long term simulations of global lakes using the variable infiltration capacity model huilin gao 1,...
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Long term simulations of global lakes using the Variable Infiltration Capacity modelHuilin Gao1, Theodore Bohn1, Michelle Vliet2, Elizabeth Clark1, and Dennis P. Lettenmaier1
1Department of Civil and Environmental Engineering, Box 352700, University of Washington, Seattle, WA 981952 Department of Earth System Science and Climate Change, Wageningen University and Research Centre, P.O. Box 47, 6700 AA Wageningen, The Netherlands
1 Objective
VIC dynamic lake/wetland module2
3 Case study of Lake Chad, Africa
This project is supported by NASA Grant NNX08AN40A – “Developing Consistent Earth System Data Records for the Global Terrestrial Water Cycle”
7 References
5 Summary and future work
4 Towards global lake simulations
Although lakes and reservoirs play a major role in the hydrology of the land
surface over substantial areas of the globe, coherent information about their
dynamics is largely lacking. The quality and completeness of information from
in situ sources varies tremendously for different countries and regions.
Recently, satellite data have provided some information about variations in
lake surface elevation (from satellite altimeters) and surface extent (from
visible and other sensors) for the largest lakes. Land surface models offer an
alternative means of gaining insights into lake dynamics. Here we use a recent
version of the Variable Infiltration Capacity (VIC) model which includes a
lake/wetland module, to simulate the 57-year (1950-2006) variations of lake
level and surface area of Lake Chad, Africa. The objectives of this study are
two-fold:
1. To test the VIC lake/wetland module, which was originally intended for
application to smaller sized lakes in high latitudes regions, over a large lake in
the tropics;
2. To gain insights into issues associated with simulating lakes and wetlands
globally using the modified version of the VIC model and ancillary data sets.
Figure 2. Schematic for the wetland algorithm: a) when the lake is at its maximum extent the soil column is saturated, b) as the lake shrinks runoff from the land surface enters the lake and c) evaporation from the land surface depletes soil moisture, d) as the lake grows, water from the lake recharges the wetland soil moisture (Bowling and Lettenmaier, 2009).
VIC lake algorithm VIC wetland algorithm
Major module characteristics:
• Multi-layer energy balance lake model of Hostetler et al. 2000 as modified
by Bowling and Lettenmaier (2009)
• Dynamic lake area allows seasonal inundation of adjacent wetlands
• Currently not part of channel network
• Lake/wetland parameters:
Lake depth-area profile;
Wfrac (Width of lake outlet, as a fraction of the lake perimeter);
Rpercent (Fraction of grid cell runoff that enters lake)
Figure 1. Schematic of the VIC lake algorithm. I: Evaporation from the lake is calculated via energy balance, II. Runoff enters the lake from the land surface, III: Runoff out of the lake is calculated based on the new stage, and IV: The stage is re-calculated (Bowling and Lettenmaier, 2009).
Figure 3 Geographic situation of the Lake Chad basin (figure cited from Coz et al., 2009)
I. Study area: the vanishing Lake Chad
Komadugu
Logone-Chari
(m)
Figure 4 Lake bathymetry from DEM.
Located in Central Africa with an area of 2,500,000 km2, the Lake Chad basin is the largest
endoreic basin in the world. Lake Chad is shared by four countries: Chad, Niger, Nigeria and
Cameroon. The hydrologically active part of the basin is mainly drained by the Chari–Logone
river system, and to a lesser extent, by the Komadugu River.
In the 1960s Lake Chad had an area of more than 26,000 km², making it the fourth largest lake
in Africa. By 2000 its extent had fallen to less than 1,500 km² due to a combination of severe
droughts and increased irrigation water usage.
II. Data and approach
III. Results
Figure 6 Modeled lake level (south part) and its comparison with observations .
Figure 5 VIC simulated discharge to the north part (a), and south part (b) of the lake; lake depth-area profile based on bathymetry of the north part (c) and south part (d).
Figure 7 Modeled lake level (north part) .
Figure 8 Modeled lake surface area and the comparisons with satellite images in selected days.
According to the bathymetry, Lake Chad features a relatively deep northern half and a very shallow southern half, with most
of its inflows from the Logone-Chari river system into the southern part. Therefore, we use two separate grid cells to
represent the lake. The southern cell is modeled first, with its forcings modified by the inflows from the southern part of the
Chad basin. The runoff from this cell is then partitioned to the inflow for the northern part and to the irrigation water usagefor the basin. For both grid
cells, the depth-area
relationship is from
topography, and rpercent = 1.
For the north wfrac = 0; for
the south wfrac is calibrated.
Forcings are from Sheffield
et al. (2006).
Results from the modeled lake level for the southern part (Fig. 6)
suggest two things. First, the lake level and its variations were
significantly reduced during the droughts in the 1970’s and 1980’s.
Second, the modeled results are
fairly consistent with
observations from satellite
altimetry. The lake level for the
northern part of the lake
indicates a disappearance in the
1970’s, with a decrease in the
lake size of more than 80% from
the mid 60s to the mid 70s. The
modeled lake water coverage
maps (based on lake level and
bathymetry) demonstrate a good
coherency with the available
satellite imagery, except for a
low bias in the southern part in
the 1963 comparison.
Global Lakes and Wetlands Database
small lakes big lakes
Aggregate within grid cell
Grid cell simulation
parameterization
Big lakes downstream?
NO YES
Routing to outlet Simulate the first downstream big lake
Modified routing network
Routing to the first downstream big lake
Figure 9 Flowchart of the global lake simulation plan.
We are in the process of simulating lakes and wetlands globally
following the procedure outlined in the flowchart below. Large lakes
and small lakes are separated using the Global Lakes and Wetlands
Database (GLWD). Only the largest lakes are represented in the model’s
river routing network, and small lakes are considered in aggregate as an
effective land cover class within each grid cell. Similar to the approach
used for Lake Chad, the large lakes are simulated using a constructed
grid cell containing the whole lake (in most cases) with its forcings
modified by the routed inflows.
Birkett, C.M., 2000, Synergistic remote sensing of Lake Chad: Variability of basin inundation. Remote Sensing of Environment, 72, 218-236.Bowling and Lettenmaier, 2009: Modeling the effects of lakes and wetlands on the water balance of Arctic environments Journal of Hydrometeorology (accepted). Coe, M. T., and Foley, J. A., 2001, Human and natural impacts on the water resources of the Lake Chad basin. Journal of Geophysical Research-Atmospheres, 106, 3349-3356.Le Coz, M., Delclaux, F., Genthon, P., and Favreau, G., 2009, Assessment of Digital Elevation Model (DEM) aggregation methods for hydrological modeling: Lake Chad basin, Africa. Computers & Geosciences, 35, 1661-1670.Lehner, B., and Doll, P., 2004, Development and validation of a global database of lakes, reservoirs and wetlands. Journal of Hydrology, 296, 1-22.Sheffield, J., Goteti, G., and Wood, E. F., 2006, Development of a 50-year high-resolution global dataset of meteorological forcings for land surface modeling. Journal of Climate, 19, 3088-3111.
In this study we used a recent version of the VIC macroscale hydrology
model with a lake/wetland module, in combination with remotely sensed
altimetry data, to simulate and verify lake level and area variations in
Lake Chad, Africa. The 57-year (1950-2006) results are consistent with
both observations and known climate change in the area.
Further steps toward global simulations are being taken, as shown in a
strategy for global implementation of the model. Future work will focus
on the parameterizations of lakes globally, and modification of the river
networks to incorporate large lakes. Irrigation water usage will be a
critical term for the model to handle to achieve realistic results.
12/25/1972
01/31/1987
10/31/1963
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