Abstract
The impact on streamflow and groundwater recharge considering future potential climate and land use changes was assessed using Semi-distributed Land-Use Runoff Process (SLURP) continuous hydrologic model. The model was calibrated and verified using 4 years (1999–2002) daily observed streamflow data for a 260.4 km2 watershed which has been continuously urbanized during the past couple of decades. The model was calibrated and validated with 0.72 average coefficient of determination and 0.69 average Nash-Sutcliffe model efficiency respectively. For the future climate change assessment, three GCMs (MIROC3.2hires, ECHAM5-OM, and HadCM3) of IPCC A2, A1B, and B1 scenarios from 1977 to 2099 were adopted, and the data was corrected using 30 years (1977–2006, baseline period) ground weather data and downscaled by Change Factor simple statistical method. The future land uses were predicted by Cellular Automata-Markov technique using the time series land use data of Landsat images. The 2080 land uses showed that the forest and paddy areas decreased 10.8% and 6.2% respectively while the urban area increased 14.2%. For the future vegetation canopy prediction, a linear regression between monthly Normalized Difference Vegetation Index (NDVI) from NOAA/AVHRR images and monthly mean temperature using eight years (1997–2004) data was derived for each land use class. The 2080s highest NDVI value was 0.64 while the current highest NDVI value was 0.51. The future assessment showed that the annual streamflow increased up to 52.8% for 2080 HadCM3 A2 scenario and decreased up to 14.5% for 2020 ECHAM5-OM A1B scenario respectively. The seasonal results showed that the spring streamflow of three GCMs clearly increased while the summer streamflow decreased for MIROC3.2 hires and ECHAM5-OM, and increased for HadCM3 corresponding to each precipitation change of GCMs. The portion of future predicted Evapotranspiration (ET) about precipitation increased up to 3.0% in MIROC3.2 hires, 16.0% in ECHAM5-OM, and 20.0% in HadCM3 respectively. The future soil moisture content slightly increased compared to 2002 soil moisture. The increase of soil moisture resulted in the increase of groundwater recharge except ECHAM5-OM. The increase of summer ET gives us a decision making in advance for the security of future water demands. Thus the increased streamflow during spring period has to be managed more carefully and efficiently than the present situation.
Similar content being viewed by others
References
Ahn, J. H., Yoo, C. S., and Yoon, Y. N. (2001). “An analysis of hydrologic changes in Daechung dam basin using GCM simulation results due to global warming.” Journal of Korean Water Resources Association, Vol. 34, No. 4, pp. 335–345.
Alcamo, J., Döll, P., Kaspar, F., and Siebert, S. (1997). Global change and global scenarios of water use and availability: An application of Water GAP 1.0. Report A9701, Center for Environmental Systems Research, University of Kassel, Germany.
Aleix S. C., Juan, B. V., Javier, G. P., Kate, B., Luis, J. M., and Thomas, M. (2007). “Modeling climate change impacts-and uncertainty-on the hydrology of a riparian system.” Journal of Hydrology, Vol. 347, Nos. 1–2, pp. 48–66.
Andersen, J., Dybkjaer, G., Jensen, K. H., Refsgaard, J. C., and Rasmussen, K. (2002). “Use of remotely sensed precipitation and leaf area index in a distributed hydrological model.” Journal of Hydrology, Vol. 264, Nos. 1–4, pp. 34–50.
Andersson, L., Wilk, J., Todd, M. C., Hughes, D. A., Earle, A., Kniveton, D., Layberry, R., and Savenije, H. G. (2006). “Impact of climate change and development scenarios on flow patterns in the Okavango River.” Journal of Hydrology, Vol. 331, Nos. 1–2, pp. 43–57.
Arnell, N. W. (1999). “Climate change and global water resources.” Global Environmental Change, Vol. 9, No. 1, pp. S31–S49.
Clarke, K. C. and Gaydos, L. J. (1998). “Loose-coupling a cellular automata model and GIS: Long-term urban growth prediction for San Francisco and Washington/Baltimore.” Journal of Geographical Information Science, Vol. 12, No. 7, pp. 699–714.
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.” Climatic Change, Vol. 69, Nos. 2–3, pp. 245–268.
Doogers, P. and Aerts, J. (2005). “Adaptation strategies to climate change and climate variability: A comparative study between seven contrasting river basins.” Physics and Chemistry of the Earth, Vol. 30, No. 6, pp. 339–346.
Duan, Q., Sorooshian, S. S., and Gupta, V. K. (1994). “Optimal use of the SCE-UA global optimization method for calibrating watershed models.” Journal of Hydrology, Vol. 158, Nos. 3–4, pp. 265–284.
Forch, G., Garde, F., and Jensen, J. (1996). “Climate change and design criteria in water resources management: A regional case study.” Atmospheric Research, Vol. 42, No. 1, pp. 33–51.
Gellens, D. and Rouline, E. (1998). “Streamflow responses of Belgian catchments to IPCC climate change scenarios.” Journal of Hydrology, Vol. 210, Nos. 1–4, pp. 242–258.
Ghosh, S. and Mujumdar, P. P. (2008). “Statistical downscaling of GCM simulations to streamflow using relevance vector machine.” Advances in Water Resources, Vol. 31, No. 1, pp. 132–146.
IPCC (2001). Climate change 2001: Scientific basis, In: Contribution of Working Group III to the Third Assessment Report of the Intergovernmental Panel on Climate Change, Metz, B. et al. (ed.), Published for the Intergovernmental Panel on Climate Change [by] Cambridge University Press, Cambridge, UK, New York, USA.
IPCC Data Distribution Centre, Available at: www.mad.zmaw.de/IPCC_DDC/html/SRES_AR4/index.html.
IPCC-TGCIA (1999). Guidelines on the use of scenario data for climate impact and adaptation assessment, Version 1, In: Carter, T. R., Hulme, M., Lal, M. (eds.), Intergovernmental Panel on Climate Change Task Group on Scenarios for Climate Impact Assessment, p. 69.
Kite, G. W. (1975). “Performance of two deterministic hydrological models.” IASH-AISH Publication, Vol. 115, pp. 136–142.
Kite, G. W. (1993). “Application of a land class hydrological model to climatic change.” Water Resources Research, Vol. 29, No. 7, pp. 2377–2384.
Kite, G. W. (2000). “Using a basin-scale hydrological model to estimate crop transpiration and soil evaporation.” Journal of Hydrology, Vol. 229, Nos. 1–2, pp. 59–69.
Kite, G. W. (2002). Manual for the SLURP hydrological model, V. 12.2.
Kite, G. W., Dalton, A., and Dion, K. (1994). “Simulation of streamflow in a macro-scale watershed using GCM data.” Water Resources Research, Vol. 30, No. 5, pp. 1546–1559.
Lee, Y. J. and Kim, S. J. (2007). “A modified CA-Markov technique for prediction of future land use change.” Journal of the Korean Society of Civil Engineers, Vol. 57, No. 6D, pp. 809–817.
Legates, D. R. and McCabe, G. J. (1999). “Evaluating the use of ‘goodness of fit’ measures in hydrologic and hydroclimatic model validation.” Water Resources Research, Vol. 35, No. 1, pp. 233–241.
Linden, S. and Woo, M. K. (2003). “Transferability of hydrological model parameters between basins in data-sparse areas, subarctic Canada.” Journal of Hydrology, Vol. 170, Nos. 3–4, pp. 182–194.
Merritt, W. S., Alila, Y., Barton, M., Taylor, B., Cohen, S., and Neilsen, D. (2006). “Hydrologic response to scenario of climate change in sub watersheds of the Okanagan basin, British Columbia.” Journal of Hydrology, Vol. 326, Nos. 1–4, pp. 79–108.
Myneni, R. B. and Williams, D. L. (1994). “On the relationship between FPAR and NDVI.” Remote Sensing of Environment, Vol. 49, pp. 200–211.
Nash, J. E. and Sutcliffe, J. V. (1970). “River flow forecasting through conceptual models: Part 1 — A discussion of principles.” Journal of Hydrology, Vol. 10, No. 3, pp. 282–290.
Pruski, F. F. and Nearing, M. A. (2002). “Runoff and soil loss responses to changes in precipitation: A computer simulation study.” Journal of Soil and Water Conservation, Vol. 57, No. 1, pp. 7–16.
Rawls, W. J., Brakensiek, D. L., and Saxton, K. E. (1982). “Estimation of soil water properties.” Transactions of the American Society of Agriculture Engineers, Vol. 25, No. 5, pp. 1316–1320.
Sellers, P. J., Tucker, P. J., Collatz, G. J., Los, S. O., Justice, C. O., Dazlich, D. A., and Randall, D. A. (1994). “A global 1 degree by 1 degree NDVI data set for climate studies. Part 2: the generation of global fields of terrestrial biophysical parameters from NDVI.” Journal of Remote Sensing, Vol. 15, No. 17, pp. 3519–3545.
Snell, S. E., Gopal, S., and Kaufmann, R. K. (2000). “Spatial interpolation of surface air temperatures using artificial neural networks: Evaluating their use for downscaling GCMs.” Journal of Climate, Vol. 13, No. 5, pp. 886–895.
Thomas, H. and Laurence, H. M. (2006). “Modelling and projecting landuse and landcover changes with a cellular automaton in considering landscape trajectories: An improvement for simulation of plausible future states.” Journal of the European Association of Remote Sensing Laboratories, Vol. 5, pp. 63–76.
Turner, M. G. (1987). “Spatial simulation of landscape changes in Georgia: A comparison of three transition models.” Landscape Ecology, Vol. 1, No. 1, pp. 29–36.
Westmacott, J. R. and Burn, D. H. (1997). “Climate change effects on the hydrologic regime within the Churchill-Nelson river basin.” Journal of Hydrology, Vol. 202, Nos. 1–4, pp. 263–279.
Wilby, R. L. and Harris, I. (2006). “A framework for assessing uncertainties in climate change impacts: Low-flow scenarios for the River Thames, UK.” Water Resources Research, Vol. 42, No. W02419, pp. 1–10.
Zhang, G. H., Fu, S. H., Fang, W. H., Imura, H., and Zhang, X. C. (2007a). “Predicting effects of climate change on runoff in the Yellow River Basin of China.” American Society of Agricultural and Biological Engineers, Vol. 50, No. 3, pp. 911–918.
Zhang, X., Srinivasan, R., and Hao, F. (2007b). “Predicting hydrologic response to climate change in the Luohe River Basin using the SWAT model.” American Society of Agricultural and Biological Engineers, Vol. 50, No. 3, pp. 901–910.
Zhou, L., Dickinson, R. E., Tian, Y., Zeng, X., Dai, Y., Yang, Z. L., Schaaf, C. B., Gao, F., Jin, Y., Strahler, A., Myneni, R. B., Yu, H., and Shaikh, M. (2003). “Comparison of seasonal and spatial variations of albedos from Moderate-Resolution Imaging Spectroradiometer (MODIS) and Common Land Model.” Journal of Geophysical Research, Vol. 108, No. 15, pp. 1–20.
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Ahn, S.R., Park, G.A., Jung, I.K. et al. Assessing hydrologic response to climate change of a stream watershed using SLURP hydrological model. KSCE J Civ Eng 15, 43–55 (2011). https://doi.org/10.1007/s12205-011-0890-9
Received:
Revised:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s12205-011-0890-9