organic content and bulk density.
Statistical and geostatistical characterization of the soil properties provided strong evidence for the existence of the influence of intrinsic or extrinsic factors on the spatial variability of the soil properties. The existence of large variations in soil properties is probably also due to the land use conditions in the study area.
CHAPTERS
CONCLUSION & RECOMMENDATION
Using hand scraper is time consuming, so to obtain more samples within the time limit, more effective sample extrusion method should be used. This information is particularly important for moisture content analysis as the moisture content of the soil is greatly influenced by these factors.
Spatial variation of total nitrogen, available phosphorus of large paddy field in Sawah Sempadan, Malaysia Science Asia. 2005 Spatial Variability Analysis of Soil Physical Properties of Alluvial Soils, Soil Science Society of America. 2004 Spatial variability of soil engineering properties at USM campus, Third National Civil Engineering Conference A W AM-2004, School of Civil Engineering, Universiti Sains Malaysia.
2004 Soil Spatial Variability Effect on Soil-Structure Interaction Studies: Enveloping Uncertainties in Structural Response Proceedings, Third UJNR Workshop on Soil-Structure Interaction, Menlo Park, California, USA. 2005 study on the spatial variability and the sampling scheme of soil nutrients in the field based on GPS and GIS, Proceedings of the 2005 IEEE Engineering in Medicine and Biology 27th Annual Conference Shanghai, China.
APPENDIX A
SOIL MOISTURE CONTENT RESULT
Average 27.89
Average 26.01
Average 24.08
Average 28.86
Average 28.34
Average 44.27
Average 31.23
Average 36.42
Average 30.73
Average 28.80
Average 25.52
Average 40.74
Average 48.82
Average 23.39
Average 34.13
Average 27.07
Average 19.96
Average 24.72
Average 29.26
Average 14.99
Average 27.30
Average 35.83
Average 25.99
Average 22.81
Average 46.34
Average 28.75
Average 37.79
Average 30.56
Average 36.95
Average 18.69
Average 21.16
Average 20.94
Average 18.67
Average 20.44
Average 22.58
Average 34.66
Average 17.11
Average 17.88
Average 18.72
Average 27.33
Average 20.41
Average 50.19
APPENDIXB
BULK DENSITY RESULTS
Average 1.3545
Average 1.3758
Average 1.4111
Average 1.3495
Average 1.2923
Average 1.3631
Average 1.3175
Average 1.4596
Average 1.4833
Average 1.4573
Average 1.3094
Average 1.2760
Averaae 1.3983
Average 1.3752
Average 1.4797
Average 1.3995
Average 1.3139
Average 1.5758
Average 1.4064
Average 1.4632
Average 1.4561
Averaae 1.4344
Average 1.3474
Average 1.4018
Average 1.4145
Average 1.4261
Average 1.4434
Average 1.4226
Average 1.3156
Average 1.4396
Average 1.4284
Average 1.4235
Average 1.4480
Average 1.4307
Average 1.3298
Average 1.4389
Average 1.4815
Average 1.5221
Average 1.2848
Average 1.3462
Average 1.4809
Average 1.3215
APPENDIXC
SOIL ORGANIC CONTENT RESULTS
Average 4.57
Average 8.43
Average 1.83
Average 6.12
Average 3.25
Average 6.81
Average 1.54
Average 8.02
Average 2.15
Average 1.61
Average 2.44
Average 5.01
Average 9.45
Average 2.88
Average 3.82
Average 0.75
Average 5.66
Average 0.64
Average 2.92
Average 2.08
Average 2.24
Average 6.38
Average 2.20
AveraRe 2.37
Average 4.85
Average 2.86
Average 4.83
Average 0.81
Average 4.88
Average 3.53
Average 2.53
Average 1.37
Average 1.22
Average 1.07
Average 1.31
Average 2.62
Average 4.65
Average 1.40
Average 1.02
Average 5.06
Average 1.95
Average 1.55
Average 4.15
APPENDIXE
PARTICLE SIZE DISTRIBUTION CHART
Fine I Medium I Coarse Fine I Medium I Coarse Cobbles
