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Advances in Meteorology
Volume 2014 (2014), Article ID 135012, 15 pages
Research Article

A System Dynamics Approach to Modeling Future Climate Scenarios: Quantifying and Projecting Patterns of Evapotranspiration and Precipitation in the Salton Sea Watershed

1U.S. Army Engineer Research and Development Center, Environmental Laboratory, Vicksburg, MS 39180-6199, USA
2Department of Wildlife & Fisheries Sciences, Texas A&M University, College Station, TX 77843, USA

Received 14 February 2014; Revised 17 April 2014; Accepted 18 April 2014; Published 19 May 2014

Academic Editor: Dong Jiang

Copyright © 2014 Michael E. Kjelland et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


The need for improved quantitative precipitation forecasts and realistic assessments of the regional impacts of natural climate variability and climate change has generated increased interest in regional (i.e., systems-scale) climate simulation. The Salton Sea Stochastic Simulation Model (S4M) was developed to assist planners and residents of the Salton Sea (SS) transboundary watershed (USA and Mexico) in making sound policy decisions regarding complex water-related issues. In order to develop the S4M with a higher degree of climate forecasting resolution, an in-depth analysis was conducted regarding precipitation and evapotranspiration for the semiarid region of the watershed. Weather station data were compiled for both precipitation and evapotranspiration from 1980 to 2004. Several logistic regression models were developed for determining the relationships among precipitation events, that is, duration and volume, and evapotranspiration levels. These data were then used to develop a stochastic weather generator for S4M. Analyses revealed that the cumulative effects and changes of ±10 percent in SS inflows can have significant effects on sea elevation and salinity. The aforementioned technique maintains the relationships between the historic frequency distributions of both precipitation and evapotranspiration, and not as separate unconnected and constrained variables.