Die Pilotphase Kleingewässermonitoring konnte als drittes Teilvorhaben zur "Umsetzung des Nationalen Aktionsplan zur nachhaltigen Anwendung von Pflanzenschutzmitteln (PSM)" erfolgreich als zweijähriges Monitoring umgesetzt werden. Es wurden für mehr als 100 Fließgewässerabschnitte in 13 Bundesländern umfassend der chemische und biologische Zustand kleiner Fließgewässer in der Agrarlandschaft zwischen April und Juli erfasst. Zusätzlich zu Schöpfproben analog zu dem behördlichen Monitoring nach Wasserrahmenrichtlinie (WRRL) wurden ereignisbasierte Wasserproben genommen, um kurzfristige Peakkonzentrationen infolge von Niederschlägen zu erfassen. Zudem wurden anthropogene Stressoren wie Gewässerstruktur, Nährstoffe und Sauerstoffdefizite hochaufgelöst aufgenommen. Die biologische Untersuchung umfasste die Beprobung der aquatischen Invertebraten- und Algengemeinschaft sowie eine Untersuchung der Ökosystemfunktion in den Kleingewässern. Die Ergebnisse zeigen, dass die im Rahmen des Zulassungsverfahrens von PSM festgelegten RAK-Werte (Regulatorisch Akzeptablen Konzentrationen) an über 73 % der untersuchten Standorte für mindestens einen PSM-Wirkstoff überschritten wurden. Besonders die Ereignisproben infolge von Regenereignissen wiesen erhöhte Konzentrationen auf, die durch Schöpfproben nicht erfasst wurden. Diese Belastungen korrelieren auch mit der ökologischen Situation der Gewässer. So erfüllt der Großteil (über 80 %) der untersuchten Fließgewässerabschnitte anhand des SPEARpesticides-Index nicht die Qualitätskriterien für einen guten Zustand. Die Pilotphase Kleingewässermonitoring zeigt, dass eine realistische Bewertung und regulatorische Nutzung eines Monitorings von PSM-Rückständen in kleinen Gewässern nur dann erfolgen kann, wenn auch erhöhte Einträge infolge von Niederschlagsereignissen berücksichtigt werden. Weiterhin treten auch unterhalb der bestehenden RAK-Werte ökologische Effekte im Gewässer auf, so dass sich die Frage nach der Protektivität der aus Labordaten abgeleiteten RAK-Werte stellt. Die Daten der ermittelten PSM-Belastung der kleinen Gewässer in der Agrarlandschaft werden dazu beitragen, Ursachen für die regelmäßige Überschreitung der bestehenden Grenzwerte zu ermitteln und Schwächen der bisherigen Risikobewertung aufzudecken. Ziel wird sein, auf dieser Basis Möglichkeiten zur Reduzierung der Einträge zu erarbeiten und regulatorische Konsequenzen zu ziehen. Siehe dazu auch Liess et al. (2021) und Weisner et al. (2021). Quelle: Forschungsbericht
[ Derived from parent entry - see the respective metadata entry ] Simulated 2D residual velocity fields in the inner German Bight were subjected to Principal Component Analysis (PCA). Residual currents were obtained from coastDat2 barotropic 2D simulations with the hydrodynamic model TRIM-NP V2.1.22 in barotropic 2D mode on a Cartesian grid (1.6km spatial resolution) stored on an hourly basis for the years 1948 - 2012 (doi:10.1594/WDCC/coastDat-2_TRIM-NP-2d) and later extended until August 2015. The present analysis refers to the period Jan 1958 - Aug 2015. The spatial domain considered is the region to the east of 6 degrees east and to the south of 55.6 degrees north. All grid nodes with a bathymetry of less than 10m were excluded. Residual velocities were calculated in two different ways: 1.) as 25h means, 2.) as monthly means. Both types of residual current data are available from * RESIDUAL_CURRENTS_195801_201508 The directory contains sub-directories for years and months. Daily residual currents for the 13th of September 1974, for instance, are stored in * RESIDUAL_CURRENTS_195801_201508/YEAR_1974/MONTH_09/TRIM2D_1974_09_13_means.nc while monthly mean residual currents for September 1974 are stored in: * RESIDUAL_CURRENTS_195801_201508/YEAR_1974/TRIM2D_1974_09_means.nc All current fields provided were interpolated from the original Cartesian model grid to a more convenient regular geographical grid (116x76 nodes). Mean residual currents are stored in: * mean_residual_currents.nc This data set contains residual velocities both on original Cartesian grid nodes and interpolated to the geographical grid. An example plot is provided: * mean_residual_currents.png For PCA, two residual velocity components from each of 12133 Cartesian grid nodes were combined into one data vector (length 2x12133), referring to 21061 daily or 692 monthly time levels. Results of two independent PCAs for either daily or monthly mean fields are stored in: * PCA_daily_residual_currents.nc * PCA_monthly_residual_currents.nc Files contain three leading Principal Components (PCs) and corresponding Emipirical Orthogonal Functions (EOFs). Again EOFs were also interpolated to a regular geographical grid. PC time series are also stored in plain ASCII format: * PCs_daily.txt * PCs_monthly.txt For monthly fields the number N of variables (N=2x12133) is much larger than the number T of time levels (T=692). Therefore, to reduce computational demands, the roles of time and space were formally interchanged. Having conducted the PCA the EOFs were then transformed back to the original spatial coordinates (cf. Section 12.2.6 in von Storch and Zwiers (1999), Statistical Analysis in Climate Research, Cambridge University Press). A much larger number of time levels made even this approach prohibitive for the full set of daily data. Therefore, PCAs were performed for six sub-periods (1958-1965, 1966-1975, 1976-1985, 1986-1995, 1996-2005, 2006-2015(Aug)) independently. EOFs obtained from these six sub-periods were then averaged to obtain EOFs representative for the whole period. Corresponding PCs were calculated by projecting daily fields onto these average EOFs. IMPORTANT: In contrast with PCA of monthly data, the PCA of daily data INVOLVES SOME APPROXIMATIONS! EOFs on the original nodes were normalized to have unit lengths. The following figures, * daily_EOF1.png * daily_EOF2.png * daily_EOF3.png show the first three EOFs obtained from daily data, assuming that corresponding PCs have the value of one standard deviation. The following two plots, * monthly_EOF1.png * monthly_EOF2.png show the leading EOFs for monthly mean data. EOF3 is omitted as it represents just a very small percentage of overall variance (1.7%).
[ Derived from parent entry - see the respective metadata entry ] Simulated 2D residual velocity fields in the inner German Bight were subjected to Principal Component Analysis (PCA). Residual currents were obtained from coastDat2 barotropic 2D simulations with the hydrodynamic model TRIM-NP V2.1.22 in barotropic 2D mode on a Cartesian grid (1.6km spatial resolution) stored on an hourly basis for the years 1948 - 2012 (doi:10.1594/WDCC/coastDat-2_TRIM-NP-2d) and later extended until August 2015. The present analysis refers to the period Jan 1958 - Aug 2015. The spatial domain considered is the region to the east of 6 degrees east and to the south of 55.6 degrees north. All grid nodes with a bathymetry of less than 10m were excluded. Residual velocities were calculated in two different ways: 1.) as 25h means, 2.) as monthly means. Both types of residual current data are available from * RESIDUAL_CURRENTS_195801_201508 The directory contains sub-directories for years and months. Daily residual currents for the 13th of September 1974, for instance, are stored in * RESIDUAL_CURRENTS_195801_201508/YEAR_1974/MONTH_09/TRIM2D_1974_09_13_means.nc while monthly mean residual currents for September 1974 are stored in: * RESIDUAL_CURRENTS_195801_201508/YEAR_1974/TRIM2D_1974_09_means.nc All current fields provided were interpolated from the original Cartesian model grid to a more convenient regular geographical grid (116x76 nodes). Mean residual currents are stored in: * mean_residual_currents.nc This data set contains residual velocities both on original Cartesian grid nodes and interpolated to the geographical grid. An example plot is provided: * mean_residual_currents.png For PCA, two residual velocity components from each of 12133 Cartesian grid nodes were combined into one data vector (length 2x12133), referring to 21061 daily or 692 monthly time levels. Results of two independent PCAs for either daily or monthly mean fields are stored in: * PCA_daily_residual_currents.nc * PCA_monthly_residual_currents.nc Files contain three leading Principal Components (PCs) and corresponding Emipirical Orthogonal Functions (EOFs). Again EOFs were also interpolated to a regular geographical grid. PC time series are also stored in plain ASCII format: * PCs_daily.txt * PCs_monthly.txt For monthly fields the number N of variables (N=2x12133) is much larger than the number T of time levels (T=692). Therefore, to reduce computational demands, the roles of time and space were formally interchanged. Having conducted the PCA the EOFs were then transformed back to the original spatial coordinates (cf. Section 12.2.6 in von Storch and Zwiers (1999), Statistical Analysis in Climate Research, Cambridge University Press). A much larger number of time levels made even this approach prohibitive for the full set of daily data. Therefore, PCAs were performed for six sub-periods (1958-1965, 1966-1975, 1976-1985, 1986-1995, 1996-2005, 2006-2015(Aug)) independently. EOFs obtained from these six sub-periods were then averaged to obtain EOFs representative for the whole period. Corresponding PCs were calculated by projecting daily fields onto these average EOFs. IMPORTANT: In contrast with PCA of monthly data, the PCA of daily data INVOLVES SOME APPROXIMATIONS! EOFs on the original nodes were normalized to have unit lengths. The following figures, * daily_EOF1.png * daily_EOF2.png * daily_EOF3.png show the first three EOFs obtained from daily data, assuming that corresponding PCs have the value of one standard deviation. The following two plots, * monthly_EOF1.png * monthly_EOF2.png show the leading EOFs for monthly mean data. EOF3 is omitted as it represents just a very small percentage of overall variance (1.7%).
[ Derived from parent entry - see the respective metadata entry ] Simulated 2D residual velocity fields in the inner German Bight were subjected to Principal Component Analysis (PCA). Residual currents were obtained from coastDat2 barotropic 2D simulations with the hydrodynamic model TRIM-NP V2.1.22 in barotropic 2D mode on a Cartesian grid (1.6km spatial resolution) stored on an hourly basis for the years 1948 - 2012 (doi:10.1594/WDCC/coastDat-2_TRIM-NP-2d) and later extended until August 2015. The present analysis refers to the period Jan 1958 - Aug 2015. The spatial domain considered is the region to the east of 6 degrees east and to the south of 55.6 degrees north. All grid nodes with a bathymetry of less than 10m were excluded. Residual velocities were calculated in two different ways: 1.) as 25h means, 2.) as monthly means. Both types of residual current data are available from * RESIDUAL_CURRENTS_195801_201508 The directory contains sub-directories for years and months. Daily residual currents for the 13th of September 1974, for instance, are stored in * RESIDUAL_CURRENTS_195801_201508/YEAR_1974/MONTH_09/TRIM2D_1974_09_13_means.nc while monthly mean residual currents for September 1974 are stored in: * RESIDUAL_CURRENTS_195801_201508/YEAR_1974/TRIM2D_1974_09_means.nc All current fields provided were interpolated from the original Cartesian model grid to a more convenient regular geographical grid (116x76 nodes). Mean residual currents are stored in: * mean_residual_currents.nc This data set contains residual velocities both on original Cartesian grid nodes and interpolated to the geographical grid. An example plot is provided: * mean_residual_currents.png For PCA, two residual velocity components from each of 12133 Cartesian grid nodes were combined into one data vector (length 2x12133), referring to 21061 daily or 692 monthly time levels. Results of two independent PCAs for either daily or monthly mean fields are stored in: * PCA_daily_residual_currents.nc * PCA_monthly_residual_currents.nc Files contain three leading Principal Components (PCs) and corresponding Emipirical Orthogonal Functions (EOFs). Again EOFs were also interpolated to a regular geographical grid. PC time series are also stored in plain ASCII format: * PCs_daily.txt * PCs_monthly.txt For monthly fields the number N of variables (N=2x12133) is much larger than the number T of time levels (T=692). Therefore, to reduce computational demands, the roles of time and space were formally interchanged. Having conducted the PCA the EOFs were then transformed back to the original spatial coordinates (cf. Section 12.2.6 in von Storch and Zwiers (1999), Statistical Analysis in Climate Research, Cambridge University Press). A much larger number of time levels made even this approach prohibitive for the full set of daily data. Therefore, PCAs were performed for six sub-periods (1958-1965, 1966-1975, 1976-1985, 1986-1995, 1996-2005, 2006-2015(Aug)) independently. EOFs obtained from these six sub-periods were then averaged to obtain EOFs representative for the whole period. Corresponding PCs were calculated by projecting daily fields onto these average EOFs. IMPORTANT: In contrast with PCA of monthly data, the PCA of daily data INVOLVES SOME APPROXIMATIONS! EOFs on the original nodes were normalized to have unit lengths. The following figures, * daily_EOF1.png * daily_EOF2.png * daily_EOF3.png show the first three EOFs obtained from daily data, assuming that corresponding PCs have the value of one standard deviation. The following two plots, * monthly_EOF1.png * monthly_EOF2.png show the leading EOFs for monthly mean data. EOF3 is omitted as it represents just a very small percentage of overall variance (1.7%).
[ Derived from parent entry - see the respective metadata entry ] Simulated 2D residual velocity fields in the inner German Bight were subjected to Principal Component Analysis (PCA). Residual currents were obtained from coastDat2 barotropic 2D simulations with the hydrodynamic model TRIM-NP V2.1.22 in barotropic 2D mode on a Cartesian grid (1.6km spatial resolution) stored on an hourly basis for the years 1948 - 2012 (doi:10.1594/WDCC/coastDat-2_TRIM-NP-2d) and later extended until August 2015. The present analysis refers to the period Jan 1958 - Aug 2015. The spatial domain considered is the region to the east of 6 degrees east and to the south of 55.6 degrees north. All grid nodes with a bathymetry of less than 10m were excluded. Residual velocities were calculated in two different ways: 1.) as 25h means, 2.) as monthly means. Both types of residual current data are available from * RESIDUAL_CURRENTS_195801_201508 The directory contains sub-directories for years and months. Daily residual currents for the 13th of September 1974, for instance, are stored in * RESIDUAL_CURRENTS_195801_201508/YEAR_1974/MONTH_09/TRIM2D_1974_09_13_means.nc while monthly mean residual currents for September 1974 are stored in: * RESIDUAL_CURRENTS_195801_201508/YEAR_1974/TRIM2D_1974_09_means.nc All current fields provided were interpolated from the original Cartesian model grid to a more convenient regular geographical grid (116x76 nodes). Mean residual currents are stored in: * mean_residual_currents.nc This data set contains residual velocities both on original Cartesian grid nodes and interpolated to the geographical grid. An example plot is provided: * mean_residual_currents.png For PCA, two residual velocity components from each of 12133 Cartesian grid nodes were combined into one data vector (length 2x12133), referring to 21061 daily or 692 monthly time levels. Results of two independent PCAs for either daily or monthly mean fields are stored in: * PCA_daily_residual_currents.nc * PCA_monthly_residual_currents.nc Files contain three leading Principal Components (PCs) and corresponding Emipirical Orthogonal Functions (EOFs). Again EOFs were also interpolated to a regular geographical grid. PC time series are also stored in plain ASCII format: * PCs_daily.txt * PCs_monthly.txt For monthly fields the number N of variables (N=2x12133) is much larger than the number T of time levels (T=692). Therefore, to reduce computational demands, the roles of time and space were formally interchanged. Having conducted the PCA the EOFs were then transformed back to the original spatial coordinates (cf. Section 12.2.6 in von Storch and Zwiers (1999), Statistical Analysis in Climate Research, Cambridge University Press). A much larger number of time levels made even this approach prohibitive for the full set of daily data. Therefore, PCAs were performed for six sub-periods (1958-1965, 1966-1975, 1976-1985, 1986-1995, 1996-2005, 2006-2015(Aug)) independently. EOFs obtained from these six sub-periods were then averaged to obtain EOFs representative for the whole period. Corresponding PCs were calculated by projecting daily fields onto these average EOFs. IMPORTANT: In contrast with PCA of monthly data, the PCA of daily data INVOLVES SOME APPROXIMATIONS! EOFs on the original nodes were normalized to have unit lengths. The following figures, * daily_EOF1.png * daily_EOF2.png * daily_EOF3.png show the first three EOFs obtained from daily data, assuming that corresponding PCs have the value of one standard deviation. The following two plots, * monthly_EOF1.png * monthly_EOF2.png show the leading EOFs for monthly mean data. EOF3 is omitted as it represents just a very small percentage of overall variance (1.7%).
[ Derived from parent entry - see the respective metadata entry ] Simulated 2D residual velocity fields in the inner German Bight were subjected to Principal Component Analysis (PCA). Residual currents were obtained from coastDat2 barotropic 2D simulations with the hydrodynamic model TRIM-NP V2.1.22 in barotropic 2D mode on a Cartesian grid (1.6km spatial resolution) stored on an hourly basis for the years 1948 - 2012 (doi:10.1594/WDCC/coastDat-2_TRIM-NP-2d) and later extended until August 2015. The present analysis refers to the period Jan 1958 - Aug 2015. The spatial domain considered is the region to the east of 6 degrees east and to the south of 55.6 degrees north. All grid nodes with a bathymetry of less than 10m were excluded. Residual velocities were calculated in two different ways: 1.) as 25h means, 2.) as monthly means. Both types of residual current data are available from * RESIDUAL_CURRENTS_195801_201508 The directory contains sub-directories for years and months. Daily residual currents for the 13th of September 1974, for instance, are stored in * RESIDUAL_CURRENTS_195801_201508/YEAR_1974/MONTH_09/TRIM2D_1974_09_13_means.nc while monthly mean residual currents for September 1974 are stored in: * RESIDUAL_CURRENTS_195801_201508/YEAR_1974/TRIM2D_1974_09_means.nc All current fields provided were interpolated from the original Cartesian model grid to a more convenient regular geographical grid (116x76 nodes). Mean residual currents are stored in: * mean_residual_currents.nc This data set contains residual velocities both on original Cartesian grid nodes and interpolated to the geographical grid. An example plot is provided: * mean_residual_currents.png For PCA, two residual velocity components from each of 12133 Cartesian grid nodes were combined into one data vector (length 2x12133), referring to 21061 daily or 692 monthly time levels. Results of two independent PCAs for either daily or monthly mean fields are stored in: * PCA_daily_residual_currents.nc * PCA_monthly_residual_currents.nc Files contain three leading Principal Components (PCs) and corresponding Emipirical Orthogonal Functions (EOFs). Again EOFs were also interpolated to a regular geographical grid. PC time series are also stored in plain ASCII format: * PCs_daily.txt * PCs_monthly.txt For monthly fields the number N of variables (N=2x12133) is much larger than the number T of time levels (T=692). Therefore, to reduce computational demands, the roles of time and space were formally interchanged. Having conducted the PCA the EOFs were then transformed back to the original spatial coordinates (cf. Section 12.2.6 in von Storch and Zwiers (1999), Statistical Analysis in Climate Research, Cambridge University Press). A much larger number of time levels made even this approach prohibitive for the full set of daily data. Therefore, PCAs were performed for six sub-periods (1958-1965, 1966-1975, 1976-1985, 1986-1995, 1996-2005, 2006-2015(Aug)) independently. EOFs obtained from these six sub-periods were then averaged to obtain EOFs representative for the whole period. Corresponding PCs were calculated by projecting daily fields onto these average EOFs. IMPORTANT: In contrast with PCA of monthly data, the PCA of daily data INVOLVES SOME APPROXIMATIONS! EOFs on the original nodes were normalized to have unit lengths. The following figures, * daily_EOF1.png * daily_EOF2.png * daily_EOF3.png show the first three EOFs obtained from daily data, assuming that corresponding PCs have the value of one standard deviation. The following two plots, * monthly_EOF1.png * monthly_EOF2.png show the leading EOFs for monthly mean data. EOF3 is omitted as it represents just a very small percentage of overall variance (1.7%).
[ Derived from parent entry - see the respective metadata entry ] Simulated 2D residual velocity fields in the inner German Bight were subjected to Principal Component Analysis (PCA). Residual currents were obtained from coastDat2 barotropic 2D simulations with the hydrodynamic model TRIM-NP V2.1.22 in barotropic 2D mode on a Cartesian grid (1.6km spatial resolution) stored on an hourly basis for the years 1948 - 2012 (doi:10.1594/WDCC/coastDat-2_TRIM-NP-2d) and later extended until August 2015. The present analysis refers to the period Jan 1958 - Aug 2015. The spatial domain considered is the region to the east of 6 degrees east and to the south of 55.6 degrees north. All grid nodes with a bathymetry of less than 10m were excluded. Residual velocities were calculated in two different ways: 1.) as 25h means, 2.) as monthly means. Both types of residual current data are available from * RESIDUAL_CURRENTS_195801_201508 The directory contains sub-directories for years and months. Daily residual currents for the 13th of September 1974, for instance, are stored in * RESIDUAL_CURRENTS_195801_201508/YEAR_1974/MONTH_09/TRIM2D_1974_09_13_means.nc while monthly mean residual currents for September 1974 are stored in: * RESIDUAL_CURRENTS_195801_201508/YEAR_1974/TRIM2D_1974_09_means.nc All current fields provided were interpolated from the original Cartesian model grid to a more convenient regular geographical grid (116x76 nodes). Mean residual currents are stored in: * mean_residual_currents.nc This data set contains residual velocities both on original Cartesian grid nodes and interpolated to the geographical grid. An example plot is provided: * mean_residual_currents.png For PCA, two residual velocity components from each of 12133 Cartesian grid nodes were combined into one data vector (length 2x12133), referring to 21061 daily or 692 monthly time levels. Results of two independent PCAs for either daily or monthly mean fields are stored in: * PCA_daily_residual_currents.nc * PCA_monthly_residual_currents.nc Files contain three leading Principal Components (PCs) and corresponding Emipirical Orthogonal Functions (EOFs). Again EOFs were also interpolated to a regular geographical grid. PC time series are also stored in plain ASCII format: * PCs_daily.txt * PCs_monthly.txt For monthly fields the number N of variables (N=2x12133) is much larger than the number T of time levels (T=692). Therefore, to reduce computational demands, the roles of time and space were formally interchanged. Having conducted the PCA the EOFs were then transformed back to the original spatial coordinates (cf. Section 12.2.6 in von Storch and Zwiers (1999), Statistical Analysis in Climate Research, Cambridge University Press). A much larger number of time levels made even this approach prohibitive for the full set of daily data. Therefore, PCAs were performed for six sub-periods (1958-1965, 1966-1975, 1976-1985, 1986-1995, 1996-2005, 2006-2015(Aug)) independently. EOFs obtained from these six sub-periods were then averaged to obtain EOFs representative for the whole period. Corresponding PCs were calculated by projecting daily fields onto these average EOFs. IMPORTANT: In contrast with PCA of monthly data, the PCA of daily data INVOLVES SOME APPROXIMATIONS! EOFs on the original nodes were normalized to have unit lengths. The following figures, * daily_EOF1.png * daily_EOF2.png * daily_EOF3.png show the first three EOFs obtained from daily data, assuming that corresponding PCs have the value of one standard deviation. The following two plots, * monthly_EOF1.png * monthly_EOF2.png show the leading EOFs for monthly mean data. EOF3 is omitted as it represents just a very small percentage of overall variance (1.7%).
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