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| Titel |
Multi-objective calibration of a surface water-groundwater flow model in an irrigated agricultural region: Yaqui Valley, Sonora, Mexico |
| VerfasserIn |
G. Schoups, C. Lee Addams, S. M. Gorelick |
| Medientyp |
Artikel
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| Sprache |
Englisch
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| ISSN |
1027-5606
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| Digitales Dokument |
URL |
| Erschienen |
In: Hydrology and Earth System Sciences ; 9, no. 5 ; Nr. 9, no. 5 (2005-12-20), S.549-568 |
| Datensatznummer |
250007045
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| Publikation (Nr.) |
 copernicus.org/hess-9-549-2005.pdf |
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| Zusammenfassung |
| Multi-objective optimization was used to calibrate a regional surface
water-groundwater model of the Yaqui Valley, a 6800 km2 irrigated
agricultural region located along the Sea of Cortez in Sonora, Mexico. The
model simulates three-dimensional groundwater flow coupled to
one-dimensional surface water flow in the irrigation canals. It accounts for
the spatial distribution of annual recharge from irrigation, subsurface
drainage, agricultural pumping, and irrigation canal seepage. The main
advantage of the calibration method is that it accounts for both parameter
and model structural uncertainty. In this case, results show that the effect
of including the process of bare soil evaporation is significantly greater
than the effects of parameter uncertainty. Furthermore, by treating the
different objectives independently, a better identification of the model
parameters is achieved compared to a single-objective approach, since the
various objectives are sensitive to different parameters. The simulated
water balance shows that 15–20% of the water that enters the irrigation
canals is lost by seepage to groundwater. The main discharge mechanisms in
the Valley are crop evapotranspiration (53%), non-agricultural
evapotranspiration and bare soil evaporation (19%), surface drainage to
the Sea of Cortez (15%), and groundwater pumping (9%). In comparison,
groundwater discharge to the estuary was relatively insignificant (less than
1%). The model was further refined by identifying zonal Kv and
Kh values based on a spatial analysis of the model residuals. |
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