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                <identifier>oai:data.mendeley.com/7w55385wp7.1</identifier>
                <datestamp>2025-05-27T14:54:49Z</datestamp>
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    <dc:creator>Sawicka, Katarzyna Małgorzata</dc:creator>
    <dc:title>Krogulec, E., Sawicka, K., &amp; Zabłocki, S., (2025), [Dataset] for Spatiotemporal Assessment of Groundwater Drought in a River Valley Aquifer Using Standardized Indices in Central Poland</dc:title>
    <dc:publisher>Mendeley Data</dc:publisher>
    <dc:description>his research is supported by four primary datasets, each contributing to the spatiotemporal assessment of hydrogeological drought in the Kampinos National Park, Poland:

Precipitation Time Series (time series_precipitation.xlsx)
This file contains monthly precipitation totals (in millimeters) recorded between January 1, 1999 and October 1, 2020. Data were collected from nine meteorological stations located within the Kampinos National Park: Izabelin, Dziekanów Leśny, Famułki, Kiścienne, Leszno, Pociecha, Wilków, Rybitew, and Granica.

Groundwater Level Time Series (time series_groundwater.xlsx)
This dataset includes monthly measurements of groundwater levels (in meters above sea level, m a.s.l.) from 56 piezometers forming part of the Kampinos National Park monitoring network. The time coverage is consistent with the precipitation dataset: from January 1, 1999 to October 1, 2020.

Meteorological Station Locations (location_precipitation stations.xlsx)
This file provides the geographical coordinates (ETRF 1989 / Poland 1992 reference system) for the nine weather stations used in the precipitation monitoring network.

Piezometer Locations (location_piezometers.xlsx)
This file contains the names and spatial coordinates (ETRF 1989 / Poland 1992) of the 56 piezometers included in the groundwater observation network.

Together, these datasets offer high-resolution temporal and spatial insight into the interactions between meteorological conditions and groundwater dynamics in a natural, protected aquifer system. They form the empirical basis for the drought index calculations and cluster-based spatiotemporal analysis presented in the study.</dc:description>
    <dc:subject>Hydrology</dc:subject>
    <dc:subject>Hydrogeology</dc:subject>
    <dc:subject>Drought</dc:subject>
    <dc:contributor>Krogulec, Ewa</dc:contributor>
    <dc:contributor>Zabłocki, Sebastian</dc:contributor>
    <dc:type>Dataset</dc:type>
    <dc:identifier>doi:10.17632/7w55385wp7.1</dc:identifier>
    <dc:identifier>oai:data.mendeley.com/7w55385wp7.1</dc:identifier>
    <dc:rights>Creative Commons Attribution 4.0 International</dc:rights>
    <dc:rights>http://creativecommons.org/licenses/by/4.0</dc:rights>
    <dc:relation>https://data.mendeley.com/datasets/7w55385wp7</dc:relation>
    <dc:date>2025-05-27T14:54:49Z</dc:date>
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