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Discussion papers | Copyright
https://doi.org/10.5194/hess-2018-109
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

Research article 09 Apr 2018

Research article | 09 Apr 2018

Review status
This discussion paper is a preprint. It is a manuscript under review for the journal Hydrology and Earth System Sciences (HESS).

Spatiotemporal Assimilation/Interpolation of Discharge Records through Inverse Streamflow Routing

Colby K. Fisher, Ming Pan, and Eric F. Wood Colby K. Fisher et al.
  • Department of Civil and Environmental Engineering, Princeton University, Princeton, NJ USA

Abstract. Poorly monitored river flows in many regions of the world have been hindering our ability to accurately estimate global water usage as well as the budgets and variability of the global water cycle. In-situ gauging sites, as well as a number of satellite-based systems, make observations of river discharge throughout the globe; however, these observations are often sparse due to, e.g., the sampling frequencies of sensors or a lack of reporting. Recently, efforts have been made to develop methods to integrate these discrete observations to gain a better understanding of the underlying processes. This paper presents an application of a fixed interval Kalman smoother based model, called Inverse Streamflow Routing (ISR), to generate spatially and temporally continuous river discharge fields from discrete observations. The method propagates the observed information across all reachable parts of the river network (up/downstream from gauging point) and all reachable times (before/after observation time) using a two-sweep procedure that first propagates information backward in time to the furthest upstream locations (inverse routing) and then propagates it forward in time to the furthest downstream locations (forward routing). The key advantages of this approach are that it (1) maintains all the physical consistencies embodied by a diffusive wave routing model (flow confluence relationships on the river network and the resulting mass balance, wave velocity and diffusivity), (2) updates the lateral influx (runoff) at pixel level (furthest upstream) to guarantee exhaustive propagation of observed information, (3) works both with a first guess of initial river discharge conditions from a routing model (assimilation) and without a first guess (pure interpolation of observations). Two sets of experiments are carried out under idealized conditions as well as real-world conditions provided by U.S. Geological Survey observations. Results show that the method can effectively reproduce the spatial and temporal dynamics of river discharge in each of the experiments presented. The performance is driven by the density of the gauge network as well as the quality of the data being assimilated. We find that when assimilating the actual USGS observations, the performance decreases relative to our idealized scenario; however, we are still able to produce an improved discharge product at each validation site. With further testing as well as global application, ISR may prove to be a useful method for extending our current network of global river discharge observations.

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Colby K. Fisher et al.
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Short summary
Poorly monitored river flows in many regions of the world have been hindering our ability to accurately estimate global water usage. In this paper we present a method to derive continuous records of streamflow from a set of in-situ gauges. Applying this method to the Ohio River basin, we found that we could reliably generate estimates of streamflow throughout the basin using only a small set of streamflow gauges, which can be useful for global river basins where we do not have good observations.
Poorly monitored river flows in many regions of the world have been hindering our ability to...
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