home    land degradation    project outcome    Gallery Flooding Flood Hazard Assessment Pilot Area • The Pilot Areas • Climate • Cover factor (C) estimation • Digital terrain analysis • Relationship between soil properties • Relationship of soil properties with different land use/cover types Methodology • Methodologies • LISEM Results • Result Soil Properties and Land Use • Runoff rate for different land cover types • Model calibration and validation • Sensitivity analysis • Land use scenarios • Rainfall size scenarios • Flooding Scenario - 2 years return period • Flooding Scenario - 10 years return period • Flooding Scenario - 20 years return period • Flooding Scenario - 50 years return period • Summary tables for each flood characteristic • Flood hazard mapping • Conclusions and Recommendation Erosion Erosion Assessment Pilot Area • The Pilot Areas • Climate • Cover factor (C) estimation • Digital terrain analysis • Relationship between soil properties • Relationship of soil properties with different land use/cover types Methodology • Methodologies • Erosion Models Result • Results • C-Factor Mapping for erosion assessment • Soil erosion assessment • Assessment of land use/cover change effect on soil erosion • Assessing critical zones for ephemeral gully formation • Erosion Assessment by Different Models • The recommended erosion models • RMMF Landslide Case I • Landslide hazard assessment • The area (Pilot 3) • Landslide Mapping in Wang Chin using digital image analysis Techniques. • Results • Discussions Case II • Doi Ang Khang (Ang Khang) (Pilot area 4) • Landslide mapping in Ang Khang using aerial photos • Landslide Inventory Mapping • Landslide modelling and Susceptibility mapping • Landslide Susceptibility Maps from the three Scenarios (models) • Comparison between Ang Khang and Wang Chin (with respect to weights of evidence modelling using morphometric parameters) Salinization Case I • Pilot area II • Soil salinity • Salinization • Geomorphology • Soils • Geopedologic map • Results Case II • CASE II - The study of Yadav, R.D. (2005), • Methodology • Crop Simulation Model • PS 123 • Results • Mathematical (Regression) Model for Crop Yield Estimation • Conclusion Case III • Case III • Modeling Salinization • Geostatistics and Interpolation (GIS and Kriging) • Model Simulation and Prediction of Salinity • Simulated Depth to water table • Tenth Years Prediction • Twenty Years Prediction • Conclusion Runoff • Surface Runoff • Methodology • Modelling Runoff • Modelling Runoff Using Empirical Approach • Modelling runoff using the Semi-physical approach • Estimation with the Curve Number Method • Results and Discussion • Generation of Scenarios • Comparison of runoff rates with soil loss map • Conclusions • Presentation of papers based on project work at international • Workshop in Lomsak • Hua Hin seminar • Training of LDD staff • GIS and RS based predictive soil mapping • Soil erosion assessment • Landslide hazard assessment • Flood hazard assessment • Soil salinity study • List of completed MSc. theses on project SOIL EROSION ASSESSMENT The annual soil loss predictions using data from 2007 ranges between 0 and 61 tons/hectare. Average soil loss was highest (26 tons/hectares/year) in agriculture area and lowest soil loss rate was found in forest area (0.99 tons/hectare/year). For degraded forest, grassland and orchard, the soil loss rates were 1.47, 5.39 and 8.76 tons/hectare/year respectively. These results proved that vegetation cover strongly influenced erosion process. Due to high vegetation cover such as in forest and degraded forest area, annual soil loss rate seems to be low, conversely in agriculture area more erosion because of less vegetation cover. Although orchard area had more canopy cover as compared to degrade forest or forest area but ground cover was low because farmers frequently remove grasses. This reason caused more erosion in orchard than degraded forest. For grassland, it depended on prior land use/cover types before. It gave less soil loss rates because some areas the farmer was not removed the residues after harvesting and let the grass growth in the areas. Table : 1 Soil loss prediction in different land use/cover 2007 Land use class Area in percent Soil loss (t/h/y) SD. Forest 12.87 0.99 0.27 Degraded Forest 34.04 1.47 0.55 Agricultrure 25.32 26.06 13.52 Grassland 11.70 5.39 3.63 Orchard 16.07 8.76 0.51 Total 100   Figure 1 : Soil loss map (Suriyaprasit, 2008) The soil loss map then was classified into erosion prone areas using threshold values adapted from literature (Morgan, 1995; Singh and Phadke, 2006). Five classes were made: very slight (1-4.99 tons/hectares/year), slight (5-9. tons/hectares/year), moderate (10-24. tons/hectares/year), severe (25- 44.99 tons/hectares/year) and very severe (> 45 tons/hectares/year). The tolerance of soil loss rate that agriculturist should be concerned was more than 10 ton/hectares/year (Morgan, 1995). This threshold was applied to Namchun watershed for the difference between slight class and moderate class. The erosion prone areas map of Namchun watershed 2007 is shown in Figure 2 . Figure 2 : Erosion prone areas classified from soil loss map (Suriyaprasit, 2008) Table 2 : Erosion prone areas in different land use/cover Land use class Soil loss rate (t/h/y) Erosion prone areas Forest 0.99 Very slight Degraded Forest 1.47 Very slight Agricultrure 26.06 Severe Grassland 5.39 Slight Orchard 8.76 Slight It was cleared that agriculture areas were high erosion level. They fell into severe class meanwhile orchard and grassland were slight class. Conversely, forest and degraded forest were found lowest erosion level (very slight). Overall areas had average 20.22 (tons/hectares/year) of annual soil loss rate. It illustrated more than tolerance soil loss value 10 (tons/hectares/year) and fell in moderate class. Development of Methodologies for Land Degradation Assessment Applied to Land Use Planning in Thailand ^go to top