and S4, which are inconsistent with monthly evaporation changes. These might be
due to the rainfall density and extreme rainfall and it requires more research.
2.5 Summary and Conclusion
In this study, the influences of climate and land use changes on stream flow in the
KRB were estimated by an application of the HYPE model. The simulated stream
flow and its components were shown to vary among different scenarios of climate
and land use. Comparing the results of climate scenarios revealed that annual and
flood seasonal stream flows had a decrease trend from 1979 to 2008, whereas dry
seasonal stream flow trended to rise. However, there is no evidence to prove the
flood risk decreased. The differences of simulated outputs between land use scenarios exhibited the conversion of FGA into urban area induced high peak flow, a
reduction in annual evaporation and an increase in annual surface runoff. In general,
the results of this study provide important information for understanding hydrology
variation, and guide water resource managers to plan decisions associated with
water environmental change.
Acknowledgments The authors thank the supports from the “One Hundred Talents Program” of
Chinese Academy of Sciences and National Natural Science Foundation of China (No. 41471460).
The first author would like to thank China Scholarship Council (CSC) for his PhD scholarships.
References
Arheimer B, Dahne J, Donnelly C (2012) Climate change impact on riverine nutrient load and
land-based remedial measures of the Baltic sea action plan. Ambio 41(6):600–612
Arnold JG, Srinivasan R, Muttiah RS, Williams JR (1998) Large area hydrologic modeling and
assessment part I: model development. J Am Water Resour Assoc 34(1):74–89
Bergstr€ om S (1976) Development and application of a conceptual runoff model for Scandinavian
catchments. Ph.D. thesis, SMHI reports RHO no. 7, Norrk€ oping
Beskow S, Norton LD, Mello CR (2012) Hydrological prediction in a tropical watershed dominated by oxisols using a distributed hydrological model. Water Resour Manag 27(2):341–363
Chu JG, Zhang C, Wang YL, Zhou HC, Shoemaker CA (2012) A watershed rainfall data
recovery approach with application to distributed hydrological models. Hydrol Process
26(13):1937–1948
Cornelissen T, Diekkru ¨ger B, Giertz S (2013) A comparison of hydrological models for assessing
the impact of land use and climate change on discharge in a tropical catchment. J Hydrol
498:221–236
Cuo L, Zhang Y, Gao Y, Hao Z, Cairang L (2013) The impacts of climate change and land cover/
use transition on the hydrology in the upper Yellow River Basin, China. J Hydrol 502:37–52
Dechmi F, Burguete J, Skhiri A (2012) SWAT application in intensive irrigation systems: model
modification, calibration and validation. J Hydrol 470:227–238
Delpla I, Jung AV, Baures E, Clement M, Thomas O (2009) Impacts of climate change on surface
water quality in relation to drinking water production. Environ Int 35(8):1225–1233
32
M. Hu et al.
due to the rainfall density and extreme rainfall and it requires more research.
2.5 Summary and Conclusion
In this study, the influences of climate and land use changes on stream flow in the
KRB were estimated by an application of the HYPE model. The simulated stream
flow and its components were shown to vary among different scenarios of climate
and land use. Comparing the results of climate scenarios revealed that annual and
flood seasonal stream flows had a decrease trend from 1979 to 2008, whereas dry
seasonal stream flow trended to rise. However, there is no evidence to prove the
flood risk decreased. The differences of simulated outputs between land use scenarios exhibited the conversion of FGA into urban area induced high peak flow, a
reduction in annual evaporation and an increase in annual surface runoff. In general,
the results of this study provide important information for understanding hydrology
variation, and guide water resource managers to plan decisions associated with
water environmental change.
Acknowledgments The authors thank the supports from the “One Hundred Talents Program” of
Chinese Academy of Sciences and National Natural Science Foundation of China (No. 41471460).
The first author would like to thank China Scholarship Council (CSC) for his PhD scholarships.
References
Arheimer B, Dahne J, Donnelly C (2012) Climate change impact on riverine nutrient load and
land-based remedial measures of the Baltic sea action plan. Ambio 41(6):600–612
Arnold JG, Srinivasan R, Muttiah RS, Williams JR (1998) Large area hydrologic modeling and
assessment part I: model development. J Am Water Resour Assoc 34(1):74–89
Bergstr€ om S (1976) Development and application of a conceptual runoff model for Scandinavian
catchments. Ph.D. thesis, SMHI reports RHO no. 7, Norrk€ oping
Beskow S, Norton LD, Mello CR (2012) Hydrological prediction in a tropical watershed dominated by oxisols using a distributed hydrological model. Water Resour Manag 27(2):341–363
Chu JG, Zhang C, Wang YL, Zhou HC, Shoemaker CA (2012) A watershed rainfall data
recovery approach with application to distributed hydrological models. Hydrol Process
26(13):1937–1948
Cornelissen T, Diekkru ¨ger B, Giertz S (2013) A comparison of hydrological models for assessing
the impact of land use and climate change on discharge in a tropical catchment. J Hydrol
498:221–236
Cuo L, Zhang Y, Gao Y, Hao Z, Cairang L (2013) The impacts of climate change and land cover/
use transition on the hydrology in the upper Yellow River Basin, China. J Hydrol 502:37–52
Dechmi F, Burguete J, Skhiri A (2012) SWAT application in intensive irrigation systems: model
modification, calibration and validation. J Hydrol 470:227–238
Delpla I, Jung AV, Baures E, Clement M, Thomas O (2009) Impacts of climate change on surface
water quality in relation to drinking water production. Environ Int 35(8):1225–1233
32
M. Hu et al.