Incorporating Groundwater-Surface Water Interaction Into River Management Models

By Valerio, A., H. Rajaram and E. Zagona, Incorporating groundwater-surface water interaction into river management models, Ground Water, 48 (5), 661-673, 2010. 

Abstract: Accurate representation of groundwater-surface water interactions is critical to modeling low river flows in the semi-arid southwestern United States. Although a number of groundwater-surface water models exist, they are seldom integrated with river operation/management models. A link between the object-oriented river and reservoir operations model, RiverWare, and the groundwater model, MODFLOW, was developed to incorporate groundwater-surface water interaction processes, such as river seepage/gains, riparian evapotranspiration, and irrigation return flows, into a rule-based water allocations model. An explicit approach is used in which the two models run in tandem, exchanging data once in each computational time step. Because the MODFLOW grid is typically at a finer resolution than RiverWare objects, the linked model employs spatial interpolation and summation for compatible communication of exchanged variables. The performance of the linked model is illustrated through two applications in the Middle Rio Grande Basin in New Mexico where overappropriation impacts endangered species habitats. In one application, the linked model results are compared with historical data; the other illustrates use of the linked model for determining management strategies needed to attain an in-stream flow target. The flows predicted by the linked model at gauge locations are reasonably accurate except during a few very low flow periods when discrepancies may be attributable to stream gaging uncertainties or inaccurate documentation of diversions. The linked model accounted for complex diversions, releases, groundwater pumpage, irrigation return flows, and seepage between the groundwater system and canals/drains to achieve a schedule of releases that satisfied the in-stream target flow.


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