Climate change impacts on the Mekong River
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1 UCL DEPARTMENT OF GEOGRAPHY Climate change impacts on the Mekong River Daniel Kingston, Richard Taylor, Julian Thompson, Martin Todd Department of Geography, University College London Geoff Kite Hydro-Logic Solutions
2 The Mekong basin 795, km 2 42km long From Tibetan plateau (>5m) to Vietnam and South China Sea China, Burma, Thailand, Laos, Cambodia & Vietnam ~ 5 million people Socio-economic importance: Fish: 7, tons, 3 species p.a. (1992) Fish are 5-8% total protein intake Agriculture Hydropower
3 Climatology Mid-May to early October: southwesterly circulation, rainy. 9% annual precip between May-Oct October-March: northeasterly circulation, dry Snow storage and release in Tibet vs monsoon rains in lower basin Mean annual rainfall ranges from 1mm in northeast Thailand to >32mm in mountainous regions of Laos. Mean annual precip (mm) (IWMI Atlas)
4 Hydrology Mean total annual discharge = 475bn m 3 6 th largest in world Mekong at Chiang Saen Mekong at Mukdahan Streamflow, m3/s Mekong Basin Streamflow Chi at Yasothon Month Mekong at Pakse, Mekong at Chiang Sen, Mekong at Mukdahan, Chi at Yasothon, Mun at Ubon Rachathani, Mun at Ubon Mekong at Pakxe
5 Hydrological model SLURP (Semi-distributed Land-Use Runoff Process) model (Kite, 1995) Semi-distributed, physically based Previously applied to the Mekong Kite, G. (21) Journal of Hydrology, 253 pp1-13. Model period Percolation Transpiration Irrigation Interception Sublimation Withdrawals Precipitation Snowmelt Infiltration Groundwaterflow Evapotranspiration Canopy Storage Snow Storage Runoff Fast Storage Interflow Slow Storage
6 Initial model set-up 13 sub-basins derived from DEM USGS GTOPO-3 Sub-basins further divided, based on land-use (9 categories) USGS data FAO world soil map
7 Re-calibration of SLURP for QUEST-GSI Change from sparse network of daily station climate data to.5 degree gridded monthly data set Change of calibration period from to QUEST period With used for model validation Namngum Chi Lancang Namou Mekong1 Modelled to Pakxe only 57,km3, ~7% of basin Mun Chi-mun Mekong2
8 Re-calibration (2) Substitution of CRU TS 3 precipitation data with University of Delaware data set Change of PET algorithm From Penman-Monteith to Linacre method Data reliability issues mean daily discharge (m -3 s -1 ) obs obs-15% obs+15% model Manual parameter adjustment Final calibration Nash-Sutcliffe =.94 Spearman coefficient = validation Consistent with calibration period mean daily discharge (m -3 s -1 ) % exceedence obs model
9 Scenarios 1-6 C prescribed warming on HadCM3 2 C prescribed warming on all 7 GCMs (HadCM3, HadGEM1, CCCMA, CSIRO, IPSL, MPI, NCAR) All 4 SRES scenarios on HadCM3 (24-69) A1b, A2, B1, B2 SRES A1b on all 7 GCMs (24-69)
10 Prescribed warming on HadCM3 Near-linear trend in annual runoff with increased mean global temperature Decreased peak season runoff Increased early season runoff anomaly (%) 5-5 Annual runoff anomaly from 1deg 2deg 3deg 4deg 5deg 6deg mean daily discharge (cumecs) deg 2deg 3deg 4deg 5deg 6deg
11 Prescribed warming on HadCM3: temperature vs precipitation Temperature climate change signal Temperature: decreasing peak season flow Precipitation: increasing flow from May-December mean daily discharge (m - 3 s -1 ) deg 2deg 3deg 4deg 5deg 6deg Precipitation climate change signal mean daily discharge (m - 3 s -1 ) deg 2deg 3deg 4deg 5deg 6deg
12 2deg prescribed warming on all GCMs Annual runoff anomaly from No consistent signal 1 Either on an annual or seasonal basis anomaly (%) 5-5 hadcm3 cccma csiro ipsl mpi ncar hadgem No outlier GCM mean daily discharge (m -3 s -1 ) hadcm3 cccma csiro ipsl mpi ncar hadgem1
13 2 degree prescribed warming: temperature vs precipitation Temperature climate change signal Temperature climate change signal very similar between GCMs Little consistency in precipitation climate change signal between GCMs mean daily discharge (m-3s-1) Precipitation climate change signal hadcm3 cccma csiro ipsl mpi ncar hadgem mean daily discharge (m-3s-1) hadcm3 cccma csiro ipsl mpi ncar hadgem
14 SRES scenarios on HadCM3 (24-69) Little difference between A1b, A2, B1 and B2 All show very small (<1%) changes in mean annual runoff Decreased peak season flow; slight increase in early season flow mean daily discharge (m -3 s -1 ) anomaly (%) Annual runoff anomaly from a1b a2 b1 b2 a1b a2 b1 b2
15 SRES A1b on all 7 GCMs (24-69) Follows pattern at 2 C prescribed warming: No consistent signal Either on an annual or seasonal basis No outlier GCM mean daily discharge (m -3 s -1 ) % anomaly annual runoff anomaly from hadcm3 cccma csiro ipsl mpi ncar hadgem hadcm3 cccma csiro ipsl mpi ncar hadgem
16 Summary: Uncertainty envelopes 1-6 C prescribed warming on HadCM3 2 C prescribed warming across all 7 GCMs mean daily discharge (m -3 s -1 ) mean daily discharge (m -3 s -1 ) HadCM3 SRES scenarios (24-269) SRES A1b across all 7 GCMs (24-69) mean daily discharge (m -3 s -1 ) mean daily discharge (m -3 s -1 ) Solid line=; dotted lines indicate upper and lower bounds of climate change signal
17 Summary GCM uncertainty > climate sensitivity and emissions uncertainty Common themes Emissions uncertainty relatively small for Uncertainty from GCMs primarily from precipitation, not temperature Little change in low flow season
18 Further work SRES A1b (24-269) GLOBAL MODEL Model uncertainty Parameterisation Model structure (comparison with global model) runoff (mm) J F M A M J J A S O N D cccma ipsl mpi ncar hadcm3 Land use change CATCHMENT MODEL Abstractions? runoff (mm) cccma ipsl mpi ncar hadcm3 J F M A M J J A S O N D
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