Application of Open Source GIS (GRASS)

Application of Open Source GIS (GRASS)

SHARE

Ramin Safamanesh
Department of Environment University Putra Malaysia
Malaysia
Email: [email protected]

Wannor Azmin Sulaiman , Firuz Ramli

Abstract
GRASS is a Geographic Information System (GIS) used for data management, image processing, graphics production, spatial modeling and visualization of many types of data. Grass allows users to analyze, store, update, model, and display data quickly and easily,(Netler, 2002).Watershed degradation due to soil erosion and sedimentation is considered to be one of the major environmental problems in Iran. In order to address the critical situations of watershed degradation as well as insufficient availability of hydrometric stations, a study on the validity of applying an empirical model (MPSIAC) developed in the arid and semi-arid conditions of the United States to predict annual average sediment yield to Iranian watershed’s condition was carried out. The Modified Pacific Southwest Inter Agency Committee model (MPSIAC) incorporates nine environmental factors that contribute to watershed’s sediment yield. The factors are surface geology, soil, climate, runoff, topography, ground cover, land use, channel and upland erosion. In this study, the model was developed for Zargeh watershed with an area of 8.8 square kilometers. The source of data input to the model was obtained from available records on rainfall and river discharge and sediment (20 years), topography, land use, geology and soil maps as well as from field surveying and laboratory analysis. GRASS GIS (ver. 5.0.0) was used to facilitate the spatial interpolation of the nine model factors and interpretation of predicted sediment yield for the entire watershed. Twenty years sediment yield records from 1981 to 2000 were used to validate the simulated model results. Using GIS/GRASS sediment yield scores by creating raster file (map) of nine factor affect sedimentation and erosion in MPSIAC model and overlying the maps, average sediment yield score map for period of records was grown up perfectly, for every pixel of map. Meanwhile results of simple linear regression analysis between simulated results and actual field records indicated that there is a significant correlation (P < 0.05) with r2 = 0.6124 and standard error of 2868.2 ton/year. In the sensitivity analysis, it was found that the most sensitive parameters of the model in the order of importance are climate, channel erosion and runoff factors. Surface geology, soil and slope factors were found to be insensitive to model output. The results of the study clearly indicated that the model can be applied to the Iranian conditions with recommended improvements be made on method to interpret upland erosion factor. The study also reveals that the model is more suitable for predicting yearly average sediment yield using GIS (GRASS) on a long time frame. The interest for this kind of model may be to establish long term watershed management plans or goals such as zoning (using GIS) of watershed's soil erosion potential where ranking is important.