Repairing the Long-term Salinity Projection Model for the Colorado River Basin

By James R. Prairie. Published in the Proceedings of the International Salinity Forum, 2005.

Abstract

Rising salinity levels have long been recognized for their adverse effects on agriculture and the damages caused to municipal systems. Using the 1999 concentration levels, economic studies have identified the cost of damages due to increased salinity levels in the lower Colorado River basin at approximately $330 million dollars per year (U.S. Department of the Interior, 2003). For these reasons, coupled with each state’s right to continued water development as they move towards fulfilling their compact appropriated waters, efforts to decrease or maintain salinity at the numeric criteria have resulted in salinity control efforts mandated by the Colorado River Basin Salinity Control Act. In order to assist in maintenance of average annual salinity levels at or below the fixed point numeric criteria a computer simulation model termed the Colorado River Simulation System (CRSS) salinity projection model was developed. This model allows decision makers to simulate the effects of increased water use on salinity concentration at the key gauges where the fixed point numeric criteria apply.
For the last few years this model has not been performing properly and could not be verified over a historic period from 1971-1990. The model has consistently over predicted salinity concentration at these key gauges causing decision makers to lose confidence in the model results. Work has recently been completed that provides a verified model for longterm salinity projection in the Colorado River basin.
In this paper we identify the problems found with the previous CRSS salinity projection model followed by the solutions we arrived at to address these issues. Finally, the solutions are incorporated in an updated CRSS salinity projection model and the results of these corrections are graphically displayed concluding with a brief discussion of where we intend to take our research efforts using the updated model.

 

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