Evaluation of global stream flow routing based on gridded run-off fluxes of Global Land Data Assimilation System (GLDAS)

Tuesday, 16 December 2014
Roshan K Shrestha1,2, Youlong Xia1, Jesse Meng3, Paul Dirmeyer2 and Michael B Ek4, (1)Environmental Modeling Center, College Park, MD, United States, (2)COLA, Fairfax, VA, United States, (3)IMSG, College Park, MD, United States, (4)NOAA/NWS/NCEP, College Park, MD, United States
The current Global Land Data Assimilation System (GLDAS) project provides detailed estimates of energy fluxes and water budget, with currently planned upgrades including improved Land Surface Model (LSM) physics, enhanced global meteorological forcing data sets, more robust soil moisture initialization, updated model specific parameter sets and an advanced snow data assimilation scheme. Because of these advancements made in the GLDAS experiment, the spatio-temporal variability of hydrologic fluxes is expected to be as good as other key land-surface fluxes. Gridded surface runoff from GLDAS experiment provides a unique opportunity to implement flow routing along the network of river system. In this experiment, we add stream flow routing in the GLDAS and investigate the stream flow variability using a computationally expensive cell-to-cell (C2C) routing scheme and a simpler source-to-sink (S2S) routing scheme. Appropriate parameterization of C2C is difficult, but it can use a detailed set of parameters, which provide an opportunity to develop a robust and realistic flow routing. On the other hand, the S2S offers simplified and computationally efficient routing solution but it needs periodic adjustments to its parameters. We will present a comparative analysis of these routing experiments, which may be useful for hydrologic estimations in data scarce regions as well as to establish an operational global stream flow prediction system.