Impacts of climate change on flooding in the river Meuse

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Impacts of climate change on flooding in the river Meuse Martijn Booij University of Twente,, The Netherlands m.j.booij booij@utwente.nlnl 2003

in the Meuse basin Model appropriateness Appropriate model components ling model River basin models Results river basin models

in the Meuse basin (1) Rainfall (extreme values) Temperature Evapotranspiration

in the Meuse basin (2) 58 56 54 52 50 48 a) NCEP-NCAR NASA-GEOS1 CGCM1 HadCM3 CSIRO9 Stations 46 44 42 40-4 -2 0 2 4 6 8 10 12 14

in the Meuse basin (3) 52 51 50 HadRM2 HIRHAM4 Stations b) 49 48 47 3 4 5 6 7 8

in the Meuse basin (4) RV(20) (mm/day) 120 100 80 60 40 Model scale Appropriate scale = 20 km 20 0 NASA-GEOS1 NCEP-NCAR CGCM1 HadCM3 CSIRO9 HadRM2 HIRHAM4 1X 2X 1X 2X 1X 2X 1X 2X 1X 2X 1X 2X 1X 2X 1X 2X

in the Meuse basin (5) Temperature (degr. C.) 25 20 15 10 5 Observed HadCM3 1XCO2 HadCM3 2XCO2 2XCO2-1XCO2 0 0 50 100 150 200 250 300 350 Day number

Model appropriateness (1) Simple models and complex models appropriate model dependent on research objectives, research area etc. data and computational costs vs. required accuracy balance of uncertainties key processes and variables appropriate temporal scales appropriate spatial scales appropriate formulations

Model appropriateness (2) Appropriate model developed is a river basin model to assess impact of climate change on river flooding Research area is Meuse basin upstream of Borgharen in Belgium and France Borgharen

Appropriate model components (1) Key variables extreme precipitation (annual maximum) temperature elevation soil type land use type Appropriate temporal scale: 1 day Appropriate spatial scales: based on loss of variability (less extreme behaviour) with larger model scales

Appropriate model components (2) RVA/RVp 1 0.9 0.8 0.7 0.6 0.5 0.4 0.3 0.2 0.1 0 0.001 0.01 0.1 1 10 L/ λ For other statistics such as variance, similar relationships dependent on correlation structure/ length λ and scale L

Appropriate model components (3) appropriate: 10 % error in estimating statistic: daily average temperature (stations): ~1000 km >> extent of river basin area annual maximum daily precipitation (stations): ~20 km (this means for the Meuse basin upstream of Borgharen > 50 precipitation stations or model cells) elevation: ~0.11 km soil type: ~3.3 km land use type: ~5.3 km integrated appropriate model scale (based on relative importance of separate scales for peak discharge) : ~ 10 km (150-200 sub-basins upstream of Borgharen) Appropriate formulations: dependent on scale (+ model used)

Rainfal modelling (1) Requirements: Climate variables at appropriate scales Precipitation (L = 20 km) for changed climate no GCM or RCM model data available at this scale statistical downscaling random cascade model Temperature (L >> extent of river basin area) GCM and RCM data can directly be used Time series of sufficient length (30 years) Multiple stochastic simulations (ensembles)

Rainfal modelling (2) Random Cascade rainfall model (e.g. Jothityangkoon et al., 2000) Temporal rainfall model for occurrence and amount Spatial rainfall model based on discrete random cascade with use of cascade generators

Rainfal modelling (3) Model grid (76 cells)

Rainfal modelling (4) Precipitation Temperature Calibration Stations (39) Stations (12) 1970-1984 1970-1984 Validation Current climate Changed climate Stations 1985-1996 Random C. (76) 30 years Random C. 30 years Stations 1985-1996 Stations 1967-1996 Stations+change 1967-1996 Potential ET Stations (8) 1970-1984 Stations 1985-1996 Stations 1967-1996 Stations+change 1967-1996

(1) current 10 years Observed ( 20 km) Precipitation (mm/day) 60 50 40 30 20 10 0 1991 1992 1993 1994 1995 1996 1997 1998 1999 Modelled (20 km) Precipitation (mm/day) 60.0 50.0 40.0 30.0 20.0 10.0 0.0 1991 1992 1993 1994 1995 1996 1997 1998 1999

(2) modelled 100-year extreme rain Current Changed 20 km scale 20 km scale

(3) modelled extreme values Annual maximum precipitation (mm/day 120 100 80 60 40 20 0 Return period (years) 1 2 5 10 20 50 Modelled current climate (min and max) Modelled changed climate (min and max) -2-1 0 1 2 3 4 5 100 Reduced Gumbel variate

(4) summary Appropriate scale statistics (20 km) Average (mm/day) 2.6 Standard deviation Wet day frequency (mm/day) 5.0 (-) Current climate Observed Modelled GCMs/ RCMs 0.63 2.7-2.9 5.1-5.3 0.45-0.46 Changed climate 2.9 5.9 0.49 Modelled 2.7-3.1 5.7-6.1 0.38-0.40 Spatial correlation length Temporal corr. cf. (lag-1) Return value (20-year) (km) (-) (mm/day) 324 0.26 57.5 332-349 0.23-0.25 57.3-63.2 389 0.23 68.8 382-404 0.24-0.26 67.8-77.6 Return value (100-year) (mm/day) 72.1 70.6-78.7 84.8 83.1-98.4 Five-day 100-year RV (mm/day) 130 122-134 142 138-157 Ten-day 100-year RV (mm/day) 174 165-173 190 182-206

River basin models (1) River basin model developed within existing flexible modelling framework HBV (SMHI, Sweden) Impact assessment with appropriate model and two additional models: 1 sub-basin (HBV-1) 15 sub-basins (HBV-15) 118 sub-basins (HBV-118) ~145 km ~37 km ~13 km

River basin models (2) HBV model: components Precipitation (rain + snow) Soil moisture Quick runoff Base flow Transformation of runoff River routing Calibration: Discharge data Relations HBV parameters and physical characteristics (e.g. infiltration capacity and soil type)

River basin models (3) HBV-1 HBV-15 HBV-118

Results river basin (1) calibration a) Discharge (m 3 /s) 3000 2500 Observed HBV-1 2000 1500 1000 500 0 Jan Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec b) Discharge (m 3 /s) 3000 Observed 2500 HBV-15 2000 1500 1000 daily discharge at Borgharen 500 0 Jan Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec c) Discharge (m 3 /s) 3000 Observed 2500 HBV-118 2000 1500 1000 500 0 Jan Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

Results river basin (2) calibration Discharge (m 3 /s) 3000 2500 2000 1500 1000 Return period (years) 1 2 5 10 20 50 Observed HBV-1 HBV-15 HBV-118 500 0-2 -1 0 1 2 3 4 Reduced Gumbel variate

Results river basin (3) validation a) Discharge (m 3 /s) 3500 3000 2500 2000 1500 1000 500 Observed HBV-15 0 Dec Dec Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Jan Feb Mar b) Discharge (m 3 /s) 3500 3000 2500 2000 1500 1000 500 Observed HBV-118 0 Dec Dec Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Jan Feb Mar

Results river basin (4) current climate Annual maximum discharge (m 3 /s) 3500 3000 2500 2000 1500 1000 500 1 2 5 10 20 50 Observed HBV-1 (min and max) HBV-15 (min and max) HBV-118 Return period (years) 100 0-2 -1 0 1 2 3 4 5 Reduced Gumbel variate

Results river basin (5) current + changed climate Discharge return values (m 3 /s) 4000 3500 3000 2500 2000 1500 1000 500 HBV-1 current climate HBV-15 current climate HBV-118 current climate HBV-1 changed climate HBV-15 changed climate HBV-118 changed climate 0 RV20 RV100

Results river basin (6) uncertainty Annual maximum discharge (m 3 /s) 4500 4000 3500 3000 2500 2000 1500 1000 500 1 2 5 10 20 50 HBV-15 individual climate models HBV-15 average climate models Return period (years) 100 0-2 -1 0 1 2 3 4 5 Reduced Gumbel variate

(1) Appropriate spatial scale for daily precipitation is about 20 km Other appropriate scales vary between 100 m 1000 km Appropriate model scale is about 10 km; 150-200 sub-basins for the Meuse basin (daily time scale) Usefulness of model appropriateness procedure ability to assess appropriate scales before model construction and integrate them into a model scale provision of a framework for decisions about reduction or expansion of data networks and needs

(2) simulates a realistic climate; all relevant observed statistics are correctly reproduced, except the wet day frequency Most important effects of climate change on precipitation are increases in variability (14 %), extreme values (18 %) and spatial correlation (13 %) is able to reproduce these changes at 20 km scale Average and extreme Meuse discharge behaviour well reproduced by three hydrological models Models results become somewhat better with increasing model complexity, differences between HBV-15 and HBV-118 small (additional discharge data may improve HBV-118)

(3) Extreme discharge is underestimated when using synthetic rainfall due to point character observed rainfall Small decrease of average discharge (~5 %) and increase in extreme discharge and variability (5-10 %) with climate change Main uncertainties are related to precipitation and extrapolation, model structure and parameter uncertainties are less important Trade-off between spatial and temporal accuracy Uncertainty in river flooding with climate change larger than change, however climate changes are systematic changes rather than random ones