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首页> 外文期刊>Advances in Meteorology >Hydrological Evaluation of Satellite Soil Moisture Data in Two Basins of Different Climate and Vegetation Density Conditions
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Hydrological Evaluation of Satellite Soil Moisture Data in Two Basins of Different Climate and Vegetation Density Conditions

机译：不同气候和植被密度条件下两种盆地卫星土壤水分数据的水文评价

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Accurate soil moisture information is very important for real-time flood forecasting. Although satellite soil moisture observations are useful information, their validations are generally hindered by the large spatial difference with the point-based measurements, and hence they cannot be directly applied in hydrological modelling. This study adopts a widely applied operational hydrological model Xinanjiang (XAJ) as a hydrological validation tool. Two widely used microwave sensors (SMOS and AMSR-E) are evaluated, over two basins (French Broad and Pontiac) with different climate types and vegetation covers. The results demonstrate SMOS outperforms AMSR-E in the Pontiac basin (cropland), while both products perform poorly in the French Broad basin (forest).The MODIS NDVI thresholds of 0.81 and 0.64 (for cropland and forest basins, resp.) are very effective in dividing soilmoisture datasets into "denser" and "thinner" vegetation periods. As a result, in the cropland, the statistical performance is further improved for both satellites (i.e., improved to NSE = 0.74, RMSE = 0.0059m and NSE = 0.58, RMSE = 0.0066m for SMOS and AMER-E, resp.). The overall assessment suggests that SMOS is of reasonable quality in estimating basin-scale soil moisture at moderate-vegetated areas, and NDVI is a useful indicator for further improving the performance.
机译：准确的土壤湿度信息对于实时洪水预测非常重要。虽然卫星土壤水分观察是有用的信息，但它们的验证通常受到基于点的测量的大的空间差异，因此它们不能直接应用于水文建模。本研究采用Xinanjiang（XAJ）广泛应用的操作水文模型作为水文验证工具。两种广泛使用的微波传感器（SMOS和AMSR-E）进行了评估，两种盆地（法国广泛和庞氏型），具有不同的气候类型和植被覆盖。结果展示了庞蒂亚克盆地（农田）中的SMOS优于AMSR-E，而两种产品在法国宽阔的盆地（森林）中的表现不佳。MODIS NDVI阈值0.81和0.64（用于农田和森林盆地，resp。）非常有效地将粪便isture数据集分成“密集”和“更薄”植被期。结果，在农作物中，卫星（即，改进于NSE = 0.74，RMSE = 0.0059M和NSE = 0.58，RMSE = 0.0066米，SMOS和AMER-E，AMER-E，AMER-E，RESP的统计性能进一步改善了统计性能。整体评估表明，SMOS在中等植物区估算盆地土壤水分方面具有合理的质量，NDVI是一种有用的指标，用于进一步提高性能。

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