A large-scale horizontal routing model to be coupled to land surface parametrization schemes

Lohmann, Dag; NOLTE-HOLUBE, RALPH; Raschke, E.

doi:10.1034/j.1600-0870.1996.t01-3-00009.x

Cited by 239 publications

(152 citation statements)

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“…The 0.125°VIC model for the Columbia is very similar to the model implemented at 0.25°described by Matheussen et al (2000). Simulated gridcell runoff and baseflow are then processed with a river routing model (Lohmann et al, 1996(Lohmann et al, , 1998 to produce streamflow in the Yakima Basin. Data are presented for the magnitude of the flow where the Yakima River joins the Columbia River.…”

Section: Hydrology Simulationsmentioning

confidence: 99%

Comparison of various precipitation downscaling methods for the simulation of streamflow in a rainshadow river basin

Salathé

2003

Intl Journal of Climatology

138

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Global simulations of precipitation from climate models lack sufficient resolution and contain large biases that make them unsuitable for regional studies, such as forcing hydrologic simulations. In this study, the effectiveness of several methods to downscale large-scale precipitation is examined. To facilitate comparisons with observations and to remove uncertainties in other fields, large-scale predictor fields to be downscaled are taken from the National Centers for Environmental Prediction-National Center for Atmospheric Research reanalyses. Three downscaling methods are used: (1): a local scaling of the simulated large-scale precipitation; (2) a modified scaling of simulated precipitation that takes into account the large-scale wind field; and (3) an analogue method with 1000 hPa heights as predictor.A hydrologic model of the Yakima River in central Washington state, USA, is then forced by the three downscaled precipitation datasets. Simulations with the raw large-scale precipitation and gridded observations are also made. Comparisons among these simulated flows reveal the effectiveness of the downscaling methods. The local scaling of the simulated large-scale precipitation is shown to be quite successful and simple to implement. Furthermore, the tuning of the downscaling methods is valid across phases of the Pacific decadal oscillation, suggesting that the methods are applicable to climate-change studies.

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Section: Hydrology Simulationsmentioning

confidence: 99%

Comparison of various precipitation downscaling methods for the simulation of streamflow in a rainshadow river basin

Salathé

2003

Intl Journal of Climatology

138

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“…Source-to-sink methods, which use an impulse response function to calculate the travel time from individual grid boxes (sources) to a specific point on the river network (a sink) [Lohmann et al, 1996;Nijssen et al, 2001]. These methods therefore estimate the lumped response for all grid boxes above a desired sink (e.g., above a gauging station), assuming the runoff routing processes are linear and stationary .…”

Section: A5 Channel/floodplain Routingmentioning

confidence: 99%

Improving the representation of hydrologic processes in Earth System Models

Clark

Fan

Lawrence

et al. 2015

Water Resources Research

452

404

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Many of the scientific and societal challenges in understanding and preparing for global environmental change rest upon our ability to understand and predict the water cycle change at large river basin, continent, and global scales. However, current large-scale land models (as a component of Earth System Models, or ESMs) do not yet reflect the best hydrologic process understanding or utilize the large amount of hydrologic observations for model testing. This paper discusses the opportunities and key challenges to improve hydrologic process representations and benchmarking in ESM land models, suggesting that (1) land model development can benefit from recent advances in hydrology, both through incorporating key processes (e.g., groundwater-surface water interactions) and new approaches to describe multiscale spatial variability and hydrologic connectivity; (2) accelerating model advances requires comprehensive hydrologic benchmarking in order to systematically evaluate competing alternatives, understand model weaknesses, and prioritize model development needs, and (3) stronger collaboration is needed between the hydrology and ESM modeling communities, both through greater engagement of hydrologists in ESM land model development, and through rigorous evaluation of ESM hydrology performance in research watersheds or Critical Zone Observatories. Such coordinated efforts in advancing hydrology in ESMs have the potential to substantially impact energy, carbon, and nutrient cycle prediction capabilities through the fundamental role hydrologic processes play in regulating these cycles.

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“…C and D are referred to as channel wave velocity and diffusivity parameters following our upstream literature (Lohmann et al, 1996(Lohmann et al, , 1998. Note that a more precise name for C is in fact the wave celerity (Beven, 1979), which better distinguishes it from the fluid velocity measured in river channels.…”

Section: A Linear Routing Modelmentioning

confidence: 99%

“…Here we choose the University of Washington (UW) routing model (Lohmann et al, 1996(Lohmann et al, , 1998, which is a relatively simple linear routing model developed for coupling with land surface models (LSMs), and it has been calibrated, implemented and validated in many large-scale streamflow studies Nijssen et al, 1997). The inputs to the UW routing model are runoff fields defined on a rectangular computing grid -the format used by most LSMs.…”

Section: A Linear Routing Modelmentioning

confidence: 99%

Inverse streamflow routing

Pan

Wood

2013

Hydrol. Earth Syst. Sci.

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Abstract. The process whereby 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 to 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 fixed interval smoothing. We refer to this streamflowto-runoff process as "inverse routing". Inversion experiments are performed using both synthetically generated and real streamflow measurements over the Ohio River basin. Results show that inverse routing can effectively reproduce the spatial field of runoff and its temporal dynamics from sufficiently dense gauge measurements, and the inversion performance can also be strongly affected by low gauge density and poor data quality.The runoff field is the only component in the terrestrial water budget that cannot be directly measured, and all previous studies used streamflow measurements in its place. Consequently, such studies are limited to scales where the spatial and temporal difference between the two can be ignored. Inverse routing provides a more sophisticated tool than traditional methods to bridge this gap and infer finescale (in both time and space) details of runoff from aggregated measurements. Improved handling of this final gap in terrestrial water budget analysis may potentially help us to use space-borne altimetry-based surface water measurements for cross-validating, cross-correcting, and assimilation with other space-borne water cycle observations.

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A large-scale horizontal routing model to be coupled to land surface parametrization schemes

Cited by 239 publications

References 0 publications

Comparison of various precipitation downscaling methods for the simulation of streamflow in a rainshadow river basin

Comparison of various precipitation downscaling methods for the simulation of streamflow in a rainshadow river basin

Improving the representation of hydrologic processes in Earth System Models

Inverse streamflow routing

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