基于多源遥感数据的河套灌区干旱时空演变特征

利用中国气象局陆面数据同化系统（CLDAS）验证了2015—2016年土壤水分主动-被动微波数据集（SMAP）在河套灌区的适用性，基于土壤水分亏缺指数（SWDI ）和干旱周百分比（PDW）分析了作物生育期内灌区农业干旱时空演变规律，通过两个参考指标检验了SWDI在河套灌区的精度。结果表明：（1）SMAP在河套灌区的适用性较好；区域尺度上，SMAP和CLDAS的相关系数为0.65；栅格尺度上，约有69%的栅格表现良好（R>0.5），且多集中在灌区西南部和东北部。（2）严重干旱主要发生在4月下旬到5月中旬、7月下旬到8月下旬以及9月中旬到10月中旬，主要集中在灌区的西南部、中部和东部；2015—2016年PDW值略有增大，干旱事件的持续时间有所延长。（3）大气水分亏缺量（AWD）表征的气象干旱在时间上显示2 a内灌区干旱月份为5—8月；空间上，除去地形原因，SWDI和AWD的相关性较为显著，且有一半格点通过了显著性水平为0.01的显著检验，表明基于SWDI对河套灌区进行干旱状况分析具有较高的可信度。

Spatiotemporal characteristics of drought in the Hetao irrigation district based on remote sensing data from multi\|sources

The China Meteorological Administration land data assimilation system (CLDAS) was used to evaluate the applicability of the Soil Moisture Active Passive (SMAP) dataset. The soil water deficit index (SWDI) and percentage of drought week (PDW) were calculated to investigate the spatiotemporal evolution of agricultural drought in the Hetao Irrigation District (HTID). The accuracy of SWDI was examined by comparing with the atmospheric water deficit (AWD) that calculated based on the China Meteorological Assimilation Datasets for SWAT model (CMADS) dataset. The main results were as following: (1) A good applicability of soil moisture produced by SMAP was demonstrated in the HTID. At the regional scale, temporal variation trends of soil moisture between SMAP and CLDAS was consistent and the mean correlation coefficient of the whole irrigation area was 0.65. At the grid scale, approximately 69% of grids showed a high correlation (R>0.5), which was mainly located in the Southwest and Northeast of the HTID. (2) Severe drought mainly occurred in three periods (from the end of April to the mid\|May, from the end of July to the end of August, and from the mid\|September to mid\|October, respectively) and concentrated in the Southwest, Middle and East of the HTID. The values of PDW during 2015-2016 increased slightly, implying a prolonged duration of drought events. (3) Except for topographical factors, the correlation between SWDI and AWD was very significant with half of the grids passing the significance test of 0.01, indicating that investigation of drought conditions in the HTID based on SWDI derived from SMAP is credible.