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Erschienen in:
2019 | OriginalPaper | Buchkapitel
Automated Updating of Land Cover Maps Used in Hydrological Modelling
verfasst von : Muhammad Haris Ali, Thaine H. Assumpção, Ioana Popescu, Andreja Jonoski
Erschienen in: Business Information Systems Workshops
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Abstract
Urbanization and rapid growth in population are common development in many catchments and flood plains, often leading to increased flood risks. In hydrological models of regions with urban spread out, the parameters representing changes in land cover need to be frequently updated for obtaining better estimations of the discharge (runoff). This article presents an automated method for incorporating updated model parameters (SCS curve numbers) as per new land cover maps, and using them in a hydrological model. The presented work is developed for one part of Kifisios catchment in Greece, which is a pilot area of the Horizon 2020 SCENT research project (https://scent-project.eu/), focused on producing updated land use/land cover maps using crowdsourcing data provided by citizens, combined with data from remote sensing and drone images.
The method uses a newly available land cover map, which, together with other data, is automatically geo-processed in ArcGIS to provide updated SCS curve numbers. This is achieved using Python programing language and the ArcPy libraries of ArcGIS. The updating of the pre-developed HEC-HMS hydrological model with new SCS curve numbers is implemented in MATLAB, through a specialized API for changing inputs to the HEC-HMS model. The whole process is executed via a GUI developed in MATLAB, which also allows to run the HEC-HMS automatically, and present updated results - discharge hydrographs.