| 2007 Fourth Assessment Report(AR4)of IPCC(The United Nations Intergovernmental Panel on Climate Change)in 2007 and the Fifth Assessment Report(AR5)of IPCC in 2013 showed that the climate warming is an indisputable fact that causes serious damage to global and regional water resources.The global warming leads to water circulation intensification and precipitation redistribution spatiotemporally,causing hydrological changes in reginal scale.Located in the humid monsoon climate zone of East Asia,the Poyang Lake Basin is sensitive to climate change.Since 1959,Poyang Lake basin has suffered drought events frequently leading to lake waters shrunking,water quality deteriorating,threat to wetland ecology.As an important economic and ecological region of the Yangtze River Economic Belt,analyzing drought response under the future climate is of a significance for drought preventions and water resources management.Based on the hydrological model and GCMs,this paper obtained results as the following:1.Stream flow simulation and verification in ungauged zones by coupling hydrological and hydrodynamic models:a case study of the Poyang Lake ungauged zoneTo solve the problem of estimating and verifying streamflow without direct observation data,we estimated streamflow in ungauged zones by coupling a hydrological model with a hydrodynamic model,using the Poyang Lake Basin as a test case.To simulate the streamflow of the ungauged zone,we built a SWAT model for the entire catchment area covering the upstream gauged area and ungauged zone;and then calibrated the SWAT model using the data in the gauged area.To verify the results,we built two hydrodynamic scenarios(the original and adjusted scenarios)for Poyang Lake using the Delft3D model.In the original scenario,the upstream boundary condition is the observed streamflow from the upstream gauged area,while it is the sum of the observed from the gauged area and the simulated from the ungauged zone in the adjusted scenario.Using this method,we estimated the streamflow of the Poyang Lake ungauged zone as16.4±6.2 billion m~3/a,representing?11.24%of the annual total water yield of the entire watershed.Of the annual water yield,70%(11.48 billion m~3/a)concentrates in the wet season,while 30%(4.92 billion m~3/a)comes from the dry season.The ungauged streamflow significantly improves the water balance with the closing error decreased by13.48 billion m~3/a(10.10%of the total annual water resource)from 30.20±9.1 billion m~3/a(20.10%of the total annual water resource)to 16.72±8.53 billion m~3/a(10.00%of the total annual water resource).The method can be extended to other lake,river,or ocean basins where observation data is unavailable.2.Argricultural drought assessment using a new drought index considering both environmental water supply and vegetation water demandTranditional argricultural drought indexes doesn't combine evironmentaal water supply and vegetation water demand.In this study,a new drought index considering both environmental water supply and vegetation water demand(SMVD)was developed.The method used soil moisture condition index(SMCI)and potential evapotranspiration condition index(PETCI)to measure the environmental water supply and vegetation demand,respectively.SMVD was defined as the standard value of accumulated product of 1-SMCI and PETCI.Using SMVD to evaluate the agricultural drought in the Poyang Lake Basin,the dought showed temporal and spatial patterns.In terms of temporal distribution,the SMVD drought showed obvious seasonal changes:the SMVD drought was mainly concentrated in autumn.Compared with the wet year,the drought year SMVD drought are more serious obviously.In the spatial pattern,drought in the area with high forest coverage changes less,compared to the area with less forest.The drought in the dry year is less serious while the drought in the wet year is more serious.3.Variations of future precipitations in Poyang Lake Watershed under the global warming using a spatiotemporally distributed downscaling modelTraditional statistic downscaling methods are processed on independent stations,which ignores spatial correlations and spatiotemporal heterogeneity.In this study,a spatiotemporally distributed downscaling model(STDDM)was developed.The method interpolated observations and GCM(Global Climate Models)simulations to continual finer grids;then created relationship,respectively for each grid at each time.We applied the STDDM in precipitation downscaling of Poyang Lake Watershed using MRI-CGCM3(Meteorological Research Institute Coupled Ocean-Atmosphere General Circulation Model3),with an acceptant uncertainty of?4.9%,and created future precipitation changes from 1998 to 2100(1998-2012 in the historical and 2013-2100 in RCP8.5scenario).The precipitation changes showed increasing heterogeneities in temporal and spatial distribution under the future climate warming.In the temporal pattern,the wet season precipitation increased with change rate(CR)=7.33 mm/10a(11.66 mm/K)while the dry season precipitations decreased with CR=-0.92 mm/10a(-4.31 mm/K).The extreme precipitation frequency and intensity were enhanced with CR=0.49 days/10a and7.2mm·day-1/10a respectively.In the spatial pattern,precipitations in wet or dry season showed an uneven change rate over the watershed,and the wet or dry area exhibited a wetter or drier condition in the wet or dry season.Analysis with temperature increases showed precipitation changes appeared significantly(p<0.05 and R?0.56)correlated to climate warming.The results implicated the increasing risk of flood-droughts under global warming and were a reference for water balance analysis and water resource planting.4.Drought response to climate warming change based on Model EnsemblesTo resolving conflicts between the low temporal resolution of GCM model ensembles and the high temporal resolution of SWAT model input meteorology data,a new temporal downscaling for model ensemble based on a GCM with high resolution was developed.We create GCM ensembles with monthly scale by 29 GCM models using Genetic Algorithm.We create bias coefficient between the model ensembles and MRI-CGCM3 with daily scale;and use the bias coefficient to correct MRI-CGCM3 daily data.The corrected Mri-CGCM data is the special downscaling model ensembles.Base on the data,the hydrological model of the future climate is constructed.Result with base(1976-2005)and future time(2071-2100)shows that,dynamic of future meteorological elements,hydrological factors and drought were established.For the meteorological elements,rainfall showed an increasing trend in the wet season and a decreasing trend in the dry season;temperature and solar radiation showed an increasing trend throughout the year.For the hydrological elements,the evapotranspiration showed an increasing trend,and the increasement was greater than that of precipitation;the soil moisture showed a decreasing trend;the water yield showed an increasing trend during the extreme wet period and a decreasing trend during the extreme dry period.The meteorological drought showed a wetter trend overall;the wet season and the dry season showed different trends—wet season become wetter while the dry season become drier.The agricultural drought showed a drier trend overall;the wet season and dry season both become wetter.Hydrological drought showed drier trend,and the wet season and the dry season showed different trends—wet season become wetter while dry season become drier.Changes in meteorological,hydrological drought will increase the risk of flooding and drought;while the trend of agricultural drought increases the risk of agricultural production.The research results have an important guidance for the rational allocation of water resources. |
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