Response Of Runoff To Vegetation And Climate Change In The Liujiang Watershed

In recent years,with the impact of climate change and human activities,the problem of water resources has become increasingly serious in the world.Unique geological and geomorphic structure in the karst regions not only made local ecological environment fragile,utilization of water resources difficult,occurrence of drought and flood disasters frequent,but also was more sensitive to environmental change.The influences of climate change and human activity on runoff may have scale dependence.However,few studies have been carried out in karst regions.Meanwhile,in the context of global warming,climate change has an important impact on the future water resources in the watersheds.Thus,it is essential to investigate the multi-scale response of runoff to vegetation and climate change,and to assess the impact of climate change on runoff in the future.The results can provide the scientific basis for the rational utilization of water resources,the sustainable development of social economy,and ecological environment protection in the region.In the current study,the Liujiang watershed is selected in the southwest karst region.The correlation of runoff with vegetation and climate factors at different scales was quantified using multivariate empirical mode decomposition(MEMD).By coupling distributed hydrological model SWAT and SDSM statistical downscaling model,the response of runoff to climate change was evaluated in the Liujiang watershed.The aim of study is to provide basis of decision to watershed managers.The main contents and research results are as follows:(1)In 1982-2015,by the Mann-Kendall trend test,temperature and NDVI showed a significant increasing trend(P<0.05);runoff and precipitation showed a decreasing trend but not significant(P>0.05);potential evapotranspiration showed a increasing trend but not significant in the Liujiang watershed(P>0.05).(2)Using MEMD,the multivariate data of runoff and its influencing factors was decomposing into four intrinsic mode functions(IMFs)and a residue.It can find that the variance contributions of runoff is main in the scale of 3.1 and 15.5 years in the Liujiang watershed.(3)It can be found that scale-dependent relationships between runoff and its influencing factors.At different scales,precipitation and potential evapotranspiration were always significantly correlated with runoff(P<0.05),while the temperature and NDVI were no significantly correlated with runoff at some scales in the Liujiang watersheds(P>0.05).(4)The SWAT model has great applicability in the Liujiang watershed.The sensitivity parameters of runoff on the Liujiang watershed were identified as CN2,ALPHA?BNK and GWQMN.The SWAT model simulated monthly runoff well with the determining factor R~2and the Nash efficiency coefficient NSE are 0.92 and 0.91 in calibration period,respectively,and are 0.91 and 0.89 in validation period,respectively.(5)The SDSM model also has great applicability in the Liujiang watershed,each predictand meets the accuracy requirement.The atmospheric circulation factors of A2and B2 are outputted in the HadCM3 model,the downscaling prediction is carried out using the SDSM model.The future maximum temperature,minimum temperature and precipitation was calculated in the Liujiang watershed.These predictands show a fluctuating and rising trend in 2021-2060 and 2061-2099,respectively.(6)By coupling calibrated SWAT model and HadCM3 model,the future runoff was predicted.From the perspective of interannual change,in the scenario of A2 and B2,the runoff showed an upward trend compared with the base period in 2021-2060 and 2061-2099.From the perspective of spatial change,the runoff in the western sub-watersheds is more sensitive to climate change,and the increase of runoff is much larger than sub-watersheds in the eastern region.In the future,the spatial pattern of runoff is changing.S epecifically,runoff in the southeast is greater than in the northwest in base period,but runoff in the southwest is greater than in the northeast in the future.