A New Probabilistic Approach for Evaluation of the Effects of Climate Change on Water Resources
Subject Areas : Article frome a thesis
1 - دانشجوی دکتری مهندسی منابع آب، گروه مهندسی آبیاری و آبادانی، پردیس کشاورزی و منابع طبیعی، دانشگاه تهران
2 - دانشیار گروه مهندسی آبیاری و آبادانی، پردیس کشاورزی و منابع طبیعی، دانشگاه تهران،
Keywords: Climate Change, probabilistic approach, performance criteria, Aidoghmoush River, East Azerbaijan,
Abstract :
The climate change (CC) shall certainly affect the water resources. As the presumed negative effects are serious matter of concern to countries experiencing water shortage, these phenomena have to be studied. Therefore, a new probabilistic approach was taken to evaluate the CC impacts on stream flow. To generate climate change scenarios in the foreseeable future and under A2 emission scenarios, the HadCM3 model was employed. By introducing climatic variable time series in future periods to the IHACRES hydrological model, long-term stream flow simulation scenarios were produced. By fitting the statistically different distributions on the runoff produced by using the goodness-to-fit tests, the most appropriate statistical distribution for each month was chosen and relevant statistical parameters were extracted and compared with the statistical parameters of runoff during the base period. Results showed that the long-term average annual runoff during the three future periods will decrease compared with the base period. Despite the reduction in the total runoff volume in the future periods compared with the baseline period, the decrease was concerned with the medium and high flow. The low flow rates, the total volume of runoff for the future periods compared with the baseline period will increase 47, 41, and 14%, respectively. To assess the further impact of annual average runoff on flow rates, it is necessary to examine the correlations of time series using the stream flow transmission probability. To compare the stream flow probability in each of the future periods with base period stream flow in each month, the stream flow was discretized and the performance criteria were used.
This approach was used for the Aidoghmoush River, East Azerbaijan. Results show a low coefficient of correlation and high error indicators.
3. Acharya, A., T.C. Piechota, and G.
Tootle. 2011. Quantitative assessment of
climate change on the hydrology of the
North Platte River Watershed, Wyoming.
J. Hydrol. Eng. doi: 10.1061/ (ASCE)
HE.1943-5584.0000543.
4. Diaz-Nieto, J., and R.L. Wilby. 2005. A
comparison of statistical and climate
change factor methods: Impacts on low
flows in the River Thames, United
Kingdom. Climatic Change 69: 245–268.
5. Ekström, M., B. Hingray, A. Mezghani,
and P.D. Jones. 2005. Regional climate
model data used within the SWURVE
project 2: addressing uncertainty in
regional climate model data for five
European case study areas. Hydrol. Earth
Sys. Sci. 11: 1085-1096.
6. Hu, T.S., K.C. Lam, and S.T. Ng. 2001.
River flow time series prediction with a
range dependent neural network. Hydrol.
Sci. J. 46: 729-745.
7. IPCC. 2008. Climate change and water.
Cambridge University Press.
8. Jakeman, A.J., and G.M. Hornberger.
1993. How much complexity is
warranted in a rainfall-runoff model?
Water Resour. Res. 29: 2637-2649.
9. Kite, G.W. 1977. Frequency and risk
analysis in hydrology. Water Resour.
Public. Fort Collins, Colorado, pp, 224.
10. Lin, J.Y., C.T. Cheng, and K.W. Chau.
2006. Using support vector machines for
long-term discharge prediction. Hydrol.
Sci. J. 51: 599-612.
11. Littlewood, I.G., K. Down, J.R. Parker,
and D.A. Post. 1997. IHACRES:
Catchment-scale rainfall streamflow
modelling (PC version) Version 1.0 -
April 1997. Institute of Hydrology,
Centre for Ecology and Hydrology,
Wallingford, Oxon, UK.
http://www.nwl.ac.uk/ih/www/products/
mswihacres.html.
12. Lorena, L., V. Leonardo, R. Enrique, and
L. Goffredi. 2010. Basin-scale water
resources assessment in Oklahoma under
systematic climate change scenarios
using a fully distributed hydrologic
model. J. Hydrol. Eng. 15: 107-118.
13. Moriasi, D.N. 2007. Model evaluation
guidelines for systematic quantification
of accuracy in watershed simulations.
Trans. ASABE 50: 885-900.
14. Traynham, L., R. Palmer, and A.
Polebitski. 2011. Impacts of future
climate conditions and forecasted
population growth on water supply
systems in the Puget Sound region. J.
Water Resour. Plan. Manage. 137: 318-
326.
15. Wilby, R.L., and I. Harris. 2006. A
framework for assessing uncertainties in
climate change impacts: Low flow
scenarios for the River Thames, UK.
Water Resour. Res. 42: 1-10.
16. Yu, P.S., T.C. Yang, and C.K. Wu. 2002.
Impact of climate change on water
resources in southern Taiwan. J. Hydrol.
260: 161-175.
17. Zhange, J.Y., G.Q. Wang, R.M. He, and
C.S. Liu. 2009. Variation trends of
runoffs in the Middle Yellow River Basin
and its response to climate change. Adv.
Water Sci. 20: 153-158.
