How to model water quality using SWAT model in the Amazon catchment?

Transcription

1 6 ème réunion scientifique du SO HYBAM 26-3 Octobre- Cuzco- Pérou How to model water quality using SWAT model in the Amazon catchment? SAUVAGE, S., SANCHEZ-PEREZ J.M., With the collaboration of SANTINI W., MARTINEZ J.M., MOREIRA-TURCQ P., LAVADO W.,GUYOT J.L... and who wants to come and work with us

2 Environmental changes (Human activities and Climate) Scientifical context Water resources and ecological services Hydro, C, N, P, Pesticides, metals, organic pollutants Quantify the specific role of natural biodegradation processes In the critical zone at multi-scale In different pedo-climatic context FLOW/CHEMISTRY/BIOLOGY

3 Our speciality : data development and modeling tools integrating Ecological functions Saint Laurent : Wetlands processes Obi, Yenisei : Permafrost hydrology Cuba : metals transport, Karst system Alluvial areas : interaction between surface water and groundwaters Mekong, Red River : wetlands, paddy rices, reservoirs Yantze : Biofilm, Reservoir, Sediment transport / wetlands areas Amazone : Wetlands; Reservoirs Oued rivers : Hydrology and pollutants tarnsport in non permanent rivers, Hyporheic zones Parana, Paraguay : Wetlands, Reservoir processes

4 Hydro-agro-environmental Models Spatial resolution> < Landscape scale 1 km² 1 km² 1 km² 1 km² 1 km² 1 km² Explicatf Power Mecanistic models : low calibration procedure Empirical models : calibration procedure Physically based model 3D MOHID Conceptual model SWAT, SENEQUE/Riverstrahler MGB NANI Approach Empirical model Input ex: precipitation Output ex: discharge; Nitrogen Sparrow, Green, Nutting approaches Annually Daily Horary Temporal resolution

5 Worldwide application, free model, easy to implement GIS Platform ArcSWAT Share experiences and implemented new processes Developers group to improve the model New improvements will be used for all

6 Different time and space scale Small Scale 3 km² Large Scale km 2 Nitrates fluxes kg/j/ha Comparaison des flux de nitrates à la sortie du bassin Gers Amont 1,E+ 1,E-1 en kg/j/ha 1,E-2 1,E-3 1/1/1996 1/1/1997 1/1/1998 1/1/1999 1/1/2 1/1/21 1/1/22 1/1/23 1/1/24 1/1/25 Flux simulé Flux mesuré Ferrant et al. 29 Lu et al. submitted

7 SWAT concepts Physical-based model, semi-distributed Watershed model agronomy module (EPIC) River model (Qual2E) Outlet Slope Soils Lansduse HRU Hydrological Response Unit Sub-basin basin J. G. Arnold, R. Srinivasan, R. S. Muttiah, and J. R. Williams. Large area hydrologic modeling and assessment - part 1 : Model development. Journal Of The American Water Resources Association, 34(1) :7389, February 1998.

8 SWAT concepts Inputs : Climate and anthropic activities Outlet SBV Slope Soils Lansduse HRU BV Hydrological Response Unit Sub-basin basin Outputs : Hydrology, SS Nitrates, Pesticides J. G. Arnold, R. Srinivasan, R. S. Muttiah, and J. R. Williams. Large area hydrologic modeling and assessment - part 1 : Model development. Journal Of The American Water Resources Association, 34(1) :7389, February 1998.

9 How to calibrate/evaluate the model? Data measurements : Remote sensing : snow cover Nitrates fluxes kg/j/ha Comparaison des flux de nitrates à la sortie du bassin Gers Amont 1,E+ 1,E-1 en kg/j/ha 1,E-2 1,E-3 1/1/1996 1/1/1997 1/1/1998 1/1/1999 1/1/2 1/1/21 1/1/22 1/1/23 1/1/24 1/1/25 Flux simulé Flux mesuré Cross modelling validation : river/aquifer exchanges (Martin et al. in review) 2SWEM/SWAT comparisons (Sun et al. 215)

10 In the case of the Amazonia watershed Combining remote sensing/data measurement + Expertise of Different scientists In different domains = Modelling of the functioning of Amazonia watershed and/or Sub-watershed Water resources and ecological services Ex : The model complete the network measurements Improve the knowledge Can help for management decisions

11 In the case of the Amazonia watershed Step 1 : Hydrology (Presentation of José Sanchez and coll.) : Amazonia 35 Monthy river dischage (m 3 /s) Rio Amazones (Obidios) Obs, Rio Amazones (Obidios) Sim, Step 2 : Sediment (William Santini and Coll) : Ucayali Monthy river dischage (m 3 /s Rio Amazones (Obidios) Obs, Rio Amazones (Obidios) Sim, 5 janv. févr. mars Delay effect avr.- mai- juin- juil.- août sept. oct.- nov. déc.- Step 3 : Dissolved element NO3 (DOC and POC) Step 4 : Others contaminants THE IMPORTANT ROLE OF ALLUVIAL PLAIN Transient storage zone

12 Martin et al. in revision, Geophysical Journal. Water resources at the scale of the Watershed ex: The Garonne (France) 51 km² Area: 51 5 km Precipitation Precipitation: 9 mm/yr Average annual discharge: 6 m3 s-1 Alluvial soil: 6% of the total area Agriculture: 31% of the total area 1 mm/year 8 6 ET 4 Water yield 2 Groundwater flow Sub-Surface Runoff Snow

13 Modelling the alluvial plain in different study sites in Europe With a complex model Complex Modelling : 3D MOHID Key parameters SWAT Bernard-Jannin, 215

14 SWAT-LUD (Landscape Unit Darcy) model Impermeable layer Sun et al., Hydrological Processes. In press LU 3 LU 2 LU 1 Channel LU 1 LU 2 LU 3 Based on flooded water volume F S S S LU 3 Naiman and Decamps, 1997 Matteo et al., 26 WL L LU 2 LU 1 L I I L I GW L Darcy s equation (1856): Denitrification G Subbasin-LU G G Organic Carbon NO 3 - Anaerobic environment + en zone saturée du sol Rich organic carbon content in soil table depth Flooding (Sun, 215)

15 Quantity Quality Calibration Validation Calibration Validation 92 LU 1 (1999-2) 92 LU 1 (213) Groundwater level (m NGF) P15 Simulated Groundwater level (m NGF) P9 Simulated D-99 J- F- M- A- M- J- J- A- S- O- 92 LU 2 (1999-2) 92 LU 2 (213) Groundwater level (m NGF) P22 Groundwater level (m NGF) P22 Simulated 85 85

16 The model «talks» to us Quantity 1 7 m Annually river-aquifer exchanged water quantity flooded river to aquifer aquifer to river net Quality 2 Annually denitrification rate (kg N-NO 3- /ha/y) Riparian Poplar Agriculture 3 2,5 2 1,5 1,5 Kg N-NO3-/ha J-93 J-95 J-97 J-99 J-1 J-3 J-5 J-7 J-9 denitrification Discharge J-11 J

17 Control parameters? The model «talks» to us 2 Annually denitrification rate (kg N-NO 3- /ha/y) 15 DOC denitrification 1 POC denitrification 5 Riparian Poplar Agriculture NO3 control Groundwater level control Denitrification rate (kg N-NO - 3 /ha/y) NO 3 - R² =, Nitrate Concentration (mg L -1 ) Denitrification rate (kg/n-no 3 - /ha/y) SL1 R² =,72 1 1,5 2 2,5 3 Groundwater level (m)

18 SWAT-LUD model : adapted and applied to Amazonia Nitrates Modelling DOC, POC =.. +. C (adapted from Ludwig and Probst, 1996) + %=. /( 2)+1 (adapted from Ludwig and Probst, 1996; Boithias et al., 214) %COP relation : % de carbone in the sub-layers of the soil Min SS concentration NEED TO WORK WITH RESEARCHERS INVOLVED IN PROCESSES

19 Applications to help management Water resources

20 Identification of pollution sources (and control parameters) Particulate sources (erosion) Sub basins Dissolved (nitrates) slope + Agriculture +++ Soil+ Slope +++ Agriculture ++ Soil + Oeurng et al. (21) Boithias et al. (214) 2

21 How to use the model for end users issues? Risks for Surface water supply pesticides contamination Mean pollution concentration in 21 Mean pollution concentration during a flood event du 1 au 1 mai 21 53% of the metolachlor annual flux is exported in 1 days <,1 µg.l-1,1-.5 µg.l-1 >,5 µg.l-1 <,1 µg.l-1,1-.5 µg.l-1 >,5 µg.l-1 Boithias et al

22 Integrating the tool in a platform adapted to the local issues but also for research and training SOIL/RIVER/GROUNDWATER/LAKE Continuum at the scale of a watershed Suspended sediment (mg -1 l ) Rain Intensity Forecast modelling 1 2 Rain falls (mm) 5 22

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