‹ › ×

    FRED
    • Contact
    • GDPR policy
    • Imprint
    • About
    • Sign Up
    • Login
    • SEARCH
    • Search and find
    • Packages
    • Map
    • By Category ...
      • Study sites
      • Sampling sites
      • Parameters
      • Sampling types
      • Species groups
      • Current DOIs

    572 Discharge and nitrate records at Peat North, Peat South, Demnitz Mill, DM27 and Berkenbruck

    Title
    Discharge and nitrate records at Peat North, Peat South, Demnitz Mill, DM27 and Berkenbruck
    Period
    1992-01-01 till 2019-01-01
    Period length
    27 years
    Sampling interval
    1 year
    Description

    The dataset consist of discharge records at Demnitz Mill and in-stream nitrate records at Peat North, Peat South, Demnitz Mill, DM27 and Berkenbruck.

    Keywords
    Discharge; nitrate; DMC catchment
    Study site
    Demnitzer Mühlenfließ
    Contact
    Songjun Wu
    Licence for data
    All rights reserved. Please send a request to Songjun Wu if you like to use this data. Mind our data policy: IGB Data Policy

    Data files (e.g. excel)

    TitlecreatedFiletypeActions
    Discharge_nitrate_DMC.csv 07. Jun. 2021 09:36 datatable: .csv Download

    Machine Readable Metadata Files

    FRED provides all metadata of this package in a maschine readable format. There is a pure XML file and one EML file in Ecological Metadata Language. Both files are published under the freeODC-ByLicence.

    • Discharge_and_nitrate_records_at_Peat_North,_Peat_South,_Demnitz_Mill,_DM27_and_Berkenbruck.xml
    • Discharge_and_nitrate_records_at_Peat_North,_Peat_South,_Demnitz_Mill,_DM27_and_Berkenbruck.eml

    You are about to leaving FRED and visting a third party website. We are not responsible for the content or availability of linked sites.

    To remain on our site, click Cancel.

    Parsing data File

    Estimated Time:

    Why does it take so much time?

    While parsing a file, the database has to perform various tasks, some of them needs a lot of CPU and memory for larger files.

    • preprocessing: means automatic detection of headlines, table body, format values or csv-separators
    • copying: means read the file cell by cell and copy all elements to the database. During this format settings can be calculated (for example iso-time)
    • analyzing: check out for different data types (can be time, numeric or text)