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Evaluation of drought indices via remotely sensed data with hydrological variables

机译:通过具有水文变量的遥感数据评估干旱指数

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An intercomparison among standard and remotely sensed drought indices was conducted using streamflow and soil moisture measurements collected in the Little River Experimental Watershed, Georgia, US, during the period from 2000 to 2008. All drought indices exhibited a linear, monotonic association with soil moisture, but there was a non-linear monotonic association between the drought indices and streamflow. Of the indices examined, the Evaporative Stress Index (ESI) showed reasonable performance with about 90% accuracy capturing moderate drought conditions and 80% accuracy capturing severe drought conditions in comparison to observed soil moisture and streamflow. While the ability of the ESI to capture shorter term droughts is equal or superior to the Palmer Drought Severity Index (PDSI) when characterizing droughts based on soil moisture and streamflow thresholds, the accuracy of the ESI was less efficient in the case of severe droughts. A drought index developed from the Advanced Microwave Scanning Radiometer (AMSR-E) soil moisture product showed reasonable correlations with the observed soil moisture and streamflow. However the ESI, Vegetation Health Index (VHI), and PDSI demonstrated greater skill in detecting drought in this study region. Multi-variable linear regression models revealed that the joint use of PDSI and appropriate remote sensing products improved predictions of observed hydrologic variables. Overall, the ESI was identified as a promising drought index for characterizing streamflow and soil moisture anomalies, particularly in regions where precipitation observations are unavailable, sparsely distributed, or biased with respect to regional averages.
机译:在2000年至2008年期间,使用在美国佐治亚州小河实验流域收集的流量和土壤湿度测量值,对标准干旱指数和遥感干旱指数进行了比较。所有干旱指数均与土壤水分呈线性单调关联,但是干旱指数与水流量之间存在非线性单调关联。在所检查的指标中,与观察到的土壤湿度和水流相比,蒸发应力指数(ESI)显示出合理的性能,其中90%的精度捕获中等干旱条件,而80%的精度捕获恶劣干旱条件。当根据土壤湿度和水流阈值表征干旱时,ESI捕获短期干旱的能力等于或优于Palmer干旱严重性指数(PDSI),但在严重干旱的情况下,ESI的准确性较低。由高级微波扫描辐射计(AMSR-E)得出的土壤水分产物的干旱指数与观测到的土壤水分和水流具有合理的相关性。但是,ESI,植被健康指数(VHI)和PDSI在该研究地区表现出了更高的检测干旱的能力。多变量线性回归模型显示,PDSI和适当的遥感产品的联合使用改善了对观测水文变量的预测。总体而言,ESI被认为是用于表征水流和土壤湿度异常的有希望的干旱指数,特别是在没有降水观测,分布稀疏或相对于区域平均值偏见的地区。

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