Abstract
A combination of in-situ climatic variables and remote sensing data could provide dynamic information that facilitates to get effective dryness or wetness situations for planetary ecosystems. Thus, the traditional standardized precipitation evapotranspiration index (SPEI) was revisited by drought index (DI) using satellite soil moisture data and land surface evapotranspiration from Penman-Monteith-Leuning Version 2 (PML_V2) datasets to assess the dryness over 2417 station’s grid points in China. DI was compared with the self-calibrating Palmer drought severity index (scPDSI), SPEI and composite drought index (CDI) for three major land cover classes (croplands, grasslands, and forests) area. The independent evaluation was carried out using sun-induced chlorophyll fluorescence (vegetation photosynthesis), and normalized difference vegetation index datasets including crop yield. Results exhibited that DI performance was comparable with CDI than scPDSI and SPEI to capture the impact of drought on vegetation photosynthesis. Vegetation productivity assessed by NDVI was significantly affected by dryness in the northern and southern part of China using DI, CDI and scPDSI and compared to SPEI. DI displayed a positive correlation with wheat, maize, and rice yield. Revisited drought index showed significant results for vegetation productivity but still necessitate future work to improve DI for agricultural drought research.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
