University of Twente Student Theses
Spatial Modelling and Timely Prediction of Salinization using SAHYSMOD in GIS Environment: (a case study of Nakhon Ratchasima,Thailand)
Desta, Tsegay Fithanegest (2009) Spatial Modelling and Timely Prediction of Salinization using SAHYSMOD in GIS Environment: (a case study of Nakhon Ratchasima,Thailand).
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| Abstract: | Salinization is a complex process, often initiated from subsurface. This is one of the reasons why it is so difficult in tracing it at its earliest stage of development, using a wide range of techniques and methods. For that matter agricultural productivity is observed to be hampered by the development of root zone salinity through the use of brackish water during spate irrigation and capillary rise of saline water table. The salinity problem of the northeast of Thailand in general, and that of the Korat area in particular is due to rise of saline groundwater table and deposition of salts on the surface through capillary action. Thus it is difficult to trace back its early stage using optical remote sensing (RS) alone. In this study we apply an integration of (hydrological) modelling and remote sensing (RS) to track down the temporal and spatial soil salinization process in the area. The numeric hydrological model, SAHYSMOD, is used to image the subsurface solute movement by parameterizing the surfaces and subsurface water movement through the interaction of climate, soil, crop and human responses factors. Use is also made of RS, which addresses the status of the soil salinity event at time of surveillance. Through the ‘give and take’ type process of both techniques in GIS environment modelling of the salinization process became possible, both in space and time dimension. Here, GIS plays the role integration the results of the two techniques. The results are then extrapolated to the unsampled section of the study area using the devised decision support system (decision tree). By doing so the intended objectives of the study: detecting salinity change in time and spaces and modelling salinization as a process have been achived. The model has answered two basic questions of the research, 1), to define the source of salinity of the area; the rise of saline groundwater table, and 2) geopedological mapping units which are prone to salinization. The supervised image classification has made it clear that the low lying areas have been invaded at time of imaging. The model predictions have identified those areas which were less salt affected soils or not at all in the image classification are now prone to be affected due to the rise of saline groundwater table. According to 20 years of prediction from the model salinization route (development) is towards the west side of the study area, which is currently none saline, with a rate of 20% per year per geomorphic unit area coverage. That means areas which are currently (non saline=NS) and have total area coverage of 234.20 km2, are endangered and could be changed into salt affected soils if and only if the existing conditions have not changed to the favour of the environment. Key words: spatial modelling, prediction, SAHYSMOD, ECFC and DSS |
| Item Type: | Essay (Master) |
| Faculty: | ITC: Faculty of Geo-information Science and Earth Observation |
| Programme: | Geoinformation Science and Earth Observation MSc (75014) |
| Link to this item: | https://purl.utwente.nl/essays/91629 |
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