01.11.2015| Folie 1 Assessment of diffuse sources for pollution Meeting of the Working Group "Statistics of the Environment“ Sub-Group "Water“ 9 - 10 October.

Slides:



Advertisements
Similar presentations
Reporting sheet no.4 Emissions of pollutants Peter Kristensen SoE meeting 12 June 2007, Copenhagen.
Advertisements

Reporting sheet no.4 Emissions of pollutants Peter Kristensen, EEA Joint Eionet NRC Freshwater and Drafting group State of the Environment and Trends meeting.
Brian Kronvang EEA Workshop September 2008 U N I V E R S I T Y O F A A R H U S Danish Environmental Research Institute Department of Freshwater Ecology.
Institute of Freshwater Ecology and Inland Fisheries Changes of agricultural diffuse nutrient inputs in major European river systems and their contribution.
Source apportionment of nitrogen and phosphorous inputs into the aquatic environment - An EEA assessment presented by János Fehér h. Associate Professor.
Water Quality H. Behrendt, M. Grossmann, H. Gömann, U. Mischke, A. Schöll, J. Steidl GLOWA-Elbe GLOWA Status conference 19 May 2005 Cologne Linkages of.
4 th International Symposium on Flood Defence Generation of Severe Flood Scenarios by Stochastic Rainfall in Combination with a Rainfall Runoff Model U.
Development of DRAIN-WARMF Model to Simulate Water Flow & Nitrogen Transport From an Agricultural Watershed: “ Subsurface Flow Component” Shadi Dayyani.
The Wisconsin River TMDL: Linking Monitoring and Modeling Ann Hirekatur, Pat Oldenburg, & Adam Freihoefer March 7, 2013 Wisconsin River TMDL Project Team.
Some of my current research: Modeling sediment delivery on a daily basis for meso-scale catchments: a new tool: LAPSUS-D By: Saskia Keesstra and Arnaud.
Land Use Change and Its Effect on Water Quality: A Watershed Level BASINS-SWAT Model in West Georgia Gandhi Raj Bhattarai Diane Hite Upton Hatch Prepared.
L-THIA Long-Term Hydrologic Impact Assessment Model ….provides relative estimates of change of runoff and non point source pollutants caused due to land.
Surface Water Simulation Group. Comprehensive watershed scale model developed and supported by the USDA-ARS capable of simulating surface and groundwater.
Hydrologic/Watershed Modeling Glenn Tootle, P.E. Department of Civil and Environmental Engineering University of Nevada, Las Vegas
Engineering Hydrology (ECIV 4323)
Soil Water Assessment Tool (SWAT) Model Input
Eduardo Mondlane UniversityInstitute for Water Resource, Rhodes University PhD Proposal-Progress Agostinho Vilanculos Supervisors: - Prof. Denis Hughes.
Dr. R.P.Pandey Scientist F. NIH- Nodal Agency Misconception: A DSS takes decisions ---(No)
Riga, 25 th April 2007 Expert meeting Twinning LV/2005-IB/EN/01 Water Quality.
Twinning water quality modelling in Latvia Helene Ejhed, Kickoff meeting Twinning on development of modelling capacity to support water quality.
1 Flood Hazard Analysis Session 1 Dr. Heiko Apel Risk Analysis Flood Hazard Assessment.
Characterization Report Module 2: Water Budget, Pressures and Impacts, Significant Water Management Issues, Monitoring, Characterization Report Characterization.
Watershed Assessment and Diagnosis of Condition for August 20, 2007 Joe Magner and Greg Johnson MPCA.
National Environmental Research Institute Department of Freshwater Ecology WFD-Monitoring in Denmark NOVANA Brian Kronvang NERI.
1 Drainage and Environment, Results of the Monitoring of Non Point Source Pollution Viesturs Jansons Department of Environmental Engineering and Water.
Twinning water quality modelling in Latvia Helene Ejhed, Final workshop Twinning on development of modelling capacity to support water quality.
1 Evaluating and Estimating the Effect of Land use Changed on Water Quality at Selorejo Reservoir, Indonesia Mohammad Sholichin Faridah Othman Shatira.
CE 424 HYDROLOGY 1 Instructor: Dr. Saleh A. AlHassoun.
Twinning water quality modelling in Latvia Helene Ejhed
Assessment of Runoff, Sediment Yield and Nutrient Load on Watershed Using Watershed Modeling Mohammad Sholichin Mohammad Sholichin 1) Faridah Othman 2)
Engineering Hydrology (ECIV 4323)
ALTERRA Organic matter / nitrogen simulations with SWAP/ANIMO Joop Kroes & Piet Groenendijk.
The Drainage Basin System
Higher Hydrosphere Drainage Basins[Date] Today I will: - Know what a drainage basin is - Be able to explain it in terms of inputs, processes or outputs.
1. The Study of Excess Nitrogen in the Neuse River Basin “A Landscape Level Analysis of Potential Excess Nitrogen in East-Central North Carolina, USA”
Collecting, Processing and Distributing of Water Statistics in the Republic of Belarus Zhanna Vasilevskaya, Belarus International Work Session on Water.
 Before break, we discussed watersheds and what constitutes a watershed. How do you think water moves through a watershed?
AOM 4643 Principles and Issues in Environmental Hydrology.
Priority Substances Inventory Guidance a step towards international harmonization Joost van den Roovaart.
Surface Water Surface runoff - Precipitation or snowmelt which moves across the land surface ultimately channelizing into streams or rivers or discharging.
Module 2: GIS and data CCM version2, and other necessary data layer (JRC) Positioning of EIONET-water sites within the geometry of the catchment areas.
WEAP Demand Management
How much water will be available in the upper Colorado River Basin under projected climatic changes? Abstract The upper Colorado River Basin (UCRB), is.
GLOWA-Elbe II Statuskonferenz 14. Dez Potsdam Horst Gömann, FAL-LR Horst Gömann & Peter Kreins Institute of Rural Studies, Federal Agricultural Research.
Kristina Schneider Kristi Shaw
Hydrology and application of the RIBASIM model SYMP: Su Yönetimi Modelleme Platformu RBE River Basin Explorer: A modeling tool for river basin planning.
DIAS INFORMATION DAY GLOBAL WATER RESOURCES AND ENVIRONMENTAL CHANGE Date: 09/07/2004 Research ideas by The Danish Institute of Agricultural Sciences (DIAS)
Load Estimation Using Soil and Water Assessment Tool (SWAT)
NOPOLU System2 Large scale assessment of non-point nutrient sources.
Hydrology and application of the RIBASIM model SYMP: Su Yönetimi Modelleme Platformu RBE River Basin Explorer: A modeling tool for river basin planning.
Modeling with WEAP University of Utah Hydroinformatics - Fall 2015.
Sanitary Engineering Lecture 4
1 WaterWare description Data management, Objects Monitoring, time series Hydro-meteorological data, forecasts Rainfall-runoff: RRM, floods Irrigation water.
Nitrogen loading from forested catchments Marie Korppoo VEMALA catchment meeting, 25/09/2012 Marie Korppoo, Markus Huttunen 12/02/2015 Open DATA: Nutrient.
Kristina Schneider Kristi Shaw
Integrating Environment, Climate-Change & Water
Distributed modelling
Image courtesy of NASA/GSFC
Environmental modeling application domains
EC Workshop on European Water Scenarios Brussels 30 June 2003
Hydrology CIVL341.
Reporting sheet no.4 Emissions of pollutants
Engineering Hydrology (ECIV 4323)
Work on Agriculture and Water Linkages EEA in cooperation with JRC
Characterisation of water bodies in Austria – dangerous substances
Hydrology CIVL341 Introduction
H. Behrendt (IGB), H. Gömann (FAL), C. Sartorius (ISI)
Engineering Hydrology (ECIV 4323)
HELCOM and the Baltic Sea
Presentation transcript:

| Folie 1 Assessment of diffuse sources for pollution Meeting of the Working Group "Statistics of the Environment“ Sub-Group "Water“ October 2007 Luxembourg Katharina Lenz

| Folie 2 Contents Relevance of diffuse sources The EUROHARP-project Overview of different models Modeling of diffuse sources of heavy metals Summary & conclusion

| Folie 3 Diffuse sources /point sources Point sources Diffuse sources Diffuse sources are of high relevance !

| Folie 4 Diffuse sources /point sources in the Danube River Basin Danubs - project: Nutrient Fluxes in the Danube Basin Insitute for Water Quality and Waste management, Vienna University of Technology (2005). Nutrient Management in the Danube and ist Impact on the Black Sea, Final Report

| Folie 5 Relevance of diffuse sources EEA (2005). Source apportionment of nitrogen and phosphorus inputs into the aquatic environment, EEA- Report No7/2005

| Folie 6 Diffuse sources - Background Diffuse pollution cannot be measured, it has to be modeled! Validation of model with measured values at monitoring sites (monitoring networks) Water Framework Directive (WFD): harmonised tools/ methodologies to quantify nutrient losses from diffuse sources Project EUROHARP ( Objective: Comparison of different catchment scale modeling approaches for characterisation of the relative importance of point and diffuse pollution in surface freshwater systems Performance of 9 quantification tools in 17 European-wide river catchments Coordination: NIVA (Norvegian Institute for Water Research)

| Folie 7 EUROHARP

| Folie 8 EUROHARP QT no. Name of the QT Modelling institute Nutrients 1 NL - CATALTERRA(NL)[N, P] 2 Irish method-REALTAKMM (IRL)[P] 3 N-LESS NERI (DK)[N] 4 MONERIS FV-IGB (D)[N, P] 5 TRK (SOILN/HBV) SLU / SMHI (S)[N, P] 6 SWAT EC-JRC/NTUA (GR)/IRSA-CNR (I) [N, P] 7 EVENFLOW ADAS (UK)[N] 8 NOPOLU IFEN / BETURE-CEREC (F) [N, P] 9 Source apportionmentNERI (DK)[N, P] Process oriented, dynamic models: QT 1, 5, 6: dynamics of the fate of nutrient inputs in the soil are modelled in a two or three-dimensional way, often on a daily basis. Comprehensive representation of all individual system processes Semi-empiric models: QT 3, 4, 7: using a series of simpler, conceptual (semi-) empirical or statistical functions QT 2, 8, 9: do not consider soil processes, but can serve as “broad brush” tools to assess pollutant loads at catchment level.

| Folie 9 EUROHARP: 17 catchments Austria: Gurk catchment MONERIS SWAT NOPOLU Source apportionment Catchment area: 2.602km 2 Elevation Range: m Rainfall: 905 mm Arable land: ha Grassland: ha Forest: ha (55%) Lakes: 17 (>2 ha) Inhabitants: River Course Length: 150 km

| Folie 10 EUROHARP: N Balance for the Gurk Catchment per year t N/aSWATMONERISSA N-Input: Point sources Atmospheric deposition on water bodies Loss from woodland and other non- agricultural land Loss from agricultural land Total N-Input N-Output: Load Retention Total N-Output

| Folie 11 EUROHARP: P Balance for the Gurk Catchment per year t P/aSWATMONERISSA P-Input: Point Sources Atmospheric deposition on water bodies 20,4 Loss from woodland and other non- agricultural land Loss from agricultural land Total P-Input P-Output: Load Retention Total P-Output

| Folie 12 EUROHARP-Catchment Gurk: Results ModelSWATMONERISNOPOLUSAmeasured values Total area (ha) Agricultural land (ha) Period:1995– – – –1999 Flow (Mio m 3 /y) –902 Load (t N/y) –2.165 Load (t P/y) –82

| Folie 13 MONERIS

| Folie 14 MONERIS: MOdeling Nutrient Emissions in RIver Systems 7 pathways: atmospheric deposition groundwater tile drainage paved urban areas erosion surface runoff (dissolved nutrients) discharges from point sources (municipal waste water treatment plants and industrial discharges) Basic input into the model: Data on river flow water quality ( GIS integrating digital maps (e.g. hydrogeo- logical maps, soil maps) statistical information (inhabitants, land use)

| Folie 15

| Folie 16

| Folie 17 Phosphorus EinwohnerFläche Atmosphär -ische Deposition Abschwem- mung DränagenErosion Grund- wasser Punkt- quellen versiegelte urbane Flächen Gesamt Landwirt- schaftliche Aktivitäten PLR Nr. Planungs- raum [E][km²][t/a] 1Rhein Elbe Donau bis Jochenstein Donau unterhalb Jochenstein March Mur Drau Leitha, Raab und Rabnitz Gesamt Österreich ,6%24,4%0,2%41,9%10,9%17,5%4,4%100,0%36,6% MONERIS: Austrian example Phosphorus

| Folie 18 MONERIS model +: No model calibration needed Good applicability for catchments size ≥ 500 km 2 Representation of full N- and P-cycle Identification of emission pathways Consideration of retention processes in groundwater and surface water Scenario calculations possible -: Empirical approaches limited in their applicability (particularly for semi-arid regions) limited spatial distribution Uncertainty increases with decreasing catchment size limited temporal variations (5 years annual values) GIS data needed to parameterise the model

| Folie 19 SWAT

| Folie 20 SWAT SWAT: 3 dimensional/continous time watershed model that operates on a daily time step at basin scale. management & timing of agricultural practises  rivers Nitrogen processes in the soil described in SWAT

| Folie 21 SWAT Precipitation Irrigation Rain Snow Snow melt Surface Runoff Transmission Losses Infiltration Snow cover Soil Storage Soil Evaporation Plant Uptake and Transpiration Lateral Flow Percolation Soil Water routing (10 layers) Sreamflow Irrigation Diversion Transmission Losses Route to next Reach or Reservoir Shallow Aquifer Irrigatio n RevapSeepag e Return Flow Pond/ Reservoir Water Balance P/R Evaporation Irrigation P/R Outflow P/R Seepage Deep Aquifer Irrigation SWAT: hydrological processes

| Folie 22 SWAT model +: good representation of hydrological conditions (3 runoff components, ETR, snow melt…) spatial distribution of hydrologic characteristics diverse options for land management river chemistry comprehensive definition of soil characteristics calculation of components of N- and P-cycle, distinction between land and water phase Calculation on daily timestep -: model calibration in general Number of parameters to be calibrated on HRU-, subbasin- or basin-level definition of some hydrologic parameter not on same level (snow melt-basin level, soil-HRU, GW- subbasin) no connection between GW-recharge and baseflow for N-cycle (no scenario calcuations) Limitation in applicability regarding catchment area Erosion (P-emissions) decisively dependent on well calibrated surface runoff components

| Folie 23 NOPOLU NOPOLU: N-balance; N-surplus + transfer model dep. on soil characteristics  part of it to surface waters Nitrogen input balance used within NOPOLU

| Folie 24 SOURCE APPORTIONMENT Source apportionment (SA): based on the assumption: Total nitrogen and phosphorus loads at the selected river measurement site (Lriver) represent the sum of the nitrogen and phosphorus discharges from point sources (DP), the nitrogen and phosphorus losses from diffuse sources (LOD) and the natural background losses of nitrogen and phosphorus (LOB). Furthermore retention of nitrogen and phosphorus in the rivers is taken into account (R). LOD = Lriver - DP - LOB + R

| Folie 25 Applicability of models Main questions: - is the model valid for use under the specific catchment conditions being considered? - what is the temporal and spatial scale at which model output is required, and which chemical species need to be modelled? - what are the resource limitations (time and data costs) on a particular study (the models vary widely in their high or low data input requirements and time needed for model applications)

| Folie 26 Diffuse sources: Heavy metals Fuchs, S.; Scherer, U.; Hillenbrand, T.; Marscheider-Weidemann, F.; Behrendt, H.; Opitz, D. (2002): Emissions of Heavy Metals and Lindane into River Basins of Germany. UBA-Texte 55/02, Berlin, Germany

| Folie 27 Diffuse sources: Heavy metals Upgrade of nutrient models for application on heavy metal emissions MONERIS (Oltmann et al., 2003): addition of heavy metal typical transport processes and specific pathways to the basic module: historic mining activities shipping Update of input data concerning heavy metals Data inquiries to improve the input data are needed

| Folie 28 Summary & Conclusion  Diffuse sources represent an important source for nutrients and heavy metals into the aquatic environment  Calculation/ modeling of diffuse source pollution is an issue for water experts  ask at universities, ministries, water associations  Diffuse sources issue of WFD  contact administrative bodies responsible for WFD - implementation  Different models vary considerably as regards input data, complexity, resources needed and level of process representation  Choice of methodology/ model used individually based on requirements in a country

| Folie 29 Thank you for your attention!