Implementing a Catchment-Based, National-Scale Land Surface and River Routing Model Zhao Liu 1 ( email@example.com ), James S. Famiglietti 1, 2 , HyungJun Kim 3, 2
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Implementing a Catchment-Based, National-Scale Land Surface and River Routing Model
Zhao Liu1 (firstname.lastname@example.org), James S. Famiglietti1, 2, HyungJunKim3, 2
1. Department of Earth System Science, University of California, Irvine, CA, 92697
2. UC Center for Hydrologic Modeling, University of California, Irvine, CA, 92697
3. Institute of Industrial Science, University of Tokyo, Tokyo, Japan
The main motivation of this study is to characterize how accurately we can estimate river discharge, river depth and inundation under a catchment-based hydrological and routing modeling system (CHARMS) framework. Here we present a national-scale implementation of CHARMS that includes an explicit representation of the river network upscaled from the NHDPlusdataset (Fig.1). There are two main components in CHARMS: a land surface model based on the Community Land Model (CLM) 3.5, which is modified for implementation on a catchment template; and a river routing model that considers the water transport of each river reach in each catchment.
Figure1: Explicit representation of river networks for the national- scale CHARMS modeling template. It includes 2959 catchment cross the nation and there is one main river reach in each catchment. Different colors represent the strahler stream order for each river reach.
Figure 3: Schematic plots of river cross section profile in CHARMS
Figure 4: The derived bankfull depth (left) and bankfull width (rigut) of the rivers in the Mississippi Basin
Fig.5 shows the comparison between the simulation and the observations. These are preliminary results without any calibration. The simulated discharge compare fairly well with the observations. CHARMS is able to capture both the seasonal and the daily variability at upstream. The accuracy of the simulated discharge decrease towards the downstream. Inappropriate constant empirical relationship describing the river cross-section profile , poor runoff generation from from CLM3.5, and no consideration of lakes and reservoirs/anthropogenic effect/human regulation can all contribute to this discrepancy. More work still need to be done.
Figure 5: Simulate discharge compared with USGS gauge observations. The gauge stations are labeled as red dots on Fig. 2.
Figure 2: Interpolation scheme of converting grid-based CLM3.5 to catchment-based CLM 3.5. It shows the 1 degree grid covering the country and the intersected Mississippi basin with 1/8 degree grid. The blue line is the main river reach of the Mississippi Basin, and the red dots are the USGS gauge stations.
This work was supported by grants from the NASA Earth and Space Science Graduate Fellowship program.
 Goteti, G., J. S. Famiglietti, and K. Asante (2008), A Catchment-Based Hydrologic and Routing Modeling System with explicit river channels, J. Geophys. Res., 113(D14), D14116.
 Community Land Model 3.5: http://www.cgd.ucar.edu/tss/clm/distribution/clm3.5
Bjerklie, D. M., S. L. Dingman, and C. H. Bolster (2005), Comparison of constitutive flow resistance equations based on the Manning and Chezy equations applied to natural rivers, Water Resour. Res., 41(11), W11502.