基于SWAT模型的格尔木河上游分布式水文模拟和径流预测

研究格尔木河流域水文循环过程并预测未来流域水资源的变化特征,对地区生态环境保护和下游盐湖矿产资源可持续开发利用具有重要意义。选取格尔木水文站以上区域构建SWAT(Soil and Water Assessment Tool)分布式水文模型。采用大气同化数据集为气象驱动,联合区域内纳赤台和格尔木水文站的实测月尺度径流数据进行参数的率定和验证。在率定期和验证期内,纳什效率系数、确定性系数和相对偏差系数均达到了良好的标准,表明SWAT模型在格尔木河高寒山区流域水文过程模拟中具有较好的适用性。研究表明流域降水量偏少,地表径流量、壤中流量与降水量的变化趋势具有较好的一致性,降水量年际变化中蒸散发量为主要消耗量,占40.26%。根据未来气候预测模型RegCM4.6,预测路径浓度RCP2.6、RCP4.5和RCP8.53种情景下格尔木河未来40年径流量呈增加趋势。3种情景下的年平均径流量较基准期(2006—2018年)分别增加了7.63%、11.01%、15.96%;随着温室气体排放浓度的增加,径流量呈现出增加趋势,特别是夏秋季增幅较大。短时间内径流量增大可能会引发格尔木市洪涝灾害,破坏盐湖企业生产设施;但若将洪水资源进行调控和利用,不仅防范了洪涝灾害,同时也利于解决盐湖企业日渐增大的用水需求难题。

Global warming projections using the human–earth system model BNU-HESM1.0

Future climate change is usually projected by coupled earth system models under specific emission sce- narios designed by integrated assessment models （IAMs）, and this offline approach means there is no interaction between the coupled earth system models and the IAMs. This paper introduces a new method to design possible future emission scenarios and corresponding climate change, in which a simple economic and climate damage component is added to the coupled earth system model of Beijing Normal University （BNU-ESM）. With the growth of population and technological expertise and the declining emission-to-output ratio described in the Dynamic Inte- grated Climate-Economy model, the projected carbon emission is 13.7 Gt C, resulting in a 2.4℃ warming by the end of the twenty-first century （2080-2099） compared with 1980-1999. This paper also suggests the importance of the land and ocean carbon cycle in determining the CO2 con- centration in the atmosphere. It is hoped that in the near future the next generation of coupled earth system models that include both the natural system and the social dimension will be developed.

Modeling the impacts of drying trend scenarios on land systems in northern China using an integrated SD and CA model

Climate-induced drought has exerted obvious impacts on land systems in northern China.Although recent reports by the Intergovernmental Panel on Climate Change(IPCC) have suggested a high possibility of climate-induced drought in northern China,the potential impacts of such drying trends on land systems are still unclear.Land use models are powerful tools for assessing the impacts of future climate change.In this study,we first developed a land use scenario dynamic model(iLUSD) by integrating system dynamics and cellular automata.Then,we designed three drying trend scenarios(reversed drying trend,gradual drying trend,and acceleration of drying trend) for the next 25 years based on the IPCC emission scenarios and considering regional climatic predictions in northern China.Finally,the impacts of drying trend scenarios on the land system were simulated and compared.An accuracy assessment with historic data covering 2000 to 2005 indicated that the developed model is competent and reliable for understanding complex changes in the land use system.The results showed that water resources varied from 441.64 to 330.71 billion m3 among different drying trend scenarios,suggesting that future drying trends will have a significant influence on water resource and socioeconomic development.Under the pressures of climate change,water scarcity,and socioeconomic development,the ecotone(i.e.,transition zone between cropping area and nomadic area) in northern China will become increasingly vulnerable and hotspots for land-use change.Urban land and grassland would have the most prominent response to the drying trends.Urban land will expand around major metropolitan areas and the conflict between urban and cultivated land will become more severe.The results also show that previous ecological control measures adopted by the government in these areas will play an important role in rehabilitating the environment.In order to achieve a sustainable development in northern China,issues need to be addressed such as how to arrange land use structure and patterns rationally,and how to adapt to the pressures of climate change and socioeconomic development together.

Impacts and uncertainty analysis of elevated temperature and CO_2 concentration on wheat biomass

Impacts of climatic change on agriculture and adaptation are of key concern of scientific research. However, vast uncertainties exist among global climates model output, emission scenarios, scale transformation and crop model parameterization. In order to reduce these uncertainties, we integrate output results of four IPCC emission scenarios of A1 FI, A2, B1 and B2, and five global climatic patterns of HadCM3, PCM, CGCM2, CSIRO2 and ECHAM4 in this study. Based on 20 databases of future climatic change scenarios from the Climatic Research Unit （CRU） , the scenario data of the climatic daily median values are generated on research sites with the global mean temperature increase of 1℃（GMT＋ID）, 2℃（GMT＋2D） and 3℃（GMT＋3D）. The impact of CO2 fertilization effect on wheat biomass for GMT＋I D, GMT＋2D and GMT＋3D in China＇s wheat-producing areas is studied in the process model, CERES-Wheat and probabilistic forecasting method. The research results show the CO2 fertilization effect can compensate reduction of wheat biomass with warming temperature in a strong compensating effect. Under the CO2 fertilization effect, the rain-fed and irrigated wheat biomasses increase respectively, and the increment of biomass goes up with temperature rising. The rain-fed wheat biomass increase is greater than the irrigated wheat biomass. Without consideration of CO2 fertilization effect, both irrigated and rain-fed wheat biomasses reduce, and there is a higher probability for the irrigated wheat biomass than that of the rain-fed wheat biomass.