River Network Routing on the NHDPlus Dataset

Abstract

The mapped rivers and streams of the contiguous United States are available in a geographic information system (GIS) dataset called National Hydrography Dataset Plus (NHDPlus). This hydrographic dataset has about 3 million river and water body reaches along with information on how they are connected into networks. The U.S. Geological Survey (USGS) National Water Information System (NWIS) provides streamflow observations at about 20 thousand gauges located on the NHDPlus river network. A river network model called Routing Application for Parallel Computation of Discharge (RAPID) is developed for the NHDPlus river network whose lateral inflow to the river network is calculated by a land surface model. A matrix-based version of the Muskingum method is developed herein, which RAPID uses to calculate flow and volume of water in all reaches of a river network with many thousands of reaches, including at ungauged locations. Gauges situated across river basins (not only at basin outlets) are used to automatically optimize the Muskingum parameters and to assess river flow computations, hence allowing the diagnosis of runoff computations provided by land surface models. RAPID is applied to the Guadalupe and San Antonio River basins in Texas, where flow wave celerities are estimated at multiple locations using 15-min data and can be reproduced reasonably with RAPID. This river model can be adapted for parallel computing and although the matrix method initially adds a large overhead, river flow results can be obtained faster than with the traditional Muskingum method when using a few processing cores, as demonstrated in a synthetic study using the upper Mississippi River basin.

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

“…Their lower unit triangular shape, the total number of nonzero elements per row, and their ability to be solved in a few iterations has been stable in all existing RAPID studies [David et al, 2011a[David et al, , 2011b[David et al, , 2013a[David et al, , 2013b. One could therefore expect that the mathematical approaches used in this study would behave well from a scaled-size speedup perspective, although such investigation is admittedly beyond the scope of this study.…”

“…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).…”

“…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). Additional information on RAPID-including download links for the source code corresponding to this study [David, 2013] as well as versions corresponding to previous studies-is available at http://rapidhub.org.…”

“…As in previous studies [David et al, 2011b[David et al, , 2013a[David et al, , 2013b, an optimization procedure designed to minimize the square errors between observations and simulations at the daily time step was used to determine the parameters of RAPID simulations. The optimal set of parameters was chosen by determining the values of two scalars k k and k x such that …”

“…Differences of such magnitude among results obtained with various resolution schemes are hence also to be deemed expected and acceptable. Table 3 shows the differences obtained among 3 hourly averaged output files for a series of resolution schemes including the traditional Muskingum method on one core [McCarthy, 1938], the matrix-based Muskingum method of equation (1) solved directly on one core [David et al, 2011b], the matrix-based Muskingum method solved iteratively on 1-32 cores [David et al, 2011b[David et al, , 2013a, and the trans-boundary Muskingum method with large subbasins approximation solved with two iterations on 1-32 cores (this study).…”