Risk Assessment of Climate Change Impacts on Runoff in Urmia Lake Basin, Iran
Publication: Journal of Hydrologic Engineering
Volume 21, Issue 8
Abstract
Urmia Lake, the largest lake in Iran, is an important water body and habitat for a variety of different species. Data of ten climate models among the atmosphere ocean general circulation models (AOGCMs) were assembled for the 2021–2050 period under A2 and B1 emission scenarios. First, both the 30-year historic (1961–1990) and 30-year future monthly temperature and precipitation in the region were generated and weighted by the beta function () that assigns weights to AOGCMs based on the model evaluations. Then, the cumulative density function (CDF) in each month was determined. Precipitation and temperature values at 25, 50, and 75% probability were extracted from the CDFs. Subsequently these values were introduced to the Long Ashton Research Station Weather Generator model (LARS-WG) to downscale and produce time series of temperature and precipitation in the future, subject to the uncertainty of climate models. Then, these monthly time series at different risk levels were introduced into the artificial neural network (ANN) model and future monthly runoff time series were generated. The findings indicated a decrease in the flow into the lake of the order of 21, 13, and 0.3% under the A2 scenario and an increase of 4.7, 13.8, and 18.9% under the B2 scenario with respect to the observation period at 25, 50, and 75% risk levels, respectively. The results of this study highlight the necessity to immediately and effectively cut back on the water use in the basin not only to remedy the projected climate change effects in the future, but also to ensure gradual reclamation of the ongoing environmental crisis.
Get full access to this article
View all available purchase options and get full access to this article.
Acknowledgments
Dr. Saeid Saeidijam is appreciated for providing technical assistance. Also, the authors appreciate the reviewers who provided valuable comments to improve the manuscript.
References
Carter, T. R., Hulme, M., and Lal, M. (1999). “Guidelines on the use of scenario data for climate impact and adaptation assessment.” Version 1, Intergovernmental Panel on Climate Change, Task Group on Scenarios for Climate Impact Assessment, IPCC-TGCIA, 〈http://unfccc.int/resource/cdroms/na1/vanda/Resourscematerials/Climate/ScenarioData.pdf〉 (Feb. 14, 2012).
Chen, J., Brissette, F. P., and Leconte, R. (2011). “Uncertainty of downscaling method in quantifying the impact of climate change on hydrology.” J. Hydrol., 401(3–4), 190–202.
Collins, W. D., et al. (2006). “The community climate system model: CCSM3.” J. Clim., 19(11), 2122–2143.
Coulibaly, P., Anctil, F., and Bobee, B. (2000). “Daily reservoir inflow forecasting using artificial neural networks with stopped training approach.” J. Hydrol., 230(3–4), 244–257.
Deg-Hyo, B., Il-Won, J., and Lettenmaier, D. P. (2011). “Hydrologic uncertainties in climate change from IPCC AR4 GCM simulations of the Chungju Basin, Korea original.” J. Hydrol., 401(1–2), 90–105.
Delworth, T. L., Broccoli, A. J., Rosati, A., and Stouffer, R. J. (2006). “GFDL’s CM2 global coupled climate models. Part 1: Formulation and simulation characteristics.” J. Clim., 19(5), 643–674.
Déqué, M., Dreveton, C., Braun, A., and Cariolle, D. (1994). “The ARPEGE/IFS atmosphere model: A contribution to the French community climate modeling.” Clim. Dyn., 10(4), 249–266.
Diaz-Nieto, J., and Wilby, R. L. (2005). “A comparison of statistical downscaling and climate change factor methods: Impacts on low flows in the river Thames.” Clima. Change, 69(2), 245–268.
Downing, J. A., et al. (2006). “The global abundance and size distribution of lakes, ponds, and impoundments.” Limnol. Oceanogr., 51(5), 2388–2397.
Giglioli, N., and Saltelli, A. (2003). “Simlab 2.2: Software for sensitivity and uncertainty analysis, Simlab manual.” Institute for Systems Informatics and Safety, Ispra, Italy.
Gordon, C., et al. (2000). “The simulation of S.S.T., sea ice extents and ocean transport in a version of the Hadley Center coupled model without flux adjustments.” Clim. Dyn., 16(2–3), 147–168.
Hassanzadeh, E., Zarghami, M., and Hassanzadeh, Y. (2012). “Determining the main factors in declining the Urmia Lake level by using system dynamics modeling.” J. Water Resour. Manage., 26(1), 129–145.
Hasumi, H., and Emori, S., eds. (2004). “K-1 coupled model (MIROC) description.” K-1 Technical Rep. 1, 〈www.ccsr.u-tokyo.ac.jp/kyosei/hasumi/MIROC/tech-repo.pdf〉 (Sep. 1, 2012).
Haykin, S. (1994). Neural networks—A comprehensive foundation, Macmillan College, New York.
Hourdin, F., et al. (2006). “The LMDZ4 general circulation model: Climate performance and sensitivity to parameterized physics with emphasis on tropical convection.” Clim. Dyn., 27(7), 787–813.
K-1 Model Developers. (2004). “K-1 coupled model (MIROC) description.”, Center for Climate System Research, Univ. of Tokyo, Tokyo.
Katz, R. W. (2002). “Techniques for estimating uncertainty in climate change scenarios and impact studies.” Adv. Clim. Res., 20(2), 167–185.
Lawless, C., and Semenov, M. A. (2005). “Assessing lead-time for predicting wheat growth using a crop simulation model.” Agric. For. Meteorol., 135(1–4), 302–313.
Lawrence, D., et al. (2012). “Climate change impacts and uncertainties in flood risk management: Examples from the North Sea region.”, Norwegian Water Resources and Energy Directorate, Oslo, Norway.
Motiee, H., and McBean, E. (2009). “An assessment of long term trends in hydrologic components and implications for water levels in Lake Superior.” Hydrol. Res., 40(6), 564–579.
Pope, V., Gallani, M. L., Rowntree, P. R., and Stratton, R. A. (2000). “The impact of new physical parameterizations in the Hadley Centre climate model: HadAM3.” Clim. Dyn., 16(2–3), 123–146.
Prudhomme, C., Jakob, D., and Svensson, C. (2003). “Uncertainty and climate change impact on the flood regime of small UK catchments.” J. Hydrol., 277(1–2), 1–23.
Ramsar Convention. (1972). 〈http://www.unesco.org/mabdb/br/brdir/directory/biores.asp〉 (Jan. 24, 2012).
Roeckner, E., et al. (1996). “The atmospheric general circulation model ECHAM-4: Model description and simulation of present-day climate.”, Max-Planck—Institut fur Meteorologie, Hamburg, Germany.
Schmidt, G. A., et al. (2006). “Present day atmospheric simulations using GISS ModelE: Comparison to in-situ, satellite and reanalysis data.” J. Clim., 19(2), 153–192.
Semenov, M. A., Brooks, R. J., Barrow, E. M., and Richardson, C. W. (1998). “Comparison of the WGEN and LARS-WG stochastic weather generators in diverse climates.” Clim. Res., 10, 95–107.
Solomon, S., et al. (2007). “Climate change, the physical science basis, contribution of working group I to the fourth assessment report of the intergovernmental panel on climate change.”, Cambridge University Press, Cambridge, U.K.
Somura, H., Arnold, J., Hoffman, D., Takeda, I., Mori, Y., and Di Luzio, M. (2009). “Impact of climate change on the Hii River basin and salinity in Lake Shinji: A case study using the SWAT model and a regression curve.” Hydrol. Processes, 23(13), 1887–1900.
Yao, H., Scott, L., Guay, C., and Dillon, P. (2009). “Hydrological impacts of climate change predicted for an inland lake catchment in Ontario by using monthly water balance analyses.” J. Hydrol. Processes, 23(16), 2368–2382.
Yu, G., and Shen, H. (2010). “Lake water changes in response to climate change in northern China: Simulations and uncertainty analysis.” J. Quat. Int., 212(1), 44–56.
Zarghami, M., Abdi, A., Babaeian, I., Hassanzadeh, Y., and Kanani, R. (2011). “Impacts of climate change on runoffs in east Azerbaijan, Iran.” Int. J. Global Planet. Change, 78(3–4), 137–146.
Zeinoddini, M., Tofighi, M. A., and Vafaee, F. (2009). “Evaluation of a dike type causeway impacts on the flow and salinity regimes in the Urmia Lake.” Int. J. Great Lakes Res., 35(1), 13–22.
Zeray, L. A., Jackson, R., and Dilnesaw Alamirew, Ch. (2007). “Climate change impact on Lake Ziway watershed water availability, Ethiopia.” Catchment Lake Res., 136, 376–385.
Information & Authors
Information
Published In
Journal of Hydrologic Engineering
Volume 21 • Issue 8 • August 2016
Copyright
© 2016 American Society of Civil Engineers.
History
Received: May 8, 2015
Accepted: Jan 7, 2016
Published online: Mar 24, 2016
Published in print: Aug 1, 2016
Discussion open until: Aug 24, 2016
Authors
Metrics & Citations
Metrics
Citations
Download citation
If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Simply select your manager software from the list below and click Download.