径流是洞庭湖等长江中下游通江湖泊水量变化的重要驱动因素,土地利用/覆盖变化(Land Use and Cover Change,LUCC)通过改变下垫面特征,强烈改变了流域水文过程,并进一步影响了湖泊水量变化。然而,受气候变化等多因子复杂交互作用,LUCC对...径流是洞庭湖等长江中下游通江湖泊水量变化的重要驱动因素,土地利用/覆盖变化(Land Use and Cover Change,LUCC)通过改变下垫面特征,强烈改变了流域水文过程,并进一步影响了湖泊水量变化。然而,受气候变化等多因子复杂交互作用,LUCC对“径流—湖泊水量”关系的影响方式与贡献特征依然面临较强的不确定性,成为流域水资源规划与管理面临的关键理论瓶颈。针对上述问题,基于SWAT水文模型,采用2001~2019年MODIS遥感数据产品,系统分析了洞庭湖流域LUCC对“径流—湖泊水量”的影响特征。结果表明:(1)洞庭湖流域多年平均径流和湖泊水量分别为2371亿m^(3)和682亿m^(3),季节上均表现为5~9月份较高、10~4月份较小的单峰型分布特征,径流年际变化趋势较弱(y=14.926x+2222.1,R^(2)=0.0439,p<0.01),而湖泊水量则呈现较缓慢的下降趋势(y=-4.1473x+723.880,R^(2)=0.0667,p<0.01);(2)洞庭湖湖泊水量与流域径流量呈显著正相关性,年际尺度上可表示为y=0.173x+272.11(R^(2)=0.5885,p<0.01),月尺度上则可表示为y=0.2494x+7.2574(R^(2)=0.5657,p<0.01);(3)LUCC对“径流—湖泊水量”关系具有较强影响,其对多年年均径流量贡献约为364亿m^(3),约占多年径流总量的15.4%,对湖泊水量贡献约63亿m^(3),占总蓄水量的9.2%。研究结果有助于正确认识与把握洞庭湖等通江湖泊水量变化的内在影响机制,并为流域相关水资源治理与规划提供科学的辅助支撑。展开更多
Scenario prediction was introduced to better understand urban dynamics and to support urban planning. Taking the Dongguan central urban area of the Pearl River Delta, China as an example, three urban development scena...Scenario prediction was introduced to better understand urban dynamics and to support urban planning. Taking the Dongguan central urban area of the Pearl River Delta, China as an example, three urban development scenarios, historical trend (HT) scenario, forest protection (FP) scenario, and growth restriction (GR) scenario, were designed and transplanted into the SLEUTH model through the parameter self-modification method. The quantitative analysis results showed that the urban area would expand continuously from 2003 to 2030 under the HT scenario. More land resources would be saved under the GR scenario than FP scenario. Furthermore, the urban growth under the HT and FP scenarios would come to a steady state by 2020, while this deadline of the GR scenario would be postponed to 2025. The spatial pattern analysis using five spatial metrics, class area, number of patches, largest patch index, edge density, and contagion index, showed that under all the scenarios, the urban patches would become bigger and the form would become more compact, and the urban form under the GR scenario would be the smallest and most heterogeneous. These demonstrated that the GR scenario was more effective in meeting the goal of land protection and sustainable development for the study area.展开更多
文摘径流是洞庭湖等长江中下游通江湖泊水量变化的重要驱动因素,土地利用/覆盖变化(Land Use and Cover Change,LUCC)通过改变下垫面特征,强烈改变了流域水文过程,并进一步影响了湖泊水量变化。然而,受气候变化等多因子复杂交互作用,LUCC对“径流—湖泊水量”关系的影响方式与贡献特征依然面临较强的不确定性,成为流域水资源规划与管理面临的关键理论瓶颈。针对上述问题,基于SWAT水文模型,采用2001~2019年MODIS遥感数据产品,系统分析了洞庭湖流域LUCC对“径流—湖泊水量”的影响特征。结果表明:(1)洞庭湖流域多年平均径流和湖泊水量分别为2371亿m^(3)和682亿m^(3),季节上均表现为5~9月份较高、10~4月份较小的单峰型分布特征,径流年际变化趋势较弱(y=14.926x+2222.1,R^(2)=0.0439,p<0.01),而湖泊水量则呈现较缓慢的下降趋势(y=-4.1473x+723.880,R^(2)=0.0667,p<0.01);(2)洞庭湖湖泊水量与流域径流量呈显著正相关性,年际尺度上可表示为y=0.173x+272.11(R^(2)=0.5885,p<0.01),月尺度上则可表示为y=0.2494x+7.2574(R^(2)=0.5657,p<0.01);(3)LUCC对“径流—湖泊水量”关系具有较强影响,其对多年年均径流量贡献约为364亿m^(3),约占多年径流总量的15.4%,对湖泊水量贡献约63亿m^(3),占总蓄水量的9.2%。研究结果有助于正确认识与把握洞庭湖等通江湖泊水量变化的内在影响机制,并为流域相关水资源治理与规划提供科学的辅助支撑。
基金Support by the National Natural Science Foundation of China (No. 40671127)the National High Technology Research and Development Program of China (No. 2006AA120102)+1 种基金the National Science & Technology Pillar Program in the Eleventh Five-year Plan Period (No. 2008BAK49B04)the National Next Generation Internet Program of China (No. CNGI-09- 01-07)
文摘Scenario prediction was introduced to better understand urban dynamics and to support urban planning. Taking the Dongguan central urban area of the Pearl River Delta, China as an example, three urban development scenarios, historical trend (HT) scenario, forest protection (FP) scenario, and growth restriction (GR) scenario, were designed and transplanted into the SLEUTH model through the parameter self-modification method. The quantitative analysis results showed that the urban area would expand continuously from 2003 to 2030 under the HT scenario. More land resources would be saved under the GR scenario than FP scenario. Furthermore, the urban growth under the HT and FP scenarios would come to a steady state by 2020, while this deadline of the GR scenario would be postponed to 2025. The spatial pattern analysis using five spatial metrics, class area, number of patches, largest patch index, edge density, and contagion index, showed that under all the scenarios, the urban patches would become bigger and the form would become more compact, and the urban form under the GR scenario would be the smallest and most heterogeneous. These demonstrated that the GR scenario was more effective in meeting the goal of land protection and sustainable development for the study area.
