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Hydrological modelling of the Fischbachtal catchment using two sources of precipitation data

Kissel, Michael and Rebscher, Angela and Bach, Anna and Schmalz, Britta (2018):
Hydrological modelling of the Fischbachtal catchment using two sources of precipitation data.
In: 17th Biennial Conference ERB2018 (Euromediterranean Network of Experimental and Representative Basins), Darmstadt, 11.-14.09.2018, [Online-Edition: http://erb-network.simdif.com/],
[Conference or Workshop Item]

Abstract

Precipitation is the most important input in hydrological rainfall runoff modelling. Traditionally precipitation is recorded at rain gauges on the surface and interpolated to give a regional average. However, in more recent years an increasing amount of precipitation data from remote sensing has become available. This offers the potential for a better spatial representation of precipitation and is especially of interest for areas with no or very few rain gauges. Two main questions that arise are how the acquired data of the two sources differ and how this impacts the rainfall runoff modelling process. Currently a study is being undertaken for the Fischbach catchment in the federal state of Hesse, Germany, to address aspects of these questions. Data from several surface rain gauges as well as remote sensing data is available. The remote sensing data is acquired from the Global Precipitation Measurement (GPM) mission with a daily resolution. Precipitation data will be compared on different timescales e.g. monthly, seasonal etc.. The catchment will be modelled with a hydrological model named BlueM. A modified curve number approach is used to calculate excess precipitation for each sub catchment. Calibration is performed with BlueM.Opt and resulting parameter setsare compared. The study ends in July of 2018 and selected first results will be shown.

Item Type: Conference or Workshop Item
Erschienen: 2018
Creators: Kissel, Michael and Rebscher, Angela and Bach, Anna and Schmalz, Britta
Title: Hydrological modelling of the Fischbachtal catchment using two sources of precipitation data
Language: English
Abstract:

Precipitation is the most important input in hydrological rainfall runoff modelling. Traditionally precipitation is recorded at rain gauges on the surface and interpolated to give a regional average. However, in more recent years an increasing amount of precipitation data from remote sensing has become available. This offers the potential for a better spatial representation of precipitation and is especially of interest for areas with no or very few rain gauges. Two main questions that arise are how the acquired data of the two sources differ and how this impacts the rainfall runoff modelling process. Currently a study is being undertaken for the Fischbach catchment in the federal state of Hesse, Germany, to address aspects of these questions. Data from several surface rain gauges as well as remote sensing data is available. The remote sensing data is acquired from the Global Precipitation Measurement (GPM) mission with a daily resolution. Precipitation data will be compared on different timescales e.g. monthly, seasonal etc.. The catchment will be modelled with a hydrological model named BlueM. A modified curve number approach is used to calculate excess precipitation for each sub catchment. Calibration is performed with BlueM.Opt and resulting parameter setsare compared. The study ends in July of 2018 and selected first results will be shown.

Uncontrolled Keywords: precipitation, remote sensing, hydrological rainfall runoff modelling
Divisions: 13 Department of Civil and Environmental Engineering Sciences
13 Department of Civil and Environmental Engineering Sciences > Institute of Hydraulic and Water Resources Engineering
13 Department of Civil and Environmental Engineering Sciences > Institute of Hydraulic and Water Resources Engineering > Engineering Hydrology and Water Management
Event Title: 17th Biennial Conference ERB2018 (Euromediterranean Network of Experimental and Representative Basins)
Event Location: Darmstadt
Event Dates: 11.-14.09.2018
Date Deposited: 25 Apr 2019 11:08
Official URL: http://erb-network.simdif.com/
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