采用渔子溪流域三期遥感影像(1986、1994和2002年)获取该区域的土地利用/覆被资料,并结合实际调查数据、采用斑块驱动模型模拟得到该流域1986~2004年间逐年土地利用变化数据;然后根据该模拟数据以及渔子溪流域不同时间尺度的气象和径流资料,采用逐步线性回归和多元非线性回归方法,对渔子溪流域不同时间尺度下降雨-土地利用-径流系统及其内部各元素之间的关系进行了统计分析,结果表明:(1)不同时间尺度下径流量与降雨量的相关关系具有明显差别,土地利用变化对降雨-径流关系有重要影响,在年尺度上,降雨量对径流量的影响要大于气温对径流的影响,而在月尺度上则相反。(2)不同时间尺度下非线性回归的模拟误差要比线性模拟误差下降1.18%~23.8%,且不同影响因子在不同时间尺度上的非线性程度各不相同。
Based on remote sensing images in three different years (1986, 1994 and 2002), patch-dynamics model is used to simulate the annual land use/cover change (LUCC) from 1986 to 2004 in Yuzixi catchment. Using the modeling results of LUCC, the linear regression model and multivariate nonlinear regression model are employed to analyze the relationship between runoff, rainfall and LUCC at different time scales. The results show that: (1) The correlation coefficients between rainfall and runoff at different time scales are significantly different. The coefficient at monthly scale is the largest, which is 0.807. The coefficient at daily scale is the smallest (0.311). The results also show that, at daily scale, the time lag of rainfall and runoff has to be taken into account. (2) The results of partial correlation analysis show that, at different time scales, LUCC has significant impacts on the relationship between rainfall and runoff. At yearly scale, the impact of rainfall on runoff is larger than that of temperature on runoff, while the results at monthly scale are the reverse. The relationships between runoff and LUCC in Yuzixi catchment at different time scales are also different. Only at monthly scale, the significance of partial correlation analysis is acceptable. (3) At different time scales, the modeling accuracies of multivariate nonlinear regression analysis are higher than that of linear regression analysis. The nonlinear characteristics of different factors at different time scales are different. For example, the nonlinear index of rainfall at monthly scale is the largest (8.3) and the nonlinear index at daily scale is the smallest (0.4) (runoff is the dependent variable). The nonlinear index of temperature is 2.2 at month scale and the nonlinear index is 1.6 at daily scale. The nonlinear index of resident area is 0.725 at monthly scale and the nonlinear index is 1.01 at daily scale.
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