Effects of Geographic Information Quality on Soil Erosion Prediction
Buch in deiner Nähe kaufen
Beschreibung
Soil erosion is one of the most serious problems in the mountainous areas. Geographic Information Systems (GIS) are widely applied to predict soil erosion, as all factors on soil erosion can be extracted by spatial analysis. Therefore, the quality of spatial data plays a great role on the prediction and the most appropriated data should be used for input data to the model.
The purpose of this study is to evaluate the sensitivity of GIS data quality for the Revised Universal Soil Loss Equation (RUSLE) model. Different quality of GIS data input for two catchments in Switzerland and a catchment in Thailand are applied to the calculation. A programmed Visual Basic Application (VBA) extension on ArcGIS 9.2 and the geostatistics analysis are used for the calculation.
Moreover, the study aims to improve the soil erosion prediction, experienced from the study, using GIS technology. In order to achieve the aim, the study recommends different methods:
the use of GIS database of different soil-scales, the soil GIS data sharing, the Web-based GIS soil data and the soil erosion metadata model.
From the study, the developed algorithm (VBA application) is implemented on ArcGIS 9.2 Interface and has shown to be a good tool for the RUSLE model in the study areas. The results of the study present that in the heterogeneous slope area, the finer Digital Elevation Model (DEM) yields more accurate the soil erosion values. In contrast, in the flatter area, coarse DEM derives similar results to the finer ones. The finer DEMs are expensive, therefore it should be used as necessary.
Also, the channelization results using different methods, which combine DEM and a Vector River Network (VRN), are completed. The results show that the VRN is very effective to identify the channels starting points. The study highly recommends to combine the VRN with the DEM for channelization in all cases.
Furthermore, the soil erosion metadata model is established conforming to the ISO 19115. It is found that the basic GIS data (DEM, Vector River Network, etc.) can apply to ISO 19115, but specific metadata (soil types, cropping types, etc.) is needed to identify the particular data.
Altogether, the GIS data transfer, the interoperability in GIS, a unique standard for soil classifications, Spatial Data Infrastructures (SDI) and the soil erosion metadata model should be completed for all soil data in order to share all data from different sources or organizations. The methodologies will support all users to access the most appropriate GIS data and then obtain the more accurate soil erosion.
Autor*in
Karika Kunta
Themen in »Effects of Geographic Information Quality on Soil Erosion Prediction«
Bodenerosion Erosion Geografische Informationssysteme Hochwasser Hochwasservorhersage Hydrologische Vorhersage Modelle und Simulation in der Bodenkunde Modellrechnung Prognose Wassererosion