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 METHODOLOGIES 1. Soil properties and land use study In order to supplement and implement the runoff modelling approach conducted in this study, certain soil properties that play key roles in the generation of runoff were assessed in relation to different land use types and in relation to one another. These soil properties are including organic matter content, porosity, bulk density, saturated hydraulic conductivity, initial soil moisture content and saturated soil moisture content. Soil physical properties are the most important factors influencing the rate of water that can infiltrate into the soil. Infiltration serves as indicators for the influence of land use on the soil (Zimmermann et al., 2006) and it has also a reducing effect on the generation of runoff volume in a catchment. 2. Model applications In this study, The Limburg Soil Erosion Model (LISEM) was used to quantify the amount of runoff in the upper catchment that take into account effect of land cover change and also how different factors affect surface runoff. The LISEM is constructed with the PCRater dynamic modelling language (Wesseling et al., 1996) which allows great flexibility. Moreover, on a GIS level LISEM uses a raster type representation of the catchment which allows detailed representation of the processes. In case of limited data availability, the user can also choose Green and Ampt or the Holtan equation for infiltration calculation (De Roo, 2000). The results show not only the total runoff at the outlet but also the amount of sediment. 3. Flood modeling In order to quantify the effect of the upper catchment runoff, a combined 1D2D hydraulic model is used to model the propagation of the flow over flat terrain. SOBEK 1D2D model combines one dimensional channel flow with overland flow, which is represented by a 2D-grid of elevation information. The overall methodology of the modelling is indicated in figure. Figure 1 : The overall methodology for flood modelling. References De Roo, A.P.J., 2000. Applying the LISEM Model for investigating Flood Prevention and Soil Conservation Scenarios in South-Limburg, the Netherlands. In: J. Schmidt (Editor), Soil Erosion: Application of Physically Based Models. Springer, Heidelberge, pp. 318. Wesseling, C.G., Karssenberg, D., Burrough, P.A. and Van Deursen, W.P.A., 1996. Integrating dynamic evironmental models in GIS: The development of the dynamic modeling language. Transactions in GIS, 1: 40-48. Zimmermann, B., Elsenbeer, H. and De Moraes, J.M., 2006. The influence of land-use changes on soil hydraulic properties: Implications for runoff generation. Forest Ecology and Management, 222(1-3): 29-38. http://www.sciencedirect.com/science/article/B6T6X-4HV74J4-1/2/47e54214d2f8cfa8d8777330d2a84561 Development of Methodologies for Land Degradation Assessment Applied to Land Use Planning in Thailand ^go to top