Riparian Vegetation Density Mapping of an Extremely Densely Vegetated Confined Floodplain
István Fehérváry, Tímea Kiss
Abstract
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István Fehérváry, Tímea Kiss
Abstract
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The most crucial function of lowland-confined floodplains with low slopes is to support flood conveyance and fasten floods; however, obstacles can hinder it. The management of riparian vegetation is often neglected, though woody species increase the vegetation roughness of floodplains and increase flood levels. The aims are (1) to determine the branch density of various riparian vegetation types in the flood conveyance zone up to the level of artificial levees (up to 5 m), and (2) to assess the spatial distribution of densely vegetated patches. Applying a decision tree and machine learning, six vegetation types were identified with an accuracy of 83%. The vegetation density was determined within each type by applying the normalized relative point density (NRD) method. Besides, vegetation density was calculated in each submerged vegetation zone (1–2 m, 2–3 m, etc.). Thus, the obstacles for floods with various frequencies were mapped. In the study area, young poplar plantations offer the most favorable flood conveyance conditions, whereas invasive Amorpha thickets and the dense stands of native willow forests provide the worst conditions for flood conveyance. Dense and very dense vegetation patches are common in all submerged vegetation zones; thus, vegetation could heavily influence floods.
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The most crucial function of lowland-confined floodplains with low slopes is to support flood conveyance and fasten floods; however, obstacles can hinder it. The management of riparian vegetation is often neglected, though woody species increase the vegetation roughness of floodplains and increase flood levels. The aims are (1) to determine the branch density of various riparian vegetation types in the flood conveyance zone up to the level of artificial levees (up to 5 m), and (2) to assess the spatial distribution of densely vegetated patches. Applying a decision tree and machine learning, six vegetation types were identified with an accuracy of 83%. The vegetation density was determined within each type by applying the normalized relative point density (NRD) method. Besides, vegetation density was calculated in each submerged vegetation zone (1–2 m, 2–3 m, etc.). Thus, the obstacles for floods with various frequencies were mapped. In the study area, young poplar plantations offer the most favorable flood conveyance conditions, whereas invasive Amorpha thickets and the dense stands of native willow forests provide the worst conditions for flood conveyance. Dense and very dense vegetation patches are common in all submerged vegetation zones; thus, vegetation could heavily influence floods.
Key concepts: Riparian zone, Floodplain, Vegetation (pathology), Thicket, Levee, Hydrology (agriculture), Environmental science, Riparian forest