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Details

Autor(en) / Beteiligte
Titel
Prediction of flood discharge and flood flow depth using a hydraulic model and flood marks on the trees in ungauged forested watersheds
Ist Teil von
  • Journal of forest science (Praha), 2022, Vol.68 (5), p.190-198
Ort / Verlag
Prague: Czech Academy of Agricultural Sciences (CAAS)
Erscheinungsjahr
2022
Link zum Volltext
Quelle
EZB Free E-Journals
Beschreibungen/Notizen
  • It is difficult to estimate flood discharges and the flood zones as well as to design hydraulic structures in rivers without using hydrometric stations. Furthermore, using different models to determine the mentioned cases will be accompanied by errors. Therefore, flood marks on the trunks of trees located in the Babolrood riverbed were used to determine the peak discharge, flood flow depth, and flood zone in northern Iran. First, a hydraulic model for the study river was provided using topographic maps with a scale of 1: 1 000, HEC-GeoRAS extension (GIS), and HEC-RAS model. Then, the flood marks of past floods in the form of silt and clay sediments (deposits on the trees in the riverbed) were evaluated and the maximum flood flow depth was determined. Finally, the peak discharge of the past flood was estimated by the trial-and-error method to achieve the flood flow depth in the different river reaches. Then, the hydraulic model using the flow depth data was calibrated in the reaches, and, in the final step, based on the flood marks of other reaches, the model was validated. According to the results, the maximum instantaneous discharge rate of the study flood was 155 m3·s–1 and the maximum flood flow depth was about 2 m. Furthermore, the results showed that the flood mark data in forest lands can be used as a tool for the calibration and validation of hydraulic models. The present methodology is an efficient method for determining the flood peak discharge, spatial variation of the flood depth, and flood zone in forest watersheds without hydrometric stations.
Sprache
Englisch; Tschechisch; Slowakisch
Identifikatoren
ISSN: 1212-4834
eISSN: 1805-935X
DOI: 10.17221/6/2022-JFS
Titel-ID: cdi_doaj_primary_oai_doaj_org_article_2683f8a7fe4d40bb88d94166bf18c9a3

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