Eco-hydrological assessment of German lowland catchments experiences and challenges- N. Fohrer, B. Schmalz, G. HörmannH

Transcription

1 Eco-hydrological assessment of German lowland catchments experiences and challenges- N., B. Schmalz, G. HörmannH Dep. Hydrology & Water Resources Management Ecology Centre, CAU Kiel 1

2 Landscape processes in lowlands Low hydraulic gradients Large water retention/storage potential caused by lakes and wetlands Saturation overland flow > infiltration excess overland flow (Horton) High spatial variability in soils due to ice-age Connected/unconnected potholes Alpine Low mountain Lowland 2

3 Anthropogenic Impacts Tile drains Ditches River regulations 3

4 Assessment of lowland processes: -the catchments- 4

5 Treene and Kielstau catchments Kielstau-EZG (obere Treene) 5 UBA

6 Sampling strategy: nested approach Treene catchment: 517 km², 60 km river length Kielstau catchment 50 km², 11 km river length drained section of Kielstau catchment 0.15 km², 200 m ditch length 6

7 Assessment of water quality 7

8 Potential nutrient entry pathways Hennebach (Kysweek) Moorau # # # # # # ## Kielstau 8

9 Continuous observation and sampling Parameter Phosphate (PO 4 _P) Ammonium (NH 4 _N) Total Phosphorus (TP) Method Spectrophotometry Spectrophotometry Spectrophotometry Nitrate (NO 3 ) Ion chromatography Dep. Hydrology Chloride & Water (Cl) Resources Management, Ion chromatography CAU Kiel Sulphate (SO 4 ) Ion chromatography 9

10 In situ measurement campaingns 10

11 Water quality transects sampling strategy - 16 sampling points - 9 tributaries 11

12 Ammonium-N mainly from point sources NH4-N [mg/l] 2,5 2 1,5 1 Moorau ( 1 WWTP & poultry farm) Ammonium Hennebach ( 3 WWTP!) 0, Messpunkt oberhalb unterhalb/ep im Zulauf GK I GK I-II GK II GK II-III GK III 12

13 Nitrate-N- mainly non-point sources Nitrat NO3-N [mg/l] Messpunkt oberhalb unterhalb/ep im Zulauf GK I GK I-II GK II GK II-III GK III 13

14 Water quality assessment - LAWA 1998 Nitrate nitrogen 0.0 LAWA class III-IV (great burden) NO3_N mg/l All the other sampling points reached at least LAWA class III (enhanced burden) Apr Apr May Jun Jun Jul Aug Aug Sep Oct Oct Nov Dec Dec Jan Feb Feb Mar-06 Moorau tributary Moorau tributary precipitation mm precipitation NO3_N (mg/l) I: zero burden I-II: very low burden II: moderate burden II-III: significante burden III: enhanced burden III-IV: great burden 14

15 Eco-hydrological modelling 15

16 Maps Input data for the Kielstau catchment Digital elevation model (LVermA, 1995) Land use (DLR, 1999) Soil map (BGR, 1999) Time series data: -- climate data data (DWD) -- discharge values (LANU) 16

17 Simulated distribution Ergebnis of 1drainage density, GIS- based algorithm Modelled drainage areas ca. 38% of the catchment Golon,

18 Validation of drainage algorithm Agricultural area 381 ha Drained areas (digitized) 141 ha 37% (d. LN) Drained ares (modelled) 184 ha 48% (d. LN) Exact overlap 98,5 ha 70% Absolute area difference 11% Golon,

19 Stepwise model calibration of the Kielstau Model - initial parameterization Model GW_DELAY Model - 50 GW_DELAY, GWQMN 1250 Model - GW_REVAP 0.2 Model - REVAPMN 0.01 Model - ponds & wetlands Model - Tile drainage Model - CN2 adjustments Statistical criteria Nash-Sutcliffe Index Correlation coefficient Calibrated period:

20 5 4,5 4 3,5 3 2,5 2 1,5 1 0,5 0 Daily runoff Kielstau Nash-Sutcliffe Index: 0,71 Correlation: 0,82 MAE: 0,18 RSME: 0,36 r2: 0,66 measured modelled Jan. 91 Jul. 91 Jan. 92 Jul. 92 Jan. 93 Jul. 93 Jan. 94 Jul. 94 Jan. 95 Jul. 95 Jan. 96 Jul. 96 Jan. 97 Jul. 97 Jan. 98 Jul. 98 Jan. 99 Jul. 99 (Tavares 2006) 20 Jul. 90 Jan. 90 discharge [m³/s]

21 Nitrate loads per day simulated and measured /1/2005 5/1/2005 6/1/2005 7/1/2005 8/1/2005 9/1/ /1/ /1/ /1/2005 1/1/2006 2/1/2006 3/1/2006 4/1/2006 5/1/2006 6/1/2006 7/1/2006 8/1/2006 9/1/ /1/2006 Zeit Bieger, kg/day

22 Geese Farm, active from Oktober - December 22

23 Comparision of modelling performance in different landscapes 23

24 Model performance - hydrology ME, r Krofdorfer Forst Dietzhölze Dill Aar1 Low mountain Aar2 mountain range Haiger Weiherbach Treene Stör Lowlands Kielstau 24 ME r

25 future perspectives 25

26 Modelling the ecological potential of aquatic habitats Watershed Hydrology and erosion Discharge dynamics, sediment load In-stream Hydraulics Flow velocity, water depth, sediment transport Ecological functions for each parameter and each species River Morphology Substrate, plants, V depth Ecological potential Kiesel (in prep.), phd thesis Jens Kiesel,

27 SWAT model for XiangXi river in simulation discharge Xingshan discharge [m3/s] Köplin,, Cai Qinghua, Jiang Tong

28 Thank you to my team Lake water quality (Anne Grudzinski) runoff & Water quality (Filipa Tavares, u.a.) Drainage (Jona Golon) Vielen Dank Water quality transects (Katrin Bieger) Treene-Model (Thorsten Dey) Kielstau-Models (Filipa Tavares, Yong Zhang, Katrin Bieger, u.a.) für Ihre Aufmerksamkeit! Event based nutrient entry (Katrin Bieger) Stör model (Nadine Dobslaff) Habitat model (Jens Kiesel) Interaction Groundwater- Surface water (Pina Springer) 28

29 Department Hydrology & Water Resources Management, Ecology Centre, Kiel University 29