Application of Stochastic Analysis, Modeling and Simulation (SAMS) to Selected Hydrologic Data in the Middle East
Abstract
Water resources in the Middle East are very scarce and the management of these resources is a challenge. In this paper, the use of stochastic analysis, modeling, and simulation (SAMS) software package to selected hydrologic data in the Middle East (namely Jordan and Saudi Arabia) are explored. Modeling and simulation experiments were conducted to test the capabilities of SAMS to be used for stochastic modeling and simulation in the Middle East region. The hydrologic data used in this study consist of historic observed rainfall data of different lengths at various sites in Jordan and Saudi Arabia. The models used in this study include: autoregressive moving average (ARMA) models, periodic autoregressive moving average (PARMA) models, multi-site contemporaneous autoregressive moving average (CARMA) models, and temporal disaggregation models. Results indicate that SAMS can be used as a tool for stochastic modeling and simulation of hydrologic data in Jordan and Saudi Arabia. It is important for managers and decision makers of water resources in these countries to be able to use sophisticated tools such as SAMS while deciding water management policies in these countries.
Keywords:
stochastic analysis, modeling, simulation, hydrologic dataDownloads
References
O. G. B. Sveinsson, J. D. Salas, W. L. Lane, D. K. Frevert, Stochastic Analysis, Modeling, and Simulation (SAMS), Version 2007, User’s Manual, Colorado State University, 2007
T. B. McKee, N. J. Doesken, J. Kleist, “The Relationship of Drought Frequency and Duration to Time Scales”, Eighth Conference of Applied Climatology, Anaheim, USA, January 17–22, 1993
J. D. Salas, N. Saada, C. H. Chung, Stochastic Modeling and Simulation of the Nile River System Monthly Flows, Hydrologic Science and Engineering Program, Department of Civil Engineering, Colorado State University, 1995
J. D. Salas, N. Saada, C. H. Chung, W. L. Lane, D. K. Frevert, Stochastic Analysis, Modeling, and Simulation (SAMS), Version 2000-User’s Manual, Colorado State University, 2000
W. L. Lane, D. K. Frevert, Applied Stochastic Techniques: (Personal Computer Version): User Manual, Bureau of Reclamation, US Department of Interior, 1990
N. Saada, “Simulation of long term characteristics of annual rainfall in selected areas in Saudi Arabia”, Computational Water, Energy, and Environmental Engineering, Vol. 4, No. 2, pp. 18-24, 2015 DOI: https://doi.org/10.4236/cweee.2015.42003
N. Saada, “Time series modeling of monthly rainfall in arid areas: Case study for Saudi Arabia”, American Journal of Environmental Sciences, Vol. 10, No. 3, pp. 277-282, 2014 DOI: https://doi.org/10.3844/ajessp.2014.277.282
N. Saada, A. Abu-Romman, “Multi-site modeling and simulation of the standardized precipitation index (SPI) in Jordan”, Journal of Hydrology: Regional Studies, Vol. 14, pp. 83-91, 2017 DOI: https://doi.org/10.1016/j.ejrh.2017.11.002
Downloads
How to Cite
License
Authors who publish with this journal agree to the following terms:
- Authors retain the copyright and grant the journal the right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.
- Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) after its publication in ETASR with an acknowledgement of its initial publication in this journal.
