Continental‐scale water and energy flux analysis and validation for North American Land Data Assimilation System project phase 2 (NLDAS‐2): 2. Validation of model‐simulated streamflow

Abstract

[1] This is the second part of a study on continental-scale water and energy flux analysis and validation conducted in phase 2 of the North American Land Data Assimilation System project (NLDAS-2). The first part concentrates on a model-by-model comparison of mean annual and monthly water fluxes, energy fluxes and state variables. In this second part, the focus is on the validation of simulated streamflow from four land surface models (Noah, Mosaic, Sacramento Soil Moisture Accounting (SAC-SMA), and Variable Infiltration Capacity (VIC) models) and their ensemble mean. Comparisons are made against 28-years (1 October 1979-30 September 2007) of United States Geological Survey observed streamflow for 961 small basins and 8 major basins over the conterminous United States (CONUS). Relative bias, anomaly correlation and Nash-Sutcliffe Efficiency (NSE) statistics at daily to annual time scales are used to assess model-simulated streamflow. The Noah (the Mosaic) model overestimates (underestimates) mean annual runoff and underestimates (overestimates) mean annual evapotranspiration. The SAC-SMA and VIC models simulate the mean annual runoff and evapotranspiration well when compared with the observations. The ensemble mean is closer to the mean annual observed streamflow for both the 961 small basins and the 8 major basins than is the mean from any individual model. All of the models, as well as the ensemble mean, have large daily, weekly, monthly, and annual streamflow anomaly correlations for most basins over the CONUS, implying strong simulation skill. However, the daily, weekly, and monthly NSE analysis results are not necessarily encouraging, in particular for daily streamflow. The Noah and Mosaic models are useful (NSE > 0.4) only for about 10% of the 961 small basins, the SAC-SMA and VIC models are useful for about 30% of the 961 small basins, and the ensemble mean is useful for about 42% of the 961 small basins. As the time scale increases, the NSE increases as expected. However, even for monthly streamflow, the ensemble mean is useful for only 75% of the 961 small basins.

Enhanced fixed-size parallel speedup with the Muskingum method using a trans-boundary approach and a large subbasins approximation

“…At the core of this application is a river network routing model called RAPID [David et al, 2011b] simulating discharge in all river reaches of the Mississippi River Basin as described in a near-global hydrographic data set called HydroSHEDS [Lehner et al, 2008]. Estimates of surface and subsurface runoff were derived from second phase of the North American Land Data Assimilation System (NLDAS2), [Xia et al, 2012a[Xia et al, , 2012b [David et al, 2011b] is a river network routing model based on a matrix version of the Muskingum method given in equation (1). The principal modification made to RAPID compared to previous studies [David et al, 2011a[David et al, , 2011b[David et al, , 2013a[David et al, , 2013b] is the addition of the trans-boundary Muskingum method with large subbasins approximation given in equation (5).…”

Comparing potential recharge estimates from three Land Surface Models across the western US

“…NLDAS-2 (Mitchell et al, 2004;Xia et al, 2012aXia et al, , 2012b integrates observation-based and model reanalysis data to drive LSMs offline. It executes at 1/8th-degree grid spacing at an hourly temporal scale over central North America, enabled by the Land Information System (LIS; Kumar et al, 2006;Peters-Lidard et al, 2007).…”

“…Past multi model evaluation in NLDAS-2 has been used for evaluating surface water and energy fluxes (Wei et al, 2013), such as soil moisture (Mo et al, 2011;Mo et al, 2012;Xia et al, 2014, in press-a, in press-b), evapotranspiration (Long et al, 2014), soil temperature , and streamflow (Mo et al, 2012;Xia et al, 2012b). Although there have been efforts to compare the continental scale water and energy-fluxes among LSMs for NLDAS-2 (Xia et al, 2012a) model performance was only evaluated with surface water (Xia et al, 2012b).…”

“…Although there have been efforts to compare the continental scale water and energy-fluxes among LSMs for NLDAS-2 (Xia et al, 2012a) model performance was only evaluated with surface water (Xia et al, 2012b). No particular efforts have been made using these models to simulate and characterize the amount and seasonality of recharge in the western US, mostly due to the limited availability of recharge data.…”

“…This process has a significant influence on the recharge estimates because the recharge in the LSMs is the function of water content in the bottom layer. These differences could be related to energy balance or water balance constraints (Mitchell et al, 2004;Peters-Lidard et al, 2007;Rodell et al, 2011;Xia et al, 2012b;Cai et al, 2014).…”