黑河流域土地覆盖分类数据的建立及其影响的模拟

Landuse Patterns of Heihe River Basin and Its Impact Modeling

基于黑河流域1∶100000土地覆盖分布图,融合了1∶1000000植被分类图,按照美国地质调查局(USGS)提出的土地覆盖分类标准,合成了与全球土地覆盖类型分类标准相同的空间分辨率为1 km黑河流域土地覆盖类型分布(简称综合分类)。将综合分类数据与USGS全球土地覆盖类型数据在黑河流域范围内进行对比,发现土地覆盖类型分布变化区域主要集中在流域中游的绿洲区,许多绿洲在全球数据中体现为草地,在综合分类中为灌溉农田,同时综合分类数据中较全球数据增加了许多城镇用地。利用两套土地覆盖类型分布数据对2003年黑河流域中上游大气要素进行了模拟,比较了不同土地覆盖类型分布对气温等大气要素的影响,结果显示,土地覆盖参数中地表反照率和比辐射率的空间分布与近地层大气要素和土壤温、湿场分布的空间相关性高;比辐射率和粗糙度变化对局地大气、土壤要素影响较大,绿洲区土地覆盖类型大多由草地变为灌溉农田,导致了气温升高,其中不排除城市化的影响,无论从特征参数变化与大气要素模拟值变化场的空间相关性还是特征参数变化引起的气温变化的关系看,气温变化与比辐射率变化关系较密切。在黑河流域中上游可以通过增大灌溉农田比辐射率来提高气温模拟的准确性,这一结论还需要更多的观测与模拟的验证。

Based on the 1 ： 100000 landcover map of the Heihe river basin in 2000 and the global 25type classification systems, the 30 s landcover map of the Heihe river basin （Heihe data for short） was brought out combined with the 1 ： 1000000 vegetation classification map, which is the same classification format with global 30 s landcover data （USGS data for short） brought forward by Loveland at the begin ning of 1990＇s. By the comparison between these two datasets, it is found that the landcover type difference mainly locates at the middle reache of the baisn, where the landcover type is most grassland in the global data and irrigated cropland/pasture in the Heihe data. These two landcover data sets were implied into atmospheric model to investigate the influence of different landcover data on environmental element modeling. The following results were concluded. Except for wind field, shortwave radiation and ground heat flux, simulated environmental element distribution patterns are higher related to albedo, emmisivity pattern than the roughness and resistance. The different landcover types in the middle reache lead to the local air temperature increase. Urban effect is included maybe. Either from the spatial correlation coefficient between environmental element pattern itself and landcover pattern or from air temperature changes near surface because of land cover alteration at meteorology stations, simulated air temperature near surface was affected by emmisivity greatly than the other parameters. There are not much observation to estimate emmisivity, one could get more accurate air temperature simulation results by raise emmisivity. Absolutely, it needs more observation and simulation study to validate.