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Estimating Monthly Rainfall in Rural River Basins Under Climate Change: an Improved Bias-correcting Statistical Downscaling Approach : Volume 10, Issue 6 (03/06/2013)

By Jayasekera, D. L.

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Book Id: WPLBN0004011796
Format Type: PDF Article :
File Size: Pages 50
Reproduction Date: 2015

Title: Estimating Monthly Rainfall in Rural River Basins Under Climate Change: an Improved Bias-correcting Statistical Downscaling Approach : Volume 10, Issue 6 (03/06/2013)  
Author: Jayasekera, D. L.
Volume: Vol. 10, Issue 6
Language: English
Subject: Science, Hydrology, Earth
Collections: Periodicals: Journal and Magazine Collection (Contemporary), Copernicus GmbH
Historic
Publication Date:
2013
Publisher: Copernicus Gmbh, Göttingen, Germany
Member Page: Copernicus Publications

Citation

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Kaluarachchi, J. J., & Jayasekera, D. L. (2013). Estimating Monthly Rainfall in Rural River Basins Under Climate Change: an Improved Bias-correcting Statistical Downscaling Approach : Volume 10, Issue 6 (03/06/2013). Retrieved from http://hawaiilibrary.net/


Description
Description: Civil and Environmental Engineering Department Utah State University Logan, Utah, 84322-4100, USA. This study extended the work of Kim et al. (2008) to generate future rainfall under climate change using a discrete-time/space Markov chain based on historical conditional probabilities. A bias-correction method is proposed by fitting suitable statistical distributions to transform rainfall from the general circulation model (GCM) scale to watershed scale. The demonstration example used the Nam Ngum River Basin (NNRB) in Laos which is a rural river basin with high potential for hydropower generation and significant rain-fed agriculture supporting rural livelihoods. This work generated weekly rainfall for a 100 yr period using historical rainfall data from 1961 to 2000 for ten selected weather stations. The bias-correction method showed the ability to reduce bias of the mean values of GCMs when compared to the observed mean amount at each station. The simulated rainfall series is perturbed using the delta change estimated at each station to project future rainfall for the Special Report on Emission Scenarios (SRES) A2. GCMs consisting of third generation coupled general circulation model (CGCM3.1 T63) and European center Hamburg model (ECHAM5) projected an increasing trend of mean annual rainfall in the NNRB. Seasonal rainfall percent changes showed an increase in the wet and dry seasons with the highest increase in the dry season mean rainfall of about 31% from 2051 to 2090. While the GCM projections showed good results with appropriate bias corrections, the Providing REgional Climates for Impacts Studies (PRECIS) regional climate model significantly underestimated historical behavior and produced higher mean absolute errors compared to the corresponding GCM predictions.

Summary
Estimating monthly rainfall in rural river basins under climate change: an improved bias-correcting statistical downscaling approach

Excerpt
Abbaspour, K. C., Faramarzi, M., Ghasemi, S. S., and Yang, H.: Assessing the impact of climate change on water resources in Iran, Water Resour. Res., 45, W10434, doi:10.1029/2008WR007615, 2009.; ADB – Asian Development Bank: Lao People's Democratic Republic: Preparing the Cumulative Impact Assessment for the Nam Ngum 3 Hydropower Project, Technical Assistance Consultant's Report, Project Number 40514, Financed by the Japan Special Fund) Prepared by Vattenfall Power Consultant AB in Association with Ramboll Natura AB and Earth Systems Lao, February 2008, Sweden, 2008.; Akhtar, M., Ahmad, N., and Booij, M. J.: The impact of climate change on the water resources of Hindukush–Karakorum–Himalaya region under different glacier coverage scenarios, J. Hydrol., 255, 148–163, doi:10.1016/j.jhydrol.2008.03.015, 2008.; Anandhi, A., Frei, A., Pierson, D. C., Schneiderman, E. M., Zion, M. S., Lounsbury, D., and Matonse, A. H.: Examination of change factor methodologies for climate change impact assessment, Water Resour. Res., 47, W03501, doi:10.1029/2010WR009104, 2011.; Arnell, N. W., Hudson, D. A., and Jones, R. G.: Climate change scenarios from a regional climate model: estimating change in runoff in southern Africa, J. Geophys. Res., 108, 4519, doi:10.1029/2002JD002782, 2003.; Christensen, J. H., Carter, T. R., Rummukainen, M., and Amanatidis, G.: Evaluating the performance and utility of regional climate models: the PRUDENCE project, Climatic Change, 81 (Suppl.), 1–6, 2007.; Déqué, M., Jones, R. G., Wild, M., Giorgi, F., Christensen, J. H., Hassell, D. C., Vidale, P. L., Rockel, B., Jacob, D., Kjellstrom, E., de Castro, M., Kucharski, F., and van den Hurk, B.: Global high resolution versus Limited Area Model climate change projections over Europe: quantifying confidence level from PRUDENCE results, Clim. Dynam., 25, 653–670, doi:10.1007/s00382-005-0052-1, 2005.; Eastham, J., Mpelasoka, F., Mainuddin, M., Ticehurst, C., Dyce, P., Hodgson, G., Ali, R., and Kirby, M.: Mekong River Basin Water Resources Assessment: Impacts Of Climate Change, CSIRO: Water for a Healthy Country National Research Flagship, Australia, 2008.; Efron, B. and Tibshirani, R. J.: An Introduction to the Bootstrap, Chapman and Hall, New York, 1993.; Fowler, H. J., Ekström, M., Kilsby, C. G., and Jones, P. D.: New estimates of future changes in extreme rainfall across the UK using regional climate model integrations: 1. Assessment of control climate, J. Hydrol., 300, 212–233, 2005.; Fowler, H. J., Blenkinsop, S., and Tebaldi, C.: Linking climate change modeling to impacts studies: recent advances in downscaling techniques for hydrological modeling, Int. J. Climatol., 27, 1547–1578, 2007.; Grotch, S. L. and MacCracken, M. C.: The use of general circulation models to predict regional climatic change, J. Climate, 4, 286–303, 1991.; Frei, C., Schöll, R., Fukutome

 

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