Inverse Streamflow Routing and Its Applications
Abstract
The process where the spatially distributed runoff (generated through saturation/infiltration excesses, subsurface flow, etc.) travels over the hillslope and river network and becomes streamflow is generally referred as 'routing'. In short, routing is a runoff-to-streamflow process, and the streamflow in rivers is the response to runoff integrated in both time and space. Here we develop a methodology to invert the routing process, i.e., to derive the spatially distributed runoff from streamflow (e.g. measured at gauge stations) by inverting an arbitrary linear routing model using a data assimilation technique ' fixed interval smoothing'. We refer this streamflow-to-runoff process as 'inverse routing'. Inversion experiments are performed using both synthetically generated and real streamflow measurements over the Ohio river basin and Red-Arkansas river basin. Results show that inverse routing can very effectively reproduce the spatial field of runoff and its temporal dynamics from gauge measurements. Runoff field is the only component in terrestrial water budget that cannot be directly measured and all previous studies use streamflow measurements in its place. Consequently, such studies are limited to scales where the spatial and temporal difference between the two can be ignored. Now inverse routing bridges the gap and provides a best, if not only, mean to estimate runoff field at fine spatial/temporal scales from observations. Closing this final gap in terrestrial water budget analysis opens up opportunities in using space-borne altimetry based surface water measurements for cross-validating, cross-correcting, and assimilation with other space-borne water cycle observations. Concept of Inverse Routing
- Publication:
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AGU Fall Meeting Abstracts
- Pub Date:
- December 2013
- Bibcode:
- 2013AGUFM.H43M..05P
- Keywords:
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- 1860 HYDROLOGY Streamflow;
- 1910 INFORMATICS Data assimilation;
- integration and fusion;
- 1850 HYDROLOGY Overland flow;
- 1839 HYDROLOGY Hydrologic scaling