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Browsing by Subject "Digital Elevation Model"

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  • thumbnail.journal.alt
    Item type:Thesis, Access status: Restricted ,
    Conceptual hydrological and hydrogeological model of the Stichtse Rijnlanden in the Netherlands
    (Data obrony: 2018-05-30) Teuerle, Anna
    Wydział Geologii, Geofizyki i Ochrony Środowiska
    The hydrogeological conceptual model was made for the Stichtse Rijnlanden region in the Netherlands. The model is based on the literature review and by using the advanced Dinoloket geological data base, KNMI climatic conditions, the hydrogeological model REGIS II, and data from the municipal office in Stichtse Rijnlanden. It is supported with hydrological analysis of DEM in the ArcGIS program. Langbroekerwetering, as part of the Stichtse Rijnlanden region, represents hydrogeological conditions.
  • thumbnail.journal.alt
    Item type:Article, Access status: Open Access ,
    Designation of flood risk zones using the Geographic Information System Technique and remote sensing data in Wasit, Iraq
    (Wydawnictwa AGH, 2021) Rasn, Kouther Hasheem; Nsaif, Qutaiba Abdulwahhab; Al-Obaidi, Mudhar; John, Yakubu Mandafiya
    Floods are a great concern for people and infrastructure, and this is an is‑sue which has increased in several regions around the globe in recent years. This study aims to evaluate flood risk areas and create a flood risk map using in‑tegrated remote sensing data and a geographic information system (GIS) in the Wasit governorate - eastern Iraq. Specifically, GIS‑based multi‑criteria analy‑sis (MCA) was used to map flood hazard areas using a four‑criteria layer which is as follows: flow accumulation, slope, rainfall, and elevation. These four layers are standardized and combined using the overlay approach in ArcGIS software and a final map was produced. The study area was divided into five zones based on the results map, namely: very low, low, medium, high, and very high, according to the flood risk area. The resulting map indicates that over 60% of the study area is likely to experience a high and very high level of propensity of flooding. This study could be useful for government planners and decision‑makers to predict potential flooding areas and enhance flood management plans.