Evaluation of the Surface Water Balance of Southeast Asia from a Land Surface Model and
ERA40 Reanalysis
Mergia Y. Sonessa1, Jeffrey E. Richey2 and Dennis P. Lettenmaier1
1Department
of Civil and Environmental Engineering, Box 352700, University of Washington, Seattle, WA 98195
2School of Oceanography Campus Box 355351, University of Washington, Seattle, WA 98195 - 7940
Steve Burges retirement symposium, March 24 - 26, 2010
ABSTRACT
Understanding the water and energy balances of a region (which are linked through
evapotranspiration, a common term) is a key first step toward understanding regional
hydroclimatic sensitivities to long-term climate change. The Southeast Asia region is one of the
most populous on the globe, and therefore key practical issues, such as the region’s food and fiber
production capabilities, are intricately linked to possible changes in its hydroclimatic regime.
Furthermore, the region contributes much higher particulate organic carbon (POC) fluxes to the
sea on a per unit area basis than most of the global land area. We compare two approaches to
estimating the surface energy and moisture flux terms under recent historical conditions for a
region consisting of seven major southeast Asia river basins plus the Kingdom of Bhutan. The first
approach is application of the Variable Infiltration Capacity (VIC) land surface hydrology model
forced by gridded precipitation and temperature, and other gridded radiant fluxes and
meteorological variables. The second is analysis of the ERA-40 reanalysis, which result from
application of a frozen version of the European Centre for Medium Range Weather Forecasting
(ECMWF) weather forecast model with data assimilation as used in operational weather
forecasting. Both approaches produce gridded (at one-half degree spatial resolution in the case of
VIC, and about one degree spatial resolution for ERA-40) surface moisture and energy fluxes. In
the case of VIC, both water and energy budgets close by construct, where ERA-40 budgets must
include a non-closure (so-called analysis increment) term to account for the effects of data
assimilation. We compare the model-simulated moisture and energy flux terms with independent
observations from in situ sources (in the case of streamflow and precipitation) and satellite
(downward solar and longwave radiation, and total water storage change). Observed streamflow
from different gauging stations will be used to evaluate the modeled water balance. Computations
are also made of estimates from both approaches of moisture recycled within SEA, and its seasonal
variations.
Streamflow Simulations – VIC – Seasonal flow and Monthly Timeseries
Mekong at Chiang Sean
Mekong at Chiang Sean
R2 = 0.91
NS = 0.80
Mekong at Mukdahan
Mekong at Mukdahan
R 2 = 0.93
NS = 0.83
M = 1687.5 mm
SD = 776.5 mm
M = 847.6 mm
SD = 298.8 mm
Mekong at Luang Prabang
Mekong at Luang Prabang
Mekong at Nong Khai
= 0.94
NS = 0.85
M = 853.3mm
SD = 511.5 mm
M = 317.1 mm
SD = 272.3 mm
R2 = 0.92
NS = 0.83
R2
M = 946 mm
SD = 232.9 mm
Mekong at Nong Khai
VIC and ERA40
Mekong at Pakse
Mekong at Pakse
Irrawaddy Sagaing
Irrawaddy at Sagaing
R2 = 0.92
NS = 0.81
R2 = 0.96
NS = 0.92
•ERA ET varies less than that of VIC ET, which ranges from 0 – 2900 mm per annum. VIC ET is
highest in the Sittang basin while ERA40 ET is highest in the southern part of the Mekong
basin.
•ERA40 RF ranges from 2 – 2200 mm annually and VIC RF ranges from 2 to 2800 mm.
3
Basins included
Mekong
Model Forcings and Parameters
Forcing
• Min/max Temperature (T) data obtained from
Climate Research Unit (CRU)
Salween
• Monthly precipitation (P)statistics was obtained
from the University of Delaware (UDel)
Red River
Song Ma
• Missing data for observed data (CRU and UDel)
was filled using quantile mapping with
NCEP/NCAR data.
6
Future Work
 Computing Moisture recycling
Runoff Ratio
VIC simulated the streamflow reasonably well with high correlation coefficients
and Nash-Sutcliffe efficiencies especially for the Mekong basin for which a number
of gauging stations with observed flow records are available.
The P and RF by ERA40 and VIC show similar seasonal patterns. ERA40 RF is
Energy Balance terms ( downward solar generally higher than VIC RF while P from both are quite comparable.
radiation and long-wave
radiation)
 All water balance terms , VIC RF, ET and P show high variability across the
Total water storage change
basins than ERA RF, ET and P, respectively.
Although streamflow observations are yet to be obtained for complete assessment
PPTN, mm/month
RF, mm/month
RF, mm/month
RF, mm/month
ET, mm/month
ET, mm/month
ET, mm/month
PPTN, mm/month
Songma - PPTN
Songma - RF
Sittang - RF
Sittang - ET
Salween- ET
Red River- ET
Key
M = Mean
SD = Standard Deviation
PPTN = Precipitation
RF = Runoff
ET = Evapotranspiration
NS = Nash-Sutcliff Efficiency
Songma - ET
All the basins have a clearly defined P cycle that peaks during the months of June to September except for
Chao-phraya and Songma which have two peaks in May and September. For these two basins and Salween
the VIC P is always lower than ERA40 P; while for the remaining basins they match each other quite well.
Both ERA40 and VIC P show similar patterns.
RF shows similar pattern as P. There is a big discrepancy between ERA40 RF and VIC RF. Especially
between months of May and November , ERA40 RF is much higher than VIC RF for all basins.
ERA40 ET varies very small throughout the year while VIC ET has the same pattern as VIC P having peaks
during the months of June to September.
of the entire basin, from the results of the three basins, Mekong, Irrawaddy and
Land Surface Parameters
• Soil data prepared using FAO Soil Program.
Soil depth was initially approximated and
corrected using iterative calibration of
streamflow by the UA-SCEM method
Sittang
Salween- RF
CONCLUDING REMARKS
Mekong - ET
Sittang - PPTN
Salween- PPTN
PPTN, mm/month
•For the other two basins, Sittang and Irrawaddy, for which observed stream flow
is obtained (though for only ten years, 1978-1988), the simulations were not as
good as for the Mekong basin. Investigation as to the reasons is ongoing. For the
Irrawaddy basin, while the low flows are simulated well, the VIC simulated flows
during peak flow months July – September are substantially higher than the
observed flow. In the case of Sittang basin, the timing of the peak flows is
shifted forward by about a month.
RF, mm/month
•The ERA40 data cover 45 years from September 1957 to August 2002
of which 32 years (1970 – 2001) of precipitation, evapotranspiration
and runoff were used.
Irrawaddy- ET
ET, mm/month
•The relatively high values of Nash-Sutcliffe Efficiency (NS), which describes the
prediction skill of the modeled flows as compared to observations, are also
indicative of a good simulation
PPTN, mm/month
R2 = 0.75
NS = 0.55
ET, mm/month
Chao-Phraya - ET
Red River- RF
Mekong - RF
RF, mm/month
Sittang at Toungoo
Irrawaddy- RF
ET, mm/month
Sittang at Toungoo
RF, mm/month
•ERA40 - Reanalysis (Uppala et al. 2005) was used for comaprison
with VIC simulation. The ERA40 data are available at 1.125 degree
spatial resolution and were interpolated to the ¼ degree grid using an
inverse distance interpolation.
•Streamlows simulated by VIC for the different basins are well correlated with
their corresponding observed flow especially in the Mekong Basin, although
some seasonal biases are apparent
RF, mm/month
Chao-Phraya - RF
Red River- PPTN
Mekong - PPTN
PPTN, mm/month
Irrawaddy- PPTN
PPTN, mm/month
PPTN, mm/month
Chao-Phraya - PPTN
• Soil and vegetation
parameters
• Three soil layers
Irrawaddy
M = 1944.3mm
SD = 654.9 mm
•The annual mean P, ET and RF over the seven basins are shown above. The P range is higher
for the VIC simulation (380– 4400 mm) than for ERA-40 which ranges from 560 – 3400 mm per
annum. However, both of them show similar patterns in P distribution over the region with
highest P for Irrawaddy and lowest P in the north of Salween and Mekong basins. Overall,
the VIC P field shows more variability over the area than the ERA40 P.
• Large scale hydrologic model
(Liang et al. 1994 ) that solves: the
full water and energy balances
• Run at 1/4 degree spatial
resolution for this study
• Uses as an input:
• Climatic forcing (P, T, wind
speed), downward solar and
longwave radiation, humidity
2
Precipitation (P) – ET – Runoff (RF)
5
ET, mm/month
1
4
Sittang, VIC simulation capability for the region can be considered very promising.
References
Liang, X., D. P. Lettenmaier, E. F. Wood, and S. J. Burges, A Simple hydrologically Based Model of Land Surface Water and Energy Fluxes for
GSMs, J. Geophys. Res., 99(D7), 14,415-14,428, 1994
Uppala, S. M., and Coauthors, 2005. The ERA-40 Re-analysis. Quart. J. Royal Meteor. Soc., 131, 2961-3012, doi:10.1256/qj.04.176.
Chao Phraya
• Veg data prepared from MODIS 2000.
.