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 CROP SIMULATION MODEL Crop simulation models, are mathematical representations of plant growth process. These processes are dependent on crop genotype, environment and management. Crop growth models are described by various authors/researchers These models are WOFOST, PS123, EPIC and CROPWAT. WOFOST can predict yield of annual crop on the basis of climate and soil data. It has facility to calculate water limited and nutrient limited crop yield. EPIC model can be used to estimate soil productivity under different degrees of erosion. Similarly, CROPWAT model is used for calculation of water and irrigation requirements on a monthly basis from weather, soil and crop data. These models have played an important role as an indispensable tool for supporting scientific research, crop management and policy analysis . However, these models do not have facility to simulate solute movement (especially salinity). All these facility along with salinity are available in CropSyst (Cropping System Simulation model) and have been tested in many countries under different climatic conditions. According to Stockle et al.(2003), CropSyst is a users friendly, multi-year, multi-crop, daily time step cropping systems simulation model developed to serve as an analytical tool to study the effect of climate, soils, and management on cropping systems, productivity and the environment. It has a facility to link to GIS software, a weather generator. The model is also used to simulate the soil water and nitrogen budgets, crop growth and development, crop yield, crop phenology, canopy and root growth, biomass production, residue production and decomposition, soil erosion by water, and salinity. However, these simulation processes are affected by the parameters such as weather, soil characteristics, crop characteristics and crop management these include crop rotation, cultivar selection, irrigation, nitrogen fertilization, soil and irrigation water salinity, tillage operation and residue management. CropSyst Figure 1 : Simulation flow chart of CropSyst model References FAO, A computer programme for irrigation planning and management. 1992. Stockle, C.O., Donatelli M., and Nelson R., CropSyst, a cropping systems simulation model. European Journal of Agronomy, 2003. 18(3-4): p. 289-307. Van Diepen, C.A., Van Diepen, C.A., W0lf, J., Van Keulen, H., Berkhout, J.A.A,, Land Evaluation: from intuition to quantification. Advances in soilsciences, 1991. 15: p. p. 139-204. Williams, J.R., Jones , C. A., Kiniry, J.R., Spanel, D.A,, The EPIC crop growth model. ASAE, 1989. 32(2). Yang, H.S., Dobermann, A., Lindquist, J. L., Walters, D. T., Arkebauer, T. J., Cassman, K. G.,, Hybrid-maize--a maize simulation model that combines two crop modeling approaches. Field Crops Research, 2004. 87(2-3): p. 131-154. Development of Methodologies for Land Degradation Assessment Applied to Land Use Planning in Thailand ^go to top