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Complementarity Characteristics of Actual and Potential Evapotranspiration and Spatiotemporal Changes in Evapotranspiration Drought Index over Ningxia in the Upper Reaches of the Yellow River in China
- Source :
- Remote Sensing, Vol 14, Iss 23, p 5953 (2022)
- Publication Year :
- 2022
- Publisher :
- MDPI AG, 2022.
-
Abstract
- Based on energy balance theory, using Theil–Sen median trend analysis and the Mann–Kendall test, this research studied the applicability of the complementary theory of evapotranspiration (ET) over Ningxia in the Upper Reaches of the Yellow River with MOD16 ET product and the measured data of meteorological stations, based on which ET drought index (EDI) was proposed for the first time. Moreover, the usability of EDI was also verified and its influencing factors were analyzed. The results revealed that there was a complementary relationship between AET and PET in 91.1% of the area in Ningxia, including strictly complementary and asymmetrically complementary relationships in 69.2% and 21.9% of the total area, respectively. EDI ranged from 0 to 1 and was useful to accurately reflect the degree of drought of the study area on the annual and monthly scales. From 2001 to 2020, the average annual EDI was 0.66, and the smallest monthly EDI was in January and the largest was in May. EDI of different time scales had different influencing factors. Precipitation was the most influencing factor of annual EDI, but the influencing factors of monthly EDI was different over time. However, surface non-precipitation water replenishment, such as irrigation, had great impact both on annual EDI and monthly EDI. The application scope of the theory of ET complementarity was extended to the study area for the first time, and EDI was proposed and applied, which will provide a theoretical basis and empirical reference for drought research based on ET data in arid and semi-arid areas.
Details
- Language :
- English
- ISSN :
- 20724292
- Volume :
- 14
- Issue :
- 23
- Database :
- Directory of Open Access Journals
- Journal :
- Remote Sensing
- Publication Type :
- Academic Journal
- Accession number :
- edsdoj.f0f75c27f6f49ef9c2f26f36fe6b92a
- Document Type :
- article
- Full Text :
- https://doi.org/10.3390/rs14235953