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An Improved Grid-Xinanjiang Model and Its Application in the Jinshajiang Basin, China

机译:改进的Grid-Xinanjiang模型及其在金沙江盆地的应用

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A modified form of the distributed Grid-Xinanjiang model (GXAJ) characterizing the infiltration excess and saturation excess runoff mechanisms coupled to a two-source potential evapotranspiration model (TSPE) was proposed to simulate the hydrological process and study the spatiotemporal pattern of the precipitation, evapotranspiration, and soil moisture in the Jinshajiang River basin. In the flow routing module, the flow is routed by the physically nonlinear Muskingum–Cunge method. The TSPE model can calculate the spatiotemporal variation of the potential canopy transpiration (CT), interception evaporation (IE), and potential soil evaporation (SE). Subsequently, the calculated potential evapotranspiration (PE) is coupled to the GXAJ model to calculate the water budget in each grid. An a priori parameter estimation was developed to obtain the spatially varied parameters from geographical data, including digital elevation model (DEM) data, soil data, vegetation data, and routing data. Hydrometeorological data were interpolated to 4750 grids with cell sizes of 10 km × 10 km by the Thiessen Polygon method. The DEM data was used to extract the flow direction, river length, hillslope, and channel slopes and to adjust the altitude-related meteorological variables. The reprocessed Moderate Resolution Imaging Spectroradiometer (MODIS) leaf area index (LAI) from the Beijing Normal University (BNU) dataset, which has a spatial resolution of 1 km × 1 km, was used to obtain the spatiotemporal variation in the LAI. The developed GXAJ model was applied to three sub-basins in the Jinshajiang River basin and was compared to the traditional GXAJ model. The developed GXAJ model satisfactorily reproduced the streamflow at each catchment outlet and matched the peak discharges better than the traditional GXAJ model for both the dry and wet seasons. The uneven distribution of the simulated mean annual evapotranspiration in the whole watershed was closely related to the vegetation types, ranging from 189.81 to 585.45 mm. Forest and woodland, shrubland, grassland, and cropland were shown to have mean annual evapotranspiration values of 485.6, 289.4, 275.9, and 392.3 mm, respectively. The ratios of the annual evapotranspiration to precipitation (E/P) of the forest, woodland, shrubland, grassland, and cropland were 54, 83, 53, and 48%, respectively.
机译:提出了一种修正形式的分布式网格-新安江模型(GXAJ),该模型描述了入渗过量和饱和过量径流机制,并结合了两源潜在蒸散模型(TSPE),以模拟水文过程并研究降水的时空模式,蒸散量与金沙江流域土壤水分在流路由模块中,通过物理非线性Muskingum-Cunge方法路由流。 TSPE模型可以计算潜在冠层蒸腾量(CT),截留蒸发量(IE)和潜在土壤蒸发量(SE)的时空变化。随后,将计算出的潜在蒸散量(PE)耦合到GXAJ模​​型,以计算每个网格中的水量预算。进行了先验参数估计,以从地理数据(包括数字高程模型(DEM)数据,土壤数据,植被数据和路线数据)获得空间变化的参数。通过蒂森多边形法将水文气象数据插值到4750个网格,网格大小为10 km×10 km。 DEM数据用于提取流向,河流长度,山坡和河道坡度,并调整与海拔相关的气象变量。来自北京师范大学(BNU)数据集的经过重新处理的中分辨率成像光谱仪(MODIS)叶面积指数(LAI)具有1 km×1 km的空间分辨率,用于获得LAI的时空变化。将开发的GXAJ模​​型应用于金沙江流域的三个子流域,并与传统的GXAJ模​​型进行了比较。在干旱和潮湿季节,开发的GXAJ模​​型都能令人满意地重现每个集水区出口处的水流,并比传统GXAJ模​​型更好地匹配峰值流量。在整个流域中,模拟的年均蒸散量的不均匀分布与植被类型密切相关,范围从189.81到585.45 mm。森林和林地,灌木丛,草地和农田的年蒸散量分别为485.6、289.4、275.9和392.3 mm。森林,林地,灌木丛,草原和农田的年蒸散量与降水(E / P)的比率分别为54%,83%,53%和48%。

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