Water Science and Engineering 2018, 11(2) 157-166 DOI:   https://doi.org/10.1016/j.wse.2018.07.002  ISSN: 1674-2370 CN: 32-1785/TV

Current Issue | Archive | Search                                                            [Print]   [Close]
Information and Service
This Article
Supporting info
PDF(3519KB)
Reference
Service and feedback
Email this article to a colleague
Add to Bookshelf
Add to Citation Manager
Cite This Article
Email Alert
Keywords
SWAT
Hydropower generation
Climate change
Sensitivity analysis
Nash-Sutcliffe efficiency (NSE)
Authors
Mohammad Mehedi Hasan
Guido Wyseure
PubMed
Article by Mohammad Mehedi Hasan
Article by Guido Wyseure

Impact of climate change on hydropower generation in Rio Jubones Basin, Ecuador

Mohammad Mehedi Hasan a, *, Guido Wyseure b

a Hydraulic Research Directorate, River Research Institute, Faridpur 7800, Bangladesh
b Department of Earth and Environmental Sciences, KU Leuven, 3001 Leuven, Belgium

Abstract

This study attempted to use the soil and water assessment tool (SWAT), integrated with geographic information systems (GIS), for assessment of climate change impact on hydropower generation. This methodology of climate change impact modeling was developed and demonstrated through application to a hydropower plant in the Rio Jubones Basin in Ecuador. ArcSWAT 2012 was used to develop a model for simulating the river flow. The model parameters were calibrated and validated on a monthly scale with respect to the hydro-meteorological inputs observed from 1985 to 1991 and from 1992 to 1998, respectively. Statistical analyses produced Nash-Sutcliffe efficiencies (NSEs) of 0.66 and 0.61 for model calibration and validation, respectively, which were considered acceptable. Numerical simulation with the model indicated that climate change could alter the seasonal flow regime of the basin, and the hydropower potential could change due to the changing climate in the future. Scenario analysis indicates that, though the hydropower generation will increase in the wet season, the plant will face a significant power shortage during the dry season, up to 13.14% from the reference scenario, as a consequence of a 17% reduction of streamflow under an assumption of a 2.9°C increase in temperature and a 15% decrease in rainfall. Overall, this study showed that hydrological processes are realistically modeled with SWAT and the model can be a useful tool for predicting the impact of climate change.

Keywords SWAT   Hydropower generation   Climate change   Sensitivity analysis   Nash-Sutcliffe efficiency (NSE)  
Received 2017-05-30 Revised 2018-02-19 Online: 2018-04-30 
DOI: https://doi.org/10.1016/j.wse.2018.07.002
Fund:
Corresponding Authors: Mohammad Mehedi Hasan
Email: mmhasan@rri.gov.bd
About author:

References:

Abbaspour, K.C., 2007. SWAT-CUP: SWAT Calibration and Uncertainty Analysis Programs, A User Manual. Swiss Federal Institute of Aquatic Science and Technology, Duebendorf.

Abbaspour, K.C., Yang, J., Maximov, I., Siber, R., Bogner, K., Mieleitner, J., Zobrist, J., Srinivasan, R., 2007. Modelling hydrology and water quality in the pre-alpine/alpine Thur watershed using SWAT. Journal of Hydrology 333(2-4), 413–430. https://doi. org/10.1016/j.jhydrol.2006.09.014.

Arnold, J.G., Srinivasan, R., Muttiah, R.S., Williams, J.R., 1998. Large area hydrologic modeling and assessment, Part I: Model development. Journal of  the American Water Resources Association 34(1), 73–89. https://doi.org/10.1111/j.1752-1688.1998.tb05961.x.

Arnold, J.G., Moriasi, D.N., Gassman, P.W., Abbaspour, K.C., White, M.J.,  Srinivasan, R., Santhi, C., Harmel, R.D., van Griensven, A., van Liew, M.W., et al., 2012. SWAT: Model use, calibration, and validation. Transactions of the ASABE, 55(4), 1345–1352.  https://dx.org/10.13031/2013.42256.

Bárdossy, A., 2007. Calibration of hydrological model parameters for ungauged catchments. Hydrology and Earth System Sciences 11(2), 703–710.

Boyle, D.P., Gupta, H.V., Sorooshian, S., 2000. Toward improved calibration of hydrologic models: Combining the strengths of manual and automatic methods. Water Resources Research 36(12), 3663–3674. https://doi.org/10.1029/2000WR900207.

Bradley, R.S., Vuille, M., Diaz, H.F., Vergara, W., 2006. Threats to water supplies in the tropical Andes. Science 312(5781), 17551756. https://doi.org/10.1126/science.1128087.

Buytaert, W., Célleri, R., de Bièvre, B., Cisneros, F., Wyseure, G., Deckers, J., Hofstede, R., 2006. Human impact on the hydrology of the Andean páramos. Earth-Science Reviews 79(1-2), 53–72. https://doi.org/10.1016/j.earscirev.2006.06.002.

Buytaert, W., Iñiguez, V., de Bièvre, B., 2007. The effects of afforestation and cultivation on water yield in the Andean páramo. Forest Ecology and Management 251(1-2), 22–30. https://doi.org/10.1016/j.foreco.2007.06.035.

Buytaert, W., Vuille, M., Dewulf, A., Urrutia, R., Karmalkar, A., Célleri, R., 2010. Uncertainties in climate change projections and regional downscaling in the tropical Andes: Implications for water resources management. Hydrology and Earth System Sciences 14(7), 1247–1258. https: //doi.org/10.5194/hess-14-1247-2010.

Dibike, Y.B., Coulibaly, P., 2005. Hydrologic impact of climate change in the Saguenay watershed: comparison of downscaling methods and hydrologic models. Journal of Hydrology 307(1-4), 145–163. https://doi.org/10.1016/j.jhydrol.2004.10.012.

Eckhardt, K., Fohrer, N., Frede, H.G., 2005. Automatic model calibration. Hydrological Processes 19(3), 651–658. https://doi.org/10.1002/hyp.5613.

Emck, P., 2007. A Climatology of South Ecuador: With Special Focus on the Major Andean Ridgeas Atlantic-Pacific Climate Divide. Ph. D. Dissertation.  Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen.

Enerjubones, 2014. Enerjubones S.A. https://www.celec.gob.ec/enerjubones
[
Retrieved July 15, 2014].

Espinoza Villar, J.C., Ronchail, J., Guyot, J.L., Cochonneau, G., Naziano, F., Lavado, W., de Oliveira, E., Pombosa, R., Vauchel, P., 2009. Spatio-temporal rainfall variability in the Amazon Basin countries (Brazil, Peru, Bolivia, Colombia, and Ecuador). International Journal of Climatology 29(11), 1574–1594. https://doi.org/10.1002/joc.1791.

Ficklin, D.L., Luo, Y.Z., Luedeling, E., Zhang, M.H., 2009. Climate change sensitivity assessment of a highly agricultural watershed using SWAT. Journal of Hydrology 374(1-2), 16–29. https://doi.org/10.1016/j.jhydrol.2009.05.016.

Fontaine, T.A., Klassen, J.F., Cruickshank, T.S., Hotchkiss, R.H., 2001. Hydrological response to climate change in the Black Hills of South Dakota, USA. Hydrological Science Journal 46(1), 27–40. https://doi.org/10.1080/02626660109492798.

Fowler, H.J., Ekström, M., Blenkinsop, S., Smith, A.P., 2007. Estimating change in extreme European precipitation using a multimodel ensemble. Journal of Geophysical Research: Atmospheres 112(D18), D18104. https://doi.org/10.1029/2007JD008619.

Githui, F., Gitau, W., Mutua, F., Bauwens, W., 2009. Climate change impact on SWAT simulated streamflow in western Kenya. International Journal of Climatology 29(12), 1823–1834. https://doi.org/10.1002/joc.1828.

Gupta, H.V., Sorooshian, S., Yapo, P.O., 1999. Status of automatic calibration for hydrologic models: Comparison with multilevel expert calibration. Journal of Hydrologic Engineering 4(2), 135–143. https://doi.org/10.1061/(ASCE)1084-0699(1999)4:2(135).

Houghton, J.T., Ding, Y., Griggs, D.J., Noguer, M., van der Linden, P.J., Dai, X., Maskell, K., Johnson, C.A., 2001. Climate Change 2001: The Scientific Basis. Cambridge University Press, Cambridge.

Huntingford, C., Jones, R.G., Prudhomme, C., Lamb, R., Gash, J.H.C., Jones, D.A., 2003. Regional climate-model predictions of extreme rainfall for a changing climate. Quarterly Journal of the Royal Meteorological Society, 129(590), 1607–1621. https://doi.org/10.1256/qj.02.97.

Koch, F., Prasch, M., Bach, H., Mauser, W., Appel, F., Weber, M., 2011. How will hydroelectric power generation develop under climate change scenarios? A case study in the Upper Danube Basin. Energies 4(10), 15081541. https://doi.org/10.3390/en4101508.

Li, T.J., Wang, G.Q., Chen, J., Wang, H., 2011. Dynamic parallelization of hydrological model simulations. Environmental Modelling & Software 26(12), 1736–1746. https://doi.org/10.1016/j.envsoft.2011.07.015.

Madani, K., 2011. Hydropower licensing and climate change: Insights from cooperative game theory. Advances in Water Resources 34(2), 174–183. https://doi.org/10.1016/j.advwatres.2010.10.003.

McCuen, R.H., Knight, Z., Cutter, A.G., 2006. Evaluation of the Nash-Sutcliffe efficiency index. Journal of Hydrologic Engineering 11(6), 597–602. https://doi.org/10.1061/(ASCE)1084-0699(2006)11:6(597).

Mora, D.E., Campozano, L., Cisneros, F., Wyseure, G., Willems, P., 2014. Climate changes of hydrometeorological and hydrological extremes in the Paute Basin, Ecuadorean Andes. Hydrology and Earth System Sciences 18(2), 631–648. https://doi.org/10.5194/hess-18-631-2014.

Moriasi, D.N., Arnold, J.G., van Liew, M.W., Bingner, R.L., Harmel, R.D., Veith, T.L., 2007. Model evaluation guidelines for systematic quantification of accuracy in watershed simulations. Transactions of the ASABE 50(3), 885–900. https://doi.org/10.13031/2013.23153.

Muñoz, P., Célleri, R., Feyen, J., 2016. Effect of the resolution of tipping-bucket rain gauge and calculation method on rainfall intensities in an Andean Mountain gradient. Water 8(11), 534. https://doi.org/10.3390/w8110534.

Neitsch, S.L., Arnold, J.G., Kiniry, J.R., Williams, J.R., King, K.W., 2002. Soil and Water Assessment Tool, Theoretical Documentation, Version 2000. Agricultural Research Service, Temple. http://swat.tamu.edu/media/1290/swat2000theory.pdf
[
Retrieved December 21, 2013].

Neitsch, S.L., Arnold, J.G., Kiniry, J.R., Williams, J.R., King, K.W., 2005. Soil and Water Assessment Tool, Theoretical Documentation, Version 2005. Agricultural Research Service, Temple. http://swat.tamu.edu/media/1292/swat2005theory.pdf
[
Retrieved January 5, 2014].

Park, J.Y., Park, M.J., Joh, H.K., Shin, H.J., Kwon, H.J., Srinivasan, R., Kim, S.J., 2011. Assessment of MIROC3.2 HiRes climate and CLUE-s land use change impacts on watershed hydrology using SWAT. Transactions of the ASABE 54(5), 1713–1724. https:// doi.org/10.13031/2013.39842

Santhi, C., Arnold, J.G., Williams, J.R., Hauck, L.M., Dugas, W.A., 2001. Application of a watershed model to evaluate management effects on point and nonpoint source pollution. Transactions of the ASAE 44(6), 1559–2129. https://doi.org/10.13031/2013.7041.

Schoups, G., van de Giesen, N.C., Savenije, H.H.G., 2008. Model complexity control for hydrologic prediction. Water Resources Research 44(12), W00B03. https://doi.org/10.1029/2008WR006836.

Shrestha, N.K., Shakti, P.C., Gurung, P., 2010. Calibration and validation of SWAT model for low-lying watersheds: A case study on the Kleine Nete watershed, Belgium. Hydro Nepal: Journal of Water, Energy and Environment, 6, 47–51. https://doi.org/10.3126/hn.v6i0.4194.

Tamm, O., Luhamaa, A., Tamm, T., 2016. Modeling future changes in the North-Estonian hydropower production by using SWAT. Hydrology Research 47(4), 835-846. https://doi.org/10.2166/nh.2015.018.

Urrutia, R., Vuille, M., 2009. Climate change projections for the tropical Andes using a regional climate model: Temperature and precipitation simulations for the end of the 21st Century. Journal of Geophysical Research: Atmospheres 114(D2), D02108-D02122. https://doi.org/10.1029/2008JD011021.

van Griensven, A., Meixner, T., Grunwald, S., Bishop, T., Diluzio, M., Srinivasan, R., 2006. A global sensitivity analysis tool for the parameters of multi-variable catchment models. Journal of Hydrology 324(1-4), 10–23. https://doi.org/10.1016/j.jhydrol.2005.09.008.

van Liew, M.W., Arnold, J.G., Garbrecht, J.D., 2003. Hydrologic simulation on agricultural watersheds: Choosing between two models. Transactions of the ASAE 46(6), 1539–1551. https://doi.org/10.13031/2013.15643.

van Liew, M.W., Arnold, J.G., Bosch, D.D., 2005. Problems and potential of auto calibrating a hydrologic model. Transactions of the ASAE 48(3), 1025–1040. https://doi.org/10.13031/2013.18514.

Vuille, M., Bradley, R.S., Werner, M., Keimig, F., 2003. 20th Century climate change in the tropical Andes: Observations and model results. Climatic Change 59(1-2), 75–99. https://doi.org/10.1023/A:1024406427519.

Similar articles
1.Reza BARATI, Sajjad RAHIMI, Gholam Hossein AKBARI.Analysis of dynamic wave model for flood routing in natural rivers[J]. Water Science and Engineering, 2012,5(3): 243-258
2.Xu-ming WANG, Hai-jun LIU, Li-wei ZHANG, Rui-hao ZHANG.Climate change trend and its effects on reference evapotranspiration at Linhe Station, Hetao Irrigation District[J]. Water Science and Engineering, 2014,7(3): 250-266
3.Li-juan XUE1,2, Li-jiao LI1, 3, Qi ZHANG*1.Hydrological behaviour and water balance analysis for Xitiaoxi catchment of Taihu Basin[J]. Water Science and Engineering, 2008,1(3): 44-53
4.Yan-wei SUN; Xiao-mei WEI; Christine A. POMEROY.Global analysis of sensitivity of bioretention cell design elements to hydrologic performance[J]. Water Science and Engineering, 2011,4(3): 246-257
5.Xiao-meng SONG, Fan-zhe KONG, Che-sheng ZHAN Ji-wei HAN, Xin-hua ZHANG.Parameter identification and global sensitivity analysis of Xinanjiang model using meta-modeling approach[J]. Water Science and Engineering, 2013,6(1): 1-17
6.Xin CAI; Ying-li WU; Jian-gang YI; Yu MING.Research on shape optimization of CSG dams[J]. Water Science and Engineering, 2011,4(4): 445-454
7. Wei ZHANG, Shou-sheng MU, Yan-jing ZHANG, Kai-min CHEN.Seasonal and interannual variations of flow discharge from Pearl River into sea[J]. Water Science and Engineering, 2012,5(4): 399-409
8. Lin-lin CAI, Guang-wei ZHU, Meng-yuan ZHU, Hai XU, Bo-qiang QIN.Effects of temperature and nutrients on phytoplankton biomass during bloom seasons in Taihu Lake[J]. Water Science and Engineering, 2012,5(4): 361-374
9.Jun-feng Dai, Jia-zhou Chen, Guo-an Lü, Larry C. Brown, Lei Gan.Application of SWAT99.2 to sensitivity analysis of water balance components in unique plots in a hilly region[J]. Water Science and Engineering, 2017,10(3): 209-216
10.Jun Liu, Gloria Appiah-Sefah, Theresa Oteng Apreku.Effects of elevated atmospheric CO2 and nitrogen fertilization on nitrogen cycling in experimental riparian wetlands[J]. Water Science and Engineering, 2018,11(1): 39-45
11.Qi-ming Zhong, Sheng-shui Chen, Zhao Deng .A simplified physically-based breach model for a high concrete-faced rockfill dam: A case study[J]. Water Science and Engineering, 2018,11(1): 46-52
12.Zohreh Sheikh Khozani, Hossein Bonakdari, Isa Ebtehaj.An expert system for predicting shear stress distribution in circular open channels using gene expression programming[J]. Water Science and Engineering, 2018,11(2): 167-176

Copyright by Water Science and Engineering