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Streamflow and water balance intercomparisons of four land surface models in the North American Land Data Assimilation System project

Streamflow and water balance intercomparisons of four land surface models in the North American Land Data Assimilation System project
Streamflow and water balance intercomparisons of four land surface models in the North American Land Data Assimilation System project

This paper is part of a series of papers about the multi-institutional North American Land Data Assimilation System (NLDAS) project. It compares and evaluates streamflow and water balance results from four different land surface models (LSMs) within the continental United States. These LSMs have been run for the retrospective period from 1 October 1996 to 30 September 1999 forced by atmospheric observations from the Eta Data Assimilation System (EDAS) analysis, measured precipitation, and satellite- derived downward solar radiation. These model runs were performed on a common 1/8° latitude-longitude grid and used the same database for soil and vegetation classifications. We have evaluated these simulations using U.S. Geological Survey (USGS) measured daily streamflow data for 9 large major basins and 1145 small- to medium-sized basins from 23 km2 to 10,000 km2 distributed over the NLDAS domain. Model runoff was routed with a common distributed and a lumped optimized linear routing model. The diagnosis of the model water balance results demonstrates strengths and weaknesses in the models, our insufficient knowledge of ad hoc parameters used for the model runs, the interdependence of model structure and model physics, and the lack of good forcing data in parts of the United States, especially in regions with extended snow cover. Overall, the differences between the LSM water balance terms are of the same magnitude as the mean water balance terms themselves. The modeled mean annual runoff shows large regional differences by a factor of up to 4 between models. The corresponding difference in mean annual evapotranspiration is about a factor of 2. The analysis of runoff timing for the LSMs demonstrates the importance of correct snowmelt timing, where the resulting differences in streamflow timing can be up to four months. Runoff is underestimated by all LSMs in areas with significant snowfall.

LDAS, Streamflow, Water balance
0148-0227
D07S91 1-22
Lohmann, Dag
f8974c4b-bc29-499f-8270-9adf64cd0afe
Mitchell, Kenneth E.
91d961dc-4337-4c48-aace-74ebe14f1e2b
Houser, Paul R.
67aba422-f8ae-4d1d-a33f-2e6117ee1d54
Wood, Eric F.
8352c1b4-4fd3-42fe-bd23-46619024f1cf
Schaake, John C.
d9224d5c-d695-4d9b-88bb-2bfbfe8eeb61
Robock, Alan
48548a44-cb37-4c27-b96c-3826a9769fef
Cosgrove, Brian A.
04c1e698-3d7c-412a-8d15-1fe35635e687
Sheffield, Justin
dd66575b-a4dc-4190-ad95-df2d6aaaaa6b
Duan, Qingyun
b75b3e1f-c6c8-4062-bc33-e1d10a87f25b
Luo, Lifeng
e9b25aa8-e877-45a6-bdca-53aba9bbde84
Higgins, R. Wayne
93759215-b563-4735-8137-9acc5f14fc93
Pinker, Rachel T.
42f0f84f-36c8-412d-a317-851f70c6fe7d
Tarpley, J. Dan
e4eb84c6-998f-4269-999a-bcddabb8796c
Lohmann, Dag
f8974c4b-bc29-499f-8270-9adf64cd0afe
Mitchell, Kenneth E.
91d961dc-4337-4c48-aace-74ebe14f1e2b
Houser, Paul R.
67aba422-f8ae-4d1d-a33f-2e6117ee1d54
Wood, Eric F.
8352c1b4-4fd3-42fe-bd23-46619024f1cf
Schaake, John C.
d9224d5c-d695-4d9b-88bb-2bfbfe8eeb61
Robock, Alan
48548a44-cb37-4c27-b96c-3826a9769fef
Cosgrove, Brian A.
04c1e698-3d7c-412a-8d15-1fe35635e687
Sheffield, Justin
dd66575b-a4dc-4190-ad95-df2d6aaaaa6b
Duan, Qingyun
b75b3e1f-c6c8-4062-bc33-e1d10a87f25b
Luo, Lifeng
e9b25aa8-e877-45a6-bdca-53aba9bbde84
Higgins, R. Wayne
93759215-b563-4735-8137-9acc5f14fc93
Pinker, Rachel T.
42f0f84f-36c8-412d-a317-851f70c6fe7d
Tarpley, J. Dan
e4eb84c6-998f-4269-999a-bcddabb8796c

Lohmann, Dag, Mitchell, Kenneth E., Houser, Paul R., Wood, Eric F., Schaake, John C., Robock, Alan, Cosgrove, Brian A., Sheffield, Justin, Duan, Qingyun, Luo, Lifeng, Higgins, R. Wayne, Pinker, Rachel T. and Tarpley, J. Dan (2004) Streamflow and water balance intercomparisons of four land surface models in the North American Land Data Assimilation System project. Journal of Geophysical Research: Atmospheres, 109 (D7), D07S91 1-22. (doi:10.1029/2003jd003517).

Record type: Article

Abstract

This paper is part of a series of papers about the multi-institutional North American Land Data Assimilation System (NLDAS) project. It compares and evaluates streamflow and water balance results from four different land surface models (LSMs) within the continental United States. These LSMs have been run for the retrospective period from 1 October 1996 to 30 September 1999 forced by atmospheric observations from the Eta Data Assimilation System (EDAS) analysis, measured precipitation, and satellite- derived downward solar radiation. These model runs were performed on a common 1/8° latitude-longitude grid and used the same database for soil and vegetation classifications. We have evaluated these simulations using U.S. Geological Survey (USGS) measured daily streamflow data for 9 large major basins and 1145 small- to medium-sized basins from 23 km2 to 10,000 km2 distributed over the NLDAS domain. Model runoff was routed with a common distributed and a lumped optimized linear routing model. The diagnosis of the model water balance results demonstrates strengths and weaknesses in the models, our insufficient knowledge of ad hoc parameters used for the model runs, the interdependence of model structure and model physics, and the lack of good forcing data in parts of the United States, especially in regions with extended snow cover. Overall, the differences between the LSM water balance terms are of the same magnitude as the mean water balance terms themselves. The modeled mean annual runoff shows large regional differences by a factor of up to 4 between models. The corresponding difference in mean annual evapotranspiration is about a factor of 2. The analysis of runoff timing for the LSMs demonstrates the importance of correct snowmelt timing, where the resulting differences in streamflow timing can be up to four months. Runoff is underestimated by all LSMs in areas with significant snowfall.

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More information

e-pub ahead of print date: 9 April 2004
Published date: 16 April 2004
Keywords: LDAS, Streamflow, Water balance

Identifiers

Local EPrints ID: 480931
URI: http://eprints.soton.ac.uk/id/eprint/480931
ISSN: 0148-0227
PURE UUID: 4be4ed18-5ba9-4230-814d-7fff75ddb66a
ORCID for Justin Sheffield: ORCID iD orcid.org/0000-0003-2400-0630

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Date deposited: 10 Aug 2023 16:59
Last modified: 17 Mar 2024 03:40

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Contributors

Author: Dag Lohmann
Author: Kenneth E. Mitchell
Author: Paul R. Houser
Author: Eric F. Wood
Author: John C. Schaake
Author: Alan Robock
Author: Brian A. Cosgrove
Author: Qingyun Duan
Author: Lifeng Luo
Author: R. Wayne Higgins
Author: Rachel T. Pinker
Author: J. Dan Tarpley

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