岷江上游植被冠层降水截留的空间模拟

 通过对岷江上游实地踏查和定位观测研究，结合MODIS遥感数据，利用“3S”技术对岷江上游植被冠层降水截留进行了空间模拟。研究结果表明：岷江上游植被叶面积指数（LAI）与增强性植被指数（EVI）以二项式关系拟合效果较好。由于归一化植被指数（NDVI）存在的饱和问题，研究采用EVI反演LAI，统计结果表明：岷江上游LAI值在0～2之间的占28.57%,在2～4.5之间的占63.06%，大于4.5的占8.37%，其中LAI最大值为7.394；从冠层最大降水截留模拟结果来看: 植被较好的地区，如卧龙、米亚罗的植被冠层最大降水截留量较大，而干旱河谷、上游高山草甸等地的植被冠层最大降水截留量相对较低；附加冠层降水截留与降雨量呈线性相关，模型验证时以此为基础，模型模拟的结果较为理想。

MODELING CANOPY RAINFALL INTERCEPTION IN THE UPPER WATERSHED OF THE MINJIANG RIVER

The headwaters of the Minjiang River are on the eastern edge of the Tibetan plateau. Canopy rainfall interception plays an important role in the water balance at the regional-scale. Many studies on canopy rainfall interception have been carried out at the stand level but less effort has been devoted towards understanding canopy interception at large scale, neither in the Minjiang River basin nor other areas. In this study, modeling canopy rainfall interception in subalpine forests and meadows in the upper reaches of the Minjiang River was carried out by using field surveys, MODIS data, and RS, GPS and GIS technologies. LAI (leaf area index) , vegetation cover and canopy capacity per unit leaf area were the main parameters used in the model. LAI was derived from the vegetation index and measured using a LAI-2000 in the forests and LAI-3000 in the sub-alpine meadows. The LAI of coniferous stands were multiplied by a correction factor because of the clumped arrangement of needles in the crown. Normalized difference vegetation index (NDVI) and enhanced vegetation index (EVI) were composed by red, near-infrared and blue reflectances from the 500 m 32-day composites available from the MODIS level 3 surface reflectance (MOD09A1). The results indicated that LAI was non-linearly correlated to NDVI and EVI. EVI was preferable to NDVI as NDVI saturates in well-vegetated areas and the degree of correlation between LAI and EVI is higher than that between LAI and NDVI. The results showed that the LAI of vegetation in the upper reaches of the Minjiang River were in the following categories: 28.57% between 0 and 2, 63.06% between 2 and 4.5, and 8.37% above 4.5. LAI was estimated using EVI, and the results showed that LAI could better reflect the spatial distribution of the vegetation. LAI in the upper watershed was lower than down river due to a large number of trees in the down river. Vegetation cover was derived from NDVI. The spatial distribution of canopy capacity per unit leaf area was modeled on the basis of a vegetation-classification map (1:1000000) . Canopy rainfall interception in the well-vegetated areas was higher than that in other areas. The model was validated using field measurements made in Wolong and Miyaluo and some additional sites in the upper watershed of the Minjang River. Empirical expressions to describe evaporation from the wet canopy were derived from additional sites and evaporation from the wet canopy was closely correlated to rainfall. Based on the empirical expressions, simulation results showed that there was a 15.4 percent error in Wolong and a 19.4 percent error in Miyaluo.