Identification of homogenous regions in Gorganrood basin (Iran) for the purpose of regionalization

نویسندگانAbdolhay, A - Saghafian, B - Golian, S - Moramarco, T - Shamsaee, A
نشریهNatural Hazards
ارائه به نام دانشگاهTechnical and Engineering Department, Science and Research Branch Islamic Azad University
شماره صفحات1427-1442
شماره مجلد61
ضریب تاثیر (IF)1.901
نوع مقالهFull Paper
تاریخ انتشار2012
رتبه نشریهISI
نوع نشریهچاپی
کشور محل چاپهلند

چکیده مقاله

Estimation of flood in basins with poor condition of hydrometric stations as in quantity and quality is a dominant problem around the world, mainly in developing country where lack of funds and human resources cause more limitation in number of gauging stations. One of the areas that experience frequent floods and also suffer from small number of stations in Iran is Gorganrood basin. So there is a great need for the estimation and prediction of runoff in this area to prevent any future floods. Due to insufficient station in this area, direct prediction of flood is not applicable. Regional flood frequency analysis is a practical and widely used solution for these situations, which involves the identification of homogenous regions. Gorganrood region was hydrologically homogenized according to the extracted parameters that influence the floods. One of these parameters was Normalized Difference Vegetation Index (NDVI) driven from MODIS images. Curvature is another parameter that relates to topographic attributes. From factor analysis, the most appropriate variables were selected. According to these parameters (NDVI, curvature, area, slope…), the regions were classified into homogenous regions. For the purpose of homogenization, hierarchical (wards) clustering, fuzzy clustering and Kohonen method were applied. L-moment technique was used for the investigation of the results. The heterogeneity measure for one of the groups (Group 1) was more than two; therefore some modifications were applied. The region was grouped into two homogenous subregions. All of the clustering methods showed same results. The models showed that class 4 of NDVI is influential on flood in some return periods. The resulted models can be applied in future studies in different aspects of practical hydrology.

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