Modeling hydrological discharge from land to sea in the Arctic drainage basin

Size: px

Start display at page:

Download "Modeling hydrological discharge from land to sea in the Arctic drainage basin"

Maurice Harris
5 years ago
Views:

1 David Gustafsson, Kristina Isberg Modeling hydrological discharge from land to sea in the Arctic drainage basin Assoc. Prof., Dr. Berit Arheimer Head of Hydrological Research Swedish Meteorological and Hydrological Institute (SMHI)

International Association of Hydrological Sciences (IAHS) Predictions in Ungauged Basins (PUB) 2003-2012 Theme 1: Catchment

Approaches to Data-Collection Theme 5: New Hydrological Theory Theme 6: New Approaches to Modelling Theme 7: International Working

2 International Association of Hydrological Sciences (IAHS) Predictions in Ungauged Basins (PUB) Theme 1: Catchment Classification Theme 2: Conceptualisation of Process Heterogeneity Theme 3: Uncertainty Analyses and Model Diagnostics Theme 4: New Approaches to Data-Collection Theme 5: New Hydrological Theory Theme 6: New Approaches to Modelling Theme 7: International Working Groups Theme 8: Integration and Demonstration Projects CALL FOR PAPERS IAHS 90th anniversary - PUB Symposium Delft, October

3 Hydrological monitoring network not enough for the WDF Information requested in sites Methods for PUB had to be applied

4 HYdrological Predictions for the Environment (HYPE) model Lindström et al., 2010, Hydrology Research :

5 S-HYPE overall model performance different versions

6 HYPE applications * *First hindcast delivered for oceanographic model !

7 Hindcast ( ) Forecast (10 days?) Climate projections ( ) UNDERSTANDING of the system and it s CHANGE

8 WHY Arctic? ~11% of world s river-runoff flows to the Arctic ocean (Gleick, 2000) >50% of freshwater to the Arctic Ocean is river runoff (Barry and Serreze, 2000) 30% is Ungauged This freshwater governs: Sea ice formation and thus amount of insolation Deepwater formation and thus global ocean circulation Near-surface stratification and thus biological production Increasing trend in runoff

9 Previous efforts WCRP GEWEX: MAGS, GAME-Siberia, (BALTEX) Land-surface parameterisation schemes (PILPS) WCRP ACSYS (90 s): Based on GEWEX + PILPS Multimodel pan-arctic hydrology (20 s): CHASM, CLM, ECMWFC, NOAH, VIC More???

10 Pan-Arctic hydrological model Total Area: 23 x 10 6 km 2 Number of subbasins: Discharge to sea: 3300 outlets Average area of subbasins: 756 km 2 Number of individ. lakes: 1800 Note: Greenland still not included

11 Forcing data

12 Köppen Geiger Climate Classification Snow, Humid, Cold summer Polar tundra Semiarid spots! Snow, Humid, Warm summer

13 Permafrost frozen ground Continuous permafrost is common in Arctic-HYPE domain Ref:NSIDC National Snow and Ice Data Centre

Available global databases in use for the set-up Routing - Subbasins - Geodata

gov/) LandUse: Global Land Cover 2000 (http://bioval.jrc.ec.europa.

at) Lakes: GLWD, Global Lakes and Wetlands database (http://gcmd.nasa.

uni-frankfurt.de) Observations Discharge observations: r-arcticnet (http://www.

ca) USGS (http://water.usgs.gov/nwis) Snow water equivalent: GlobSnow (www.globsnow.

$precipitation, short wave radiation, snow fraction): WFDEI$

14 Available global databases in use for the set-up Routing - Subbasins - Geodata Topography (routing/delineation): Hydro1K ( LandUse: Global Land Cover 2000 ( Soil: Harmonized World Soil Database ( Lakes: GLWD, Global Lakes and Wetlands database ( Irrigated area: GMIA ( Cropdata: MIRCA2000 ( Observations Discharge observations: r-arcticnet ( GRDC ( HYDAT ( USGS ( Snow water equivalent: GlobSnow ( Evaporation: Fluxnet ( ECMWFC ERA-products corrected with CRU och GPCC Forcing data (Temperature, precipitation, short wave radiation, snow fraction): WFDEI (Watch-Forcing-Data-Era-Interim), WATCH forcing data 20 th century,

Hydro1K: routing/delineation GLWD: larger lakes are inserted as

15 Delineation of subbasins and routing data tailoring WHIST: The World Hydrological Input data Set-up Tool Hydro1K GLWD Gauging stations Hydro1K: routing/delineation GLWD: larger lakes are inserted as individual subbasins Gauging stations: the published catchment area are used for validation

16 1349 Gauging stations: used for set-up, calibration and validation Mostly daily time-series Mostly monthly time-series Daily time series has been valuable during the set up and calibrations but the model is evaluated for monthly discharge data

17 The availability of observed discharge reaches a maximum around 1980, but then there is an abrupt decrease.

18 Adjustment and check of gauging stations for validation of routing and delineation Ref. Hydro1K

19 Check of published catchment area vs modelled Ob River *River Ob has inland sinks and the effective drainage area is not always the same as the actual overall area. Ob* Ob*

20 Mean elevation of elevation (Tailored for subbasins) Verkhoyansk range Rocky mountain Central Siberian plateau Altai mountains West Siberian plain Ural mountains Canadian shield Queen Elizabeths Islands and standard deviation of elevation has been used for corrections Ref. Hydro1K

21 LandUse (from GLC2000, tailored for subbasins) Forest Bare Open land with vegetation Crops Nelson Ob

22 LandUse (from GLC2000 tailored for subbasins) Lakes Glaciers Great Bear Great Slave Athabasca Winnipeg Baikal Wetland flooded Wetland others Vasuyugan bog

23 Soil types (from HWSD, reclassified and tailored for subbasins) Medium Coarse Shallow/Rock Organic

FluxNet evaporation Qualitative evaluation using

24 WATCH Forcing data ( GPCC and CRU corrected ERA-interim and ERA-40 In HYPE model: elevation and regional corrections based on calibration with discharge, GlobSnow SWE and FluxNet evaporation Qualitative evaluation using independent climatology, ie. from Environment Canada, Unesco Atlas of the World Balance.

25 Arctic HYPE model domain - Temperature Era-Interim WFDEI Difference (i.e. CRU correction)

26 Lat ( N) Lat ( N) Lat ( N) and precipitation Prec(mm), EI Annual Precipitation Era-Interim Prec(mm), WFDEI WFDEI Rel.Diff(%) (WFDEI-EI)/EI Lon ( E) Difference (i.e. GPCC correction)

27 Research in Progress: Use of ESA GlobSnow Satellite SWE product -> Adaption of snow melt model for high latitudes Necessary to include solar radiation term in snow melt function Pure temperature index melts too late, too quickly, or not at all [under development] Assimilation of ESA GlobSnow ( SWE data for dynamic correction of precipitation forcing data: Daily SWE data Updating of off-line SWE model using Ensemble Kalman Filter Dynamic monthly precipitation (and temperature) correction factors

28 Research in Progress: Some tests for Artic drainage area in North America Obs. SWE Model. SWE Uppdated SWE Correction SWE Correction Prec. Correction Temp

Snow Water Equivalent (mm) Discharge (m3/s) Arctic-HYPE Research in Progress: Use of GlobSnow SWE data - Calibration Too early spring melt peak when calibrated vs GlobSnow & Discharge: 900 800 700

29 Snow Water Equivalent (mm) Discharge (m3/s) Arctic-HYPE Research in Progress: Use of GlobSnow SWE data - Calibration Too early spring melt peak when calibrated vs GlobSnow & Discharge: SWE+Q calib (KGE 0.59, NSE 0.49, RE 26%) (swrad+temp) SWE+Q calib (KGE 0.47, NSE 0.26, RE 24%) (swrad+temp) Q calib only (KGE 0.86, NSE 0.75, RE 7%) Q-obs GlobSnow SWE Confirmed by GlobSnow comparison with Canadian In-Situ data: From GlobSnow Newsletter no 6., 2010 Source: Solution: Optimize versus discharge, conditional that SWE is acceptable

30 Model performance (volume error) WATCH Forcing Data (ERA 40 corrected with CRU+GPCC )

31 Model performance (volume error) WATCH Forcing Data (ERA 40 corrected with CRU+GPCC )

32 Model performance (NSE, monthly average) NSE = tradeoff between variance, correlation och bias WATCH Forcing Data (ERA 40 corrected with CRU+GPCC )

33 Model performance (NSE, monthly average) NSE = tradeoff between variance, correlation och bias WATCH Forcing Data (ERA 40 corrected with CRU+GPCC )

34 River Discharge mean annual

35 m3/s m3/s m3/s m3/s Arctic-HYPE 2 x 104 Sim Yukon 1.5 Obs Sim Obs Sim Obs J F M A M J J A S O N D 2.5 x 104 Mackenzie 2 8 x 104 Lena J F M A M J J A S O N D 0 J F M A M J J A S O N D Month 10 x 104 Yenisei J F M A M J J A S O N D Month (still) Too early spring flood peak at river mouths in the model, but (partly) Similar trends in seasonal pattern : Yukon: increasing autumn flow (then going back), earlier spring flood Mackenzie: decreasing flow (then back to normal), model decrease all years Lena: model flow increase 95-09, but data ends 1994 Yenisei: decrease in summer flow, earlier spring flood

36 Discharge trends (based on model results ) % of mean flow

37 Discussion Need for hydrological models in coupled atmosphere and ocean climate models? Use hydrological models to integrate discharge data information in analysis of climate models/data? Use satellite snow data to assess hydrological model and re-analysis data in ungauged basins However: important to recognize satellite data uncertainties! Need for further model development/assessment for present climate and for future climate scenarios: Snow melt and evaporation processes too strong dependence on air temperature in present model Lake and wetland dynamics Melting permafrost impact on soil water storage capacity, flow paths and hydrological respons Need for river discharge observations to monitor hydrological changes in Arctic!

38 Arctic challenges Inland sinks Greenland still no routing Many lakes in some areas Winter evaporation Glaciers Palsa bogs Ice plugs Meandring and human activity Permafrost landscape

39 Thank you for your attention!

Hydrological modelling of the Lena River using SWIM

Hydrological modelling of the Lena River using SWIM Michel Wortmann 1 1 Potsdam Institute for Climate Impact Research (PIK), Germany July 8, 214 Contents 1 The Lena catchment and data used 1 1.1 Discharge