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以涟水流域为研究对象,选用1990年、2000年、2010年三期土地利用数据资料,将1985-2014年30 a气象条件相应划分为1985-1994年、1995-2004年、2005-2014年三段气象背景时期,并组合细分为7种模拟情景,应用SWAT分布式水文模型模拟不同情景下的径流量,探讨气候和土地利用变化对流域径流的影响。利用PSO粒子群优化算法,以克林效率系数KGE为目标函数,通过湘乡站实测径流数据校准模型参数。运用p-factor、r-factor评价模拟的不确定性,采用相关系数R2、纳什效率系数NS和偏差百分比PBIAS评价模型模拟效果,评价结果表明不同土地利用情景下,校准期和验证期的模拟效果均达到可信程度,模拟的不确定性较小。组合情景间模拟分析结果表明,1985-2014年30 a间,气候变化使涟水流域径流不断减少,土地利用变化使径流有所增加,年径流深总体呈现下降趋势。气候变化对涟水流域径流变化的影响贡献率在逐渐上升,从71.4%上升到了86.3%。土地利用变化对径流变化的影响贡献率则相应下降,从28.6%降低至13.7%。因此,在气候变化背景下,科学管理流域水资源还需要充分考虑流域土地资源空间配置结构和利用方式。
Taking Lianshui basin as the research object, the land use data of 1990, 2000 and 2010 were selected to divide the 30-day period from 1985 to 2014 into 1985-1994, 1995-2004 and 2005-2014 Three stages of meteorological background, and subdivided into seven simulated scenarios, the use of SWAT distributed hydrological model to simulate the runoff in different scenarios to explore climate and land-use changes on the impact of runoff. Using PSO particle swarm optimization algorithm and Kering efficiency coefficient KGE as objective function, the model parameters were calibrated by the measured data of runoff in Xiangxiang station. The p-factor and r-factor were used to evaluate the simulation uncertainty. The correlation coefficient R2, Nash efficiency coefficient NS and deviation percentage PBIAS were used to evaluate the model simulation results. The evaluation results showed that the simulation effect of calibration period and verification period under different land use scenarios All have reached a credible level with less uncertainty in simulation. The simulation results show that during the period of 30 years from 1985 to 2014, the runoff of Lianshui River Basin decreased with the climate change, the runoff increased with the land use change, and the annual runoff depth showed a downward trend. The contribution of climate change to runoff change in Lianshui River Basin is gradually increasing from 71.4% to 86.3%. The contribution of land use change to runoff change decreased correspondingly from 28.6% to 13.7%. Therefore, under the background of climate change, the scientific management of water resources in the basin needs to take full account of the spatial allocation of land resources and utilization patterns.